Quantum Error Correction: Surface Code & Fault-Tolerant Computing
Quantum error correction news: logical qubits, surface code, fault-tolerant quantum computing, QEC. Error mitigation & suppression.
Quantum error correction (QEC) is the critical enabler for fault-tolerant quantum computing, protecting quantum information from environmental noise through redundant encoding across multiple physical qubits. Recent breakthroughs demonstrated below-threshold error correction where logical qubit error rates fall below physical qubit rates.
The 2D surface code is the leading QEC approach due to high error threshold (~1%), local nearest-neighbor interactions, and compatibility with superconducting chip designs. Recent breakthroughs include Google's Willow demonstrating below-threshold surface code scaling, and IBM's Heavy Hex optimizing qubit connectivity for surface code implementation.
India's Quantum Error Correction Research
India's National Quantum Mission includes quantum error correction in its basic science research component. The Foundation for QC Innovation at IISc Bengaluru addresses error correction as part of its quantum computing development. The Harish-Chandra Research Institute (HRI) and Institute of Mathematical Sciences (IMSc) conduct theoretical research on quantum error correction codes.
The NQM targets developing intermediate-scale quantum computers with 50-1000 physical qubits, requiring error mitigation and eventually error correction to achieve quantum advantage. The mission includes development of indigenous control electronics and error mitigation techniques.
quantum-computingThe Best Quantum Computing Stocks to Buy Today
By Keithen Drury – Apr 10, 2026 at 2:23PM ESTKey PointsPure play IonQ holds the world record for the most accurate quantum computing.Microsoft and Alphabet serve as excellent legacy quantum investing alternatives. Quantum computing may seem like a far-fetched technology, but the reality is that it's rapidly progressing to the point where it's starting to become useful in many applications. These investors should position themselves accordingly, as quantum computing could have a huge upside if investors pick the right stocks. I've got three stocks that I think are best positioned for quantum computing success. Investors should maintain some exposure to these stocks in case their breakthroughs cause them to go parabolic. Image source: Getty Images. IonQ IonQ (IONQ +2.03%) is one of the leaders of the quantum computing race. Its leadership status comes from its world-record holding system, which delivered 99.99% fidelity in a common test that quantum computing companies use to test accuracy. This is a huge deal, because the primary reason why we don't see more widespread quantum computing is its relative inaccuracy. IonQ believes that the 99.99% threshold is good enough for the company to start scaling its device to have millions of qubits by 2030. For reference, it plans to implement this technology to build a 256-qubit system this year. Should IonQ develop an accurate quantum computing system with millions of qubits by 2030, it could take the world by storm and be one of the top-performing quantum computing stocks, especially in applications where perfect accuracy is critical. ExpandNYSE: IONQIonQToday's Change(2.03%) $0.57Current Price$28.65Key Data PointsMarket Cap$10BDay's Range$28.14 - $29.3752wk Range$23.48 - $84.64Volume465KAvg Vol21MGross Margin-2267.11% However, the reason why IonQ has achieved this incredible accuracy figure is the architecture it's designing its computer around. It's using a technology called trapped ion, which trades accuracy for speed. Th
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quantum-computingRigetti’s New 108-Qubit Quantum System Might Change The Case For Investing In Rigetti Computing (RGTI) - simplywall.st
Rigetti’s New 108-Qubit Quantum System Might Change The Case For Investing In Rigetti Computing (RGTI) simplywall.st
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quantum-computingInfleqtion: Quantum Hype Meets Real Business
Yiannis Zourmpanos15.32K FollowersFollow5ShareSavePlay(10min)Comments(4)SummaryInfleqtion generated $32.5 million in revenue in FY2025, growing roughly 3x since 2023, driven primarily by sensing and timing products.Around two-thirds of revenue comes from sensing applications like atomic clocks and RF systems, with computing contributing the remaining portion.The company raised $516 million in 2026, significantly strengthening its balance sheet and reducing near-term dilution and survival risks.Infleqtion currently operates 1,600 physical qubits and 12 logical qubits, targeting 100+ logical qubits by the 2028 commercialization stage.Total addressable markets exceed $160 billion across computing and sensing, where even sub-0.1% penetration implies $100–150 million revenue potential. Just_Super/iStock via Getty Images Investment Thesis The market still treats Infleqtion, Inc. (INFQ) as a distant quantum computing bet. I think that misses the real opportunity. This is an already profitable company developing essential technology in an era where everythingThis article was written byYiannis Zourmpanos15.32K FollowersFollowHi, I'm Yiannis. Spotting winners before they