Quantum Computing Developments

🚨 **CYBERSECURITY ALERT: The Quantum Threat Just Got Real** Chinese researchers have successfully broken RSA encryption using D-Wave's quantum annealing computers - and this should alarm every business leader and cybersecurity professional. **Why this matters:** **1. RSA encryption is EVERYWHERE** - It secures virtually all internet traffic, credit card transactions, online banking, and corporate communications. When researchers say they've cracked it, they're talking about breaking the foundation of digital security as we know it. **2. This wasn't done with theoretical "future" quantum computers** - They used D-Wave's commercially available quantum annealing systems that organizations can actually purchase and deploy TODAY. As the research team noted: "This is the first time that a real quantum computer has posed a substantial threat to multiple full-scale SPN structured algorithms in use today." While they demonstrated this on a 22-bit RSA key (smaller than production systems), the methodology shows a clear path forward. The implications are staggering - if scaled up, this could render current encryption obsolete much sooner than the "10-15 years" timeline experts have been predicting. **The bottom line:** Organizations need to start planning their migration to quantum-resistant encryption NOW, not later. The quantum computing threat to cybersecurity just shifted from "someday" to "today." Post-quantum cryptography has been under development for a while but is rarely implemented at this point. We need to push it much faster. The original paper was published eight months ago but was only verified by peers recently. #Cybersecurity #QuantumComputing #RSAEncryption #InfoSec #DigitalSecurity #QuantumThreat #PQC #cybersecurity #Innovation D-Wave

Japan has placed a real Quantum computer online, letting people worldwide access advanced computing power through the internet today. This moment signals a shift where Quantum machines move from labs into shared global use. Researchers students and developers can now interact with real Quantum hardware without traveling or owning expensive systems. It turns a distant concept into a practical tool available with a connection. Unlike traditional computers that use bits, Quantum computers use qubits which can exist in multiple states at once. This allows certain problems to be explored in ways classical machines cannot match. Japan’s system is carefully controlled, offering guided access so users can learn test and experiment responsibly while protecting the delicate hardware from misuse or overload. This step matters because access changes innovation. When tools are shared, ideas grow faster. Students can practice on real systems, researchers can compare results, and small teams can test concepts without massive funding. It lowers barriers and spreads knowledge beyond elite labs into classrooms startups and curious minds across the world. The system does not replace everyday computers, and it will not instantly solve all problems. Quantum machines are specialized and still developing. But each real world use teaches engineers how to improve stability accuracy and scale. Progress comes through use feedback and patience, not hype or shortcuts. Moments like this show technology becoming more open and collaborative. Japan’s move invites the world to learn together and shape the future carefully. Quantum computing promises new ways to study materials security and nature itself. Giving global access builds trust curiosity and shared progress. It reminds us that science advances best when knowledge is opened not hidden and when powerful tools are guided by responsibility learning and cooperation for the benefit of everyone everywhere.

Last week, IBM announced its intent to acquire HRL Laboratories, LLC. This week, the cover of Nature features a significant milestone from the HRL quantum team: a digitally controlled silicon quantum processing unit that integrates exchange-only spin qubits, cryogenic CMOS control electronics, and a novel high-density superconducting interconnect into a single architecture. (https://lnkd.in/eMSj47jS) This work addresses one of the central challenges in quantum computing: how to scale quantum systems without an unmanageable increase in control hardware, wiring complexity, and power consumption. By moving quantum control into the cryostat, the team demonstrated an autonomous error correction routine using a fully integrated system rather than relying on racks of room-temperature electronics. The results include an order-of-magnitude improvement in exchange-only qubit performance, implementation of repetition-code error correction and quantum error detection, and a path toward manufacturing quantum processors and control systems using advanced semiconductor technologies. In other words, the researchers showed that instead of relying on entire rooms of electronics to manage fragile qubits, the system could autonomously perform key functions at cryogenic temperatures, paving the way for smaller, more efficient, and far more scalable quantum computers. At IBM Quantum, we recently published a blog introducing spin qubits and how they compare with superconducting qubits (https://lnkd.in/e5aSTgyc). In summary, these two different modalities are more complementary than adversarial, both leveraging state-of-the-art silicon fabrication and advanced manufacturing techniques.What makes this result particularly interesting is its focus on the systems architecture required to scale quantum computing, from qubits and cryogenic control to interconnects and error correction. Congratulations to the HRL team on having this achievement featured on the cover of Nature, a well-deserved recognition of both the scientific significance and systems-level engineering demonstrated in this work. Progress toward fault-tolerant quantum computing will require innovation across the entire stack. This paper is an excellent example of that approach and highlights why we are excited about the opportunity to bring HRL's exceptional quantum capabilities into IBM Research. Paper: https://lnkd.in/eFz5M2Wk Video: https://lnkd.in/eWCv63pc

