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Topological Quantum Computing: Microsoft Majorana Qubits & Error Protection

Topological quantum computing news: Microsoft Azure Quantum, Majorana fermions, topological qubits. Intrinsic error protection research.

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Topological quantum computing represents the most ambitious approach to fault-tolerant quantum computation, encoding information in global topological properties of quantum systems rather than individual particles. This intrinsic error protection theoretically enables quantum computing with hardware error rates orders of magnitude higher than conventional qubits require.

Microsoft Azure Quantum leads development through its Station Q research division, pursuing topological qubits based on Majorana zero modes—quasiparticles that are their own antiparticles and exist at the boundaries of topological superconductors. When braided, Majorana modes perform quantum gates that depend only on the braiding topology, not local perturbations.

India's Topological Quantum Research

India's theoretical physics community contributes to topological quantum computing research through institutions including the Tata Institute of Fundamental Research (TIFR) Mumbai, Indian Institute of Science (IISc) Bengaluru, and the International Centre for Theoretical Sciences (ICTS) Bengaluru. Research focuses on topological phases of matter, anyonic statistics, and quantum information theory foundations. The National Quantum Mission does not currently prioritize topological qubit hardware development, focusing instead on superconducting, photonic, and neutral atom platforms with nearer-term viability.

Key Advantages

Key advantages include intrinsic topological protection eliminating need for active quantum error correction overhead, hardware error tolerance potentially 1,000x higher than other qubit types, and stable quantum information storage. Current challenges include experimental verification of Majorana modes remaining contentious, requirements for exotic materials at millikelvin temperatures, and no confirmed demonstration of topological qubit operation.

Recent Progress

Recent progress includes new generation experiments using improved hybrid semiconductor-superconductor devices (InAs/Al, InSb/Al heterostructures) reporting more robust Majorana signatures. Microsoft continues significant investment despite delays.

Fisica Team Quantifies Decay Rates in Majorana Qubitsquantum-computing

Fisica Team Quantifies Decay Rates in Majorana Qubits

Analytical equations now detail how external disturbances impact Majorana qubits for the first time, moving beyond previous approximations. Sauri Bhattacharyya and Bernard van Heck from Dipartimento di Fisica, Sapienza Universit`a di Roma developed equations describing a Majorana qubit’s steady state, parity leakage rate, and decoherence rate within a topological superconductor experiencing quasiparticle poisoning, a process where unwanted particles disrupt coherence. The analysis shows that imperfections in materials influence majorana qubit stability; these qubits represent a potential pathway toward constructing more resilient quantum computers. The team’s analysis reveals initial protection against computational errors diminishes when key characteristics within the qubit change due to external disturbances affecting its coherence. This quantitative understanding will aid future development by enabling interpretation of data from experimental prototypes. Their work details how external disturbances impact Majorana qubits, unusual states of matter potentially useful for storing quantum information because they are naturally protected from certain types of noise. The team derived analytical expressions describing a qubit’s behaviour within a topological superconductor experiencing quasiparticle poisoning, disruptions caused by unwanted particles impacting coherence. The analysis reveals that initial error protection decreases as characteristics change in the qubit itself; this is similar to tracking how a spinning top gradually slows down through friction and energy loss over time. These findings provide quantitative insight into interpreting data from experimental prototypes and will support further development towards building more resilient quantum computers, although questions remain regarding precisely how these disturbances affect long-term stability. Increased Energy Splitting Mitigates Decoherence via Quasiparticle Poisoning in Topological Qubits A key indi

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WVU physicist wins NSF award to design quantum materialsquantum-computing

WVU physicist wins NSF award to design quantum materials

photo Jennifer Shephard · wvutoday.wvu.edu Subhasish Mandal, an assistant professor at West Virginia University, has received a National Science Foundation CAREER award to design materials essential for advancing quantum computing. Unlike regular computers that rely on bits of 0 or 1, quantum computers utilize quantum states capable of existing in multiple configurations simultaneously; however, maintaining these states proves challenging. Mandal’s research investigates how electrons interact with atomic vibrations within materials, interactions believed to be key to stabilizing quantum states. “One of the biggest challenges in quantum technology is finding materials that can maintain their quantum behavior outside carefully controlled laboratory environments,” Mandal said. CAREER Award Fuels Quantum Material Design at WVU Rather than relying solely on physical experimentation, Mandal’s approach prioritizes simulations to narrow the field of potential candidates before laboratory work begins. “Instead of making every quantum material possible to see which perform well, researchers could first use software to run simulations to identify the most promising options,” Mandal said, outlining the efficiency gains this method offers. Mandal’s research centers on materials constructed from stacked atomic layers, a technique allowing for the creation of quantum properties unattainable in single-element materials. These investigations will utilize advanced computer methods and large-scale simulations to determine if materials exhibit superconductivity, the lossless flow of electricity, and topological quantum states, which resist external disturbances. Scientists theorize that combining these two properties could provide the foundation for building practical quantum computers. The project extends beyond material discovery, with a significant focus on workforce development. Mandal intends to create accessible educational resources about quantum science and technology, alongsid