break out is what I do best.Experience: Previously worked at Deloitte and KPMG in external/internal auditing and consulting. Education: Chartered Certified Accountant, Fellow Member of ACCA Global, with BSc and MSc degrees from U.K. business schools. Investment Style: Spotting high-potential winners before they break out, focusing on asymmetric opportunities (with at least upside potential of 3-5X outweighing the downside risk). By leveraging market inefficiencies and contrarian insights, we seek to maximize long-term compounding while protecting against capital impairment.Risk management is paramount—we seek a strong margin of safety to protect against capital impairment while maximizing long-term compounding. Our 2-3 year investment horizon allows us to ride out volatility, ensuring that patience, disciplin
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quantum-computingIQM Establishes First U.S. Quantum Technology Center in Maryland’s Discovery District
IQM Establishes First U.S. Quantum Technology Center in Maryland’s Discovery District IQM Quantum Computers has announced the opening of its first U.S. Quantum Technology Center, located within the University of Maryland’s Discovery District in College Park. The move is a strategic expansion into the North American market, placing the company within the Capital of Quantum (CoQ) initiative—a $1 billion public-private partnership designed to accelerate the regional quantum economy. By establishing this hub, IQM intends to interface directly with the federal research community, including the National Institute of Standards and Technology (NIST), NASA Goddard, and the Army Research Laboratory (DEVCOM). The new center is designed to function as a collaborative workspace for local startups, academic institutions, and federal partners. A primary focus of the facility will be the integration of superconducting quantum processors with High-Performance Computing (HPC) service providers. IQM plans to leverage Maryland’s talent pipeline, which features a high concentration of quantum scientists, to build local engineering teams. This presence in College Park is intended to support the commercialization of advanced quantum hardware and software while aligning with U.S. national policies on quantum information science. Maryland’s Discovery District currently hosts over 60 companies and federal agencies, forming a dense cluster of specialized infrastructure. The addition of IQM’s technology center supports the state’s five-year roadmap to drive innovation and knowledge generation in the sector. Through this facility, IQM aims to provide its full-stack superconducting systems and cloud platform to American research laboratories and enterprises, further diversifying the technical modalities available within the regional quantum ecosystem. For the official press release regarding the U.S. expansion, visit the IQM newsroom here. April 10, 2026 Mohamed Abdel-Kareem2026-04-10T07:36:40-0
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quantum-computingPasqal and True Nexus Partner to Optimize Alternative Protein Design via Quantum Computing
Pasqal and True Nexus Partner to Optimize Alternative Protein Design via Quantum Computing Pasqal and Saudi-based computational intelligence firm True Nexus (a branch of AI Bobby) have entered a strategic partnership to apply neutral-atom quantum computing to the study of protein functionality. The initiative focuses on addressing technical barriers in the alternative protein industry, specifically the difficulty of predicting how proteins behave—including gelation and texture—within complex food systems. This collaboration follows Pasqal’s announced intent to go public via a business combination with Bleichroeder Acquisition Corp. II (Nasdaq: BBCQ). The primary objective of the partnership is the development of a vectorized, dynamic 3D model of protein gelation. This model is designed to integrate variables such as molecular structure, extraction parameters, and environmental processing conditions. By utilizing neutral-atom quantum processors, the companies aim to simulate molecular interactions and variables with higher precision than is currently achievable through classical computational methods. The project seeks to transition alternative protein development from empirical trial-and-error toward a design-driven methodology. The long-term goal of the collaboration is to establish a reference model for protein functionality to assist ingredient companies in seed development, crop optimization, and precision fermentation. By improving the predictability of protein behavior, the companies aim to address the functionality gap between animal-based and alternative proteins. This model is intended to serve as a technical guide for the food industry to achieve consistent texture and performance in sustainable protein products. For the technical announcement regarding the partnership and protein modeling objectives, consult the Pasqal newsroom here. April 10, 2026 Mohamed Abdel-Kareem2026-04-10T06:15:37-07:00 Leave A Comment Cancel replyComment Type in the text displayed
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quantum-computingQuantrolOx and RAQS Quantum Partner to Scale Automation and Workforce Development in Asia Pacific
