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Quantum Cloud Services: AWS Braket, Azure Quantum & IBM Quantum

Quantum cloud computing news: QCaaS platforms, AWS Braket, Azure Quantum, IBM Quantum Experience. Cloud quantum access & hybrid computing.

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Quantum computing cloud services democratize access to quantum hardware, enabling researchers, enterprises, and developers to experiment with quantum processors without multi-million-dollar infrastructure investments.

Major global platforms include IBM Quantum with 20+ systems (5-1,000+ qubits); Amazon Braket providing hardware-agnostic access to IonQ, Rigetti, OQC, and D-Wave systems; and Microsoft Azure Quantum offering diverse hardware including IonQ, Quantinuum, and Rigetti.

India's Quantum Cloud Infrastructure

India's National Quantum Mission plans indigenous quantum cloud infrastructure development. The Foundation for QC Innovation at IISc Bengaluru will provide access to quantum computing resources as hardware matures. Until indigenous platforms are operational, the Department of Science and Technology facilitates cloud access to international quantum computers for Indian researchers.

The Andhra Pradesh Quantum Valley Tech Park, developed in partnership with IBM and TCS, will provide cloud access to an IBM Quantum System Two with 156-qubit Heron processor—the largest quantum computer in India. TCS will support development of algorithms and applications for Indian industry and academia through this facility.

The NQM targets making quantum computing resources accessible to startups, MSMEs, and researchers, with the quantum fabrication facilities at IISc Bengaluru and IIT Bombay providing prototyping and testing access.

Town to get millions for IBM Quantum project - Mid Hudson Newsquantum-computing

Town to get millions for IBM Quantum project - Mid Hudson News

TOWN OF POUGHKEEPSIE – The proposed IBM Quantum computing facility at the existing IBM campus on South Road (Route 9) in the town has become a financial windfall worth millions of dollars for the town.  The $54 million IBM has agreed to pay the town is separate from the Payment in Lieu of Taxes (PILOT) application that IBM submitted to the Dutchess County IDA.  If approved on Tuesday, the PILOT will require IBM to pay Dutchess County, the Town of Poughkeepsie, and the Spackenkill Union Free School District a set amount instead of annual taxes.

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Three-uniform edge-ordered hypergraph quantum states: entanglement and its relation to hypergraph propertiesquantum-computing

Three-uniform edge-ordered hypergraph quantum states: entanglement and its relation to hypergraph properties

--> Quantum Physics arXiv:2609.30399 (quant-ph) [Submitted on 24 Sep 2026] Title:Three-uniform edge-ordered hypergraph quantum states: entanglement and its relation to hypergraph properties Authors:N. A. Susulovska, Kh. P. Gnatenko View a PDF of the paper titled Three-uniform edge-ordered hypergraph quantum states: entanglement and its relation to hypergraph properties, by N. A. Susulovska and 1 other authors View PDF HTML (experimental) Abstract:The encoding of 3-uniform edge-ordered weighted hypergraphs into multiqubit quantum states is proposed. We derive an analytical expression for the geometric measure of entanglement of hypergraph quantum states and establish its relation to hypergraph properties. The results establish a direct connection between the local structure of hypergraphs, hyperedge weights, and the entanglement of the corresponding quantum states. For equally weighted hypergraphs, it is shown that the entanglement depends explicitly on the vertex degree. The dependence of entanglement on hypergraph parameters is studied analytically and using quantum computing. Hypergraph states associated with chain, star, regular lattice, and binary-tree hypergraphs are examined, and their entanglement is quantified using quantum computing. These results open up the possibility of studying hypergraph properties with quantum programming. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2609.30399 [quant-ph]   (or arXiv:2609.30399v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2609.30399 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Nataliia Susulovska [view email] [v1] Thu, 24 Sep 2026 18:04:35 UTC (7,410 KB) Full-text links: Access Paper: View a PDF of the paper titled Three-uniform edge-ordered hypergraph quantum states: entanglement and its relation to hypergraph properties, by N. A. Susulovska and 1 other authorsView PDFHTML (experimental)TeX Source view license Current

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Topology from disorderquantum-computing