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Floquet Majorana XYZ Codes with Tunable Logical Dynamicsquantum-computing

Floquet Majorana XYZ Codes with Tunable Logical Dynamics

--> Quantum Physics arXiv:2609.10683 (quant-ph) [Submitted on 9 Sep 2026] Title:Floquet Majorana XYZ Codes with Tunable Logical Dynamics Authors:Xinyu Sun, Hong Yao View a PDF of the paper titled Floquet Majorana XYZ Codes with Tunable Logical Dynamics, by Xinyu Sun and Hong Yao View PDF HTML (experimental) Abstract:We construct Floquet codes from the Majorana XYZ subsystem code with local realizations both in qubits and directly in microscopic Majorana modes with lattice size $L\times L$. For a three-step cycle, odd $L$ supports one static logical qubit, whereas even $L$ supports two. For even $L$ with $L=4n+2$, both logical qubits admit time-independent Pauli representatives. For $L=4n$, by contrast, one Pauli of the second logical qubit remains fixed throughout the cycle, while every representative of its conjugate must evolve through the measurement cycle. This distinction follows from a parity-dependent algebraic obstruction and disappears when the cycle is reduced to two steps, which restores a fully static logical pair. Thus, the same encoded logical degree of freedom can be switched between static and partially dynamical forms by the measurement schedule. With one open direction, suitable protocols can be implemented using only local Majorana parity measurements. To our knowledge, this is the first Floquet-code family with both a local qubit representation and a direct microscopic Majorana realization. Comments: Subjects: Quantum Physics (quant-ph); Statistical Mechanics (cond-mat.stat-mech); Strongly Correlated Electrons (cond-mat.str-el) Cite as: arXiv:2609.10683 [quant-ph]   (or arXiv:2609.10683v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2609.10683 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Xinyu Sun [view email] [v1] Wed, 9 Sep 2026 18:00:02 UTC (108 KB) Full-text links: Access Paper: View a PDF of the paper titled Floquet Majorana XYZ Codes with Tunable Logical Dynamic

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Assistant Professor in Physics specialising in Quantum Information Theoryquantum-computing

Assistant Professor in Physics specialising in Quantum Information Theory

Assistant Professor in Physics specialising in Quantum Information Theory Application deadline: Monday, October 5, 2026Employer web page: https://www.uu.se/en/department/physics-and-astronomy/research/quantum-matter-theoryJob type: ProfessorshipTags: quantum networksquantum error correctionquantum correlationsquantum measurement theorytopological and geometric aspects of quantum informationmathematical foundations of quantum information theoryWe are looking for an assistant professor (tenure-track) who wants to develop and strengthen our research and education in quantum information theory at the international forefront. The position is within the Quantum Matter Theory research program. Together with the Materials Theory program, we offer a world-class environment for research with interests spanning from strongly correlated and topological quantum states of matter and theoretical aspects of quantum information to first-principles electronic structure calculations and green energy solutions. The position is also tied to the Centre for Geometry and Physics, an interdisciplinary research center to advance fundamental knowledge in mathematics and theoretical physics in, and at the interface between, geometry and physics. The Centre is a Swedish Research Council Center of Excellence, administrated jointly by the Department of Physics and Astronomy and Department of Mathematics. The subject area covers theoretical quantum information research that strengthens, possibly in a complementary way, current research activities within the Quantum Matter Theory program and connects to the Centre for Geometry and Physics. Current research activities span several contemporary areas of physics and mathematical physics. Of particular interest for this recruitment are activities in, but not limited to, quantum networks, quantum error correction, quantum correlations, quantum measurement theory, topological and geometric aspects of quantum information, and mathemati

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IonQ, NVIDIA, and qBraid Demonstrate 54% Error Reduction in Mid-Circuit Quantum Simulationsquantum-computing

IonQ, NVIDIA, and qBraid Demonstrate 54% Error Reduction in Mid-Circuit Quantum Simulations