QuantrolOx and RAQS Quantum Partner to Scale Automation and Workforce Development in Asia Pacific QuantrolOx, a developer of measurement and automation platforms for quantum hardware, has partnered with Singapore-based RAQS Quantum to bring its Quantum EDGE platform and Quantum EDGE Academy to the Asia Pacific region. Announced at GITEX Asia 2026, the collaboration addresses the industry-wide bottleneck of manual control and calibration by providing research institutions, national initiatives, and enterprise R&D teams with automated workflows. RAQS Quantum will lead regional integration and commercial deployment, with activities expected to begin in the second half of 2026. The partnership focuses on the control and automation layer of the quantum stack, positioning QuantrolOx’s hardware-agnostic solutions between the QPU and control electronics. By unifying measurement and data management, the Quantum EDGE platform allows for the creation of open-architecture testbeds, reducing the reliance on specialized manual intervention. This shift is intended to improve the operational reliability and performance of quantum processors as they move from isolated laboratory experiments toward scalable, real-world applications within the region’s emerging quantum infrastructure. Beyond hardware automation, the collaboration emphasizes quantum workforce development through the Quantum EDGE Academy. As governments across the Asia Pacific region increase investment in domestic quantum engineering capabilities, the academy provides a training environment designed to upskill local talent. By combining state-of-the-art automation tools with specialized education, the initiative aims to support national upskilling strategies and accelerate the experimental workflows necessary for the region to maintain a competitive position in the global quantum landscape. For the complete technical announcement regarding the Asia Pacific expansion, consult the official QuantrolOx press release he
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quantum-computingQ-CTRL Proposes Heterogeneous Architecture to Optimize Fault-Tolerant Resource Requirements
Q-CTRL Proposes Heterogeneous Architecture to Optimize Fault-Tolerant Resource Requirements Overview of Q-NEXUS: a heterogeneous architecture made of specialized functional modules connected through an interconnect bus Q-CTRL has introduced Q-NEXUS, a heterogeneous quantum computing architecture designed to address the physical resource bottlenecks currently limiting large-scale quantum computers. Rather than scaling a single monolithic array of qubits, the Q-NEXUS framework decomposes the system into specialized functional modules: Quantum Processing Units (QPUs) for logic, Quantum Memory (QM) for storage, and Quantum State Factories (QSF) for resource generation. This approach seeks to resolve the “tyranny of numbers”—the unsustainable growth of control wiring and cryogenic load—by centralizing high-speed operations while offloading storage to simplified, high-density tiers. A primary technical insight in the Q-CTRL paper is that qubits in algorithms like RSA-2048 factorization are inactive for approximately 96–97% of all logical clock cycles. In a monolithic design, these idle qubits sit in expensive, actively error-corrected hardware, where they continue to accumulate decoherence and consume system resources. Q-NEXUS addresses this by segregating storage into a hierarchical memory system. This includes Static Transversal Quantum Memory (STQM), which uses ultra-long-coherence substrates like rare-earth ions to store states without active error correction, and Random-Access Quantum Memory (RAQM), which utilizes slower but stable modalities like neutral atoms for long-term storage. The transition from monolithic to heterogeneous organization enables massive gains in computational reliability and efficiency. According to Q-CTRL’s detailed accounting, the Q-NEXUS architecture achieves up to a 551× reduction in algorithmic logical error for specific subroutines and a 138× reduction in physical qubit requirements for fault-tolerant benchmarks. For the factorization of
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A landmark first: Solving Differential Equations with Logical Neutral-Atom Qubits
Home – FTQC – A landmark first: Solving Differential Equations with Logical Neutral-Atom Qubits A landmark first: Solving Differential Equations with Logical Neutral-Atom Qubits FTQC Hardware +End-to-end application with logical qubits+From Building Blocks to Full Applications+Why This Application?+The Results: Logical Qubits Outperform Physical Ones+What’s Next+Stay Tuned Apr 10, 2026 +End-to-end application with logical qubits+From Building Blocks to Full Applications+Why This Application?