Quantum Doom Clock Blog

QDC#11: Hot Quantum Summer

Richard Carback and Colton Dillion — Thu, 11 Jun 2026 12:00:00 GMT

QDC#11: Hot Quantum Summer

GM frens, this is the Quantum Doom Clock with Colton Dillion and Richard Carback, the founders of Quip Network, building the world's shared quantum computer.

When we last wrote, we highlighted the algorithm that could break ECDSA with fewer than 500,000 physical qubits by the research team out of Google, Ethereum, and Stanford with the details hidden by a zero knowledge proof (ZKP). In particular, we had criticized this as "more marketing than substance" with skepticism about both the efficacy of a ZKP, and the fidelity of the approach more generally. We were right:

Researcher André Schrottenloher trivially bypassed the ZKP by combining existing research.
There are now even more improved circuits, courtesy of EigenLab AI research improvement approach over at ECDSA Fail, featuring a 40% improvement as of this writing.

Yet again we are a couple weeks late on this update. We had to sort through over 4000 articles to find over 500 publications with actual new updates across them, so you will notice that this is a very beefy update post. The amount of new high signal information is becoming difficult for our team to parse, therefore expect changes in the form of slightly more frequent updates to keep things tractable. The theme of this one is just the overwhelming amount of advances across many of the different areas we track, and we think this will be the trend for the summer.

The Narrowing Case for Skepticism

Scott Aaronson, a quantum pioneer who is also a popular skeptic of quantum claims, is now beating a different drum. He now explains that recent experimental results in two-qubit gate fidelity are closing the gap toward practical error correction. This progress undermines previous skeptical arguments that correlated noise would prevent large-scale computation. The hardware advantages are structural, occurring when algorithms leverage specific mathematical properties like entanglement, not algorithmic! Scott is now sounding the alarm:

"if quantum computers start breaking cryptography a few years from now, don’t you dare come to this blog and tell me that I failed to warn you. This post is your warning."

Dr. David Gunnarsson argues that the industry is now waiting for a single, high-impact commercial application to trigger mass adoption. As we have been fond of saying recently, the focus is shifting from technical metrics toward demonstrating commercial value. We expect to see more high-profile examples in the coming year as the latest generation hardware starts to roll out.

Impressive Next Generation Hardware Announcements

Microsoft researchers released a preprint describing Majorana 2, and now claims their quantum chip can maintain qubit information for over 20 seconds. Everyone is still very skeptical of these claims, and so are we. If true, these advances are absolutely transformative.

Chinese groups also had two major announcements:

Origin Quantum launched the Wukong-180, their fourth-generation superconducting quantum computer with 180 computational qubits.
The University of Science and Technology announced the Jiuzhang 4.0 photonic quantum computer prototype, which can solve Gaussian boson sampling problem in just 25 microseconds.

We're excited to be getting cloud access to the Wukong, which is in line with current offerings by IBM et al. We expect to see confirmations with random circuit sampling and other experiments.

Real World Use Cases

A number of real world use case announcements were released. We are breaking this one down by sector in listicle format for you:

Physics:

Alice & Bob is collaborating with Los Alamos National Laboratory and GE Vernova to simulate the magnetic properties of new materials. Powerful permanent magnets that do not require rare earth elements eliminates reliance on a brittle part of the global supply chain.
Researchers at the Niels Bohr Institute engineered quantum dots that emit single photons compatible with existing fiber optic networks.

Biomedical:

IBM, RIKEN, and Cleveland Clinic successfully simulated a protein consisting of 12,635 atoms using a hybrid quantum-classical approach. This large-scale simulation represents a significant milestone for drug discovery and life sciences research.
Qubit Pharmaceuticals and the Centre for Quantum Technologies have partnered to develop and test quantum algorithms for molecular simulation. Researchers will use Quantinuum hardware to determine if these methods provide a practical advantage in drug development over classical techniques.

Finance:

IonQ developed a hybrid quantum-classical process to solve complex portfolio optimization problems. This method utilizes a 100-physical-qubit system to demonstrate advantages in risk minimization and return maximization.

Tech:

Cisco developed a universal quantum switch to route information between different systems.
Multiverse Computing developed a method to reduce AI uncertainty by integrating quantum circuit blocks into large language models.
HSBC, Haiqu, and academic researchers developed a method to encode complex probability distributions into shallow quantum circuits.

This is a lot of concrete developments over a short period of time.

Benchmarking

A number of benchmarking models are coming out, and many are being used to optimize the hardware. The Johns Hopkins team created a noise-modeling framework with sevenfold greater predictive accuracy for superconducting processors. Leonardo Placidi and colleagues analyzed how qubit connectivity impacts computational complexity, finding that sparse architectures can increase circuit depth by 30%. Such connectivity-aware frameworks are essential for determining when quantum hardware can truly surpass classical limits.

We also saw several optimizations. For example, Qruise automated the calibration of a 21-qubit QPU to drastically reduce bring-up time. AQT achieved a Quantum Volume of 32768 on its LYNX trapped-ion system. Pasqal demonstrated that an error-detecting code can reduce average errors by over 50% during machine learning workflows.

Frameworks and datasets for benchmarks are also becoming prominent. Alice & Bob introduced a five-criteria framework to standardize logical qubit measurements across different hardware. Sudip Vhaduri and colleagues evaluated the efficiency of quantum machine learning models on the MNIST dataset. Lastly, researchers developed a standardized metric to quantify energy efficiency by comparing algorithmic performance to hardware power consumption.

Algorithmic Advancements

We saw a number of quantum simulation and algorithmic advances. Researchers at the Jülich Supercomputing Centre and NVIDIA fully simulated a 50-qubit universal quantum computer using the JUPITER exascale supercomputer. This achievement surpasses previous simulation records and provides a high-fidelity benchmark for testing algorithms before they reach physical hardware. We had believed simulation at this scale was not possible, and going much further is likely intractable unless you introduce approximation to the approach.

Speaking of approximation approaches, physicists at the Center for Computational Quantum Physics and Boston University used tensor networks to simulate complex quantum systems on a personal laptop. Aalto University researcher also developed a quantum-inspired algorithm to model complex quasicrystals using tensor networks. Such work is always characterized as challenging assertions of quantum supremacy, but our attitude is that we needed to understand quantum to get to this point, so there is an intrinsic value to the entire space when you see such developments.

It is also simply not correct to look at such a result and assume there is no quantum supremacy. For example, Pasqal demonstrated that logical qubits outperform physical qubits when solving differential equations.

Lastly, we are also seeing a lot of resource optimization work. Quanscient and Haiqu developed a One-Step Simplified Lattice Boltzmann Method algorithm to reduce qubit requirements for fluid simulations. QuEra Computing researchers proposed a new architecture to reduce resource overhead in fault-tolerant quantum computing, and Nvidia released an Ising AI model suite to assist with quantum processor calibration and error correction.

Business News

A few major business announcements stand out. IBM and the U.S. Department of Commerce will launch Anderon, a dedicated 300-millimeter quantum chip foundry based in Albany, New York. This initiative is supported by a $1 billion CHIPS Act incentive and a $1 billion investment from IBM to accelerate the engineering of fault-tolerant systems. The foundry aims to provide advanced wafer fabrication for multiple hardware vendors, securing American leadership in quantum manufacturing.

D-Wave Quantum has unveiled a strategic roadmap to develop commercial, fault-tolerant gate-model systems. The company targets a 100-logical-qubit (NOT physical) architecture by 2032 using a specialized superconducting dual-rail qubit design. This plan focuses on reducing the physical qubit overhead required for error correction through hardware-level detection.

Other notable developments:

Quantinuum is preparing for a major Nasdaq IPO that could value the firm as high as $20 billion.
IonQ achieved a technological milestone by completing its first sale of a 256-qubit system.
Rigetti Computing announced plans to invest $100 million in the United Kingdom to deploy a 1,000-qubit system.
Microsoft invested over €134 million in a specialized research laboratory in Denmark to drive commercial use.

The Quantum Doom Clock is brought to you by Richard Carback and Colton Dillion, the cofounders of Quip Network.

The Quantum Doom Clock is a monthly mailing list that summarizes news for Quantum Computing and its effects on the cryptography and cryptocurrency spaces. We do not sell your e-mail.

Tick Tock Goes the ECDSA, April 2026

Richard Carback and Colton Dillion — Tue, 07 Apr 2026 12:00:00 GMT

Tick Tock Goes the ECDSA, April 2026

GM frens, this is the Quantum Doom Clock with Colton Dillion and Rick Carback, the founders of Quip Network, the worldwide quantum computer. If you appreciate the blog, check out our open-source post-quantum wallets on Ethereum, Solana, and Bitcoin L2s, which can help you access quantum resources on the network. Code and docs available here.

Two papers hit arXiv this last month that demand your attention. A new resource estimate for breaking 256-bit elliptic curve cryptography — co-authored by researchers from Google Quantum AI, the Ethereum Foundation's Justin Drake, and Stanford's Dan Boneh — shows Shor's algorithm can break ECDSA with fewer than 500,000 physical qubits and fewer than 70 million Toffoli gates on superconducting hardware. The paper says this "can execute in minutes." We ran the numbers on the stated parameters and estimate roughly 8-9 minutes. Separately, a team from Oratomic, Caltech, and UC Berkeley demonstrated that Shor's algorithm can operate at cryptographically relevant scales with as few as 10,000 neutral-atom qubits — trading speed for a dramatic reduction in qubit count. Together, these results shatter even our rather aggressive narrative.

Minutes, Not Hours — Everything Changes

We predicted the qubit resource drop. We published it in January 2025 and updated our estimates to be more aggressive in April. The reduction from millions of physical qubits to under half a million is expected, but the speed is the surprise. Our previous hardware estimates put the attack window at roughly 8 hours to several weeks, with costs north of $100,000. We need to fully parse the paper, but we definitely will be updating the doom clock because executing in minutes rewrites the threat model entirely.

Neither paper mentions Bitcoin by name, though both target 256-bit elliptic curve cryptography, which is the same ECDSA that secures every Bitcoin transaction. The Google/EF/Stanford paper specifically states that "first fast-clock CRQCs would enable attacks on public mempool transactions." Our original advice for Bitcoin holders, notably keeping less than $100k in your wallet while rotating to a fresh public key hash after every transaction, had assumed an attacker would need at least hours or days of compute time to crack an exposed key. That window just slammed shut. If an attacker can derive your private key in minutes, that's faster than most transactions confirm. The mempool becomes a hunting ground and miner extracted value (MEV) will now take on a whole new meaning!

It is also worth noting who authored the Google paper. Justin Drake is a senior researcher at the Ethereum Foundation who just last month elevated post-quantum security to a top strategic priority. Dan Boneh is one of the most cited cryptographers alive. These are the people who built the systems they are now explaining how to break.

Galaxy, We Have a Problem

Not two weeks before this paper dropped, Galaxy published a report claiming 66% of Bitcoin was not vulnerable to quantum attack. You can throw that analysis in the bin. Galaxy's assumptions made the same assumption we did about time to crack a key. The calculus changes not just for exposed legacy keys but for every Bitcoin holder when the attack time collapses to the point where mempool transactions are live targets.

The ZK "Disclosure" — A Press Release Wrapped in Cryptography

The authors wrapped their findings in a zero-knowledge proof, stating that they "use a zero-knowledge proof to validate these results without disclosing attack vectors." An interesting choice, but we find it ultimately more marketing than substance. First, the US government can trivially compel disclosure under existing law. Second, without the underlying details, it is a barrier to evaluate the efficacy of the algorithm on real hardware. Third, this is not a zero-day exploit. We are years from a machine that can execute this attack. Unless the authors believe a government already has access to a cryptographically relevant quantum computer (which is unlikely) hiding the algorithm does not fit any reasonable definition of responsible disclosure. Publish it, let the community fully vet it, and let defenders prepare.

