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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.

Enabling Hybrid HPCQC Workflows with a Heterogeneous Software Stackquantum-computing

Enabling Hybrid HPCQC Workflows with a Heterogeneous Software Stack

--> Quantum Physics arXiv:2608.14827 (quant-ph) [Submitted on 14 Aug 2026] Title:Enabling Hybrid HPCQC Workflows with a Heterogeneous Software Stack Authors:Muhammad Nufail Farooqi, Minh Chung, Burak Mete, Eric Mansfield, Bernd Hoffmann, Teemu Mattsson, Laura Schulz, Jorge Echavarria View a PDF of the paper titled Enabling Hybrid HPCQC Workflows with a Heterogeneous Software Stack, by Muhammad Nufail Farooqi and 7 other authors View PDF HTML (experimental) Abstract:In this work, we demonstrate hybrid High Performance Computing-Quantum Computing (HPCQC) workflows on a production petascale system. The demonstration combines three components: the SuperMUC-NG supercomputer at the Leibniz Supercomputing Centre (LRZ), a 20-qubit superconducting quantum processor provided by IQM Quantum Computers (IQM), and Munich Quantum Valley (MQV)'s Munich Quantum Software Stack (MQSS). Integrating quantum processors into High Performance Computing (HPC) systems requires a heterogeneous software stack capable of orchestrating classical and quantum resources within established supercomputing workflows. MQSS treats Quantum Processing Units (QPUs) as scheduler-managed accelerators and it performs resource coordination following a two-level scheduling scheme. Slurm performs system-level allocation by exposing QPUs as Generic RESources (GRES), while the MQSS Quantum Resource Manager & Compiler Infrastructure (QRM&CI) performs just-in-time compilation and subsequent dispatch of quantum circuits. To integrate with existing HPC operations without modifying the scheduler core, MQSS introduces an open-source SLURM Plugin Suite based on Prolog/Epilog scripts and SPANK modules. Experimental results show that hybrid HPCQC workflows can be executed without significant latency overhead compared to conventional workloads. The presented architecture provides a portable integration model for quantum accelerators on large-scale HPC systems and is directly applicable to next-generation Hewlett Pac

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Researchers Map Six-Stage STRIDE Threats Across Quantum-as-a-Service Pipelinequantum-computing

Researchers Map Six-Stage STRIDE Threats Across Quantum-as-a-Service Pipeline

Researchers from the University of Jyväskylä have released a six-stage STRIDE threat model that maps attack surfaces across the full Quantum-as-a-Service pipeline used by IBM Quantum, Amazon Braket, and IonQ. The matrix organizes published quantum attacks, classical inheritances, and under-studied gaps, while identifying three cross-stage chains that elevate overall risk. Full technical details and the threat matrix appear in the arXiv preprint accepted as a QCE26 poster. The post Researchers Map Six-Stage STRIDE Threats Across Quantum-as-a-Service Pipeline appeared first on The Qubit Report.

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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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The International Workshop on Quantum Computing, Privacy and Securityquantum-computing

The International Workshop on Quantum Computing, Privacy and Security

The International Workshop on Quantum Computing, Privacy and Security Acronym: IWQPS2026Dates: Tuesday, September 22, 2026 to Friday, September 25, 2026Web page: The International Workshop on Quantum Computing, Privacy and Security (IWQPS2026)Registration deadline: Tuesday, September 1, 2026Submission deadline: Tuesday, August 25, 2026Tags: quantum machine learningquantum computingcybersecurityQuantum computing is expected to significantly reshape the landscape of secure computing and software and network infrastructures. As quantum technologies continue to evolve, traditional security approaches and software design paradigms face new challenges, requiring the development of quantum-aware architectures and resilient software systems. This workshop aims to explore the intersection of quantum computing with privacy and security. It will provide a forum for researchers and practitioners to discuss how emerging quantum technologies, including quantum algorithms, quantum communication protocols, and quantum machine learning, can influence the design and deployment of software systems. Topics of interest include full and hybrid classical–quantum software architectures, quantum-aware security mechanisms and programming models for quantum-enabled platforms. The workshop will also examine how quantum technologies can be integrated into modern computing environments such as cloud infrastructures, distributed systems, and large-scale networked platforms. By bringing together experts from quantum computing, software engineering, artificial intelligence, data science and cybersecurity, the workshop aims to foster interdisciplinary collaboration and identify emerging research challenges and opportunities for building secure, scalable, and intelligent distributed software architectures in the quantum era. We invite submissions describing original research, position papers, or case studies related to the intersection of quantum computing privacy and se

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The Rise of Superconducting Erasure Qubits – an Industry Perspectivequantum-computing