+The Results: Logical Qubits Outperform Physical Ones+What’s Next+Stay Tuned Authors: Pascal Scholl, Adrien Signoles, Lucia Garbini End-to-end application with logical qubits For the first time, the Pasqal team solved differential equations using quantum kernels at the logical qubit level. In our latest work, we’ve implemented a complete end-to-end application using logical qubits moving beyond testing sub-routines to delivering an actual computational solution. This proof-of-concept used 2 logical qubits on Pasqal’s neutral atom quantum processor. Previously, this same processor demonstrated analog quantum computing capabilities, including applying machine learning to molecular toxicity prediction, and managing financial risk. Now, for the first time, that same hardware has demonstrated logical computations. validates a critical milestone: logical qubits can tackle real problems beyond theoretical building blocks. From Building Blocks to Full Applications Fault-tolerant quantum computing (FTQC) relies on logical qubits that protect against noise: even though errors occur on the underlying physical qubits, the computation remains error-tolerant, delivering correct results. If you’re new to FTQC, our post on understanding fault-tolerant quantum computing breaks down how this approach works and why it’s essential for delivering the full value of quantum computing Until now, FTQC research has focused mostly on sub-routines of c
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quantum-computingSPINS Project Aims for Millions of Stable Semiconductor Qubits
A 50 million euro investment will fuel the SPINS project, a pan-European effort to establish a new research and production environment for semiconductor quantum chips mirroring existing manufacturing processes. The consortium, coordinated by imec and comprised of 25 European organizations including the University of Jyväskylä, will focus on three material platforms, Si/SiGe, Ge/GeSi, and SOI, to create scalable, stable spin qubits. This initiative aims to bolster European sovereignty in quantum technology and ultimately produce chips containing hundreds of millions of stable qubits for future quantum computing applications. Professor Juha Muhonen from the University of Jyväskylä stated that the University of Jyväskylä’s involvement in such an ambitious European project strengthens the position of Finland and the University in the development of quantum technologies and provides a unique link between research laboratories and industrial applications. EU SPINS Project Advances Semiconductor Spin Qubit Development Unlike many quantum computing approaches, SPINS concentrates specifically on semiconductor-based spin qubits, a choice driven by the potential for leveraging established microfabrication techniques and materials. The consortium is not limiting itself to a single material, but instead pursuing development across three distinct platforms: Si/SiGe, Ge/GeSi, and SOI, demonstrating a pragmatic, multi-pronged strategy to address the inherent material science challenges. This collaborative undertaking, officially launched on April 1, 2026, unites 25 European organizations, research and technology organizations, industry partners, and academic groups, coordinated by imec, and aims to solidify Europe’s position in the rapidly evolving field of quantum technology. The project’s scope extends beyond fundamental research, with a clear objective of translating laboratory advancements into industrial-scale production of quantum chips for future computing applications; proj
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quantum-computingClassical Data Limits Quantum Computing’s Broad Impact
Haimeng Zhao is addressing a fundamental hurdle preventing widespread adoption of quantum computing: efficiently integrating classical data into quantum algorithms. Despite advances in experimental capabilities, demonstrating broad societal impact beyond niche areas like quantum materials simulation and cryptanalysis remains a significant challenge, largely due to the difficulty of accessing real-world, classically-generated data in a quantum format, a problem known as the data loading problem. Their new framework, termed quantum oracle sketching, offers a solution by processing data as a continuous stream and applying small quantum rotations to incrementally build an accurate quantum oracle. “We live in an effectively classical world, dammit, and maybe classical computers and AI already suffice for most of our problems,” Zhao playfully suggests, adapting a famous quote from Richard Feynman, highlighting the need to bridge the gap between classical data and quantum processing. Data Loading Bottleneck Hinders Broad Quantum Advantage While quantum computers excel at simulating quantum materials and certain cryptographic tasks, these applications are inherently quantum or possess mathematical structures easily exploited by quantum algorithms; extending this advantage to everyday problems proves far more difficult. The core issue stems from the fact that most modern computation relies on processing vast amounts of noisy, classical data, the very fuel powering the success of machine learning and artificial intelligence. This data, originating from the macroscopic classical world, doesn’t naturally lend itself to the delicate, specialized structures quantum computers require. Imagine attempting to simultaneously read a million movie reviews; the conventional, sequential access of classical computers presents a bottleneck for quantum systems. To address this, Haimeng Zhao has developed a framework called “quantum oracle sketching,” which allows for optimal access to classi