IonQ, NVIDIA, and qBraid Demonstrate 54% Error Reduction in Mid-Circuit Quantum Simulations Trapped-ion hardware provider IonQ (NYSE: IONQ), high-performance computing leader NVIDIA, and quantum software startup qBraid have published joint research demonstrating an application-native error mitigation framework for deep Trotterized quantum chemistry. Executed on an IonQ Barium-based development system (similar to the forthcoming IonQ Tempo architecture) alongside GPU-accelerated classical computing, the team achieved a 54% reduction in logical error rates compared to direct physical Trotter executions during a 6-qubit encoded simulation step. [ IonQ–NVIDIA–qBraid Error Mitigation Framework ]Algorithmic ArchitecturePhysical & Hybrid Hardware StackKey Benchmark Findings• Generalized Superfast Encoding (GSE)• Barium Trapped-Ion QPU (IonQ Tempo Class)• 54% Lower Logical Error Rate vs. Direct Trotter• Clifford Noise Reduction (CliNR) Protocol• NVIDIA GH200 Grace Hopper Superchip• 0% Fidelity Gain if Measurements Are Deferred• Active Mid-Circuit Measurement (MCM)• CUDA-Q & cuStabilizer Software Libraries• ML Model Selected Top Stabilizers from 57k Samples Arresting Cascading Noise via Active Mid-Circuit Intervention Simulating complex fermionic systems in chemistry and materials science requires Trotterization—a technique that breaks continuous time-evolution into deep sequences of quantum gates. In conventional NISQ executions, physical noise accumulates exponentially across successive Trotter steps, destroying the target signal (“the deep Trotter dilemma”). The joint research addresses this bottleneck by replacing long, non-local Jordan-Wigner strings with localized encodings and active error detection: Generalized Superfast Encoding (GSE): Maps fermionic operators to qubits using lower Pauli weights and local Majorana loop stabilizers, reducing circuit depth requirements and providing an inherent error-detecting structure. Clifford Noise Reduction (CliNR): Prepa

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Symmetry-enriched topological order in tensor networks: Defects, gauging and anyon condensationquantum-computing

Symmetry-enriched topological order in tensor networks: Defects, gauging and anyon condensation

AbstractWe study symmetry-enriched topological order in two-dimensional tensor network states by using graded matrix product operator algebras to represent symmetry-induced domain walls. A close connection to the theory of graded unitary fusion categories is established. Tensor network representations of the topological defect superselection sectors are constructed for all domain walls. The emergent symmetry-enriched topological order is extracted from these representations, including the symmetry action on the underlying anyons. Dual phase transitions, induced by gauging a global symmetry, and condensation of a bosonic subtheory, are analyzed and the relationship between topological orders on either side of the transition is derived. Several examples are worked through explicitly.Featured image: A domain wall matrix product operator in a tensor network state with symmetry-enriched topological order.Popular summaryThe interplay of symmetry and topology in entangled states of quantum matter produce physical phenomena such as the fractionalization of charge on anyonic quasiparticle excitations. Tensor networks provide a tractable classical framework for the simulation of complex quantum states. In this work we extend that framework to include general symmetry actions on topological states of quantum matter in two dimensions.► BibTeX data@article{Williamson2026symmetryenriched, doi = {10.22331/q-2026-09-01-2199}, url = {https://doi.org/10.22331/q-2026-09-01-2199}, title = {Symmetry-enriched topological order in tensor networks: {D}efects, gauging and anyon condensation}, author = {Williamson, Dominic J. and Bultinck, Nick and Verstraete, Frank}, journal = {{Quantum}}, issn = {2521-327X}, publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}}, volume = {10}, pages = {2199}, month = sep, year = {2026} }► References [1] Lev Davidovich Landau and Evgenii Mikhailovich Lifshitz. ``Course of theoretical physics''. Pergamon Press.

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Quantum Resource Estimation for Simulating the SYK Model with Trotterization, qDRIFT, and Asymmetric Qubitizationquantum-computing

Quantum Resource Estimation for Simulating the SYK Model with Trotterization, qDRIFT, and Asymmetric Qubitization

--> Quantum Physics arXiv:2608.27573 (quant-ph) [Submitted on 27 Aug 2026] Title:Quantum Resource Estimation for Simulating the SYK Model with Trotterization, qDRIFT, and Asymmetric Qubitization Authors:Brian Goldsmith, Larissa Kroell, Nishna Aerabati View a PDF of the paper titled Quantum Resource Estimation for Simulating the SYK Model with Trotterization, qDRIFT, and Asymmetric Qubitization, by Brian Goldsmith and 2 other authors View PDF HTML (experimental) Abstract:The Sachdev-Ye-Kitaev (SYK) model has been identified as a promising candidate to run on early fault-tolerant quantum computers due to the relatively modest resources required to probe non-trivial physics (namely holographic duality and AdS/CFT correspondence). As such, it is crucial that the details of how to run such a simulation are well understood. Using PsiQuantum's Construct platform, we implement and analyze three different approaches to simulate the SYK model: Trotterization, qDRIFT, and asymmetric qubitization with Quantum Signal Processing. We provide an open-source library containing implementations for SYK simulation using all three methods, which we use to obtain quantum resource estimates for qubit and T gate count as functions of the number of Majorana modes and precision. We find that while qDRIFT and Trotterization benefit from a lower qubit count, the large number of T gates required lead to asymmetric qubitization being advantageous in most cases. This reinforces previous theoretical considerations. We intend both the implementations and the estimates to be useful for researchers to continue to study the SYK model and understand how the techniques and resources vary. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.27573 [quant-ph]   (or arXiv:2608.27573v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2608.27573 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Brian Goldsmith [view email] [v1] Thu, 27 Aug 2026 18:02:16 UTC