Topology from disorder

Topological phases of matter have long been studied in idealized pure states at absolute zero. Two experiments now show how controlled disorder can give mixed states measurable topological features in quantum simulators. 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 Rent or buy this article Prices vary by article type from$1.95 to$39.95 Learn more Prices may be subject to local taxes which are calculated during checkout Fig. 1: Emergence of topology and topological phase boundaries in disordered quantum simulators. Subjects Quantum simulation Topological matter Ultracold gases Sensory Ethnography in Urban Anthropology ReferencesYue, Z. et al. Nat. Phys. 22, 844–850 (2026).Article  Google Scholar  Su, L. et al. Nat. Phys. https://doi.org/10.1038/s41567-026-03381-6 (2026).Article  Google Scholar  Senthil, T. Annu. Rev. Condens. Matter Phys. 6, 299–324 (2015).Article  ADS  Google Scholar  Chen, X., Gu, Z.-C., Liu, Z.-X. & Wen, X.-G. Science 338, 1604–1606 (2012).Article  ADS  Google Scholar  Ma, R. & Wang, C. Phys. Rev. X. 13, 031016 (2023). Google Scholar  Preskill, J. Quantum 2, 79 (2018).Article  Google Scholar  Google Quantum AI and Collaborators. Nature 638, 920–926 (2025).Article  ADS  Google Scholar  Evered, S. J. et al. Nature 645, 341–347 (2025).Article  ADS  Google Scholar  Braun, C. et al. Nat. Phys. 20, 1306–1312 (2024).Article  Google Scholar  Yao, R. et al. Nat. Phys. 20, 1726–1731 (2024).Article  Google Scholar  Download referencesAuthor informationAuthors and AffiliationsDepartment of Ph

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Quantum Zeitgeist Weekly Digestquantum-computing

Quantum Zeitgeist Weekly Digest

Logical qubits were the yardstick this week. Microsoft and Qolab published a definition of what makes a logical qubit scalable, and Infleqtion entangled 30 of them on its neutral-atom machine. IonQ showed that the classical decoding behind error correction can run on one ordinary CPU, removing a hardware bottleneck many had expected. Germany put money behind the same goal. It picked planqc and the LOGIQC consortium in its €640 million competition for error-corrected computers, and committed €122 million to a QUDORA-led project aiming for 50 logical qubits. IQM’s latest sales, in Brazil, Japan and a four-country European group, include staged upgrades toward logical operations in Finland. IonQ had the busiest week. Its Superion 256 is headed to NVIDIA’s research center, Florida International University and a new manufacturing site in South Korea. QuEra’s own survey found 45 percent of buyers now rank a fault-tolerance roadmap among their top criteria, though cost still comes first. Companies still count qubits, but buyers now want to know how many of them will be reliable. 1. Microsoft Quantum Defines Scalable Logical Qubit Characteristics Microsoft Quantum researchers, working with Qolab, have set out a definition of a scalable logical qubit. A logical qubit is one reliable unit of quantum information built from many error-prone physical qubits and kept alive by repeated error correction. The team judges them on reliability, scale, capability and performance, and says gains in one often cost ground in another. Microsoft is also working with Atom Computing and QuNorth on the Magne project, which aims to deliver a machine with more than 1,200 physical qubits encoding 50 logical qubits by late 2026. The definition gives buyers a way to compare machines on more than raw qubit count. Read more 2. IonQ Runs Real-Time Error Correction Decoder on a Single CPU IonQ has run a real-time error correction decoder on a single standard CPU. A decoder reads the error signals from a

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Zapata Quantum’s Sumit Kapur joins Boston’s Power 50 leadersquantum-computing

Zapata Quantum’s Sumit Kapur joins Boston’s Power 50 leaders

Sumit Kapur, chief executive of Boston-based quantum software company Zapata Quantum, has been named to the Boston Business Journal’s 2026 Power 50: Movement Makers list. The recognition follows a two-year period where Kapur led a restructuring focused on developing applications to run on rapidly advancing quantum hardware. “I am honored to be recognized alongside so many outstanding leaders in Boston,” said Kapur, adding that the achievement reflects Zapata Quantum’s origins in “the long arc of innovation that began in Harvard’s quantum computing lab and The Engine built by MIT.” Kapur’s Restructuring Positions Zapata for Quantum Application Leadership The company, which regained SEC reporting status and now trades on the OTCQB Venture Market under the ticker ZPTA, completed a $15 million financing round in April 2026 as the final step in this strategic shift, bringing total funding to $93 million. This capital infusion followed earlier Series An and B rounds in 2021 and 2023, and a bridge financing in 2025, enabling a rebuilding of the team and deepened industry partnerships, Zapata Quantum says. Kapur’s leadership prioritized re-integrating founding expertise from Harvard’s quantum computing lab, alongside new hires from established technology firms like Palantir, Oracle and Northrop Grumman. This blend of academic rigor and commercial experience was designed to accelerate the development of quantum software applications, addressing a critical bottleneck as quantum hardware rapidly advances. The company’s collaborative work with NVIDIA, using agentic AI to expedite quantum algorithm discovery, exemplifies this application-focused approach. Zapata’s Quantum Pilot platform, launched in early access on September 22, further demonstrates this commitment by providing enterprises with tools to evaluate the potential of quantum solutions. The impact of this restructuring extends beyond internal development, as evidenced by recognition of Zapata’s research with the Dana-