We may be standing at a moment in time for Quantum Computing that mirrors the 2017 breakthrough on transformers – a spark that ignited the generative AI revolution 5 years later. With recent advancements from Google, Microsoft, IBM and Amazon in developing more powerful and stable quantum chips, the trajectory of QC is accelerating faster than many of us expected.   Google’s Sycamore and next gen Willow chips are demonstrating increasing fidelity. Microsoft’s pursuit of topological qubits using Majorana particles promises longer coherence times and IBM’s roadmap is pushing towards modular error corrected systems. These aren’t just incremental steps, they are setting the stage for scalable, fault tolerant quantum machines.   Quantum systems excel at simulating the behavior of molecules and materials at atomic scale, solving optimization problems with exponentially large solution spaces and modeling complex probabilistic systems – tasks that could take classical supercomputers millennia. For example, accurately simulating protein folding or discovering new catalysts for carbon capture are well within quantum’s potential reach.   If scalable QC is just five years away, now is the time to ask : What would you do differently today, if quantum was real tomorrow ?. That question isn’t hypothetical – it’s an invitation to start rethinking foundational problems in chemistry, logistics, finance, AI and cryptography.   Of course building quantum systems is notoriously hard. Fragile qubits, error correction and decoherence remain formidable challenges. But globally public and private institutions are pouring resources into cracking these problems. I was in LA today visiting the famous USC Information Sciences Institute where cutting edge work on QC is underway and the energy is palpable.   This feels like a pivotal moment. One where future shaping ideas are being tested in real labs. Just as with AI, the future belongs to those preparing for it now. QC Is an area of emphasis at Visa Research and I hope it is part of how other organizations are thinking about the future too.

Thought you knew which #quantumcomputers were best for #quantum optimization? The latest results from Q-CTRL have reset expectations for what is possible on today's gate-model machines. Q-CTRL today announced newly published results that demonstrate a boost of more than 4X in the size of an optimization problem that can be accurately solved, and show for the first time that a utility-scale IBM quantum computer can outperform competitive annealer and trapped ion technologies. Full, correct solutions at 120+ qubit scale for classically nontrivial optimizations! Quantum optimization is one of the most promising quantum computing applications with the potential to deliver major enhancements to critical problems in transport, logistics, machine learning, and financial fraud detection. McKinsey suggests that quantum applications in logistics alone are worth over $200-500B/y by 2035 – if the quantum sector can successfully solve them. Previous third-party benchmark quantum optimization experiments have indicated that, despite their promise, gate-based quantum computers have struggled to live up to their potential because of hardware errors. In previous tests of optimization algorithms, the outputs of the gate-based quantum computers were little different than random outputs or provided modest benefits under limited circumstances. As a result, an alternative architecture known as a quantum annealer was believed – and shown in experiments – to be the preferred choice for exploring industrially relevant optimization problems. Today’s quantum computers were thought to be far away from being able to solve quantum optimization problems that matter to industry. Q-CTRL’s recent results upend this broadly accepted industry narrative by addressing the error challenge. Our methods combine innovations in the problem’s hardware execution with the company’s performance-management infrastructure software run on IBM’s utility-scale quantum computers. This combination delivered improved performance previously limited by errors with no changes to the hardware. Direct tests showed that using Q-CTRL’s novel technology, a quantum optimization problem run on a 127-qubit IBM quantum computer was up to 1,500 times more likely than an annealer to return the correct result, and over 9 times more likely to achieve the correct result than previously published work using trapped ions These results enable quantum optimization algorithms to more consistently find the correct solution to a range of challenging optimization problems at larger scales than ever before. Check out the technical manuscript! https://lnkd.in/gRYAFsRt