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Hardware-Aware Fermion-to-Qubit Mappings for Simulating the 2D Hubbard Model on Heavy-Hexagon Quantum Processorsquantum-computing

Hardware-Aware Fermion-to-Qubit Mappings for Simulating the 2D Hubbard Model on Heavy-Hexagon Quantum Processors

--> Quantum Physics arXiv:2608.25024 (quant-ph) [Submitted on 25 Aug 2026] Title:Hardware-Aware Fermion-to-Qubit Mappings for Simulating the 2D Hubbard Model on Heavy-Hexagon Quantum Processors Authors:Alessio Esposito, Andrea Giachero, Zoltàn Zimboràs, Leonardo Banchi View a PDF of the paper titled Hardware-Aware Fermion-to-Qubit Mappings for Simulating the 2D Hubbard Model on Heavy-Hexagon Quantum Processors, by Alessio Esposito and Andrea Giachero and Zolt\`an Zimbor\`as and Leonardo Banchi View PDF HTML (experimental) Abstract:Quantum simulation of strongly correlated fermionic systems is among the most promising near- term applications of quantum computing, but its practical efficiency depends critically on the choice of fermion-to-qubit mapping and on the connectivity of the underlying hardware. In this work we address this problem in the context of the two-dimensional Hubbard model, simulated on IBM superconducting quantum processors with heavy-hexagon connectivity. We numerically benchmark the Jordan-Wigner, Bravyi-Kitaev, and Bonsai transformations, evaluating their Pauli weight and SWAP overhead across seven heavy-hexagon chips of increasing size. We show that, while the Bravyi-Kitaev mapping initially exhibits a lower Pauli weight, this advantage is eliminated once routing costs are taken into account, confirming the Bonsai mapping as the most hardware-efficient baseline transformation for this architecture. We then use the Bonsai mapping to construct the qubit Hamiltonian of the 2D spinful Fermi-Hubbard model, introducing a simulated annealing algorithm that optimizes the assignment of Majorana strings to lattice sites, reducing the cost function by nearly 50% percent. Finally, we simulate on quantum hardware the time evolution of fermionic states up to 6x6 lattices, confirming the viability of the Bonsai encoding for hardware-aware large-scale two-dimensional simulations. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.25024 [quant-ph

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No Free Compression in Quantum Relaxations for Optimizationquantum-computing

No Free Compression in Quantum Relaxations for Optimization

--> Quantum Physics arXiv:2608.25151 (quant-ph) [Submitted on 25 Aug 2026] Title:No Free Compression in Quantum Relaxations for Optimization Authors:Stuart Hadfield View a PDF of the paper titled No Free Compression in Quantum Relaxations for Optimization, by Stuart Hadfield View PDF HTML (experimental) Abstract:Qubit-efficient quantum relaxations compress classical decision variables into expectation values on substantially fewer qubits. We ask what resource tradeoffs this compression entails for quantum optimization. For the complete quadratic-Majorana encoding on $n$ qubits, pairwise correlators can represent $m=\Theta(n^2)$ binary variables. We define the universal margin as the smallest correlator magnitude that can be guaranteed with prescribed signs for every target sign assignment. We show that it is exactly $\Delta_{\rm Maj}(n)=\tan\!\left(\frac{\pi}{4n}\right)=\Theta(1/n)$, whereas uniformly random sign assignments retain $\Theta(1/\sqrt n)$ target-specific margins. The stronger $1/n$ worst-case scaling is Majorana-specific. Moreover, arbitrary density operators and fermionic Gaussian states generate the same quadratic-Majorana covariance body, so non-Gaussian state resources cannot enlarge this two-point relaxation. Beyond Majoranas, standard quantum random access code bounds provide general information-theoretic baselines. For any fixed family of $m$ designated binary observables on $n$ qubits, the universal margin is at most $\sqrt{(2\ln2\;n/m)}$, while arbitrary random access decoding from $N$ copies with constant success probability above $1/2$ requires $nN=\Omega(m)$. For a fixed Pauli correlation encoding required to work uniformly over all targets, maintaining a fixed nonzero decoded magnitude under smooth sign decoding therefore requires a rescaling parameter that grows as the available margin shrinks. Thus, while providing substantial qubit savings, compression can shift cost into restricted expectation value geometry, smaller expectation value m

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Chicago Team Builds Integer Programming Topological Decoderquantum-computing