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Quantum Computing Stocks To Watch Today - September 26th - MarketBeatquantum-computing

Quantum Computing Stocks To Watch Today - September 26th - MarketBeat

Quantum Computing Stocks To Watch Today - September 26th Written by MarketBeatSeptember 26, 2026Add As Preferred SourceShareShareShare This ArticleLink copied to clipboard.Close Image from MarketBeat Media, LLC. Key Points Five quantum-computing stocks to watch are IonQ (IONQ), D-Wave Quantum (QBTS), Quantinuum (QNT), Quantum Computing (QUBT), and Horizon Quantum Computing (HQ), selected for their recent trading volume. IonQ and D-Wave provide cloud-based access to quantum systems, while Quantum Computing focuses on photonics-based machines, quantum sensing, random-number generation, and cybersecurity applications. The sector is moving toward early commercial adoption, driven partly by rising AI-related computing demand, but remains high-growth and highly speculative due to technological, financial, and regulatory uncertainties. MarketBeat previews top five stocks to own in October. MarketBeat Week in Review – 09/21 - 09/25IonQ, D-Wave Quantum, Quantinuum, Quantum Computing, and Horizon Quantum Computing Pte. are the five Quantum Computing stocks to watch today, according to MarketBeat's stock screener tool. Quantum computing stocks are shares of publicly traded companies involved in developing quantum-computing hardware, software, components, or related services. For investors, the term generally refers to a high-growth, highly speculative sector whose companies may face significant technological, financial, and regulatory uncertainties. These companies had the highest dollar trading volume of any Quantum Computing stocks within the last several days. Get IonQ alerts:Sign UpIonQ (IONQ)IonQ, Inc. engages in the development of general-purpose quantum computing systems in the United States. It sells access to quantum computers of various qubit capacities. The company makes access to its quantum computers through cloud platforms, such as Amazon Web Services (AWS) Amazon Braket, Microsoft's Azure Quantum, and Google's Cloud Marketplace, as well as through its cloud serv

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Great News for IonQ Stock Investors!quantum-computing

Great News for IonQ Stock Investors!

The quantum computing company announced a huge breakthrough. *Stock prices used were the afternoon prices of Sept. 23, 2026. The video was published on Sept. 25, 2026. Read NextSep 25, 2026 •By Chris NeigerRigetti, D-Wave, or IonQ: Which Quantum Stock Has the Best Shot at Survival?Sep 25, 2026 •By Johnny RiceIonQ Has Made Another Quantum Computing Breakthrough: Here's What a $1,000 Investment in It Could Look Like in 5 YearsSep 25, 2026 •By Will HealyBetter Quantum Computing Stock: Nvidia vs. IonQSep 25, 2026 •By Keithen Drury$500 Invested in IonQ Now Could 10x if Quantum AI Hits by 2029Sep 24, 2026 •By Keith SpeightsIonQ Cleared One of Quantum Computing's Biggest Hurdles. Should You Buy the Stock?Sep 23, 2026 •By Robert IzquierdoBigBear.ai vs. IONQ: Comparing Revenue Trends Between an Artificial Intelligence Upstart and a Quantum Computer CompanyAbout the AuthorA Fool since 2019, and a graduate of Cal State LA with a B.S. in Finance and M.A. in Economics. Parkev is an adjunct professor of Finance and enjoys reading about financial and economic history. You'll often find him writing about stocks in the consumer goods and technology sectors.TMFParkevX@TMFParkevStocks MentionedIonQNYSE: IONQ$45.48(+1.11%)+$0.50Motley Fool Stock Advisor’s Latest PickGet Access---% Avg Return*Average returns of all recommendations since inception. Cost basis and return based on previous market day close.