The Rise of Superconducting Erasure Qubits – an Industry Perspective

TECHNICAL BLOG The Rise of Superconducting Erasure Qubits – an Industry Perspective Building a commercially useful quantum computer requires more than increasing qubit numbers. The real challenge is reducing errors to the point where quantum processors can reliably outperform classical systems on meaningful problems. Maria Violaris DEVELOPER ADVOCATE Maria has a hybrid role at OQC of quantum error correction research towards building a fault-tolerant quantum computer, and technical science communication. She has a PhD in theoretical quantum information from the University of Oxford, alongside which she interned with IBM Quantum making the “Quantum Paradoxes” YouTube series. She has spearheaded multiple new initiatives in the quantum community, including the “Quantum on the Clock” Schools Video Competition; Oxford Quantum Information Society; and quantum computing workshops. She has also written for Physics World magazine; published quantum education research; and hosts a Quantum Foundations Podcast on her YouTube channel, amongst other quantum content. Today’s superconducting qubits have made remarkable progress, but error rates remain too high for large-scale, fault-tolerant quantum computing. That’s why quantum error correction (QEC) is one of the defining engineering challenges for the industry. At OQC, we are taking a hardware-first approach to solving it. Our latest Perspective article, Developments in superconducting erasure-qubits for hardware-efficient quantum error correction, explores one of the most promising directions in the field: superconducting erasure qubits. It also explains how our newly developed OQC Dimon architecture fits within the rapidly evolving research landscape. Engineering qubits that reveal their own errors Traditional quantum error correction assumes errors occur silently, requiring significant overhead to detect and correct them. Erasure qubits however, change that assumption. An erasure error occurs when a qubit leaves its computati

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Tried implementing the NAND-tree algorithm in Qiskitquantum-computing

Tried implementing the NAND-tree algorithm in Qiskit

I've been working on a Qiskit implementation of the NAND-tree quantum algorithm and thought I'd share it here. Right now it works with small finite trees. I implemented the quantum walk, the input oracle, query counting, and a few different ways of simulating the Hamiltonian. I've mostly been testing it on 2, 4, and 8 leaves. It's not a scalable implementation yet. Some parts still use dense Hamiltonian matrices, and figuring out how to get past that is one of the things I'm looking into. Here's the repo: https://github.com/mncrftfrcnm/qiskit-nand-tree-implementation If anyone here has worked with NAND-tree algorithms or quantum walks, I'd really appreciate feedback, especially if you spot something wrong with how I've handled the oracle or query counting. submitted by /u/FollowingEvery4802 [link] [comments]

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Quantinuum to Partner with the Singapore Institute of Technology to Help Develop Singapore’s Future Quantum Workforce.quantum-computing

Quantinuum to Partner with the Singapore Institute of Technology to Help Develop Singapore’s Future Quantum Workforce.

Quantinuum to Partner with the Singapore Institute of Technology to Help Develop Singapore’s Future Quantum Workforce. Quantinuum has signed a Memorandum of Understanding (MoU) with the Singapore Institute of Technology (SIT) to train and expand Singapore’s quantum workforce. Building on Quantinuum’s existing R&D footprint and the planned deployment of its Helios quantum processor in Singapore, the collaboration aims to prepare an industry-ready workforce across engineering, systems development, and applied technologies. Key Initiatives of the Partnership Practical Curriculum: Joint development of hands-on training modules tailored for both undergraduate students and working professionals. Tool Access: Direct access to Quantinuum’s suite of quantum software, development tools, and simulators for educational use. Community Engagement: Hosting regular workshops, seminars, and campus events to build local interest and technical literacy in quantum computing. This strategic alignment addresses the growing commercial demand for skilled talent, ensuring local developers and engineers gain direct exposure to state-of-the-art quantum hardware and software environments. Additional information can be found in a LinkedIn post here. August 15, 2026 dougfinke2026-08-15T20:43:39-07:00 Leave A Comment Cancel replyComment Type in the text displayed above Δ This site uses Akismet to reduce spam. Learn how your comment data is processed.

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Global Consortium Launches Quantum Optimization Benchmarking Library (QOBLIB) to Track Path to Quantum Advantagequantum-computing

Global Consortium Launches Quantum Optimization Benchmarking Library (QOBLIB) to Track Path to Quantum Advantage

An international research consortium led by IBM Quantum, Zuse Institute Berlin (ZIB), Technische Universität Berlin, and Purdue University—alongside global academic and industrial partners—has introduced the Quantum Optimization Benchmarking Library (QOBLIB). Published in Nature Computational Science (“The Quantum Optimization Benchmarking Library“), the open-source initiative establishes a standardized, model-independent benchmarking framework to evaluate quantum, classical, and hybrid algorithms across ten NP-hard combinatorial optimization problem classes. [ QOBLIB Model-Independent Benchmarking Stack ] │ ┌────────────────────────────────────────┼────────────────────────────────────────┐ ▼ ▼ ▼ The "Intractable Decathlon" Open-Source Repository & Web Portal Cross-Paradigm Evaluation • 10 Hard Combinatorial Classes. • 1,260+ Curated Problem Instances. • Head-to-Head Solver Tracking. • 20 to 3,000,000+ Variables. • 2,600+ Benchmark Submissions. • Classical MIP/QUBO Baselines. • MIP, ILP, MIQP, & QUBO Formulations. • Live Best-Known Solution Tracking. • Near-Term Quantum Hardware Runs. Structuring the “Intractable Decathlon” QOBLIB addresses a critical gap in quantum optimization: while heuristic algorithms like the Quantum Approximate Optimization Algorithm (QAOA) or quantum annealing lack theoretical performance guarantees, empirical advantage claims require rigorous comparisons against state-of-the-art classical solvers. The library curates 1,264 specific instances spanning ten problem classes that become computationally hard for classical solvers at scales ranging from tens to tens of thousands of decision variables: Market Split (Multidimensional Subset Sum): Hard binary integer linear programming (ILP) instances with dense constraint matrices (20–140 variables). Low-Autocorrelation Binary Sequences (LABS): A canonical spin-glass benchmark with applications in radar and signal processing (2–100 variables). Minimum Birkhoff Decomposition: Doubly stochasti