Chicago Team Builds Integer Programming Topological Decoder

Achieving key quantum error correction across diverse topological orders proved challenging due to limitations in existing decoders handling complex anyon behaviours. An integer linear programming (ILP) decoder now corrects errors in both Abelian and non-Abelian topological orders; it effectively manages correlated errors and varied anyon fusion rules. An improved method exists for correcting errors in quantum computers using topological codes, protecting information by encoding it within exotic particles called anyons. The new technique uses integer linear programming, a mathematical optimisation approach, to address ‘correlated’ errors where multiple data bits fail simultaneously, something previous methods struggled with. This advancement supports more complex types of topological orders, enhancing the robustness needed to build practical error-resistant quantum machines through better decoding strategies. A new technique has been unveiled for correcting errors in quantum computers using topological codes; these codes encode information within exotic particles called anyons, offering resilience against data corruption. Imagine arranging tiles on a floor, different arrangements represent unique ways to protect information even if some tiles are damaged; disturbances or ‘defects’ in that tile pattern signal an error has occurred. The team’s innovation lies in employing integer linear programming, akin to solving a puzzle where you find whole number solutions satisfying multiple rules simultaneously, to tackle ‘correlated errors affecting several bits at once and accommodate complex behaviours from various types of topological order. This advancement surpasses existing methods by effectively managing intricate scenarios and improving the robustness needed for practical machines. Reduced decoding complexity enables low error rates in diverse topological phases Error rates dropped to 8.4% for the Abelian Z 2 topological order under depolarizing noise using the new dec

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Adaptive Error Budget Allocation for Fault-Tolerant Quantum Resource Estimation: A Metaheuristic Approachquantum-computing

Adaptive Error Budget Allocation for Fault-Tolerant Quantum Resource Estimation: A Metaheuristic Approach

--> Quantum Physics arXiv:2608.19249 (quant-ph) [Submitted on 16 Aug 2026] Title:Adaptive Error Budget Allocation for Fault-Tolerant Quantum Resource Estimation: A Metaheuristic Approach Authors:Asif Akhtab Ronggon, Tasnuva Farheen View a PDF of the paper titled Adaptive Error Budget Allocation for Fault-Tolerant Quantum Resource Estimation: A Metaheuristic Approach, by Asif Akhtab Ronggon and 1 other authors View PDF HTML (experimental) Abstract:System-level resource estimation is a key component of fault-tolerant quantum computing (FTQC) toolchains. Its efficiency depends on how global error tolerance is allocated across logical operations, T-state distillation, and rotation synthesis to minimize physical resource overhead. The commonly used uniform-allocation strategy ignores circuit-specific structure and can overprovision inactive or less critical subsystems, leading to inflated space-time estimates. Prior work aims to address this limitation using supervised models trained on offline-generated datasets. However, this approach incurs additional data-generation costs and limits deployment flexibility. To overcome these drawbacks, we propose a training-free optimization framework that performs derivative-free search directly on the Azure Quantum Resource Estimator (AQRE), enabling instance-specific error budget allocation for previously unseen circuits without requiring offline training data. To evaluate robustness to optimizer choice, we instantiate the framework with two structurally distinct metaheuristics, simulated annealing and quantum particle swarm optimization. We evaluate our framework across 433 circuits spanning 2 to 91 qubits from 31 families in the MQT Bench suite. Across the benchmark suite, both methods reduce space-time cost by more than 33\% on average and agree within 1.34\% points, indicating that the gains are stable across different metaheuristic search strategies. Our analysis further finds that the optimization benefit is driven primarily

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Antidots measure anyonic charge in graphenequantum-computing

Antidots measure anyonic charge in graphene

Anyons are fractionally charged quasiparticles of the quantum Hall effect, and could one day power topological quantum computers. Trapping and measuring anyons remains difficult, but quasiparticle charges have now been measured using a gate-defined antidot in bilayer graphene. For hole-conjugate states, the parity of downstream integer edge modes sets the observed charge. This is a preview of subscription content, access via your institution Access options Access through your institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Learn more Subscribe to this journal Receive 12 print issues and online access $259.00 per year only $21.58 per issue Learn more Buy this articlePurchase on SpringerLinkInstant access to the full article PDF.USD 39.95Prices may be subject to local taxes which are calculated during checkout Fig. 1: Antidot device and measurement of fractional charge. Subjects Electronic properties and materials Quantum Hall ReferencesNayak, C., Simon, S. H., Stern, A., Freedman, M. & Das Sarma, S. Non-Abelian anyons and topological quantum computations. Rev. Mod. Phys. 80, 1083–1159 (2008). A review article about non-Abelian anyons and how braiding them could realize fault-tolerant topological quantum computation.Article  ADS  MathSciNet  Google Scholar  Glattli, D. C. Quantum shot noise of conductors and general noise measurement methods. Eur. Phys. J. Spec. Top. 172, 163–179 (2009). This review article covers experimental techniques for measuring current fluctuations, including methods for fractional charge detection.Article  Google Scholar  Dean, C., Kim, P., Li, J. I. A. & Young, A. in Fractional Quantum Hall Effects: New Developments (eds Halperin, B. I & Jain, J. K.) 317–375 (World Scientific, 2020). This book chapter reviews progress in understanding the fractional quantum Hall effects in graphene.Sim, H