Our Stance: March 2028, Not 2029

Google has updated their roadmap to achieve full quantum security by 2029. We are sticking with our March 2028 estimate and our recommendation for everyone to have a post-quantum security solution in place by then. The probability of a cryptographically relevant quantum computer (CRQC) arriving by March 28, 2028 is low, maybe 5%, but well above what any reasonable risk analyst worried about black swan events would use to justify an upgrade. Craig Gidney is now saying he would not bet against a cryptographically relevant quantum computer by 2030 as he places chances at 10% (very much in line with our thinking over a year ago). If you have loans, contracts, or custody arrangements that need to last past 2030, it is incumbent on you to upgrade now, not later.

ALL THAT SAID, we still think bitcoin, and crypto more generally, is going to be fine. BIP-360 is looking good and Project Eleven is tracking and messaging the problem (and was cited by Google). We feel the majority of the community will upgrade with plenty of time before it becomes a macro problem, even if specific wallets are not upgradeable and may be stolen in the future. We are cautiously optimistic, and you should be too.

Architecture Matters: The 10k-Qubit Result

The Oratomic/Caltech/Berkeley paper is really an exposé on how much architecture can impact resource requirements. Using a neutral-atom architecture with high-rate quantum error-correcting codes — achieving ~30% encoding rates versus ~4% for conventional surface codes — Cain et al. show that Shor's algorithm "can be executed at cryptographically relevant scales with as few as 10,000 reconfigurable atomic qubits." For ECC-256, that's 10,000 to 26,000 physical qubits with execution times "as few as 10 days." For RSA-2048, it's 11,000 to 14,000 physical qubits.

The caveat is speed — days instead of minutes. But the point stands: the qubit threshold for cryptographic relevance is not a fixed number. It is a design parameter. Oratomic reduced it by an order of magnitude compared to small-code architectures and two orders of magnitude compared to planar surface codes. Clever engineering keeps pushing the number down, and we expect it to keep falling.

QPUs Continue to Scale

The hardware race is accelerating across every qubit modality. Iceberg Quantum launched its Pinnacle Architecture using QLDPC codes, claiming RSA-2048 factorization with fewer than 100,000 physical qubits — down from millions in prior estimates. Physicists outlined techniques to scale neutral-atom systems beyond 100,000 qubits, and QuEra's 256-qubit system is already powering Berkeley Lab research into quantum defect formation.

On the superconducting side, Alice and Bob showcased advances in cat-qubit fault tolerance with their "elevator codes" slashing error rates, while Argonne and Intel deployed a 12-qubit silicon quantum dot processor — a small step but meaningful for the silicon pathway. Equal1 raised $60 million for a rack-mounted silicon quantum computer designed to slot into existing data center infrastructure like a GPU. Even Moscow State University and Rosatom deployed a 72-qubit neutral-atom prototype, signaling that the global qubit race now spans every major power.

Quantum had a significant presence at the recent NVIDIA GTC — over 40 ecosystem partner announcements and nine companies on the expo floor. This thread has a good rundown.

Quantum Advantage Takes Shape

The debate over whether quantum advantage has been achieved continues shifting from "if" to "what counts". On the applications front, Infleqtion achieved a 12-logical-qubit milestone for biomarker discovery with 0.04% error rates — one of the first demonstrations of logical qubits doing useful science. Xanadu and AMD executed hybrid quantum CFD simulations for aerospace, and IBM Research ran quantum machine learning against antibiotic resistance data with results at parity with 60-qubit experiments.

Phasecraft joined DARPA's Quantum Benchmarking Initiative to audit utility-scale timelines — a sign that the US government is now demanding receipts, not just roadmaps. Meanwhile, researchers demonstrated that quantum computing can predict photosynthetic protein structures with potential to transform medicine, and South Korea opened its first commercial quantum-AI data center focused on drug discovery.

The Steady March from Lab to Market

The quantum computing market is projected to reach $2 billion in 2026. That number will look quaint in hindsight. IonQ crossed $100M in revenue. Xanadu raised $275M with AMD as a strategic investor. Quantonation Ventures closed a €220 million second fund, more than double their first. The money is following the qubits.

On the application side, hybrid quantum-classical workflows are gaining traction. IBM is pushing quantum-centric supercomputing as a near-term architecture. It is not replacing classical compute, but accelerating specific workloads. South Korea, Taiwan, and Switzerland all launched or expanded national quantum strategies with investments in the hundreds of millions. This is no longer a research curiosity. It is infrastructure.

Quantum Computing Quick Hits

IonQ became the first quantum company to top $100 million in annual revenue and announced a 256-qubit quantum computer partnership with the University of Cambridge
SEEQC demonstrated the first quantum computer with integrated on-chip qubit control operating at millikelvin temperatures, a step toward scalable architectures
RIKEN and IBM demonstrated quantum-centric supercomputing at scale using Fugaku, IBM launched the first Quantum Nighthawk processor
Infleqtion deployed a 100-physical-qubit quantum computer at the UK's NQCC and achieved a 12-logical-qubit milestone for biomarker discovery with 0.04% error rates
Xanadu secured $275M in financing with AMD as strategic investor and executed hybrid quantum CFD simulations for aerospace
QuantWare unveiled a chiplet-based design for 10,000-qubit QPUs, though full systems are not anticipated before 2028
Rigetti delayed the launch of its flagship 108-qubit system to end of Q1 2026 while targeting higher system performance

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com.

Below are the top questions we have received since our last update.

Does the Google paper mean Bitcoin can be broken today?

No. The paper describes an algorithm that could break ECDSA with fewer than 500,000 physical qubits. The largest quantum computer today has only a few thousand qubits depending on how you count. The news is that the requirements dropped dramatically, from millions of qubits to under half a million, and from hours to minutes.

Should I move my Bitcoin to a new wallet right now?

If your Bitcoin is in a modern wallet that does not reuse addresses and uses hashed public keys (P2PKH, P2SH, or P2TR formats), your keys are not exposed on-chain until you spend. The immediate risk is to legacy P2PK addresses where public keys are permanently visible. That said, the mempool attack vector means any transaction exposes your key briefly. The best practice remains: do not hold more than you can afford to lose in any single address, and watch for post quantum wallets as they become available.

What about Ethereum?

The Ethereum Foundation, led by Justin Drake (who co-authored the Google paper), has elevated post-quantum security to a top strategic priority with $2 million in research prizes and a dedicated PQ team. Coinbase formed a quantum advisory board. Ethereum is moving faster than Bitcoin on this front, which is one advantage of having a more centralized development process.

The Clock is Ticking

The pattern from this month is unmistakable: the distance between "theoretical threat" and "engineering problem" just collapsed. Google, the Ethereum Foundation, and Stanford published an algorithm. Oratomic, Caltech, and Berkeley showed the architecture. Galaxy's report aged like milk in two weeks. The qubit counts keep falling, the timelines keep shrinking, and the people building quantum computers are now publishing papers on how to use them to break cryptography.

We have been saying this for over a year. We will keep saying it until everyone is ready. The clock is ticking but, if the community moves, and we believe it will, the story ends well.

New Year, New Qubits: Practical Quantum is Knocking on Our Door, December 2025

Richard Carback and Colton Dillion — Wed, 31 Dec 2025 17:42:29 GMT

New Year, New Qubits: Practical Quantum is Knocking on Our Door, December 2025

GM frens, this is the Quantum Doom Clock with Colton Dillion and Rick Carback, the founders of Quip Network, the world's shared quantum computer.

Happy 2026! Overall, the quantum new year arrived more stable, in more than one way. In practice, molecular qubits are now holding coherence long enough to run real-world chemistry simulations. We are now seeing converging national quantum programs springing up across the globe with government, corporate, and university partnerships focused on initiatives to accelerate and communicate quantum technology and its applications. While investments are not yet at historic levels like fiber, railroads, or AI, they are pouring in to back all of this up. Timelines, too, have collapsed from decades to years before everyone says they'll have definitive, commercially available, quantum advantage.

For this newsletter, in addition to our regularly scheduled summary of last month's news and our analysis, we are giving you a bit more: A summary of all of this year's quantum advantage claims along with our predictions for 2026.

Before that, this month we highlight Scott Aaronson's post on recent advances in quantum:

This year updated me in favor of taking more seriously the aggressive pronouncements—the “roadmaps”—of Google, Quantinuum, QuEra, PsiQuantum, and other companies about where they could be in 2028 or 2029.

Obviously, we agree.

2025 in Review: Quantum Advantage

Five groups advertised quantum supremacy or quantum advantage claims in 2025. While all claims passed peer review or scientific scrutiny to varying degrees, each faces various levels of skepticism, which highlights that the boundary between quantum and classical computational supremacy remains fiercely contested, and we’ve endeavoured to give your our opinion on each.

Notably absent is IBM, who decided to stake the contrarian claim that the quantum computing community has not yet achieved quantum advantage and instead released a quantum advantage tracker on github. This was done 2 months after getting smacked down on bogus HSBC quantum trading advantage claims, which astute readers will note we listed but did not expand on in our October newsletter—at the time, it did not make sense that a classically simulatable trading algorithm would net better trades as opposed to finding a solution more efficiently. The tracker itself is interesting but clearly geared toward their hardware and existing partners, so time will tell how useful it will be.

With that, let's get into the claims. We numbered them based on what we thought were most significant. Each of the following 6 sections starts with the organization, date, and title of what they did. We then get into the details of how real and responses they received.

1. D-Wave, March. Quantum dynamics in programmable spin glasses

In their peer-reviewed paper in Science, "Beyond-Classical Computation in Quantum Simulation", D-Wave claimed its quantum annealer achieved computational supremacy on a practically useful problem, simulating quantum dynamics in programmable spin glasses, completing time evolution of spin glass systems across 2D, 3D, and infinite-dimensional lattices. They claimed speedups of approximately 20 minutes versus one million years on Oak Ridge National Labs Frontier supercomputer.

This claim was highly controversial and faced immediate attempts at refutation, with two main challenges:

NYU/Flatiron researchers claiming similar calculations done with tensor networks in about 2 hours on a laptop. So, not 20 minutes, and not the same problem or level of complexity.
EPFL researchers claiming to use Jastrow-Feenberg wave function simulations on smaller problem sizes using 4 GPUs over 3 days. Also not 20 minutes, and not the same problem size.

Many will also point out that the D-Wave Advantage2 is an annealer, not gate-based. That means it cannot solve the same problems, so many feel it is not really a quantum computer. They are qubits, though, and it is unclear how much of a lift it would be to convert annealing qubits to gate-based, or to close the gap between annealers and adiabatic computers, which are known to be equivalent to gate-based paradigms. Any approach that yields results early is a good approach, so we think it counts.

Our conclusion is that the way they worded the claim, "beyond-classical quantum simulation," is simply too strong. The detractors have a point that the claim of one million years to simulate classically is likely overstated as methods for simulation and hardware only get better over time, not worse. We have not yet seen any attempts that yield better or faster results than D-Wave, however, so this result stands so far.

2. Google, October. Quantum Echos.

Google Quantum AI published in Nature what it called the first "verifiable quantum advantage" with its 105-qubit Willow chip implementing their Quantum Echoes algorithm using only 65 of the qubits. This measures Out-of-Time-Order Correlators (OTOC(2)), which is a metric describing quantum information scrambling in highly entangled systems. They claimed to be 13,000x faster than the Frontier supercomputer, with ~2 hours on Willow versus an estimated 3.2 years on the Frontier supercomputer.

Their work includes a molecular structure application demonstrating practical use. Specifically, they computed hydrogen atom distances in molecules containing 15 and 28 atoms, and validated against traditional NMR data, as it would otherwise only be validated with another quantum computer.

Unlike in the past, Google's quantum supremacy claims are sticking this time. With the NMR validation it looks like Google really is the first gate-based system to stake a reasonable claim to quantum advantage. We think, however, that D-Wave's results indicate potential for commercial applicability first.