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quantum-computingComputing quantum magic of state vectors
AbstractNon-stabilizerness, also known as “magic,'' quantifies how far a quantum state departs from the stabilizer set. It is a central resource behind quantum advantage and a useful probe of the complexity of quantum many-body states. Yet standard magic quantifiers, such as the stabilizer Rényi entropy (SRE) for qubits and the mana for qutrits, are costly to evaluate numerically, with the computational complexity growing rapidly with the number $N$ of qudits. Here we introduce efficient, numerically exact algorithms that exploit the fast Hadamard transform to compute the SRE for qubits ($d=2$) and the mana for qutrits ($d=3$) for pure states given as state vectors. Our methods compute SRE and mana at cost $O(N d^{2N})$, providing an exponential improvement over the naive $O(d^{3N})$ scaling, with substantial parallelism and straightforward GPU acceleration. We further show how to combine the fast Hadamard transform with Monte Carlo sampling to estimate the SRE of state vectors, and we extend the approach to compute the mana of mixed states. All algorithms are implemented in the open-source Julia package HadaMAG, which provides a high-performance toolbox for computing SRE and mana with built-in support for multithreading, MPI-based distributed parallelism, and GPU acceleration. The package, together with the methods developed in this work, offers a practical route to large-scale numerical studies of magic in quantum many-body systems.Featured image: HadaMAG workflow: a quantum state vector $|\psi\rangle$ with $d^N$ amplitudes is fed through $d^N$ fast Hadamard transforms, i.e., butterfly networks of additions and subtractions, to efficiently extract all $d^{2N}$ Pauli expectation values $\langle P \rangle$, from which measures of quantum magic, the stabilizer Rényi entropy $M_2(|\psi\rangle)$ for qubits ($d=2$) and the mana $\mathcal{M}(|\psi\rangle)$ for qutrits ($d=3$), are obtained.Popular summaryStabilizer states form a special class of quantum states that align
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quantum-computingYaqumo Secures Seed Extension From $350M Quantum VC
Yaqumo Inc., a Tokyo-based startup developing scalable neutral-atom quantum computers, has secured a Seed Extension Round from Quantonation II FPCI, marking the venture capital fund’s first investment in a Japanese company. The $350 million quantum-focused fund selected Yaqumo after a global search for promising deep-tech startups, recognizing the company’s technological capabilities and potential. This funding will accelerate Yaqumo’s research and development, expand its team, and drive commercialization efforts, strengthening its position within the growing quantum ecosystem. Kazuhiro Nakashoji, CEO of Yaqumo, said the investment is a strong validation of the company’s technology and potential, and demonstrates that Japan’s quantum industry is gaining global attention. Quantonation’s $350M Portfolio Includes Yaqumo for Seed Extension Quantonation’s investment in Yaqumo expands its $350 million portfolio to include a Japanese quantum computing startup; the firm has previously backed 38 deep-tech companies across ten countries in the US, Europe, and Asia since its founding in 2018. This Seed Extension Round funding will allow Yaqumo, headquartered in Chiyoda-ku, Tokyo, to bolster research and development of its scalable neutral-atom quantum computers, a technology the company believes is crucial for effective quantum error correction and, ultimately, practical fault-tolerant quantum computing. The investment utilizes a J-KISS convertible equity instrument, a streamlined financing method for the Japanese startup ecosystem that avoids immediate valuation determination. Olivier Tonneau, Partner at Quantonation, emphasized the firm’s confidence in the company’s business potential and Japan’s quantum science foundation, stating that Yaqumo’s team and vision are compelling for making quantum technology practical. The company, established on April 1, 2025, focuses on hardware-software co-design to achieve fast clock rates, a key element in its approach to scalable quantum
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quantum-computingUniversity of Houston Hosts Quantum Symposium with Industry and IonQ
Insider Brief The University of Houston hosted a quantum symposium with IonQ and industry leaders as part of its Quantum Initiative to align research, workforce development, and industry collaboration. The initiative builds on a statewide effort to advance quantum computing, materials, networks, and workforce development while positioning UH as a regional innovation hub. Speakers highlighted a projected global shortage of quantum talent and emphasized the need for universities to scale education and training to meet industry demand. PRESS RELEASE — As part of its Quantum Initiative, the University of Houston convened global industry leader IonQ, national laboratory partners and energy executives for the symposium, “Powering the Future: Quantum Technologies in the Energy Economy,” advancing its efforts to align research, talent and industry collaboration in quantum technologies. The