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Hardness of approximation for minimum-weight decoding of two-dimensional topological quantum codesquantum-computing

Hardness of approximation for minimum-weight decoding of two-dimensional topological quantum codes

--> Quantum Physics arXiv:2608.17109 (quant-ph) [Submitted on 17 Aug 2026] Title:Hardness of approximation for minimum-weight decoding of two-dimensional topological quantum codes Authors:Louay Bazzi, Georges Khater View a PDF of the paper titled Hardness of approximation for minimum-weight decoding of two-dimensional topological quantum codes, by Louay Bazzi and Georges Khater View PDF HTML (experimental) Abstract:Efficient decoding is essential for the practical realization of fault-tolerant quantum computers. We study the computational complexity of minimum-weight decoding for topological quantum codes. For surface codes under the depolarizing channel, we consider Minimum-Weight decoding, which seeks a minimum-weight Pauli error consistent with both the $X$- and $Z$-syndromes. For color codes under independent $X$- and $Z$-error models, we consider Separate Minimum-Weight decoding. Assuming $P\neq NP$, we establish polynomial additive inapproximability gaps for these problems. Specifically, for the toric code and the $4.8.8$ color code on the torus, no polynomial-time algorithm can always produce a solution whose weight is within $\Omega(N^{1/14})$ of the optimum, where $N$ is the number of qubits. For the planar surface code, we obtain an $\Omega(N^{1/18})$ gap. Our inapproximability results use Håstad's hardness of approximation for MAX-3SAT. Our reduction develops a general, modular framework for embedding logical constraints into coupled primal--dual join problems on a lattice. A key ingredient is a localization argument that controls unintended interactions between different parts of the construction. Subjects: Quantum Physics (quant-ph); Computational Complexity (cs.CC) Cite as: arXiv:2608.17109 [quant-ph]   (or arXiv:2608.17109v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2608.17109 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Louay Bazzi [view email] [v1] Mon, 17 Aug 2026 20

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Quantum Motion Expands to Maryland’s Discovery District to Scale US Commercial and Defense Operationsquantum-computing

Quantum Motion Expands to Maryland’s Discovery District to Scale US Commercial and Defense Operations

Quantum Motion Expands to Maryland’s Discovery District to Scale US Commercial and Defense Operations U.K.-based silicon quantum computing company Quantum Motion has established a new U.S. operational hub in the University of Maryland’s Discovery District in College Park. The site will support the company’s commercial expansion and public-sector operations, placing Quantum Motion close to U.S. federal research and defense entities, including the Defense Advanced Research Projects Agency (DARPA) and the Applied Research Laboratory for Intelligence and Security (ARLIS). [ Quantum Motion US Operational Architecture ] │ ┌─────────────────────────────────┼─────────────────────────────────┐ ▼ ▼ ▼ Silicon CMOS Hardware Stack Federal Defense Integration Regional Hub Co-Location • Standard Fab Spin-Qubit QPUs. • DARPA QBI Program Support. • UMD Discovery District Complex. • Mass-Manufacturable Silicon. • ARLIS Research Initiatives. • Capital of Quantum (CoQ) Hub. • Scalable Control Electronics. • Public-Sector Commercialization. • Co-located with IonQ & Microsoft. The expansion leverages Quantum Motion’s core technical approach—developing spin-qubit quantum processing units (QPUs) using standard silicon complementary metal-oxide-semiconductor (CMOS) manufacturing processes. By utilizing existing semiconductor foundry fabrication infrastructure, Quantum Motion aims to manufacture high-density quantum chips at scale. Key operational objectives for the Maryland facility include: Government and Defense Collaboration: Supporting U.S. defense initiatives, including participation in DARPA’s Quantum Benchmarking Initiative (QBI) to evaluate scalable hardware metrics and fault-tolerant architectures. Regional Ecosystem Integration: Joining College Park’s quantum cluster alongside IonQ, Microsoft Quantum, IQM Quantum Computers, and NanoQT. State Initiative Alignment: Supporting Maryland’s Capital of Quantum (CoQ) initiative, a state-backed program launched in 2025 to expand public

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Any experience with Microsoft Azure or Quantinuum Nexus?quantum-computing

Any experience with Microsoft Azure or Quantinuum Nexus?