3. Zuchongzhi 3.0, March. Random quantum circuit sampling

Published as a cover in Physical Review Letters, "Establishing a New Benchmark in Quantum Computational Advantage with 105-qubit Zuchongzhi 3.0 Processor", the authors from University of Science and Technology of China (USTC) claimed speedup 10^15 times faster than Frontier and 10^6 times faster than Google's Sycamore with the 105 qubit system, using only 83 for their benchmarks.

To our knowledge this is not contested, but Random circuit sampling is just a benchmark, not useful. You can also make claims similar to those against D-Wave in that faster simulations could be made, but it stands in comparison to Sycamore, so the result is legitimate but we wish it was doing something more useful like OTOC from Google.

4. Quantinuum, September. One-way communication complexity

While not peer reviewed, Quantinuum's preprint on quantum information supremacy is an interesting read. Using 12 qubits on the H1 trapped-ion system, they show the ability to complete a task that the most memory-efficient classical algorithm requires between 62 and 382 bits of memory.

Memory efficiency is not usually what we mean by quantum advantage, and there is a question when you consider that the quantum computer does need a classical control system, which has its own memory. Should that be counted?

While it is not a speedup or power efficiency, the result derives from fundamental mathematical properties of quantum mechanics. We think that counts as a kind of quantum advantage, as it demonstrates a significant difference with the quantum computing paradigm.

Also notable is that Quantinuum released a preprint about Helios. Helios is a 98-qubit trapped-ion system. The authors include random circuit sampling results demonstrating operation "well beyond the reach of classical simulation," but do not quantify it against other systems.

5. Jiuzhang 4, August. Guassian Boson Sampling.

From a different group out of USTC, their Jiuzhang preprint, “Robust quantum computational advantage with programmable 3050-photon Gaussian boson sampling,” generated boson samples in 25.6 microseconds. This is against a claim that classical simulation would take >10^42 years to produce a tensor network for simulation.

As noted in their paper, previous experiments were challenged by classical algorithms that could reproduce k-photon correlations for small k values. The new system measures correlations up to ~19 photons, which should close this loophole.

The Jiuzhang is not a general purpose gate-based system. While Gaussian Boson Sampling has some applications, they are more limited than even quantum annealers like the D-Wave. That said, the demonstration is one of quantum advantage AND it is photonics based, so it deserves the recognition.

Other Quantum Advantage Developments

While not "first" for their respective platforms, perhaps most interesting in the real world application sense is the work released by Phasecraft in October. Both of these papers simulated Fermionic dynamics on the Quantinuum H2 and the Willow chips, respectively. Quantinuum's related Fermi-Hubbard preprint is also notable. Instead of evolving an arbitrary initial state, they try to find a relevant initial state to evolve, which is an even more useful starting point.

The prospect of running the same experiments across devices enables comparison. That is what we're all about over on the quantum doom clock, so we are excited both to see these and the aforementioned quantum advantage tracker.

Our 2026 Predictions

We do not have anything to check from last year, so let's get right into what we expect for 2026:

At least one demonstrably profitable commercial deployment of a quantum computer. Not an experiment, but a computer used for demonstrable cost, power, or time savings for a commercial industry.
Either via the quantum advantage tracker or another mechanism like the Phasecraft papers, we expect to see comparative advantages of operations/performance/cost of at least 3 different available quantum computer platforms.
2-qubit gate fidelities above 99.999%. This adds another 9 to the record currently held by IonQ, and such a high fidelity would further drastically reduce the physical qubits required for an ECC break well below the current threshold of about 950k. To put it in perspective, that would allow logical qubits represented by less than 50 physical qubits. Our belief is that vendors will spend more time in the lab making better qubits rather than more, and if we do not see a new 9 we may need to acknowledge a slow down.
An ECC key of at least 24 bits will be broken on quantum hardware. Note that the classical record for ECC is 112 bits, done in 2012, so this is still a long way away from what classical computers can achieve. It's also the case that the only reliable public demonstration of any ECC key is 6 bits, so 24 is a bit of a stretch, though other authors have used hybrid methods to solve 8 bits and a new preprint claims to solve 17 bits.

We did not include a logical or physical qubit count estimate since those are all on the roadmaps by the manufacturers, so it felt too easy! Our most aggressive prediction, by far, is #3. Error correction has come a long way but that would represent a surprising result, especially if it does not come from a trapped ion system like IonQ.

QPUs Continue to Scale

Just in time for Christmas, QuEra's Gemini quantum computer was announced featuring a 260-qubit neutral atom array with high-fidelity gates and room-temperature operation, advancing scalable fault-tolerant quantum computing. It achieves 99.9% fidelity on global 1-qubit gates, 99.2% on global 2-qubit gates, and SPAM fidelity up to 99.7%. The qubits are all-to-all connected, and while not generally available, a MIT/Harvard team has had a crack at it and QuEra is accepting consultation applications.

In related news, QuantWare's VIO-40K architecture release is touted to enable mass production of 10,000-qubit quantum processors, marking a 100x leap from current industry standards. We caution that this is mostly a fabrication capabilities announcement, as buried in their data they admit that they do not anticipate any QPUs being released before 2028.

Converging Pathways to Scalable Quantum Stability

A cluster of quantum computing advancements highlighted significant progress in enhancing quantum system stability, error rates, and scalable control. Researchers at the University of Colorado at Boulder and Sandia National Laboratories developed a chip-scale optical phase modulator nearly 100 times smaller than a human hair. The optical phase modulators they designed “could help unlock much larger quantum computers by enabling efficient control of lasers required to operate thousands or even millions of qubits” and it sports a familiar CMOS process which could lead to much better scaling in photonics platforms.

As for error rate improvements, Sandia National Laboratories developed fast-feedback protocols to enable real-time calibration of 1- and 2-qubit gates, controlling drift and SPAM errors. Karlsruhe Institute of Technology (KIT) and Université de Sherbrooke in Québec developed a method to calibrate qubit charge, reducing readout faults. CSIRO and The University of Melbourne developed a quantum machine learning method that reduces hardware demands using partial error correction, advancing the path to practical quantum-enhanced learning. Macquarie University researchers, led by Dr Christina Giarmatzi fully mapped how quantum noise spreads over time, revealing time-linked errors that form a memory-like pattern undermining computation reliability. Researchers from Pennsylvania State University developed a forensic framework using graph neural networks to predict quantum error rates from public data, enabling performance assessment without confidential calibration information.

Lastly, Atom Computing developed a protocol to reset and reload lost atoms, enabling a self-repairing quantum processor that maintains qubit functionality throughout long computations. They shift the resonance of the unmeasured atoms with laser beams, then use a second set of lasers to reinitialize the system in order to join the next step in the computation. This could be very useful for long lived computations.

Quantum Network Updates

Quantum network integration is accelerating through photonic and telecom-compatible innovations. Gianvito Chiarella and his colleagues at the Max Planck Institute of Quantum Optics developed a node-heralding strategy that boosts quantum communication efficiency by reducing delays and photon loss errors. Researchers at the University of Chicago Pritzker School of Molecular Engineering developed a new method enabling quantum communication over 1,243 miles, theoretically extending quantum networks to 2,000 km.

In terms of actual results, researchers demonstrated a multiplexed quantum network node over 12 km of fiber. Aegiq Ltd. and the University of Sheffield achieved deterministic generation of complex entangled states using redundant encoding of Greenberger-Horne-Zeilinger states, boosting fusion success rates beyond 50% for scalable photonic quantum computing, and US-Based researchers announced an erbium-based molecular qubit that enables quantum systems to interface with standard fiber-optic networks using telecom wavelengths for light-based control and readout of magnetic quantum states.

Other Advances: Gold Nanoclusters, Magnetic Crystals, and Single-Molecule Qubits

Researchers from Penn State and Colorado developed tunable gold nanoclusters that offer a scalable alternative to traditional quantum systems, paving the way for practical quantum devices.
Researchers at the University of Bonn won the first-ever €50,000 Synergy Prize for pioneering work on single-molecule qubits as a more stable platform for quantum computing.
Scientists describe exciton formation in thin magnetic crystals — a discovery that opens new pathways for controlling quantum states in layered materials.
Researchers from the University of Chicago Pritzker School of Molecular Engineering identified 189 2D materials, including WS2 and Au-oxyselenides, with predicted spin qubit coherence times exceeding that of diamond.

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. We did not get any this month, but when you have them, send them our way!

Counting Qubits, Not Calories: A November Harvest to Be Thankful For, Quantum Doom Clock, November 2025

Richard Carback and Colton Dillion — Wed, 03 Dec 2025 16:43:21 GMT

Counting Qubits, Not Calories: A November Harvest to Be Thankful For, Quantum Doom Clock, November 2025

GM frens, this is the Quantum Doom Clock with Colton Dillion and Rick Carback, the founders of Quip Network, the world’s shared quantum computer. We’d like to extend a heartfelt welcome to all our new readers who discovered us this month, likely through a variety of viral tweets sharing our doomsday model. It’s possible we even got in front of Vitalik himself as he updated his timeline at Devconnect to match our Q-Day predictions. It’s a good month to start following along because we reviewed a record number of quantum stories this month, over twice as many as October. Collective awareness is clearly growing!

This November, as we gather around virtual tables filled with cranberry sauce and quantum white papers, we pause not to lament the clock’s ticking but to give thanks for the quiet revolutions unfolding in dilution refrigerators and fab ovens around the world. Every breakthrough in coherence, scaling, and error correction was a dish prepared by generations of researchers for whom we can’t express enough gratitude. Let’s eat well, think deeply, and keep building to serve the future.

This month especially we’d like to highlight the Quantum Index Report 2025 from the MIT Sloan Management School. This report primarily tracks the growth of Quantum in corporate life, noting that it now receives regular mention in company documents and earnings calls. The report itself contains a number of insights and data about how business is taking quantum seriously and indicates a massive future for growth.

From Lab to Life: Quantum Computing Embedded in Airports, Datacenters, and Beyond

The era of isolated quantum experiments is over, and the focus has shifted decisively from raw qubit counts to performance, reliability, and enterprise integrations featuring local deployments:

Open Compute Project (OCP) has launched a workstream to standardize the integration of quantum computers into classical datacenters, formalizing IBM’s real-world deployment of a 20-qubit system alongside HPC infrastructure
IBM and Cisco are building the backbone of a quantum internet capable of linking distributed fault-tolerant processors, targeting trillions of quantum gates for breakthroughs in materials and drug discovery
O’Hare Airport installed an IBM System One complete with a dilution refrigerator to demystify quantum tech for the public
NTT and OptQC are pioneering a room-temperature optical quantum computer targeting one million qubits by 2030, eliminating cryogenic constraints and advancing Japan’s quantum industrialization goals.
IonQ and Clemson solved large-scale job shop scheduling on 97-qubit hardware using a novel iterative QAOA that avoids deep circuits.
Harvard and MIT, alongside QuEra Computing, demonstrated the first integrated fault-tolerant quantum system using 448 neutral-atom qubits, successfully merging physical entanglement, logical operations, and below-threshold error correction in a single scalable platform.
Conductor Quantum and SemiQon partnered for high-fidelity silicon spin qubit fabrication with scalable CMOS-compatible control systems
Amazon Braket now offers Europe’s first trapped-ion quantum system (AQT’s IBEX Q1) with localized data residency, signaling a global shift toward quantum-as-a-service
IBM’s Qiskit Runtime now enables utility-scale dynamic circuits with real-time classical feedback, removing static circuit limitations.
AWS Quantum Technologies and Imperial College London have deployed quantum simulations of high-dimensional PDEs and the Fokker–Planck equation to model nonlinear fluid dynamics.
DARPA has selected 11 quantum companies to validate fault-tolerant architectures for utility-scale quantum operation by 2033.
Even China and India are accelerating: China Telecom launched global access to its Tianyan-287 superconducting quantum computer, while India’s National Quantum Mission is establishing chip fabrication hubs at IIT Bombay and IISc Bangalore.