Quantum error correction (QEC) is the primary strategy for protecting a quantum computer from the environment. However, there is a significant bottleneck: precise calibration is short-lived, which requires perpetually adapting the control parameters of the computer to the drifting environmental conditions. Just published in Nature, our team showed unified calibration with error-corrected computation on our Willow processor, training a reinforcement learning agent to stabilize a logical qubit and pave the way towards a quantum computer that continuously learns from its errors. Key research findings: -->✨ A New Paradigm: This work enables a future where we have a quantum computer that learns from its errors and never stops computing. Removing the need to take the system offline for calibration. --> Improved Stability: We experimentally demonstrated this framework on our Willow superconducting processor, improving the logical stability of the surface code 3.5-fold against injected drift. --> Beyond Traditional Limits: RL fine-tuning of an already well-calibrated processor yields an additional 20% suppression of the logical error rate, pushing performance beyond the limits of traditional physics-based calibration and human expert tuning. --> Scalability: Numerical simulations confirm the scalability of our RL framework, revealing that the optimization speed is independent of system size, ensuring this remains just as effective as we scale to much larger systems. This research demonstrates that the path to fault-tolerant quantum computing relies not just on better hardware, but on more intelligent control systems. I am proud of our teams for pioneering this approach, an important step towards solving the challenges in quantum information science. Nature article here: https://lnkd.in/gfuxKYJf