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Lockheed Martin opens massive quantum center to secure US arms edge - Interesting Engineeringquantum-computing

Lockheed Martin opens massive quantum center to secure US arms edge - Interesting Engineering

IBM quantum computer (left) quantum-enhanced military tech (right)IBM/Indra Group Lockheed Martin has opened a new center dedicated to turning quantum research into technologies that could serve future U.S. defense missions. The Lockheed Martin Quantum Innovation Center, known as QuIC, will bring the company’s quantum work under one organization. Engineers and researchers will develop prototypes while also evaluating technology created by outside companies and research partners. Quantum technology could eventually give military systems new capabilities in navigation, sensing and communications. Lockheed Martin has already spent more than 15 years working in those areas. The new center gives those efforts a dedicated structure as quantum research moves closer to practical applications. It will also draw on the company’s experience developing complex technologies for national security programs. New quantum hub QuIC will operate as a center of excellence for quantum research and development. Its work will cover multiple applications rather than focus on a single quantum technology. That includes integrating systems developed outside Lockheed Martin. The company can also access emerging technologies through Lockheed Martin Ventures, its corporate investment arm. Lockheed Martin recently expanded that fund to $1 billion. Its investments could give QuIC access to startups developing technologies that could complement internal research.More from MilitarySee AllMilitaryUS ally plans army of humanoid robots to conduct risky operations with drones, boost high-tech warfareMilitaryUS startup develops drone propulsion system to boost range, payload and speedMilitaryUS Navy advances new W93 nuclear warhead for submarine-launched missilesMilitaryWhat Northrop Grumman’s F/A-XX concept reveals about the Navy’s future carrier fighterInnovationWind turbines reduce radar coverage by 7% and increase blind spots by 15%, study finds Sarah Hiza, senior vice president of Technology and Inno

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Quantum hardware makerspace opens in Maryland with Fermilab’s helpquantum-computing

Quantum hardware makerspace opens in Maryland with Fermilab’s help

Credit: Ryan Postel, Fermilab · news.fnal.gov Fermilab’s open-source Quantum Instrumentation Control Kit, or QICK, is now central to a new quantum hardware makerspace established by Microsoft Quantum in Maryland’s Discovery District. The center aims to connect researchers from academia, industry, and government, providing hands-on experience with real quantum systems. Fermilab plans to expand QICK’s capabilities, adapting the control and readout system for use with a wider range of qubit types, and this work marks a step in broadening access to quantum tools and fostering development within the emerging field. Microsoft Quantum Makerspace Launches with Fermilab Partnership This collaboration directly addresses a need for hands-on quantum training, providing researchers across academia, national laboratories, and industry with a flexible tool for developing quantum applications. The makerspace will offer access to real quantum hardware alongside the expertise needed to utilize it effectively, which is a critical step in fostering growth within the emerging quantum community. Anna Grassellino, chief technology officer and associate laboratory director for the Technology Directorate at Fermilab, expressed enthusiasm for the partnership, stating, “We are thrilled that Microsoft has chosen QICK to be part of the quantum hardware makerspace and look forward to working with them on other projects as well.” Fermilab’s commitment to maintaining QICK as an open-source resource is central to this effort, allowing a broad range of users to contribute to its development and tailor it to their specific needs. Over 500 scientists worldwide already use QICK to refine qubit performance, demonstrating its existing value to the field and potential for expansion. The partnership extends beyond simply providing a tool for training; Microsoft and Fermilab are actively working to broaden the applicability of quantum-control technologies across diverse hardware platforms.

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Infleqtion Achieves 30 Entangled Logical Qubits on Sqale Neutral-Atom Quantum Processorquantum-computing

Infleqtion Achieves 30 Entangled Logical Qubits on Sqale Neutral-Atom Quantum Processor

Infleqtion Achieves 30 Entangled Logical Qubits on Sqale Neutral-Atom Quantum Processor Neutral-atom quantum technology developer Infleqtion, Inc. (NYSE: INFQ) has demonstrated 30 entangled logical qubits on its commercial Sqale™ quantum computing platform. Announced at Quantum World Congress 2026, the breakthrough encodes 30 logical qubits into just 80 physical neutral-atom qubits using a low 8:3 physical-to-logical overhead ratio, fulfilling the company’s 2026 technical roadmap commitment and marking the largest logical qubit entanglement demonstrated on a commercial neutral-atom system to date. The achievement integrates Infleqtion’s Sqale neutral-atom QPU hardware with its Superstaq™ quantum software compilation stack. By combining optical tweezers for individual qubit addressing with dynamic atom shuttling for all-to-all logical connectivity, the system executed an Instantaneous Quantum Polynomial-time (IQP) benchmark circuit containing 1,000 physical operations (1 KiloQuOp)—including four non-Clifford logical CCZ gates. The experimental run returned valid target state sampling at roughly 1,000× above the uniform-random background noise baseline. [ Infleqtion Sqale 30-Logical-Qubit Benchmark & Architecture Metrics ]Hardware & Encoding StackAlgorithmic & Gate InnovationSoftware & QEC Loss Correction• Physical Scale: 80 Neutral Atoms• Logical Scale: 30 Logical Qubits• Qubit Allocation: 10 blocks of 8 atoms• Encoding Code: [[8,3,3]] / [[8,3,2]] QEC• AI-Discovered Gate: GPT 5.6 Sol double-CZ• Gate Savings: 4 physical 2Q gates (vs 8 standard)• Non-Clifford Gates: 4 Transversal Logical CCZ• Total Execution: ~1 KiloQuOp (1,000 ops)• Compilation Platform: Superstaq• Signal-to-Noise: ~1,000× baseline• Loss Correction: Post-processing parity reconstruction quadrupled valid shot yields• Sampling Baseline: 25% hit fraction across 1B+ Hilbert outcomes• Target Applications: Q4Bio Biomarker Discovery, GPU-trained QPU inference• Roadmap Scaling Target:– 100 Log