Quantum computers continue to arrive at large corporations and government departments and we are now seeing the results of that starting to roll in, so it is only a matter of time before we see them as a staple in workplaces around the world, and perhaps even eventually in personal devices.

Beyond Isolation: Resolving Decoherence with Material Science and Network Design

Researchers managed a string of announcements this month with:

the development of erbium-based molecular qubits that operate at telecom wavelengths and seamlessly bridge quantum processors with existing fiber-optic infrastructure
a demonstration of quantum key distribution and private communication between 18 networked nodes
a massive improvement to 2D transmon qubits on high-resistivity silicon substrates which achieved quality factors exceeding 10⁷ and extending coherence into the millisecond range
a granular aluminum gralmonium qubits that defy magnetic field limitations by suppressing spin-related decoherence through spin freezing.
discovery of non-Markovian noise effects in multi-qubit systems, revealing how environmental memory distorts entanglement decay beyond standard models

These advances are representative of a broader trend showing that coherence is no longer a constraint of cryogenic isolation but an outcome of material design, qubit architecture, and topological control. Not to be left out, other institutions have been hacking away at similar problems for long-distance coherence:

University of Chicago’s Tian Zhong demonstrated coherence times that can support 2,000-km quantum links using a novel quantum memory crystal that overcomes optical signal loss. This is 200 times farther than previous limits.
Heriot-Watt researchers built a reconfigurable eight-user entanglement router using off-the-shelf optical fiber, demonstrating practical, deployable quantum networking
Oxford executed its first teleportation of quantum data between independent processors, successfully transmitting Grover’s algorithm and confirming that quantum networks are evolving from point-to-point links into multi-node systems.
These developments are further amplified by the integration of hybrid interfaces, such as the Karlsruhe Institute of Technology’s cryogenic optical memory linked to superconducting qubits, creating a multi-platform quantum fabric.

Meanwhile, noise characterization and error mitigation are becoming foundational to system design:

Johns Hopkins APL and University researchers unveiled a high-fidelity noise-mapping framework that pinpoints error sources with unprecedented precision, enabling targeted error mitigation for scalable fault-tolerant systems
In photonic systems, Quantum Pulse Ventures achieved room-temperature coherence extension via ultrafast optical pulse shaping, minimizing phase noise and photon loss
Chinese researchers achieved 1,000-fold photonic computing gains via low-loss waveguides
Quantum Art also demonstrated 10X circuit depth compression using all-to-all gates simulated on CUDA-Q
Ecole nationale Supérieure d’Informatique’s affine abstractions slashed SWAP gate overhead by leveraging mathematical symmetries in qubit connectivity
Zhaohui Yang’s Canopus framework integrated modern quantum instruction sets directly into routing, boosting circuit fidelity by up to 35%

This is a huge amount of research demonstrating progress across multiple simultaneous axes affecting horizontal scaling, data persistence, noise mitigation, and more, all signaling a maturing technology paradigm where coherence, communication, and computational efficiency are mutually reinforcing factors instead of isolated achievements.

The New Quantum Manufacturing Stack: EDA, Couplers, and Cryogenic Control

Manufacturing and infrastructure are fast becoming the new frontiers of scaling. IQM’s €40 million investment to double its Finnish production capacity now enables the annual manufacturing of over 30 superconducting quantum systems. This comes with better tooling, with Nanoacademic Technologies and Kothar Computing launching the first Quantum Electronic Design Automation (EDA) suite and, within days of that announcement, Keysight Technologies unveiled its Quantum System Analysis EDA platform. These EDA tools will be transforming chip development from physics-heavy trial-and-error into a repeatable, engineering-driven workflow.

The foundation of this shift is cemented by hardware innovations that dramatically reduce complexity and cost, which continue apace. Quantum Pulse Ventures’ directional coupler slashes qubit requirements by 90%, cutting system costs by up to $900 million per unit. AIST’s novel niobium fabrication process enables ultra-low-power superconducting circuits for qubit interfaces, achieving critical currents as low as 10 µA at ~10 mK. YQuantum’s miniaturized cryogenic systems will deliver scalable, high-fidelity control, and will help with solving one of quantum’s most persistent thermal bottlenecks.

The commercial viability of quantum systems also continues to receive further validation. Xanadu’s $3.6 billion SPAC merger with Crane Harbor Acquisition Corp secures nearly $500 million to accelerate photonic hardware development. Meanwhile USTC deployed the world’s first commercially operational neutral-atom quantum computer with 256 high-fidelity qubits. Further, IonQ reported a record revenue surge and Rigetti’s aggressive roadmap toward 1,000+ qubits by 2027, joining many of the other aggressive manufacturer estimates from these last few months, further underscoring that quantum computing is no longer an experimental pursuit.

Hardware-Integrated Quantum Error Correction Enters the Mainstream

A wave of hardware-driven breakthroughs is continuing to improve quantum error correction. Quantinuum’s Helios quantum computer achieved a record 99.9975% 1-qubit fidelity and enabling 48 logical qubits via its Guppy language, while IBM’s Nighthawk and Loom chips pushed computational complexity 30% beyond Heron by embedding fault-tolerant components directly into the hardware stack. Architectural improvements are not limited to superconducting platforms: IonQ’s room-temperature trapped-ion system achieved a 13:1 error correction overhead ratio. IQM’s Halocene platform introduced modular hardware explicitly engineered for scalable error mitigation.

On the error correction side, NVIDIA’s NVQLink is enabling real-time error correction by tightly coupling GPUs with quantum processors through CUDA-Q, partnering with nine U.S. national labs to accelerate classical decoding at scale. University of Tokyo’s novel QLDPC codes, combined with concatenated Steane codes and qudits, achieve constant space and polylogarithmic time overhead that reduces fault-tolerance overhead by up to 40% compared to traditional qubit-based approaches. Harvard and Princeton’s 448-atom neutral-atom arrays and Google’s dynamic surface codes enable real-time error detection and suppression below a critical threshold, while NTT and OptQC’s optical quantum collaboration leverages IOWN infrastructure to embed error correction into photonic communication from the start, targeting one million qubits by 2030 without cryogenic constraints.

The final piece of this new paradigm is algorithmic co-design: Cornell’s Multi-Core Circuit Decoder treats each logical gate as an independent decoding module, explicitly modeling correlated errors from entangling operations. This is complemented by the framework of quantum magic propagation via the bipartite magic gauge, which now allows researchers to predict where non-Clifford resources emerge in circuits, enabling targeted resource allocation. Together, these advances signal a new era: fault-tolerant quantum computing is no longer a distant goal but an engineered reality, built from the qubit up.

Quantum-Resistant Cryptographic Infrastructure Emerges as Global Priority

Saudi Aramco’s deployment of Pasqal’s 200-qubit system triggered alarms over quantum threats to blockchain, and China’s Hanyuan-1 secured an export order to Pakistan. This signals that state-backed quantum capabilities are becoming operational tools that are beginning to have geopolitical implications. These moves reflect a continuing global pivot where quantum advantage is no longer treated like a distant threat but an active strategic domain

The U.S. Congress introduced new bipartisan legislation to mandate federal agencies adopt post-quantum cryptography, and the Pentagon has elevated quantum sensing and secure communication to core battlefield capabilities, accelerating partnerships with national labs and startups. As far as tangible progress, TELUS integrated Palo Alto Networks’ post-quantum cryptography into its enterprise VPN service, offering protection against harvest-now-decrypt-later attacks and researchers have successfully embedded Dilithium and FALCON into a Raspberry Pi-based IoT-blockchain system running Ethereum’s Proof-of-Stake, showing that quantum-resistant signatures can function on low-power edge devices.

Simulating Many-Body Physics: Ion Traps, Waveguides, and Superconductors Unite

Simulation plays a critical role in Quantum development, providing a critical validation layer, ensuring algorithms can be tested at scales that mirror real-world hardware. Most notably, this month Jülich and NVIDIA created record-breaking 50-qubit quantum computer simulation on the JUPITER exascale system, surpassing their prior 48-qubit record from 2022 and demonstrating unprecedented scaling in quantum simulation capabilities.

Meanwhile, at Universität Heidelberg, Christof Wetterich and colleagues at Universität Heidelberg pioneered a groundbreaking approach to quantum simulation by leveraging classical electromagnetic waveguides to replicate the dynamics of multi-qubit quantum systems. This innovation circumvents the scalability bottlenecks of conventional quantum processors by using deterministic, room-temperature waveguide networks to emulate entanglement and coherent evolution, effectively turning classical wave physics into a programmable quantum simulator.

Quantum computers are also doing their fair share of simulating. Faisal Alam, Jan Lukas Bosse, Ieva Čepaitė, and their team achieved a landmark in quantum simulation by performing a programmable digital simulation of the 2D Fermi-Hubbard model on a 72-qubit superconducting quantum processor. This breakthrough enabled the first experimental observation of magnetic polaron formation and dynamical symmetry breaking in strongly correlated electron systems at scales unattainable by classical supercomputers. The team leveraged high-fidelity gate operations and error-mitigated readout techniques to maintain coherence across the lattice, demonstrating that quantum hardware has now crossed a critical threshold in simulating condensed matter phenomena with predictive accuracy.

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. There were no questions this month, which is a good thing given the girth of this month’s update!

It's Getting Spooky: Quantum Doom Clock, Halloween edition, October 2025

Richard Carback and Colton Dillion — Thu, 30 Oct 2025 21:04:39 GMT

It's Getting Spooky: Quantum Doom Clock, Halloween edition, October 2025

GM frens, this is the Quantum Doom Clock with Colton Dillion and Rick Carback, the founders of Quip Network, building the world's shared quantum computer.

This Halloween season we got a treat with concrete proof that quantum computers are not tricking us via an experiment using Einstein’s spooky action at a distance paradox. Researchers have now built a functional "quantum lie detector" that confirms these machines operate through genuine quantum mechanics—not classical mimicry.

Using Einstein’s Spooky Action Paradox to Confirm Quantum Operation

Researchers have developed a quantum lie detector that confirms large-scale quantum systems are not simulating classical behavior but genuinely exploiting entanglement. The team, led by scientists at the University of Leiden, engineered a program that performs computations impossible under classical physics and validated its quantum nature using Bell’s inequality tests across 73 qubits. This experiment closes a long-standing loophole in quantum verification, proving that quantum computers are not just fast classical machines but true quantum devices. University of Leiden’s quantum lie detector demonstrates that quantum mechanics governs these systems at scale.

The breakthrough builds on decades of foundational work in quantum foundations, with the same principles that Einstein called “spooky action at a distance” now serving as a diagnostic tool. The Bell test protocol was adapted to run on real hardware, not just theoretical models. This validation enables the design of quantum algorithms with guaranteed non-classical advantages and paves the way for quantum-secure communication protocols rooted in physical law, not computational hardness assumptions. The Leiden team’s framework is now being adopted by quantum hardware providers to certify machine authenticity before deployment.

Nobel Recognition of Foundational Quantum Technologies

The 2025 Nobel Prize in Physics was awarded to John Clarke, Michel H. Devoret, and John M. Martinis for their pioneering experiments in macroscopic quantum tunneling and energy quantization in superconducting circuits. Their 1980s work laid the physical foundation for today’s qubits, proving that quantum effects persist at macroscopic scales—a radical idea once dismissed as impossible.

The Nobel committee’s statement explicitly tied these discoveries to the rise of quantum computing, citing that their work “demonstrated that quantum mechanical properties can be made concrete on a macroscopic scale.” This formal validation elevates the field from speculative tech to established physics, accelerating academic recruitment and government funding for quantum infrastructure.

Quantum Advantage and Real-World Applications

Google’s Willow processor achieved quantum advantage not on synthetic benchmarks but on real-world molecular dynamics problems, outperforming classical supercomputers by 13,000x using their "Quantum Echoes" algorithm. This marks the first time a quantum computer solved a physically meaningful problem—modeling electron behavior in complex molecules. Google’s Quantum Echoes algorithm will enable accurate simulations of carbon capture materials and drug interactions previously intractable to classical methods.