initiative builds on momentum from the Texas Quantum Summit, a statewide alliance where UH and seven other universities identified four strategic pillars shaping the field: quantum computing, quantum materials and devices, quantum networks and workforce development. UH’s Quantum Initiative aligns its expertise with these statewide and national priorities, positioning the institution as a primary engine for innovation in the region. “The University of Houston has long been recognized for its leadership in energy research and its deep partnerships with industry,” said Claudia Neuhauser, vice president and vice chancellor for research at UH. “As energy systems evolve to incorporate advanced computation, new materials and digital infrastructure, quantum technologies will become part of that future landscape.” Building a Workforce for a Rapidly Expanding Industry Industry leaders at the symposium emphasized the urgency of preparing talent at scale. Industry data from IonQ suggests the global quantum sector could require as many as 850,000 workers within the next decade; however, current projec
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quantum-computingA streamlined quantum algorithm for topological data analysis with exponentially fewer qubits
AbstractTopological invariants of a dataset, such as the number of holes that survive from one length scale to another (persistent Betti numbers) can be used to analyze and classify data in machine learning applications. We present an improved quantum algorithm for computing persistent Betti numbers, and provide an end-to-end complexity analysis. Our approach provides large polynomial time improvements, and an exponential space saving, over existing quantum algorithms. Subject to gap dependencies, our algorithm obtains an almost quintic speedup in the number of datapoints over previously known rigorous classical algorithms for computing the persistent Betti numbers to constant additive error – the salient task for applications. However, we also introduce a quantum-inspired classical power method with provable scaling only quadratically worse than the quantum algorithm. This gives a provable classical algorithm with scaling comparable to existing classical heuristics. We discuss whether quantum algorithms can achieve an exponential speedup for tasks of practical interest, as claimed previously. We conclude that there is currently no evidence for this being the case.► BibTeX data@article{McArdle2026streamlinedquantum, doi = {10.22331/q-2026-04-10-2058}, url = {https://doi.org/10.22331/q-2026-04-10-2058}, title = {A streamlined quantum algorithm for topological data analysis with exponentially fewer qubits}, author = {McArdle, Sam and Gily{\'{e}}n,, Andr{\'{a}}s and Berta, Mario}, journal = {{Quantum}}, issn = {2521-327X}, publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}}, volume = {10}, pages = {2058}, month = apr, year = {2026} }► References [1] Gunnar Carlsson. Topological methods for data modelling. Nature Reviews Physics, 2 (12): 697–708, 2020. 10.1038/s42254-020-00249-3. https://doi.org/10.1038/s42254-020-00249-3 [2] Vin De Silva and Robert Ghrist. Coverage in sensor networks via persistent homology. Algebra
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quantum-computingObservation of genuine $2+1$D string dynamics in a U$(1)$ lattice gauge theory with a tunable plaquette term on a trapped-ion quantum computer
--> Quantum Physics arXiv:2604.07436 (quant-ph) [Submitted on 8 Apr 2026] Title:Observation of genuine $2+1$D string dynamics in a U$(1)$ lattice gauge theory with a tunable plaquette term on a trapped-ion quantum computer Authors:Rohan Joshi, Yizhuo Tian, Kevin Hemery, N. S. Srivatsa, Jesse J. Osborne, Henrik Dreyer, Enrico Rinaldi, Jad C. Halimeh View a PDF of the paper titled Observation of genuine $2+1$D string dynamics in a U$(1)$ lattice gauge theory with a tunable plaquette term on a trapped-ion quantum computer, by Rohan Joshi and 7 other authors View PDF Abstract:Quantum simulations of high-energy physics in $2+1$D can probe dynamical phenomena nonexistent in one spatial dimension and access regimes that are challenging for existing classical simulation methods. For string dynamics -- relevant to hadronization -- a plaquette term is required to realize genuine $2+1$D behavior, as it endows the gauge field with dynamics and enables the propagation of photon-like excitations. Here, we realize a U$(1)$ quantum link model of quantum electrodynamics in two spatial dimensions with a tunable plaquette term on a \texttt{Quantinuum System Model H2} quantum computer. We implement, to our knowledge, the largest quantum simulation of string-breaking dynamics reported to date, on a $5 \times 4$ matter-site square lattice using $51$ qubits. The simulation uses a shallow circuit design with a two-qubit gate depth of $28$ per Trotter step and up to $1540$ entangling gates. Starting from far-from-equilibrium string configurations, we measure the probability for the string to propagate within the lattice plane and find signatures of genuine $2+1$D dynamics only when the plaquette term is present. In a resonant regime, we observe the annihilation of string segments accompanied by the production of electron--positron pairs that screen them. We further find that, only with a nonzero plaquette term, matter creation extends across the lattice plane rather than remaining confined