Many talk about surface codes. But what if they’re not the future? Quantum Low-density parity-check (qLDPC) codes are gaining traction 𝗳𝗮𝘀𝘁. IBM is building fault-tolerant memories using Bivariate Bicycle (BB) codes. IQM Quantum Computers is designing hardware with qLDPC in mind. And now, a new experiment from China shows the 𝗳𝗶𝗿𝘀𝘁 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗾𝗟𝗗𝗣𝗖 𝗰𝗼𝗱𝗲 𝗼𝗻 𝗮 𝘀𝘂𝗽𝗲𝗿𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗶𝗻𝗴 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗼𝗿. On the 32-qubit Kunlun chip, researchers implemented: • 𝗔 [[𝟭𝟴, 𝟰, 𝟰]] 𝗕𝗕 𝗰𝗼𝗱𝗲 • 𝗔 [[𝟭𝟴, 𝟲, 𝟯]] 𝗾𝗟𝗗𝗣𝗖 𝗰𝗼𝗱𝗲    The notation [[𝗻, 𝗸, 𝗱]] describes a quantum error correction code that uses 𝗻 physical qubits to encode 𝗸 logical qubits, with 𝗱 being the code distance. Unlike surface codes, LDPC codes keep each error check (called a stabilizer) connected to only a small number of qubits—just 6 in this case—even as the code scales. That means fewer ancillas, fewer gates, and potentially lower overhead for fault tolerance. The hardware was purpose-built for this experiment: • 𝟯𝟮 𝗳𝗿𝗲𝗾𝘂𝗲𝗻𝗰𝘆-𝘁𝘂𝗻𝗮𝗯𝗹𝗲 𝘁𝗿𝗮𝗻𝘀𝗺𝗼𝗻 𝗾𝘂𝗯𝗶𝘁𝘀 • 𝟴𝟰 𝘁𝘂𝗻𝗮𝗯𝗹𝗲 𝗰𝗼𝘂𝗽𝗹𝗲𝗿𝘀, enabling non-local interactions up to 𝟲.𝟱 𝗺𝗺 apart • 𝗔𝗶𝗿 𝗯𝗿𝗶𝗱𝗴𝗲𝘀 to support a crossbar-style layout • Stabilizer checks executed in just 𝟳 𝗖𝗭 𝗹𝗮𝘆𝗲𝗿𝘀    Gate fidelities were solid: • Single qubit: 99.95% • Two-qubit: 99.22%    The decoding was performed offline using 𝗯𝗲𝗹𝗶𝗲𝗳 𝗽𝗿𝗼𝗽𝗮𝗴𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗼𝗿𝗱𝗲𝗿𝗲𝗱 𝘀𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 𝗱𝗲𝗰𝗼𝗱𝗶𝗻𝗴 (𝗕𝗣-𝗢𝗦𝗗)—an approach better suited to LDPC-style codes. Logical error rates were: • 𝗕𝗕: 𝟴.𝟵𝟭 ± 𝟬.𝟭𝟳% • 𝗾𝗟𝗗𝗣𝗖: 𝟳.𝟳𝟳 ± 𝟬.𝟭𝟮%    Both are still above the physical qubit error rate—but 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀 𝘀𝗵𝗼𝘄 𝘁𝗵𝗮𝘁 𝗮 𝟮× 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 𝗶𝗻 𝗳𝗶𝗱𝗲𝗹𝗶𝘁𝘆 𝘄𝗼𝘂𝗹𝗱 𝗯𝗲 𝗲𝗻𝗼𝘂𝗴𝗵 𝘁𝗼 𝗽𝘂𝘀𝗵 𝘁𝗵𝗲𝘀𝗲 𝗰𝗼𝗱𝗲𝘀 𝗯𝗲𝗹𝗼𝘄 𝘁𝗵𝗿𝗲𝘀𝗵𝗼𝗹𝗱. qLDPC codes are no longer just a concept—they’re being implemented, measured, and decoded on superconducting hardware. 📸 Image Credits: Ke Wang, Zhide Lu, Chuanyu Zhang et al. (2025, arXiv)

On March 2026, Google Quantum AI shared that it is expanding into neutral atom quantum computing. For over a decade, Google’s hardware work has focused on superconducting qubits. That remains their core platform. What is changing is this. They are now adding neutral atoms as a new research direction, not as a replacement, but as a complementary path. This matters. Superconducting systems are fast and support deep circuits. But they become harder to scale physically. Neutral atoms offer a different advantage. They can form large arrays with flexible connectivity, which may help with scaling qubit counts over time. Google is not saying it will run two production systems in parallel. But it is clear they want to explore multiple paths to solve the same long-term problem. The effort is being led by Adam Kaufman and is connected to the Boulder atomic physics ecosystem. My take: Relying on a single hardware approach is a risk at this stage of the industry. Exploring multiple architectures is not a pivot. It is a hedge. It reflects where quantum computing really is today. Still in the research phase, still searching for the most scalable path forward.

I was pleased to join in today’s launch of the OECD Recommendation on Quantum Technologies – the first intergovernmental standard providing shared principles and policy guidance for development and use of quantum technologies. A growing number of countries are investing in quantum computing, sensing and communication, and they are developing national strategies to guide their efforts. But progress depends on more than national efforts: quantum innovation relies on shared expertise, infrastructure and international collaboration. The OECD Recommendation helps governments and other stakeholders strengthen innovation ecosystems, promote secure and trusted access, support resilient supply chains, and foster international co-operation – while addressing risks related to security, privacy and fragmentation. Its adoption marks the beginning of the next phase of collective implementation of quantum technologies, offering a common reference point to guide policy, support co-ordination, and build trust in how quantum technologies are developed and deployed across borders. See: https://lnkd.in/ecqnDdpD Congratulations to Andrés Barreneche García, David Winickoff, Pauline Arbel, Sara Rendtorff-Smith, Audrey Plonk. #Quantum #EmergingTech #InnovationPolicy #OECD