Meanwhile, a number of real-world applications are now being deployed:

IonQ’s QC-AFQMC simulations are now being used by energy firms to model catalyst efficiency for hydrogen production.
UC Merced’s national effort on chiral molecules further proves that quantum computers are solving real chemical puzzles.
KAIST also developed energy storage materials using quantum computers for next-generation battery materials and carbon capture applications.
In the financial world, HSBC is now using Quantum Computing for bond trading. To our knowledge, this is the first real-world quantum advantage in live financial markets for portfolio optimization in production.

These developments are confirming what we have been saying since spring that quantum computing is here now. We are also starting to see a major divergence among quantum computing companies: Some are productizing while others are chasing further technological advances. It is unclear what strategy will pay off.

Major Breakthroughs in Quantum Error Correction and Fault Tolerance

QuEra’s algorithmic fault tolerance (AFT) technique reduces quantum error correction overhead by 100x, enabling logical qubits to be constructed with far fewer physical qubits. This breakthrough transforms error correction from a prohibitive resource drain into a scalable process, making fault-tolerant quantum computing feasible within five years. QuEra’s AFT framework has already been integrated into their neutral-atom quantum processors.

Meanwhile, Caltech’s 6,100-qubit neutral-atom array achieved nearly 13 seconds of entanglement coherence—a record that shatters previous limits. Caltech’s long-lived entanglement proves that qubit stability is no longer the bottleneck. Diraq’s silicon qubits also surpassed 99% two-qubit gate fidelity, demonstrating that scalable architectures can achieve the precision required for fault tolerance. These advances collectively dismantle the largest barrier to practical quantum computing.

Continued Commercial Deployments

D-Wave’s Advantage2 system has been deployed across Europe through the Q-Alliance partnership. D-Wave’s Advantage2 deployment is being used for logistics optimization in real-time supply chains. EPFL’s quantum sensors have entered the medical diagnostics market, proving that quantum technologies are no longer confined to labs.

IBM’s Quantum System Two is now operational in Spain and Japan, offering enterprise clients guaranteed uptime and SLAs for quantum workloads. IBM Quantum System Two is the first modular quantum computer deployed outside research labs with full commercial support. Also, China’s Zuchongzhi 3.0-class system is now accessible via cloud platforms to global pharmaceutical firms.

Google Quantum AI’s acquisition of Atlantic Quantum and IonQ’s $2 billion funding round from Heights Capital Management signal that quantum hardware is now a strategic asset. Google’s acquisition of Atlantic Quantum brings critical superconducting qubit expertise in-house, while SC Ventures and Fujitsu’s Project Quanta is building a quantum-powered financial modeling platform. These moves confirm that quantum computing is transitioning from research to revenue.

Other News

Time Crystals Could Power Future Quantum Computers - Researchers demonstrated time crystals enabling continuous quantum operation without energy dissipation
EeroQ Demonstrates Single-Electron Quantum Control Above 1 Kelvin - Major breakthrough achieving quantum control at >1K (vs typical ~0.01K), dramatically reducing cooling requirements
6,000-Qubit System Operating at Room Temperature - Scientists built a room-temperature quantum system with 100x error reduction
Infleqtion Integrates SLM's MEMS Modulator for Microsecond Qubit Control - Silicon-germanium MEMS enables individual qubit addressing at unprecedented speeds
QuantWare's Contralto-A Wins Quantum Effects Award 2025 - Leading quantum error correction capabilities, delivered Tenor QPU to Italy
Quantum Brilliance's 'Quoll' Named TIME Best Invention 2025 - Diamond-based qubits enabling room-temperature, compact edge quantum computing
Harvard’s continuous-operation system proves that large-scale quantum systems can run without interruption. IBM’s 156-qubit Heron chip and D-Wave’s Advantage2 deployment show that scalability is no longer theoretical—it is being engineered in parallel across architectures.
FirstQFM Secures €1.2M for Quantum Foundation Models - Developing proprietary foundation models specifically for quantum computing

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

Q: What is it with everyone claiming to be the first to achieve quantum advantage?

A: We understand your confusion. The most recent Google announcement is claiming to be the first to achieve quantum advantage on a real-world problem, after claiming something very similar last November with Google Willow. D-Wave has also repeatedly claimed supremacy and advantage on real-world problems, and IBM has also claimed supremacy on real-world problems.

The key is that these claims are now being made on real-world problems that are verifiable by classical computers, not merely synthetic benchmarks, or problems that can only be computed and verified by quantum computers. In our opinion, D-Wave was actually first to have a verifiable quantum advantage, but theirs is an annealing machine, not a Gate-based machine. Google has a valid case to claim a gate-based quantum advantage, but we will not know for sure until the public can get access to it.

When hearing such claims, the key question to ask is when we will start seeing real economic impact from quantum computing, or "when is this going to prod"? The answer in D-Wave’s case is now, and in Google’s case is unknown, but likely within the next couple years. Which leads us to the next question...

Q: Is quantum computing really commercially viable today?

A: Yes, we certainly think so. The deployments are the main evidence, if they were not ready then we would not see IBM, D-Wave, and other players investing so heavily in publicly accessible quantum hardware. The recent announcements also point to quantum systems now offering real customer use cases in pharmaceuticals, finance, and logistics. As we commonly cover in this newsletter, we are seeing repeated claims of quantum computers used in production, not just research.

Quantum Capital Explodes, September 2025

Richard Carback and Colton Dillion — Mon, 15 Sep 2025 10:00:00 GMT

Quantum Capital Explodes, September 2025

GM frens, this is the Quantum Doom Clock with Colton Dillion and Rick Carback, the founders of Quip Network, building the world's shared quantum computer.

The highlight this month is that the market is not just betting on quantum—it is pouring billions into it. Capital is flowing like water, governments moved from observation to action, and the race for quantum supremacy became a national infrastructure priority. We are not yet at the stage where your cab driver knows about it, but you would be justified in thinking we may be entering a bubble, but it is completely unclear how much value quantum will provide!

Massive Capital Infusion, Market Valuation Surge, and Government Strategic Interest

PsiQuantum’s $1B Series E and $7B valuation mark the first time a quantum company reached unicorn status without shipping a single production machine. Meanwhile, Quantinuum closed $600M at a $10B pre-money valuation as enterprise clients lock in quantum access contracts.

IQM’s $320M Series B led by Ten Eleven Ventures signals U.S. capital flowing into European quantum infrastructure. IonQ’s $1.075B acquisition of Oxford Ionics is part consolidation, part vertical integration of trapped-ion control stacks.

Most surprising, to us, is Rigetti’s $5.3B market cap now exceeds the combined revenue of every quantum startup on Earth. Investors are not waiting for industry value today, moreso speculating there is a the path to it.

Governments are matching this capital surge. Japan’s OQTOPUS homegrown system is the nation’s first fully homegrown system, while the U.S. NSF launched its $16M National Quantum Virtual Laboratory to accelerate algorithm testing. New Mexico’s Quantum Frontiers Project and Andhra Pradesh’s IBM 133-qubit deployment signal a global race for quantum sovereignty. Governments are no longer treating these as R&D projects, more like sovereign tech assets.

Quantum Internet and Networked Quantum Systems Take Shape

IonQ’s demonstration of quantum frequency conversion to telecom wavelengths is the first step toward a quantum backbone over existing fiber. This does not look like a lab experiment but infrastructure engineering. The same breakthrough enables long-haul quantum key distribution without cryogenic repeaters, a game-changer for secure government and financial networks.

Quantum Motion Technologies’ silicon CMOS-based quantum computer is now deployed at the UK’s National Quantum Computing Centre, proving quantum hardware can be built with standard semiconductor processes. This scalability enables distributed quantum nodes that can connect via optical links—exactly what the quantum internet needs. The EU’s LUMI-Q consortium is already integrating these nodes into pan-European quantum networks, turning theoretical protocols into operational reality.

Quantum LEGOs and Living Qubits

Quantum Motion’s silicon CMOS architecture introduces quantum LEGO chip modules. Each qubit module is fabricated using 300-mm wafers, allowing modular scaling like building blocks. This approach decouples qubit quality from system size, letting you add more units without re-engineering the entire stack. IBM’s Heron roadmap mirrors this, with chiplets that can be stacked and cooled in parallel.

The other interesting architectural news was University of Chicago’s biological qubits using engineered proteins as qubits that operate at room temperature. These qubits are tiny biological modules that can interface with living systems.

Hybrid Quantum-Classical Architectures Become Industry Standard

IBM and AMD’s “quantum-centric supercomputing” partnership is the new standard. Their joint architecture integrates quantum processors directly into exascale workflows—not as add-ons, but as co-processors. This isn’t theoretical: Oak Ridge’s Quoll system now runs quantum algorithms alongside Frontier’s AI workloads in real time, accelerating materials discovery by 40x.

Microsoft’s analog optical computer for AI optimization is now deployed in Azure Quantum, solving combinatorial problems 100x faster than classical GPUs. Meanwhile, Stanford’s quantum router enables superposition-based routing across quantum networks—allowing packets to explore multiple paths simultaneously. This isn’t networking. It’s quantum state routing.

Post-Quantum Cryptography (PQC) Transition Accelerates Under Government Mandate

NIST’s draft Cybersecurity White Paper 48 now outlines practices to support migration from the current set of public-key cryptographic algorithms to replacement
algorithms resistant to quantum computer-based attacks. IBM demonstrated breaking a 6-bit ECC key using a 127-qubit system, proving the fundamentals that the algorithm itself is no longer theoretical. Fortunately, the world is taking the issue seriously, with El Salvador moving all BTC reserves to newer addresses with better safety from quantum threats.

Error Mitigation Outpaces Qubit Count as Key Metric

IBM’s T-REx technique lets a 5-qubit device outperform a 156-qubit noisy system in energy calculations—by turning noise into signal. This isn’t error correction—it’s error exploitation. The same approach is now being used in quantum chemistry simulations at Argonne National Lab.

Rice University and NIST’s tomography algorithms now reconstruct quantum states from noisy measurements with 98% fidelity—making qubit count irrelevant. The latest benchmark stack for D-Wave, meanwhile, are showing the rapid progress of analog quantum optimisation with quantum annealers.

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

Q: Can we really build quantum internet with existing fiber?

A: Yes. IonQ’s telecom wavelength conversion means you don’t need new cables—just quantum repeaters. The EU’s LUMI-Q consortium is already testing this across 12 countries. Your next secure bank transfer might be encrypted with quantum keys sent over your existing broadband line. The infrastructure is already there. We just need to upgrade the encryption.

Q: If error mitigation beats qubit count, does that mean we don’t need million-qubit machines?

A: Not at all. We need both. Error mitigation builds better qubits and breaking RSA requires logical qubits which will need many physical ones. The breakthroughs we are seeing now accelerating progress, not alternate paths. They get us to cryptographically relevant quantum computers faster.

Don't "Neglecton" Quantum Architectures, August 2025

Richard Carback and Colton Dillion — Sat, 23 Aug 2025 22:30:00 GMT

Don't “Neglecton” Quantum Architectures, August 2025

The highlight of this month is Fujitsu's official announcement of their 10,000-qubit quantum computer project, targeting completion by 2030. This isn't just another research milestone—it's a fully funded, government-backed industrial project that signals quantum computing's transition from laboratory curiosity to strategic national infrastructure.

Chiplet Architectures Could Lead the Scaling Revolution

It is not just about qubit counts—it is about architecture. Rigetti's 36-qubit Cepheus-1-36Q system represents the industry's first practical success with chiplet-based quantum computing. By achieving a 2x reduction in two-qubit gate error rates compared to their previous 84-qubit monolithic system, Rigetti is following in Google Willow's footsteps and showing a modular quantum architecture that should deliver measurably better performance that you can use today.