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Mphasis and Copa Airlines Partner on Global Quantum Computing Challenge for Airline Disruption Managementquantum-computing

Mphasis and Copa Airlines Partner on Global Quantum Computing Challenge for Airline Disruption Management

Mphasis and Copa Airlines Partner on Global Quantum Computing Challenge for Airline Disruption Management IT services provider Mphasis (BSE: 526299 / NSE: MPHASIS) and Panama-based air carrier Copa Airlines have announced the winners of their joint international Quantum Computing Challenge. The hackathon brought together academic research teams from Indian Institutes of Technology (IITs) alongside the University of Calgary and the University of Lethbridge to develop hybrid quantum optimization pipelines for passenger re-accommodation during airline schedule disruptions. Passenger re-accommodation is a core operational process triggered by flight cancellations, severe weather, or sudden demand shifts. The multi-stage optimization problem requires reassigning impacted passengers to alternative flight paths while maximizing re-accommodation rates and adhering to strict operational constraints without lengthening computation runtimes. Traditionally solved via classical high-performance computing (HPC) solvers, the challenge re-engineered the pipeline to leverage quantum optimization algorithms using real operational datasets provided by Copa Airlines. [ Mphasis & Copa Airlines Quantum Challenge Architecture & Ecosystem ]Challenge PhaseEcosystem & Infrastructure PartnersEnd-to-End Technical Workflow• Phase 1: 22 IIT Teams evaluated by Mphasis & IIT-Madras faculty (6 shortlisted)• Phase 2: 6 IIT teams + 3 Canadian university teams (UCalgary / ULethbridge)• Software & QPU Platforms: Classiq, Multiverse Computing, qBraid• Ecosystem Partners: IIT-Madras, Quantum City (Alberta)• Impacted flight & passenger identification• Customer Value Management (CVM) scoring• Alternate flight ranking & pathing• Quantum-classical optimal seat assignment Organized in collaboration with Mphasis NEXT Labs, IIT-Madras, and Calgary-based ecosystem builder Quantum City, the final submissions utilized quantum software platforms provided by Classiq, Multiverse Computing,

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QC Design Unveils Meridian: Purpose-Built AI Architecture System Demonstrates Over 10× Reduction in Logical Error Ratesquantum-computing

QC Design Unveils Meridian: Purpose-Built AI Architecture System Demonstrates Over 10× Reduction in Logical Error Rates

QC Design Unveils Meridian: Purpose-Built AI Architecture System Demonstrates Over 10× Reduction in Logical Error Rates Ulm-based quantum software startup QC Design has published white paper results introducing Meridian, a specialized AI platform designed to automate and optimize fault-tolerant quantum computing (FTQC) hardware architectures. According to the study, Meridian achieved a 14.6× median reduction in evaluated logical error rates compared to state-of-the-art methods published in scientific literature across an evaluation suite of over 100 fault-tolerance design tasks. Co-founded by Dr. Ish Dhand (CEO) and Prof. Martin Plenio, QC Design developed Meridian to solve the cross-stack co-design challenge inherent in building fault-tolerant quantum systems. Designing scalable quantum processors requires simultaneous optimization across algorithm compilation, quantum error correction (QEC) code selection, syndrome-extraction circuit design, physical layout routing, and pulse control. Meridian couples specialized AI agents with Plaquette—QC Design’s quantum design-automation platform—which functions as an accurate simulation “world model.” Plaquette validates candidate architectures against physical hardware noise channels, including dephasing, crosstalk, and leakage mechanisms across superconducting, silicon spin, neutral atom, trapped ion, and photonic platforms. [ QC Design Meridian AI Benchmarking & Architecture Metrics ]Evaluation Scope & SuitePerformance vs. Published LiteraturePerformance vs. Frontier AI Agents• 100+ Design Tasks• 10 QEC Code Families• 6 Connectivity Classes• 14.6× Median LER Reduction• Improvement Range: 1.5× to 22,000ו Enables 14.6× deeper logical circuits• 43% Median LER Reduction vs. GPT-6 Astra• Max LER Reduction: 98.4% (~63× lower error)• Eliminates invalid/exploitative designs• Hardware ModalitiesSilicon Spins, Superconducting, Neutral Atoms, Trapped Ions, Photonics• Silicon-Spin Case Study29-fold LER reduction on distance-5

