How to Increase Quantum Computing Reliability

MIT Sets Quantum Computing Record with 99.998% Fidelity Researchers at MIT have achieved a world-record single-qubit fidelity of 99.998% using a superconducting qubit known as fluxonium. This breakthrough represents a significant step toward practical quantum computing by addressing one of the field’s greatest challenges: mitigating noise and control imperfections that lead to operational errors. Key Highlights: 1. The Problem: Noise and Errors • Qubits, the building blocks of quantum computers, are highly sensitive to noise and imperfections in control mechanisms. • Such disturbances introduce errors that limit the complexity and duration of quantum algorithms. “These errors ultimately cap the performance of quantum systems,” the researchers noted. 2. The Solution: Two New Techniques To overcome these challenges, the MIT team developed two innovative techniques: • Commensurate Pulses: This method involves timing quantum pulses precisely to make counter-rotating errors uniform and correctable. • Circularly Polarized Microwaves: By creating a synthetic version of circularly polarized light, the team improved the control of the qubit’s state, further enhancing fidelity. “Getting rid of these errors was a fun challenge for us,” said David Rower, PhD ’24, one of the study’s lead researchers. 3. Fluxonium Qubits and Their Potential • Fluxonium qubits are superconducting circuits with unique properties that make them more resistant to environmental noise compared to traditional qubits. • By applying the new error-mitigation techniques, the team unlocked the potential of fluxonium to operate at near-perfect fidelity. 4. Implications for Quantum Computing • Achieving 99.998% fidelity significantly reduces errors in quantum operations, paving the way for more complex and reliable quantum algorithms. • This milestone represents a major step toward scalable quantum computing systems capable of solving real-world problems. What’s Next? The team plans to expand its work by exploring multi-qubit systems and integrating the error-mitigation techniques into larger quantum architectures. Such advancements could accelerate progress toward error-corrected, fault-tolerant quantum computers. Conclusion: A Leap Toward Practical Quantum Systems MIT’s achievement underscores the importance of innovation in error correction and control to overcome the fundamental challenges of quantum computing. This breakthrough brings us closer to the realization of large-scale quantum systems that could transform fields such as cryptography, materials science, and complex optimization problems.

🚨 Exciting #quantumcomputing alert! Now #QEC primitives actually make #quantumcomputers more powerful! 75 qubit GHZ state on a superconducting #QPU 🚨 In our latest work we address the elephant in the room about #quantumerrorcorrection - in the current era where qubit counts are a bottleneck in the systems available, adopting full-blown QEC can be a step backwards in terms of computational capacity. This is because even when it delivers net benefits in error reduction, QEC consumes a lot of qubits to do so and we just don't have enough right now... So how do we maximize value for end users while still pushing hard on the underpinning QEC technology? To answer this the team at Q-CTRL set out to determine new ways to significantly reduce the overhead penalties of QEC while delivering big benefits! In this latest demonstration we show that we can adopt parts of QEC -- indirect stabilizer measurements on ancilla qubits -- to deliver large performance gains without the painful overhead of logical encoding. And by combining error detection with deterministic error suppression we can really improve efficiency of the process, requiring only about 10% overhead in ancillae and maintaining a very low discard rate of executions with errors identified! Using this approach we've set a new record for the largest demonstrated entangled state at 75 qubits on an IBM quantum computer (validated by MQC) and also demonstrated a totally new way to teleport gates across large distances (where all-to-all connectivity isn't possible). The results outperform all previously published approaches and highlight the fact that our journey in dealing with errors in quantum computers is continuous. Of course it isn't a panacea and in the long term as we try to tackle even more complex algorithms we believe logical encoding will become an important part of our toolbox. But that's the point - logical QEC is just one tool and we have many to work with! At Q-CTRL we never lose sight of the fact that our objective is to deliver maximum capability to QC end users. This work on deploying QEC primitives is a core part of how we're making quantum technology useful, right now. https://lnkd.in/gkG3W7eE