We think maintaining coherence and control fidelity as systems grow larger is the name of the game. Instead of building ever-larger monolithic quantum processors that become increasingly difficult to control, architectures like these chiplets are an option to build smaller, high-fidelity quantum processing units to work together seamlessly.

Speaking of monoliths, QuamCore secured $26 million in Series A funding to build what they claim will be the first million-qubit quantum computer. Their approach addresses the cabling bottleneck that has historically limited quantum system scaling by integrating qubit control components directly into the cryogenic environment.

Japan Goes All-In on Quantum Sovereignty

Japan made a bold statement this month with two major quantum announcements that signal the country's commitment to quantum independence. First, Japan launched its first fully homegrown quantum computer, developed entirely with domestic components and software. This achievement reduces Japan's dependence on foreign quantum technologies and demonstrates the country's growing quantum capabilities.

As we mentioned in the highlight, Fujitsu's 10,000-qubit quantum computer project, officially launched with backing from Japan's NEDO organization. The system will operate with 250 logical qubits using Fujitsu's "STAR architecture" and target completion by fiscal 2030. This isn't just a research project—it's a fully funded industrial initiative aimed at making Japan a global leader in fault-tolerant quantum computing.

The project will focus on four critical scaling technologies: high-precision qubit manufacturing, chip-to-chip interconnect technology, high-density packaging with low-cost qubit control, and advanced quantum error correction decoding. Fujitsu's roadmap extends beyond 2030, targeting 1,000 logical qubits by 2035 through integration of superconducting and diamond spin-based qubits.

Error Correction Breakthroughs Continue

The quantum error correction landscape experienced several major breakthroughs this month, bringing fault-tolerant quantum computing closer to reality.

USC researchers made headlines with their discovery of "neglecton" particles—previously overlooked quantum states that could revolutionize error correction approaches. These particles offer more stable and controllable qubits, potentially solving some of quantum computing's most persistent coherence challenges.

Meanwhile, CERN achieved a physics breakthrough by creating the world's first antimatter qubit, trapping antiprotons for quantum information processing. While still experimental, this development opens entirely new pathways for quantum computing that could be immune to certain types of environmental interference.

On the practical side, Terra Quantum introduced QMM-Enhanced Error Correction, validated on IBM hardware. Their approach demonstrates measurable improvements in quantum algorithm reliability, bringing error-corrected quantum computing closer to commercial viability.

Quantum Computing Quick Hits: Systems Scale Up

Several new quantum systems and partnerships were announced this month, showing the industry's continued momentum toward practical applications:

New Systems and Deployments:

IQM's 54-qubit Emerald QPU launched on Amazon Braket, expanding cloud-based quantum access
Keysight installed the world's largest commercial quantum control system supporting over 1,000 qubits at Japan's AIST G-QuAT Center
Intel launched pencil-eraser-sized spin qubit chips to expand quantum computing capabilities
University of Chicago researchers created functional protein qubits for quantum sensing in living cells

Major Partnerships and Funding:

Microsoft and Atom Computing announced plans to build the world's most powerful quantum computer in Denmark
IonQ partnered with Oak Ridge National Laboratory for quantum power grid optimization
Amazon disclosed a $36.7 million stake in IonQ, signaling major cloud provider commitment

Quantum-AI Integration Accelerates

The convergence of quantum computing and artificial intelligence reached new milestones this month, with practical applications beginning to emerge from research laboratories.

Los Alamos National Laboratory published breakthrough research on quantum machine learning pathways, demonstrating how quantum computers can enhance pattern recognition and optimization algorithms. Their work shows quantum advantage in specific machine learning tasks, particularly those involving complex optimization landscapes.

The Philippines' Kipu Quantum also made headlines with their Quantum Feature Mapping (QFM) technology, which improves AI accuracy in sensitive domains by leveraging quantum computational advantages for feature extraction and pattern recognition.

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

Q: With Fujitsu's 10,000-qubit announcement and chiplet breakthroughs, how much closer are we to breaking encryption?

A: They are not the only ones pushing for logical qubits well past the point necessary to break crypto. The combination of architectural improvements (chiplets), scaling commitments (10,000+ qubits by 2030), and error correction advances suggests we're moving faster than many expected, but from what we can tell we are right on track. Fujitsu's project isn't just research—it's a fully funded industrial initiative with government backing, which is exactly what we'd expect to see.

Now Quantum States are Magical, July 2025

Richard Carback and Colton Dillion — Wed, 23 Jul 2025 10:00:00 GMT

Now Quantum States are Magical, July 2025

Quantum progress continues apace. From unconditional exponential speedups to 1,000x error reductions, the quantum computing industry is no longer crawling—it's sprinting toward cryptographic relevance with regular, sustained advances that is bringing quantum dominance from "soon" to "imminent."

The highlight of this month is the logical-level magic state distillation by researchers working with Quantinuum. A magic state is a quantum state that can be reliably used for fully general quantum computation, and this report may achieve the first universal, fully fault-tolerant quantum gate set with repeatable error correction. They prepared "magic" states with an error rate of just seven mistakes per 100,000 operations, and simulations suggest they could reach just six errors per 10 billion operations on larger systems. Really promising if true, hopefully it is not just magic!

More Quantum Advantage Claims

Hot on the heels of D-Wave’s results, USC researchers have demonstrated an unconditional exponential quantum scaling advantage using two 127-qubit IBM Quantum Eagle processors. Published in Physical Review X. Like D-Wave's results, it lacks the caveats we usually see with these claims.

The team tackled a variant of Simon's problem with restricted Hamming weight, demonstrating genuine exponential speedup for circuits up to 58 qubits. As Daniel Lidar from the research team notes, "There have previously been demonstrations of more modest types of speedups like a polynomial speedup. But an exponential speedup is the most dramatic type of speed up that we expect to see from quantum computers."

This USC announcement is not alone. IonQ and Kipu Quantum solved the most complex protein folding problem ever on quantum hardware with 12 amino acids in the problem set. IonQ simulated neutrinoless double-beta decay using 32 qubits, unlocking new physics previously beyond classical reach. Finally, for those who need more existential dread in their life, researchers used a 5,564-qubit D-Wave system to model false vacuum decay that is literally simulating the death of our universe.

Error Correction Goes Parabolic

Microsoft dropped a bombshell with their 4D geometric codes that slash quantum errors by 1,000x. These codes reduce error rates so much that they require 5-6x fewer physical qubits per logical qubit. Microsoft's Krysta Svore promises "50 logical qubits in the near term, with the potential to scale to thousands."

Meanwhile, QuEra, Harvard and MIT demonstrated logical-level state distillation on neutral atoms, keeping the entire process within the error-corrected layer. Oxford physicists set yet another record with a quantum logic operation error rate of just 0.000015%. Oxford's new record is only one error in 6.7 million operations, nearly 10x better than their previous record.

Better Quantum through Silicon?

While superconducting and ion trap systems grab headlines, silicon-based quantum computers are quietly revolutionizing the field with their promise of manufacturing scalability and room-temperature operation. Xanadu's breakthrough creating GKP (Gottesman–Kitaev–Preskill) states directly on a silicon chip marks the first time error-resistant quantum states have been generated using conventional chip manufacturing. As researchers noted, this suggests "error-correcting quantum states could be produced with the same tools used to manufacture conventional computer chips."

Dynamically corrected gates in silicon singlet-triplet qubits reduced infidelities by 3x, achieving gate fidelities above 0.99. Spin-qubit control with milli-kelvin CMOS demonstrated that cryo-CMOS can efficiently perform universal logic operations with about 100,000 transistors, opening prospects for scalable "chiplet-style" control architectures.

Even more promising, researchers executed four-qubit variational algorithms in silicon photonics with integrated entangled photon sources at room temperature. This convergence of silicon manufacturing expertise with quantum computing could accelerate deployment timelines dramatically.

A Number of New System and Funding Announcements

Several new systems were announced with varying levels of qubits this month:

China's ez-Q Engine 2.0 supports over 1,000 qubits, positioning China just behind IBM and Atom Computing
Rigetti's 36-qubit system achieved 99.5% median two-qubit gate fidelity—a 2x error reduction from their previous 84-qubit system
IQM Emerald launched on AWS Braket with 54 qubits
Russia unveiled a 50-qubit cold ion quantum computer
SpinQ expects to deliver a 100-qubit system by year's end

It is important to note that many of these are not simply the lab demonstrations we are used to seeing. Nord Quantique claims their compact physical qubit with built-in error correction could scale to 1,000 qubits by 2031 while consuming 2,000x less power than supercomputers. QuiX Quantum secured €15 million after becoming the first to sell 64-qubit photonic systems commercially, and QEDMA raised $26 million for quantum noise resilience.

As for lab results, this month had a few:

HOLO's quantum breakthrough claims to boost multi-qubit efficiency by 50% while cutting classical communication by 40%
Chalmers engineers built a pulse-driven qubit amplifier that's 10x more efficient
NPL's quantum circuit imaging can locate individual defects in functioning quantum circuits
Aalto University achieved 1 millisecond coherence time for transmon qubits, crushing the previous 0.6ms record

Even the DIY community is getting involved, with hackers building NMR quantum devices on the cheap.

Crypto Pioneers Take Notice

While some in the crypto space remain dismissive of the quantum threat, some of the industry's foundational figures are making strategic moves. David Chaum, a renowned pioneer in cryptography and privacy technology, is providing his expertise to a new strategic crypto push led by tech figure Fred Krueger.

This development is notable given Krueger's past skepticism about cryptocurrency valuations and scrutiny of major players' approaches. Chaum's involvement suggests that the original architects of digital privacy are not ignoring the shifting technological landscape. When a titan of cryptography makes a new strategic move, it’s a signal that the game is changing.

Each breakthrough compounds the others. Better coherence enables better error correction. Better error correction enables larger circuits. Larger circuits enable real applications. It's a virtuous cycle spinning faster every month.

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

Q: With all these error correction breakthroughs, how close are we really to breaking encryption?

A: We are not updating the clock yet as a lot of this news is still in the lab, but note that this kind of progress is expected for the doom clock estimates to be accurate. The evidence now is crystal clear that we are likely looking at cryptographically relevant machines before 2030. Our doom clock may need another adjustment soon.

Q: Should I be worried about the universe ending in a false vacuum decay?

A: The D-Wave simulation of false vacuum decay is fascinating physics, but don't lose sleep over it. Be more worried about Bitcoin keys, and be even more excited about the advances that will come from this technology. The same quantum computers modeling cosmic catastrophes will be unlocking the secrets of materials science, drug discovery, and countless other fields much sooner than the end of the universe.

The Quantum Threat Accelerates, June 2025

Richard Carback and Colton Dillion — Wed, 18 Jun 2025 14:18:18 GMT

The Quantum Threat Accelerates, June 2025

Just days after our May newsletter, the quantum threat timeline compressed dramatically. Craig Gidney dropped a bombshell update showing that factoring 2048-bit RSA might require less than 1 million qubits, not the 20 million he previously thought. That's a 20x improvement, putting us squarely on track with our doom clock projections made earlier in the year. As New Scientist reports, this is not just an incremental improvement—--it is a fundamental leap that brings the quantum threat from "someday" to "soon", which we have been saying for some time now!

Physical Qubit Requirements Continue to Drop

The path to those million qubits is being paved by dramatic improvements in error correction. IBM and partners demonstrated the power of partial fault tolerance in Nature Communications, using the Iceberg error detection code to improve QAOA performance for problems with up to 20 logical qubits on trapped-ion hardware. This represents the largest universal quantum computing algorithm protected by error detection on practical applications to date.

Meanwhile, Xanadu achieved a significant milestone by generating photonic qubits on an integrated chip platform—the first-ever demonstration of such qubits on a chip, with their experiments showing critical features necessary for fault tolerance. Yahoo Finance notes this validates a key pillar of bosonic architectures for photonic quantum computing.