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memQ Open-Sources Industry-First Modality-Agnostic Distributed Quantum Compiler (memQ DQC)quantum-computing

memQ Open-Sources Industry-First Modality-Agnostic Distributed Quantum Compiler (memQ DQC)

memQ Open-Sources Industry-First Modality-Agnostic Distributed Quantum Compiler (memQ DQC) Quantum networking technology developer memQ Inc. has publicly released its Distributed Quantum Compiler (memQ DQC) as an open-source toolchain on GitHub. Spun out from the University of Chicago, the startup introduced the modality-agnostic software framework to provide scale-out deployment capabilities across multi-vendor, heterogeneous quantum processing unit (QPU) networks connected via optical quantum channels. The open-source release aligns with U.S. federal technology directives, including Executive Order 14413 issued in June 2026, which instructs government agencies to establish operational frameworks for quantum networking and distributed quantum computing architectures. By converting standard monolithic circuits into network-optimized OpenQASM execution graphs, memQ DQC enables developers, system integrators, and researchers to model multi-QPU execution, evaluate entanglement generation rates, and analyze resource trade-offs without requiring manual low-level quantum network programming. The modular compiler toolchain incorporates an interactive Quantum Network Constructor (QNC) that models arbitrary inter-QPU topologies (chain, ring, hub, grid, all-to-all) alongside intra-QPU physical qubit layouts. The compiler manages cross-processor dependencies by dynamically inserting state teleportation operations (qubit relocation) and gate teleportation primitives (Cat-Entangler and Cat-Disentangler protocols). Integrated discrete-event schedulers simulate heralded photon arrivals to generate time-resolved execution schedules under realistic physical hardware constraints, such as gate durations, decoherence times, and link entanglement generation rates. [ memQ DQC Open-Source Framework Feature & Capability Summary ]Software ComponentFunctional SpecificationSystem & Architectural BenefitQuantum Network Constructor (QNC)• Graphical topology configuration tool• Custom JS

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Quantum computational advantage in random-circuit sampling on IBM superconducting quantum computersquantum-computing

Quantum computational advantage in random-circuit sampling on IBM superconducting quantum computers

--> Quantum Physics arXiv:2609.28657 (quant-ph) [Submitted on 23 Sep 2026] Title:Quantum computational advantage in random-circuit sampling on IBM superconducting quantum computers Authors:Tigran Sedrakyan, Yuxuan Zhang, Hovnatan Karapetyan, Joshua D. Baktay, Hrant Gharibyan, Hayk Tepanyan View a PDF of the paper titled Quantum computational advantage in random-circuit sampling on IBM superconducting quantum computers, by Tigran Sedrakyan and 5 other authors View PDF HTML (experimental) Abstract:We report forward random-circuit sampling (RCS) on the 120-qubit Nighthawk r2 superconducting processor (\textit{ibm\_phoenix}) with square-lattice connectivity, using 61 qubits, native CZ gates, and the standard cloud execution stack with no benchmark-specific calibration. Two independent fidelity estimators---mirror benchmarking and three- and four-patch cross-entropy benchmarking (XEB)---agree with each other at every measured depth, the mirror from 4 to 40 cycles and the patched estimators from 20 to 40 cycles, across more than two orders of magnitude of fidelity decay, and exceed the first-generation Nighthawk r1 device by more than an order of magnitude at fixed depth. The 36-cycle circuits sit at the depth where tensor-network contraction cost saturates at system size: a contraction-cost estimator validated against the published Sycamore and Zuchongzhi networks places the single-amplitude cost at $\sim$$10^{22}$ complex operations. At $F_{\mathrm{XEB}}(36)=2.3\times10^{-3}$ under favorable memory assumptions this implies $1.2\times10^{27}$ machine operations within the bounded-fidelity rejection-sampling model --- more than a century of runtime on the Frontier supercomputer --- to collect a $10^{6}$-sample ensemble, which takes only 19\,s on Nighthawk r2. To our knowledge, this is the first demonstration of quantum advantage for a vanilla random-circuit sampling on a commercially and broadly accessible quantum processor that most non-expert quantum computer users can