Who has the best quantum processor today? Ask the physics community quietly and many will say: Quantinuum 𝗡𝗼𝘁 IBM Quantum. 𝗡𝗼𝘁 Google. 𝗡𝗼𝘁 IonQ. It’s easy to get caught up in roadmaps, qubit counts or quantum advantage headlines. But the real turning point for the field currently isn’t about scale. It's about fault tolerance - detecting and correcting quantum errors faster than they accumulate. Through that lens, Quantinuum’s H-Series trapped-ion system stands apart. Here’s why: • 𝗥𝗲𝗰𝗼𝗿𝗱-𝗛𝗶𝗴𝗵 𝗚𝗮𝘁𝗲 𝗙𝗶𝗱𝗲𝗹𝗶𝘁𝗶𝗲𝘀: The H-Series delivered a sustained >99.9% two-qubit gate fidelity and >99.99% single-qubit gate fidelity. This is the quality baseline to ensure any QEC code has a chance to work.    • 𝗟𝗼𝗴𝗶𝗰𝗮𝗹 𝗕𝗿𝗲𝗮𝗸-𝗘𝘃𝗲𝗻: They've repeatedly demonstrated logical qubits that are more reliable than the physical hardware they're built from—the first milestone for practical quantum computing.    • 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗮𝗹 𝗚𝗮𝘁𝗲 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Achieved logical gate fidelity an order of magnitude better than physical fidelity on 𝗻𝗼𝗻-𝗖𝗹𝗶𝗳𝗳𝗼𝗿𝗱 𝗴𝗮𝘁𝗲𝘀, which are the hardest operations to perform fault-tolerantly and essential for universal quantum computing.    • 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗔𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲: All-to-All Connectivity. The Quantum Charge-Coupled Device (QCCD) system uses ion shuttling to provide full all-to-all qubit connectivity.    • 𝗧𝗵𝗲 𝗤𝗘𝗖 𝗧𝗲𝘀𝘁𝗯𝗲𝗱: This architecture allows them to deploy a diverse range of QEC codes (Steane, Carbon, Tesseract) and test protocols like Single-Shot QEC and Fault-Tolerant Teleportation. It is literally built to explore and accelerate the FTQC roadmap.

Google's Willow chip shows that quantum error correction is starting to work. Just "starting", because while the ~1e-3 error rate reached by Willow is good, it has been achieved by others without error correction. So, how do we get error rates we couldn't reach with physical qubits alone? Easy: you "just" add more qubits in your logical qubit. But because there are errors on two dimensions in quantum computing, a 2D-structure (the surface code) is usually required to correct errors. This means that increasing protection against errors causes the number of qubits to grow quickly. With a surface code, protecting against 1 error at a time during an error correction cycle requires 17 qubits. 2 errors at a time? 49 qubits. 3 errors at a time? 97 qubits. This is the max Willow could achieve. This quadratic scaling leads Google to expect that reaching a 1e-6 error rate on a Willow-like chip will require some 1457 physical qubits (protecting against 13 errors at a time). And this is the reason why Alice & Bob is going for cat qubits instead. By reducing error correction from a 2D to a 1D problem, cat qubits make the scaling of error rates much more favorable. Even with the simplest error correction code (a repetition code), correcting one error at a time only requires 5 qubits. 2 errors? 9 qubits. 3 errors? 13 qubits. 13 errors? This is just 53 qubits instead of 1457! This situation is summarized in the graph below. It is taken from our white paper (link in the 1st comment) and I added a point corresponding to the biggest Willow experiment. Now, to be fair, Alice & Bob still needs to release the results of even a 5-qubit experiment. But when this is done, there is a fair chance the error rates will quickly catch up with those achieved by Google or others, because so few additional qubits are required to improve error rates. There are big challenges on both sides. Mastering cat qubits is hard. Scaling chips is hard. But consistent progress is being made on both sides too. Anyway, I can't wait for the moment when I can add the Alice & Bob equivalent of the Willow experiment on the chart below. And for once, I hope it will be up and to the left!