The race for better qubits is also producing stunning results. Caltech researchers led by Professor Manuel Endres demonstrated "hyper-entanglement" in neutral atoms by simultaneously controlling their motion and internal energy states—a first for massive particles. This breakthrough expands the information capacity per atom and introduces motion as a controllable quantum resource.

The crown jewel improvement here comes from Oxford. As New Scientist reports, Molly Smith, Aaron Leu, and Mario Gely created a single-qubit gate that only produces errors once in about 10 million cases. As Leu notes: "The probability of being struck by lightning in a year is about three times higher than the probability that this qubit makes an error." When individual operations become this reliable, the path to fault-tolerant quantum computing becomes dramatically clearer. That kind of reliability is on par with classical computers!

Qubit Counts Scale on Target

The exponential scaling we have been tracking on the quantum doom clock continues relentlessly. This month brought a cascade of announcements that would have seemed like science fiction just years ago.

IBM dropped perhaps the most notable announcement regarding their path to IBM Quantum Starling—projected to be the first large-scale, fault-tolerant quantum computer. Their breakthrough research charts a viable path to systems running 200 logical qubits by 2028. This timeline is pretty close to Oxford Quantum Circuits, who is also targeting 200 logical qubits by 2028 and then upwards of 50,000 logical qubits by 2034, requiring several million physical qubits using their dual rail 'Dimon' technology.

As for less ambitious timelines, Nord Quantique promises a 1,000-qubit machine by 2031 that they claim could make traditional HPC obsolete, with the ability to crack RSA-830 in an hour while slashing energy use by 99%. Xanadu's vision offers a different form of scale: a quantum computing data center by 2029 with thousands of 24 qubit quantum server racks networked together for fault-tolerant, universal quantum computing.

While these promises excite, actual deployed systems are also showing steady progress:

Infleqtion shipped a 500-qubit neutral atom system to Japan's Institute for Molecular Science
Pasqal sold a 100-qubit QPU to Canada's Distriq innovation zone
Quandela launched Belenos, a 12-qubit photonic system delivering 4,000x more computing power than its 2022 predecessor
QuEra deployed its first quantum computer outside its labs at Japan's AIST

The pattern is clear: qubit counts are scaling exponentially, exactly as our quantum doom clock predicted. More importantly, these aren't just press releases—they're actual systems being built, shipped, and put into production.

The Steady March From Lab To Market

As we have said before, the quantum computing industry is experiencing a fundamental shift from research curiosity to commercial reality. This month's developments show quantum technology moving decisively into the marketplace. Here's the rundown on the latest developments:

Quantum Computing Inc. shipped its first commercial entangled photon source to a leading research institution in South Korea.
SemiQon demonstrated large-scale characterization of quantum dot qubits using ultra-low-power cryogenic CMOS technology.
Pasqal's expansion into manufacturing with a new Canadian facility signals the industry's maturation.
IBM and Lockheed Martin's collaboration on quantum chemistry for aerospace demonstrates quantum computing solving real industrial problems.
Researchers demonstrated using a 36-qubit trapped-ion quantum computer to solve protein folding problems involving up to 12 amino acids—the largest such demonstration on real quantum hardware.
Quantum reservoir computing achieved competitive accuracies on benchmark tasks including spoken-vowel and MNIST digit classification. When given access to quantum correlations, accuracies improved by over 20 percentage points compared to classical approaches.
Researchers successfully sent quantum messages 250 kilometers over standard fiber-optic cables—the first time quantum information has been shared over normal internet infrastructure.
Nvidia's opening of a global quantum research center dedicating H100-powered supercomputers to quantum validation shows how seriously the tech giants are taking hybrid quantum-classical computing.

Crypto Conversations Intensify

MicroStrategy's Michael Saylor dismissed quantum concerns on CNBC's Squawk Box as "mainly marketing from people that want to sell you the next quantum yo-yo token." His confidence that even legitimate quantum threats from tech giants "won't be released" stands in stark opposition to everything we are about and are tracking. We think this plays out quite a bit differently.

This dismissal comes even as BlackRock updated their Bitcoin ETF prospectus to explicitly include quantum computing as a risk factor. When the world's largest asset manager acknowledges the threat while Bitcoin's loudest advocate dismisses it, investors face a confusing landscape.

Indeed, even academic perspectives are shifting. Whereas the teams from EPFL and the Flatiron Institute initially pushed back with a classical simulation that replicated aspects of D-Wave’s results from last month using a variational Monte Carlo method, those solutions fell far short of overturning D-Wave's results. The real-world implications of that are now becoming clearer and we are continuing to see more useful applications emerge as a result.

Even long-time skeptics are beginning to acknowledge the substance of recent developments. Perhaps most telling is the shift from long-time quantum skeptic Sabine Hossenfelder. Her recent explainer video acknowledges that "a recent series of quantum computing developments might mean that commercially useful quantum computers could be just a few years off."

Coming from someone who has consistently deflated quantum hype, her assessment that quantum computers are "becoming dangerous faster than we thought" carries significant weight. When skeptics start taking the threat seriously, it's time for the crypto community to move beyond denial.

Frequently Asked Questions

Q: Is the million-qubit threshold for breaking RSA really that much closer than 20 million?

A: Yes, and it's not just about raw numbers. Gidney's revision shows that improved algorithms can dramatically reduce hardware requirements. Combined with this month's error correction breakthroughs and Oxford's 1-in-10-million error rate, the path to cryptographically relevant quantum computers is shortening from multiple angles simultaneously.

Also, it is worth noting that we have been predicting this publicly since the beginning of the year.

Q: How can companies claim to compete with such different qubit counts? Is China really ahead with 1,000 qubits?

A: Qubit count alone is misleading—quality matters more than quantity. A high-fidelity 100-qubit system with good error correction can outperform a noisy 1,000-qubit system.

On its face, it is hard to evaluate many of these systems as they lack publicly verifiable testing. You can focus on metrics like quantum volume, error rates, and actual demonstrated applications rather than raw counts, but it is really impossible to say without hard results.

Q: Should I actually worry about my Bitcoin/crypto given Saylor's dismissal?

A: When BlackRock adds quantum risk to official documents while active developers create defensive protocols (QRAMP, BIP-360, etc -- see our previous newsletters), dismissing the threat seems unwise. The question is not whether quantum computers will threaten current cryptography, but when. Starting migration to post-quantum protections before it is urgent is prudent risk management.

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

Quantum Advantage Begins to Flower, May 2025

Richard Carback and Colton Dillion — Mon, 19 May 2025 10:00:00 GMT

Quantum Advantage Begins to Flower, May 2025

GM frens, this is the Quantum Doom Clock with Colton Dillion and Rick Carback, the founders of Quip Network, onramping the world to quantum computing subnets protected by post-quantum cryptography on every chain. As April's quantum showers give way to May's blooming quantum advantage, we put together this site and newsletter because the clock is ticking toward the day when your assets can be stolen by hackers with sufficiently powerful quantum computers. Check out CoinDesk’s coverage of the team’s view on the quantum threat.

Quantum Advantage Emerges: Real-World Applications

The belle of the ball this month has been D-Wave’s quantum supremacy announcement from March being backed up with a paper published in Science with Oak Ridge National Labs on April 30th. While claims of “quantum supremacy” have a murky history, this one looks legitimate with convincing evidence that their quantum computer performs magnetic materials simulation faster than regular computers. This result is further backed up by another paper published in physical review letters with similar results for spin-glass problems from researchers at USC. They even have the academics admitting to the slightly less aggressive term of “quantum advantage” in the coverage and the editors note at the top of the article!

In other words, the promise of quantum advantage is starting to show concrete signs, with quantum computers beginning to outperform classical machines in specific, complex tasks. Other example applications include:

The development of decoded quantum interferometry (DQI), which cannot run on current QPUs but has application to a broader class of optimization problems which has researchers excited about the future.
A drug discovery project by IBM, Insilico Medicine, and QuEra using quantum computers combined with AI. The idea is to identify potential cancer drugs and accelerate the search for treatments for conditions like myotonic dystrophy. The work is proving feasibility even if it is far from quantum supremacy.
Rigetti demonstrated the potential for power grid optimizations. Their quantum preconditioning technique enabled the solver to achieve 99.95% accuracy in four times fewer iterations than the original problem. This speed, even with imperfect fidelities, might offer an advantage for real-world scenarios where time is often a critical constraint, even if classical methods reach higher accuracy with more iterations.

The meta in quantum is definitely shifting its focus from theoretical "exhibition" problems to practical, real-world applications. Reflecting this trend, the U.S. House has dipped into the action with the bipartisan Quantum Sandbox for Near-Term Applications Act to accelerate quantum technology deployment through public-private cloud-based testbeds. Similarly, DARPA jumped in with its own program to scale quantum computers. These developments are a nice change from recent months when it was China’s investments dominating the news.

A Dose of Humility: Keeping it Real

While all this progress is undeniable, we encourage readers to keep a skeptical eye when you see news in this space. The most promising QPUs will not be sitting on your desktop but in a datacenter built for a supercomputer. The competition is definitely with the supercomputer market, and the fact that Google's 53-qubit computer can be simulated with 1,432 GPUs reminds us that classical computing is still a formidable competitor and hybrid approaches are crucial for the foreseeable future.

The news around D-Wave was not all absolute progress. Their team published a blockchain “Proof of Quantum Work” with interesting ideas, but which would require all participants to operate a quantum computer. That kind of requirement defeats the idea of “hard to find, cheap to verify” type of problem you need for that kind of proof system to have a secure blockchain. Our fearless leader Rick pointed this out among other problems with their claims.

More generally, all this talk of “Quantum Supremacy” is getting tired. The debate is moving beyond simple qubit counts to focus on “return on investment" and concrete business value. We feel the same about it. More practical and less hype-driven approaches to evaluating quantum technology need to be the norm moving forward.

Just take a look at this result from University College London which claims to create scalable manufacturing processes for neutral atom architectures, but they’re individually placing atoms in a grid by hand at nanoscopic scale! Doesn’t sound that scalable to us.

Quantum Computing Quick Hits: The Field Blossoms

Nonetheless, qubit counts continue to increase, so much so that New Scientist proposes that we double our entangled qubits every year:

Fujitsu Installed 256-Qubit Computer at RIKEN
IQM deployed a 5-qubit system in Poland and committed to delivering world-leading 150-qubit and 300-qubit systems to Finland by 2026 and 2027
Rigetti came back to life with a 36-qubit computer, and announced a partnership with Norma to deliver an 84-qubit cloud service
QuantWare creates a 3D chip architecture allowing better connectivity between qubits, supporting 100 to 200 qubits depending on platform architecture
A group of researchers published in Nature on their photonic qudit results, increasing the representable states up from the 2D qubit up to 3D qutrits and 4D ququarts
Researchers at university of Bristol show that qubit counts can be traded off for computational speed
Quantinuum claims to 10x their quantum volume over the last year, a measure of the useful computation that can be done with their qubits
China’s Origin quantum computers demonstrate qubit counts of over 500.

And quantum computers continue to get more accessible:

Google Cloud makes Pasqal neutral atom processors available to the public
Equal1 releases a rack-mounted quantum computer for deployment in high-performance computing environments and data centers
Nvidia opened up a global research center for quantum computing and hybrid applications, dedicating a supercomputer powered by H100s to validating results
MIT published a new method for quantum communication between photonic quantum computers over a short superconducting waveguide
Scientist sent a quantum state over 158 miles of fiber optic cable in existing infrastructure, paving the way to quantum data centers

This is really bad news for systems that are still vulnerable to quantum attacks, but fortunately defensive development has also seen some progress.

Quantum Security Updates: Addressing the Threat

The quantum threat to current cryptography remains a serious concern, and this month saw continued action preparing for a post-quantum world. You know it’s serious because Blackrock updated their Bitcoin ETF prospectus to include the advent of quantum computing as a threat to investors.