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Fermilab joins Microsoft Quantum Research Center as initial partnerquantum-computing

Fermilab joins Microsoft Quantum Research Center as initial partner

Fermilab is joining Microsoft Quantum as an initial partner in a new quantum hardware makerspace at Microsoft’s quantum research center in the University of Maryland’s Discovery District. As part of its broader collaboration with Microsoft, the QICK kit will have expanded tools to broaden access to quantum-control technologies across hardware platforms. The post Fermilab joins Microsoft Quantum Research Center as initial partner appeared first on News.

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memQ Releases Open-Source Distributed Quantum Compilerquantum-computing

memQ Releases Open-Source Distributed Quantum Compiler

Insider Brief PRESS RELEASE — memQ™, the industry leader in quantum networking for scalable and distributed quantum computing, announced today the public release of its distributed quantum compiler (DQC). This integral part of a distributed quantum computing environment will be released as a publicly available, open-source offering available on GitHub. memQ’s DQC is a compilation […]

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MOS-based silicon spin qubits assessed by DARPA’s Quantum Benchmarking Initiativequantum-computing

MOS-based silicon spin qubits assessed by DARPA’s Quantum Benchmarking Initiative

Nearly 20 companies are now engaged in a demanding six-month assessment as part of DARPA’s Quantum Benchmarking Initiative, signaling a substantial investment in a diverse range of approaches to building practical quantum computers. The initiative aims to rapidly verify if a fault-tolerant quantum computer, one where computational value exceeds cost, can be realized by 2033, a timeline far more aggressive than conventional predictions. Successful completion of this initial stage will lead to a yearlong, rigorous examination of research and development plans. DARPA’s Quantum Benchmarking Initiative: Stage A Company Selection This selection signals a significant investment in a diverse range of quantum approaches, particularly notable given the early stage of the technology and the high bar for entry into the program. DARPA launched QBI in July 2024 with the explicit goal of determining if the development of a useful, fault-tolerant quantum computer can be accelerated beyond current projections. The initiative’s core aim is rigorous verification of whether any quantum computing approach can achieve utility-scale operation, where computational value surpasses cost, by 2033. The companies selected for Stage A, including established players like IBM and Google Quantum AI, represent a broad spectrum of qubit technologies. Beyond superconducting and trapped-ion approaches, the cohort encompasses neutral atom qubits, photonic qubits, and silicon CMOS spin qubits, demonstrating DARPA’s commitment to exploring multiple pathways toward quantum advantage. Diraq, with operations spanning Australia, California, and Massachusetts, is pursuing silicon CMOS spin qubits, while QuEra Computing focuses on neutral atom qubits, highlighting the international scope of the initiative and the varied technological bets being placed. This diversity reflects an understanding that the optimal qubit technology remains an open question, and a comprehensive evaluation is important.

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Five of six Q4Bio finalists used IBM quantum hardwarequantum-computing

Five of six Q4Bio finalists used IBM quantum hardware

Five of six finalists in Wellcome Leap’s Q4Bio challenge specifically chose IBM quantum hardware to run large-scale demonstrations of algorithms designed for healthcare applications. Algorithmiq, in collaboration with Cleveland Clinic and IBM, earned the $2 million Q4Bio prize for simulating processes in photodynamic therapy, a cancer treatment. Q4Bio is targeting a timeframe of three to five years for these algorithms to run on near-term quantum computers. Q4Bio Challenge Drives IBM Quantum Hardware Adoption IBM quantum systems were important for five of six teams competing in Wellcome Leap’s Q4Bio challenge, a demonstration of practical necessity alongside potential preference in the nascent field of quantum biology. The hardware enabled execution of circuits approaching 100 qubits, a scale necessary for validating algorithms designed to tackle complex genomic data, and supported continuous refinement crucial for identifying bottlenecks. This reliance on IBM’s technology underscores the current landscape where utility-scale quantum computers are essential for translating theoretical algorithms into demonstrable results. The Q4Bio challenge, launched in 2023 with $40 million in funding, specifically required teams to run large-scale demonstrations on real quantum hardware, targeting algorithms viable within three to five years. Fred Chong, Professor at University of Chicago and Chief Scientist for Quantum Software at Infleqtion, stated that Heron QPUs could meet the challenge criteria of exceeding 50 qubits and 1,000 quantum gates. His team used these capabilities to demonstrate a hybrid quantum-classical approach improving biomarker identification compared to purely classical methods, a result contingent on access to advanced hardware. The winning team’s work used quantum computing to simulate key processes in photodynamic therapy (PDT), a cancer treatment. This framework incorporated novel methods for active space selection, state preparation, measurement, and po