Microsoft and Quantinuum reach new milestone in quantum error correction. The collaboration claims to have used an innovative qubit-virtualization system on Quantinuum's H2 ion-trap platform to create 4 highly reliable logical qubits from only 30 physical qubits. What is quantum error correction? The physical qubits, with error rates in the order of 10^-2, are combined to deliver logical qubits with error rates in the order of 10^-5. According to their press release, this is the largest gap between physical and logical error rates reported to date, and has allowed them to run ran more than 14,000 individual experiments without a single error. (https://lnkd.in/dzETsvVA) The race for the qubits count seemed to finish in 2023, with the latest update on IBM's roadmap focusing on quality rather than on quantity (https://lnkd.in/dFu52wJR, "Until this year, our path was scaling the number of qubits. Going forward we will add a new metric, gate operations—a measure of the workloads our systems can run."), and other developments in quantum error correction, like the one announced in December by Harvard University, Massachusetts Institute of Technology, QuEra Computing Inc. and National Institute of Standards and Technology (NIST)/University of Maryland in December (https://lnkd.in/dkW-TT-w) Practical quantum computing gets a little closer, although it is still a distant target. Microsoft Press release: https://lnkd.in/deJ4QCBk Quantinuum's press release: https://lnkd.in/d4Wnmvdq More details from Microsoft: https://lnkd.in/dusfZ4KY Paper: https://lnkd.in/dpPCX3td #quantumcomputing #quantumerrorcorrection #technology

While it was initially thought that we would not see reliable quantum computers until the late 2030s, recent breakthroughs have led many experts to believe that early fault-tolerant machines will be a reality sooner than expected – we're now looking at years, not decades.   The key to unlocking that reality – and one of our biggest challenges in the quantum community– is quantum error correction (QEC). Present day qubits are fragile and susceptible to quantum noise, which causes high rates of error and prevents today’s intermediate-scale quantum computers from achieving practical advantage.   Microsoft’s qubit-virtualization system combines advanced runtime error diagnostics with computational error correction to significantly reduce the noise of physical qubits and enable the creation of reliable logical qubits – which are fundamental to resilient quantum computing. Think of it like noise-cancelling headphones, but for quantum disruption! Just love that visual!   In April, we applied our qubit-virtualization system and Quantinuum’s ion-trap hardware to achieve an 800x improvement on the error rate of physical qubits, demonstrating the most reliable logical qubits on record. As we continue this groundbreaking work, we are getting closer to the era of fault-tolerant quantum computing and our goal of building a scalable hybrid supercomputer.   What’s next? Stay tuned!   #QuantumComputing #QEC #AzureQuantum 

Quantum Error Correction: Major Breakthroughs in the Past Year 🚀 The past year has been remarkable for quantum computing, with groundbreaking progress in quantum error correction (QEC) bringing us closer to realizing fault-tolerant quantum computers. Across various architectures, the advancements have been truly inspiring: 🔹 Neutral-Atom Systems: QuEra Computing Inc. & Harvard University (https://lnkd.in/dPxA2NuH), as well as with Atom Computing & Microsoft (https://lnkd.in/dV7s3Gd2), demonstrated scalable logical quantum computations and reliable qubit operations using reconfigurable neutral-atom arrays with up to 256 atoms. 🔹 Superconducting Qubits: IBM Quantum (https://lnkd.in/dzaJH6vA) and Google's Quantum AI (https://lnkd.in/dR-CTUGm) reached a major milestone with surface code quantum memory, operating below the error-correction threshold on a 100+ qubit superconducting processor. 🔹 Trapped-Ion Systems: Quantinuum & Microsoft (https://lnkd.in/d5fPzcVU) set a new standard for reliability in logical qubits with Quantinuum’s 56 qubit H2 system, advancing the precision and scalability of trapped-ion quantum processors. 🔹 Cat Qubits: Amazon Web Services (AWS) & Caltech (https://lnkd.in/d3HRd86s) developed hardware-efficient QEC using concatenated bosonic qubits, reducing the physical qubit overhead and advancing the field of fault-tolerant quantum computation.  Why it matters:❓ These achievements represent more than technological milestones—they signify a paradigm shift. The timelines for realizing fault-tolerant quantum computers are accelerating, underscoring the rapid progress across quantum architectures. #QuantumComputing #QuantumInnovation #QuantumErrorCorrection #FutureOfComputing