Fortunately, we have people like the Bitcoin devs behind the QRAMP improvement proposal and Project 11 joining BIP-360 trying to move the conversation in a positive direction. We’d be lying if we didn’t admit that we consider ourselves on the leading edge of this movement as well.

In brighter news, traditional networking stacks are already ahead of us when it comes to upgrading their protocols, as OpenSSH 10 just released their post-quantum cryptography solutions. This is bullish news for getting to use our existing infrastructure for trusted connections between peers Of course, security is an ever-evolving space that you have to keep an eye on, and even quantum computer operators are not immune to threat vectors. Don’t let your guard down!

Frequently Asked Questions

Is D-Wave really capable of factoring a 2048-bit RSA key?

Initial reports of "A First Successful Factorization of RSA-2048 Integer by D-Wave Quantum Computer" were found to be far from breaking real-world encryption, as the underlying trick was to use keys with consecutive factors. While there are infinitely many of these keys, the odds that your keys are one of them is vanishingly small.

What’s up with that huge bitcoin wallet that was dormant for a decade?

Well, we have our own opinions, but the main thing to understand is that we don’t know! It’s unclear if the rightful earner of that block reward benefitted from selling it, and there’s no way to know unless the person reliably attested their ownership a long time ago. This is what quantum vulnerabilities look like, and it’s important not to sugarcoat the uncertainty that reigns in a quantum supremacy regime.

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

Freezing the Quantum Doom Clock, April 2025

Richard Carback and Colton Dillion — Tue, 15 Apr 2025 18:37:03 GMT

Freezing the Quantum Doom Clock, April 2025

GM frens, this is the Quantum Doom Clock with Colton Dillion and Rick Carback, the founders of Quip Network: the only protocol that defends your crypto from quantum computer hackers with no need to bridge funds or change out your keys. We put together this site and newsletter because the clock is ticking toward the day when your assets can be stolen by hackers with sufficiently powerful quantum computers.

Stop the Clock!

TL;DR: We launched post-quantum Quip smart accounts on Base! More chains are coming soon. You can move to the next section if you’re here for other news.

Today we get to kick off with some very happy news, marking a new milestone in quantum-resistance. You can now send and receive tokens as well as NFTs in complete safety from quantum attackers, all while earning your share of the future QUIP supply for getting protected early.

Why is this a big deal? Well, even if you use a hardware wallet or multisig, a quantum computer hacker can calculate your seed phrase from just one signed transaction. Depositing to a quip protects you with a post-quantum, ever-changing, second key that only gets used once and then discarded. You can use your usual wallet stack to transact in a quip, and our app will rotate your second key to keep the quantum hackers guessing.

That's right, if you're using a hardware wallet or multisignature address, quips can wrap your existing workflow with one more layer of security. That way, all the layers of security have to fail in order to compromise your funds. And quips support your favorite on-chain apps as usual, so you don’t have to give up yield farming just to be a little more secure.

Feel free to give it a try and let us know what you think. We’re always striving to improve and we want to make sure that everyone has a good reason to be quantum-resistant. You can also get some sweet token rewards for depositing to a Quip and helping us bootstrap the network.

Quantum Proof Bitcoin

The Bitcoin devs are starting to take quantum computers seriously. Hunter Beast, the author of BIP-360, gave a presentation highlighting the serious concerns about Bitcoin's vulnerability to quantum computing threats. While current quantum computers are not advanced enough to pose an immediate threat, major tech companies are investing billions into quantum development, with approximately 4-6 million Bitcoins currently vulnerable to "long exposure attacks." Particularly at risk are pay-to-public-key addresses (including Satoshi's coins), reused addresses, and taproot addresses.

In addition to BIP-360, Hunter proposes an "hourglass" approach to limit processing of vulnerable transactions over time. This is not a quick fix but "an immense coordination problem" requiring action from node runners, exchanges, and the broader Bitcoin community. Despite the uncertain timeline, the potentially catastrophic consequences make preparation essential for long-term crypto asset protection. If you want to learn more, check out this epic post-talk interview with Hunter and Isabel Foxen Duke.

The Quantum FOOM Clock?

If you follow AI discourse very closely, you’ll hear a lot of arguments about FOOM, the possibility that AI will recursively self-improve faster than humans can even think and before you know it we’ll have literal galaxy-brained AI watching over us. Since we’ve arrested the march of quantum doom, maybe it’s time to look forward to all the great things we might accomplish if we have our own exponentially rapid advancements in quantum computing.

IBM is factoring numbers as high as 253 - You heard that right, it may not sound like much yet, but factoring numbers is big money. If you can factor large numbers then you can also break RSA encryption, or more optimistically you have an entry point to more complex problems like set packing, which has applications in auction optimality and social choice.
Quantinuum claims quantum advantage - When determining the likelihood of a particle to collide or decay, quantum computers have classical computers beat. Could be that we’ll get more accurate readings for more efficient nuclear energy.
Scott Aaronson demonstrates certifiable randomness - And NIST approves it for government use! This is the first NIST-certified quantum computing output, so expect to see more real-world usecases emerge over the coming months.
Alice & Bob with the Cat Qubit’s Meow - Cat qubits captured some attention when Amazon released their Ocelot platform, but Alice & Bob have shown a dazzling 160x improvement with their photonics platform. Could be that this cat will land on its feet.
Qudits make qubits look ditzy - A qubit only contemplates two possible spin states, while qudits can model n-dimensional spin states, providing even more geometric algebraic horsepower. If AI is a series of tensors with floating point values, it’s possible qudits could one day model simple AIs directly.

There are many things to look forward to, but we’re still in the infant stages. But if looking at my son crawling is any indication, the running days are not too far off!

A Dose of Humility

When you’re working in the world of quantum physics and quantum computing, it’s good to have a modicum of gravitas and reserve. The future is really uncertain and everyone is trying to do their best! But sometimes it’s hard to tell the difference between people talking up their book unscrupulously versus getting a little ahead of themselves with irrational exuberance. For the following stories, you decide:

IBM says quantum supremacy in 2 years - It’s a good thing we froze the clock, otherwise we might be panicking. IBM seems to think that we’ll have useful quantum computing 33% faster than the doom clock says to expect. Yikes!
Dwave fights off the haters - Dwave claimed quantum advantage on certain magnetic field calculation tasks, but some researchers demonstrated a classical algorithm that could keep up on a subset of their tests. Dwave sniffed saying, ‘Try ‘em all, then we’ll talk!’
Nvidia’s Jensen Huang Eats Crow - He invited every major quantum computing CEO onstage to tell them sorry for spiking your stock prices. Guess he doesn’t want to be left behind on this growing segment that has the potential to change the cost function on linear algebra.
A Quantum FOSS OS - In happy news, the University of Osaka and Fujutsu are collaborating to create open-source cloud management software for quantum computers. This will be incredibly useful, especially because quantum computing architectures are still so diverse.

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

The Quantum Doom Clock is Ticking, March 2025

Richard Carback and Colton Dillion — Sat, 08 Mar 2025 03:07:03 GMT

GM frens, this is the first edition of the Quantum Doom Clock newsletter, with Colton Dillion and Rick Carback, the founders of Quip Network: the only protocol that defends your crypto from quantum computer hackers with no need to bridge funds or change out your keys. We put together this site and newsletter because the clock is ticking toward the day when your assets can be stolen by hackers with sufficiently powerful quantum computers.

Tech Leaders Agree Time is Short

For many years, academics, tech founders, and Fortune 500 CEOs have often repeated that useful quantum computers are ten to twenty years away. But those tunes are changing and the people who should be most in-the-know are universally adjusting their timelines:

Bill Gates - "There's a possibility quantum computing will become useful in 3-5 years."
(Video Clip)
Sundar Pichai, Google CEO - "In a 5-10 year timeframe, I think you will start [to see] practically useful quantum computers."
(Video)
Hartmut Neven, Google VP of Quantum AI Lab - "We're optimistic that within five years we'll see real-world applications that are possible only on quantum computers."
Satya Nadella, Microsoft CEO - "We believe this breakthrough will allow us to create a truly meaningful quantum computer not in decades, as some have predicted, but in years."
Arvind Krishna, IBM CEO - "We feel over the next three, four, five years — I give myself till the end of the decade — we will see something remarkable happen on that front and I’m really happy where our team is."

The odd men out here are Mark Zuckerberg at Meta, who readily admitted he doesn't know much on the Joe Rogan Experience, and Jensen Huang at Nvidia, who is sticking to the old estimates---and really, really wants you to keep buying his GPUs.

The takeaway can be summed up with this gem from a long-time investor in this space, Peter Barret: "Useful quantum computing is inevitable—and increasingly imminent."

The Quantum Gold-Rush

Following Google's Willow announcement late last year and their results in Nature, the rest of big tech has jumped on the major result bandwagon alongside some newer players:

Amazon's Ocelot - with 5 "cat" (data) qubits, a buffer circuit for each for data stabilization, and 4 additional error correcting qubits. Published in Nature.
Microsoft's Majorana 1 - with 8 qubits using a topological superconducting material, claiming a "new state of matter" that only previously existed in theory. Published in Nature.
IQM Released a 50 qubit machine in partnership with the VTT Research Center in Finland. This follows a 5 qubit release in 2021 and a 20 qubit machine in 2023. We will now add this to our projections since there is now enough data for them.
Quantum Machines, which makes quantum control systems, announced a $170M capital raise.
QuEra, which has a 256 qubit processor, announced another $230M capital raise.

Don’t forget, we also have other major producers like Intel, IBM, Riken, MIT, Japan, and China, among many smaller companies, publishing regular progress and major public quantum computer results each year. We are tracking over 20 different manufacturers in our dataset.

Down to Antimony Tacks

It is worthy to note that the quantum computing revolution will be much like the AI revolution in that the key barriers to progress are theoretical rather than procedural. Once we have a highly performant logical qubit composed of repeatable physical qubit arrays, the manufacturing processes to pack those arrays into 5nm size are already well understood and operating at scale. For example:

PsiQuantum is making millions of light-based quantum chips with a new manufacturing technique. "scaling to millions of qubits will be relatively straightforward."
EeroQ claims enhanced readout speeds converting qubit measurements to classical bit outputs, which would significantly reduce our current 8-12 hr estimate for breaking keys.
Oxford used entanglement to transmit data, enabling larger modular systems to be built. Hooking together chips with quantum teleportation means you don’t have to be limited by the wafer sizes available at the factory.
UNSW researchers demonstrated an "antimony" qubit, which requires 8 errors to flip a qubit. Error correcting with these brings the physical qubit requirement down to 10s of thousands of qubits for cracking cryptographic keys.

The Doom Clock Leaps Forward

Majorana, Ocelot, and Willow all currently claim better than 10^-3 error rates. The trend is now converging toward 10^-4, so we are updating our projection accordingly. Specifically, we're adding a 0 to the `p` value and rounding the `L` logical error rate down to `1e-16`, which gives us a new code distance of 15. Instead of September 2028, the doom clock will now read:

March 8, 2028

Frequently Asked Questions

Have a question? Just e-mail us at team at quantumdoomclock dot com. Below are the top questions we have received since our last update.

Microsoft previously retracted their topoconductor research papers, is the Majorana announcement the real thing?

The paper itself has a caveat by the editors saying there is no "evidence for the presence of Majorana zero modes in the reported devices."

We believe it is real, though, because of comments by one of the authors, Chetan Nayak, explaining that the zero modes and topological qubit claims are based on progress that occurred in the year following the paper submission.

You can learn more via Scott Aaronson's blog post on the matter.

Could Bybit be covering for a quantum computer hack?

No. The announcement of Bybit's $1.5B loss to North Korea's Lazarus group had a notoriously unclear announcement about how they were hacked, but that has since been clarified. The hackers took control of the multisig wallet interface provided by the Gnosis Safe app.