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quantum-computingTen-Second Electron-Spin Coherence in Isotopically Engineered Diamond
--> Quantum Physics arXiv:2604.07439 (quant-ph) [Submitted on 8 Apr 2026] Title:Ten-Second Electron-Spin Coherence in Isotopically Engineered Diamond Authors:Takashi Yamamoto, H. Benjamin van Ommen, Kai-Niklas Schymik, Beer de Zoeten, Shinobu Onoda, Seiichi Saiki, Takeshi Ohshima, Hadi Arjmandi-Tash, René Vollmer, Tim H. Taminiau View a PDF of the paper titled Ten-Second Electron-Spin Coherence in Isotopically Engineered Diamond, by Takashi Yamamoto and 8 other authors View PDF HTML (experimental) Abstract:Solid-state spin defects are a promising platform for quantum networks. A key requirement is to combine long ground-state spin-coherence times with a coherent optical transition for spin-photon entanglement. Here, we investigate the spin and optical coherence of single nitrogen-vacancy (NV) centres in (111)-grown isotopically engineered diamond. Our diamond-growth process yields a precisely controlled $^{13}\mathrm{C}$ concentration and low-ppb nitrogen concentrations. Combined with the mitigation of 50 Hz noise using a real-time feedforward scheme and tailored decoupling sequences, this enables record defect-electron-spin coherence times of $T_2 = 6.8(1)$ ms for a Hahn echo and of $T_2^{DD} = 11.2(8)$ s under dynamical decoupling. In addition, we observe coherent optical transitions with a near-lifetime-limited homogeneous linewidth of 16.9(4) MHz and characterize the spectral diffusion dynamics. These results provide new avenues to investigate the incorporation of impurities in diamond and new opportunities for improved spin-qubit control for quantum networks and other quantum technologies. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2604.07439 [quant-ph] (or arXiv:2604.07439v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2604.07439 Focus to learn more arXiv-issued DOI via DataCite Submission history From: H. Benjamin Van Ommen [view email] [v1] Wed, 8 Apr 2026 18:00:01 UTC (1,285 KB) Full-text links: Access Paper: View a PDF
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quantum-computingOperational criteria for quantum advantage in latency-constrained nonlocal games
--> Quantum Physics arXiv:2604.07451 (quant-ph) [Submitted on 8 Apr 2026] Title:Operational criteria for quantum advantage in latency-constrained nonlocal games Authors:Changhao Li, Seigo Kikura, Akihisa Goban, Hayata Yamasaki, Shinichi Sunami View a PDF of the paper titled Operational criteria for quantum advantage in latency-constrained nonlocal games, by Changhao Li and 4 other authors View PDF HTML (experimental) Abstract:Remote entanglement enables coordinated decision making without communication and produces correlations beyond those achievable by any classical strategy, representing a practical quantum advantage in time-critical distributed decision-making problems. However, existing analyses of quantum-classical gaps in such latency-constrained tacit coordination (LCTC) have focused on idealized models that neglect the finite stationary window of the LCTC, finite operation times, and limited entanglement generation rates, leaving fundamental constraints unaccounted for. In this work, we develop a comprehensive framework to quantitatively analyze quantum advantage in LCTC that explicitly incorporates finite-duration and finite-rate operations, as well as generalized utility structures with a limited stationary window. These advances are made possible by adapting statistical certification methods for nonlocal games to the decision-making scenarios of LCTC, identifying operational criteria that must be satisfied by the hardware implementations to realize quantum advantage with sufficient statistical significance. To meet the stringent criteria, we propose time-multiplexed, event-ready operations of cavity-assisted trapped-atom quantum network nodes that provide a continuous stream of entangled qubit pairs, with decision latencies of a microsecond and decision rates of $8\times 10^3~\text{s}^{-1}$ per channel for a representative metropolitan-scale $50$-km fiber network to keep up with the fast-changing environment, such as financial markets and electric grid n
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quantum-computingQuantum Simulation of Collective Neutrino Oscillations using Dicke States