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Classiq, INGL, and IonQ Advance Quantum Optimization for Natural Gas Transmission Networksquantum-computing

Classiq, INGL, and IonQ Advance Quantum Optimization for Natural Gas Transmission Networks

Classiq, INGL, and IonQ Advance Quantum Optimization for Natural Gas Transmission Networks Quantum software company Classiq Technologies and state-owned utility Israel Natural Gas Lines Ltd. (INGL) have published joint research applying hybrid quantum-classical optimization to natural gas pipeline delivery. Published on arXiv (arXiv:2609.00825), the study demonstrates a Quantum Approximate Optimization Algorithm (QAOA) workflow to maximize gas throughput across pipeline networks under non-linear hydraulic and physical constraints, validated with physical hardware execution on the IonQ Forte-1 trapped-ion quantum computer. Managing natural gas transmission requires optimizing nodal pressure configurations to maximize customer delivery while adhering to conservation of mass at junction nodes, directional flow consistency, and minimum endpoint delivery pressures. Governed by the non-linear Panhandle-B equation, the combinatorial complexity of discretized pressure assignments grows exponentially with network size (2nd state space for d decision nodes discretized across n qubits). Classiq and INGL formulated the problem as a Quadratic Unconstrained Binary Optimization (QUBO) model using a second-degree polynomial approximation of the Panhandle-B flow exponent (αPB = 0.51). The workflow was synthesized using Classiq’s platform and tested on a representative six-node, five-directed-edge gas transmission network. In simulator-based testing with p = 30 QAOA layers, the algorithm successfully recovered the maximum-throughput valid operating point, matching classical reference solutions. To test near-term hardware feasibility, a reduced 10-qubit problem instance was deployed on the IonQ Forte-1 QPU. Remarkably, using a shallow p = 2 QAOA layer setup to limit gate noise, the QPU returned physically valid candidate operating points that bracketed the continuous classical optimum within a single pressure-discretization step. [ Classiq & INGL Gas Network QAOA Implementation Be

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CGI and D-Wave Partner to Commercialize Enterprise Quantum Optimization Across Transportation, Logistics, and Retailquantum-computing

CGI and D-Wave Partner to Commercialize Enterprise Quantum Optimization Across Transportation, Logistics, and Retail

CGI and D-Wave Partner to Commercialize Enterprise Quantum Optimization Across Transportation, Logistics, and Retail Global IT consulting firm CGI Inc. (NYSE: GIB, TSX: GIB.A) and annealing quantum computing provider D-Wave Quantum Inc. (NASDAQ: QBTS) have entered into a strategic go-to-market partnership to scale the commercial deployment of quantum optimization solutions across enterprise organizations. Building on over a year of technical collaboration, CGI will integrate D-Wave’s dual-platform quantum hardware stack—including cloud access to the Advantage2™ annealing QPU and hybrid solver services—directly into its global IT services portfolio. The joint initiative pairs CGI’s global systems integration footprint (encompassing 94,000 consultants across enterprise logistics, transportation, and public sector domains) with D-Wave’s quantum annealing hardware. The partnership focuses on co-developing production-grade quantum optimization applications designed to augment classical computing infrastructure and resolve complex combinatorial challenges in supply chain, rail transportation, retail, and energy operations. [ CGI & D-Wave Joint Enterprise Solution Portfolio ]Industry DomainTarget Workloads & Use CasesQuantum Technology StackTransportation & Rail Operations• Dynamic train scheduling & dispatching• Rail network & yard traffic management• Rolling stock & crew resource allocation• D-Wave Advantage2™ QPU• Leap™ Quantum Cloud Service• Constrained Quadratic Model (CQM) SolversRetail & Supply Chain Logistics• Multi-echelon inventory & distribution planning• Last-mile delivery vehicle routing• Workforce shifts & scheduling optimization• Hybrid Quantum-Classical Solvers• CGI Enterprise Systems Integration• Real-time operational decision enginesIndustrial & Energy Grid Infrastructure• Production line throughput planning• Grid load balancing & maintenance scheduling• Asset lifecycle & predictive maintenance• D-Wave Quant

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