I have recently started learning about and working with the QIR LLVM extension by Microsoft and others. As far as I know, Microsoft and Quantinuum are the only companies that officially use QIR for their quantum computers. They both have cloud services in Microsoft Azure Quantum and Quantinuum Nexus. They seem to have advanced simulators and optimisation tools. My question is, if any of you have ever used these? I would be interested in your experience and thoughts about them. submitted by /u/JakeX02 [link] [comments]

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Quantum Sensing Leverages ML to Track Three-Level System Phasequantum-computing

Quantum Sensing Leverages ML to Track Three-Level System Phase

Researchers affiliated with the Dipartimento di Fisica e Astronomia ”Ettore Majorana”, Università di Catania, Italy have successfully trained a multi-layer perceptron (MLP) to estimate the plaquette phase within a three-level system, demonstrating a new method for extracting information using artificial intelligence. The team utilized STImulated Raman Adiabatic Passage (STIRAP) population transfer efficiencies as the data source for the machine learning model, establishing a direct link between a specific quantum control technique and AI-driven analysis. This plaquette phase profoundly affects system dynamics by breaking coherent population trapping and inducing a non-trivial phase dependence, according to the work. The results highlight how combining coherent control and machine learning enables effective phase identification, potentially opening new perspectives for quantum technologies, specifically quantum sensing applications including synthetic gauge fields. Plaquette Phase Impacts Coherent Population Trapping The subtle interplay of quantum phases can dramatically alter system behavior, and recent work demonstrates this with the identification of a phase in three-level quantum systems that profoundly affects the system dynamics, breaking coherent population trapping. The team’s findings reveal that accurately estimating this plaquette phase is now possible through a combination of established quantum control methods and machine learning. STIRAP is a well-established technique for efficiently moving quantum populations between states, but the presence of the plaquette phase introduces complexities. The researchers discovered that the efficiency of STIRAP is affected by the phase, creating a measurable signature that a machine learning algorithm can interpret. Specifically, a multi-layer perceptron (MLP), a type of machine learning, was successfully trained to estimate the plaquette phase, demonstrating a novel way to extract information from quantum systems us

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Robust topological quantum state transfer with long-range interactions in Rydberg arraysquantum-computing

Robust topological quantum state transfer with long-range interactions in Rydberg arrays

AbstractWe develop a theoretical framework for fast, robust and high-fidelity topological quantum state transfer in one-dimensional systems with long-range couplings, motivated by chains of Rydberg atoms with dipole–dipole interactions. Such long-range interactions naturally give rise to extended Su–Schrieffer–Heeger and Rice–Mele models supporting topologically protected edge states. We show that these edge states enable high-fidelity edge-to-edge excitation transfer using both time-independent protocols, based on coherent edge state dynamics, and time-dependent protocols, based on adiabatic modulation of system parameters. Long-range couplings play a central role by enhancing the relevant energy gaps, leading to a substantial improvement in transfer efficiency compared to nearest neighbour models. The resulting transfer is robust against positional disorder, reflecting its topological origin and highlighting the potential of long-range interacting platforms for reliable quantum state transfer.Featured image: Quantum state transfer in the extended Rice-Mele model. a)-e) Rydberg excitation probability distribution and lattice configuration at representative times during an edge-to-edge quantum state transfer protocol in the extended Rice–Mele model. Empty circles denote lattice sites with zero excitation probability, while filled circles indicate non-zero excitation probability, with color intensity proportional to the local population. f) Transfer fidelity $F$ as a function of the total transfer time $T$ for increasing chain lengths from $N=4$ to $N=16$. The inset shows the temporal variation of the geometrical parameters $b$ and $h$ and of the sublattice energy offset $\hbar\Delta$ during the transfer. The grey (white) background indicates parameter regions corresponding to the non-topological (topological) phase.► BibTeX data@article{Raupach2026robusttopological, doi = {10.22331/q-2026-08-13-2190}, url = {https://doi.org/10.22331/q-2026-08-13-2190}, title = {Robu

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Williamson majorization theory of fermionic non-Gaussianityquantum-computing