--> Quantum Physics arXiv:2604.07452 (quant-ph) [Submitted on 8 Apr 2026] Title:Quantum Simulation of Collective Neutrino Oscillations using Dicke States Authors:Katarina Bleau, Nikolina Ilic, Joachim Kopp, Ushak Rahaman, Xin Yue Yu View a PDF of the paper titled Quantum Simulation of Collective Neutrino Oscillations using Dicke States, by Katarina Bleau and 4 other authors View PDF HTML (experimental) Abstract:In dense neutrino gases, which exist for instance in supernovae, the flavour states of different neutrinos may become entangled with one another. The theoretical description of such systems may therefore call for simulations on a quantum computer. Existing quantum simulations of simple toy systems are not optimal in the sense that they do not fully exploit the symmetries of the system. Here, we propose a new class of qubit-efficient algorithms based on Dicke states and the $su(2)$ spin algebra. We demonstrate the excellent performance of these algorithms both on classical and on quantum hardware. Comments: Subjects: Quantum Physics (quant-ph); High Energy Astrophysical Phenomena (astro-ph.HE); High Energy Physics - Phenomenology (hep-ph) Cite as: arXiv:2604.07452 [quant-ph] (or arXiv:2604.07452v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2604.07452 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Katarina Bleau [view email] [v1] Wed, 8 Apr 2026 18:00:06 UTC (1,549 KB) Full-text links: Access Paper: View a PDF of the paper titled Quantum Simulation of Collective Neutrino Oscillations using Dicke States, by Katarina Bleau and 4 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph < prev | next > new | recent | 2026-04 Change to browse by: astro-ph astro-ph.HE hep-ph References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × load
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quantum-computingOn Lorentzian symmetries of quantum information
--> Quantum Physics arXiv:2604.07471 (quant-ph) [Submitted on 8 Apr 2026] Title:On Lorentzian symmetries of quantum information Authors:James Fullwood, Vlatko Vedral, Edgar Guzmán-González View a PDF of the paper titled On Lorentzian symmetries of quantum information, by James Fullwood and 1 other authors View PDF HTML (experimental) Abstract:A foundational result in relativistic quantum information theory due to Peres, Scudo, and Terno, is that von Neumann entropy is not Lorentz invariant. Motivated by the "It from Qubit" paradigm, here we show that Lorentzian symmetries of quantum information emerge naturally in a pre-spacetime setting, without any reference to external variables such as position or momentum. In particular, we derive the natural action of the restricted Lorentz group $\text{SO}^+(1,3)$ on the internal degrees of freedom of a single qubit from a simple, information-theoretic principle we refer to as preservation of linear entropy. It is then shown that the Lorentz invariance of the linear entropy of a relativistic qubit is a special case of a much more general phenomenon, namely, that any spectral invariant of an operator we term the '$W$-matrix' is an $\text{SL}(2,\mathbb C)^{\otimes n}$ invariant scalar. Consequently, the linear $n$-partite quantum mutual information is shown to be an $\text{SL}(2,\mathbb C)^{\otimes n}$ invariant for all $n$-qubit states. Finally, we show that the correlation function associated with a pair of qubits in the singlet state yields the Minkowski metric on the space of qubit observables, whose symmetry group is the full Lorentz group $\text{SO}(1,3)$. In accordance with the "It from Qubit" paradigm, our results thus establish the natural emergence of relativistic spacetime structure from intrinsic properties of quantum information. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2604.07471 [quant-ph] (or arXiv:2604.07471v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2604.07
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Exponential quantum advantage in processing massive classical data
--> Quantum Physics arXiv:2604.07639 (quant-ph) [Submitted on 8 Apr 2026] Title:Exponential quantum advantage in processing massive classical data Authors:Haimeng Zhao, Alexander Zlokapa, Hartmut Neven, Ryan Babbush, John Preskill, Jarrod R. McClean, Hsin-Yuan Huang View a PDF of the paper titled Exponential quantum advantage in processing massive classical data, by Haimeng Zhao and Alexander Zlokapa and Hartmut Neven and Ryan Babbush and John Preskill and Jarrod R. McClean and Hsin-Yuan Huang View PDF Abstract:Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In this work, we prove that a small quantum computer of polylogarithmic size can perform large-scale classification and dimension reduction on massive classical data by processing samples on the fly, whereas any classical machine achieving the same prediction performance requires exponentially larger size. Furthermore, classical machines that are exponentially larger yet below the required size need superpolynomially more samples and time. We validate these quantum advantages in real-world applications, including single-cell RNA sequencing and movie review sentiment analysis, demonstrating four to six orders of magnitude reduction in size with fewer than 60 logical qubits. These quantum advantages are enabled by quantum oracle sketching, an algorithm for accessing the classical world in quantum superposition using only random classical data samples. Combined with classical shadows, our algorithm circumvents the data loading and readout bottleneck to construct succinct classical models from massive classical data, a task provably impossible for any classical machine that is not exponentially larger than the quantum machine. These quantum advantages persist even when classical machines are granted unlimited time or if BPP=BQP, and rely only on the correctness of quantum mechanics. Together, our results establish machine lear
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