Williamson majorization theory of fermionic non-Gaussianity

--> Quantum Physics arXiv:2608.10140 (quant-ph) [Submitted on 10 Aug 2026] Title:Williamson majorization theory of fermionic non-Gaussianity Authors:Xhek Turkeshi, Piotr Sierant, Poetri Sonya Tarabunga View a PDF of the paper titled Williamson majorization theory of fermionic non-Gaussianity, by Xhek Turkeshi and 2 other authors View PDF HTML (experimental) Abstract:Pure-state entanglement rests on a single algebraic backbone: majorization of the Schmidt spectrum governs state conversion under local operations and classical communication, and constrains entanglement monotones. Here we establish a corresponding majorization law for fermionic non-Gaussianity, the resource that elevates free fermions to universal quantum computation. Under any fermionic Gaussian protocol with pure state outcomes, the Williamson spectrum of a pure state's Majorana covariance matrix is weakly majorized by its ensemble average. This spectral law mirrors that of entanglement theory. It turns computable non-Gaussianity quantifiers such as fermionic antiflatness and occupation entropies into strong monotones for fermionic non-Gaussianity, and delivers necessary conditions and converse bounds on state conversion under Gaussian protocols. When fermion parity is conserved, no catalyst can remove a majorization obstruction---unless it carries parity coherence---and asymptotic interconversion is irreversible already for pure states. All relevant quantities are accessible from two-point Majorana correlators, turning the theory developed here into experimentally observable properties of quantum matter, testable on present-day quantum devices. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.10140 [quant-ph]   (or arXiv:2608.10140v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2608.10140 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Poetri Sonya Tarabunga [view email] [v1] Mon, 10 Aug 2026 18:55:03 UTC (

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This Trillion-Dollar AI Stock Offers Better Quantum Computing Exposure Than IonQ, Rigetti, or D-Wave at a Multi-Year Valuation Lowquantum-computing

This Trillion-Dollar AI Stock Offers Better Quantum Computing Exposure Than IonQ, Rigetti, or D-Wave at a Multi-Year Valuation Low

If you want quantum computing exposure without betting the farm on a pre‑profit science project, I think a case is building that Microsoft (MSFT +0.03%) is the more interesting option right now. Microsoft is a $3 trillion AI stock whose own quantum roadmap has matured quietly in the background, and with sentiment cooled after a year of worry about AI spending, you're getting that quantum upside at what looks like a multiyear valuation low instead of peak euphoria. Image source: Getty Images. Microsoft is already a quantum platform Microsoft doesn't market itself as a quantum stock, but its Azure Quantum materials read like a company that has spent years building a full stack. Azure Quantum is a cloud service where developers can run quantum programs today on hardware from partners such as IonQ (IONQ +11.86%), Rigetti (RGTI +8.53%), Quantinuum (QNT -0.29%), and Pasqal, or on advanced simulators, using the same Azure environment they use for AI and high-performance computing. That matters. Quantum is not off in a lab. It's already being wired into Microsoft's mainstream developer tools and cloud workflows. ExpandNASDAQ: MSFTMicrosoftToday's Change(0.03%) $0.13Current Price$499.99Key Data Points*:nth-last-child(-n+2)]:border-b-0">Market Cap$3.7TMarket cap calculated using publicly traded shares outstanding only. Does not include unlisted, private, or dual-class non-traded shares. Implied market cap may vary.Day's Range$498.73 - $505.1852wk Range$349.20 - $553.72Volume28.8MAvg Vol41.2MGross Margin67.94%Dividend Yield0.71% In its quantum overview, Microsoft describes Azure Quantum as an "open, flexible, and future-proofed path" that adapts to how customers actually work. The company is effectively acting as the orchestrator, sitting between enterprise demand and multiple hardware providers. That is a very different position from a single hardware vendor trying to persuade the world to come and build on its island. Azure Quantum Elements and the long game The part that re

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Ising Models Simulate Majorana Fermions in Black Hole Spacetimequantum-computing

Ising Models Simulate Majorana Fermions in Black Hole Spacetime

Researchers at the National Institute of Physics, University of the Philippines Diliman, have found that transverse-field Ising models, systems of interacting quantum spins, can effectively simulate Majorana fermions within the curved spacetime surrounding a Schwarzschild black hole. The study finds that four distinct mathematical representations of this spacetime, Schwarzschild, tortoise, Kruskal, and conformally flat, each map onto a different microscopic Ising spin model, yet all converge to the same Majorana field theory. This convergence, described as exhibiting an emergent form of general covariance, provides a rare example of a fundamental symmetry of general relativity arising as an emergent property of a condensed matter system. The authors further demonstrate how black hole particle production can be simulated and detected through spin correlation measurements, and discuss experimental platforms capable of realizing these models. The work establishes a practical route for investigating fermionic quantum field theory in curved spacetime using controllable quantum many-body systems and tabletop experiments. The assertion that distinct mathematical descriptions of the same physical spacetime can map onto fundamentally different microscopic models is now being validated through novel quantum simulations. This unexpected connection highlights a deep relationship between the mathematical tools used to describe spacetime and the underlying physical models that govern its behavior. This work builds upon the understanding that quantum field theory (QFT) emerges universally as an effective low-energy description of a broad class of quantum many-body systems. A new approach detailed in recent work suggests a pathway toward tabletop experiments utilizing condensed matter systems as analog gravitational environments. This work builds on previous findings, demonstrating how the Unruh effect can emerge in spin models representing an expanding universe. Their work details

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