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Hirata & Tsukada Build Language for Quantum-Controlled Channelsquantum-computing

Hirata & Tsukada Build Language for Quantum-Controlled Channels

A new theoretical study proposes a quantum programming language capable of expressing one of quantum information science’s most powerful control mechanisms: the quantum SWITCH. Kengo Hirata of Kyoto University and Takeshi Tsukada of Chiba University have developed a programming framework that overcomes a fundamental obstacle in controlling quantum programs with qubits. By introducing a novel linear type system, the researchers show that quantum programs involving general quantum channels can be described in a mathematically consistent way while naturally supporting the quantum SWITCH. Quantum computers derive their power from the ability of quantum data to exist in superposition, allowing a qubit to represent multiple states simultaneously. This naturally raises a deeper question: if quantum data can exist in superposition, can entire quantum programs also be placed into superposition? The quantum SWITCH, which allows the order of two quantum operations to depend on a quantum control state, has emerged as one of the best-known examples of quantum-controlled computation and has attracted considerable attention in quantum information theory. A common method for controlling quantum programs is through controlled operations. In this approach, a control qubit determines whether an operation F is applied when the qubit is in the state |1⟩ or whether the identity operation is performed when the qubit is in the state |0⟩. While this construction works well for unitary operations, Hirata and Tsukada show that it is not well-defined for general quantum channels, which include measurements, noise, and other non-unitary processes that occur in realistic quantum systems. The researchers identify the source of this limitation as the way quantum conditional branching handles measurements. Specifically, the measurements performed in the then and else branches of a conditional statement may not correspond to one another, preventing the overall program from representing a valid quant

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BTQ Technologies moves four quantum business lines toward commercial usequantum-computing

BTQ Technologies moves four quantum business lines toward commercial use

BTQ Technologies completed the acquisition of QPerfect during the second quarter of 2026, signaling a shift toward commercializing its quantum technologies platform. The company reports progress across four core business lines, including advancements in quantum software and a step toward quantum-resistant cryptocurrency infrastructure. BTQ believes the transition to quantum computing requires more than increased capability; it also demands secure systems to connect classical and quantum infrastructure, and is increasingly focused on translating technical capabilities into recurring revenue opportunities. QPerfect Acquisition Expands BTQ’s Quantum Software Capabilities The purchase adds critical software and technologies for quantum emulation, digital twins, validation, and logical quantum computing to BTQ’s existing capabilities, positioning the company to support clients designing and deploying applications on future quantum hardware. This expansion signals a shift from technological validation toward commercial execution for BTQ. The acquisition directly supports BTQ’s Quantum Accelerated Networks layer, a critical component of its overarching strategy. This strategy aims to establish trust at the silicon level, extend it across digital and blockchain networks, and integrate that trust into quantum-accelerated infrastructure. “Q2 represented an important transition for BTQ as we continued moving from technology validation toward commercial execution,” said Olivier Roussy Newton, Chief Executive Officer of BTQ Technologies. “We completed the acquisition of QPerfect, expanded customer and institutional engagements across multiple markets, advanced QSSN toward production deployment, and brought Bitcoin Quantum infrastructure to mainnet readiness.” Beyond MIMIQ, QPerfect is also developing a Digital Twin product and a Quantum Logic Unit. The company’s broader platform remains aligned with emerging cryptographic standards and regulatory initiatives globally, and its Qu

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Florida State University Launches Florida’s First Graduate Certificate in Quantum Information Science & Technologyquantum-computing

Florida State University Launches Florida’s First Graduate Certificate in Quantum Information Science & Technology

Florida State University Launches Florida’s First Graduate Certificate in Quantum Information Science & Technology Florida State University (FSU) has announced the launch of Florida’s first formal graduate credential in quantum information science and engineering: the Graduate Certificate in Quantum Information Science & Technology (QIST). Administered by the FSU Quantum Initiative, the 14-credit-hour interdisciplinary program is accepting applications through October 1, 2026, for its inaugural Spring 2027 enrollment cohort. The program bridges departments across the FSU College of Arts and Sciences and the FAMU-FSU College of Engineering—including Physics, Chemistry & Biochemistry, Computer Science, Mathematics, Materials Science & Engineering, Electrical & Computer Engineering, and Mechanical & Aerospace Engineering—to train graduate students and industry professionals across quantum materials, low-temperature device packaging, and quantum algorithm design. [ FSU QIST Graduate Certificate Ecosystem ] │ ┌─────────────────────────────────┼─────────────────────────────────┐ ▼ ▼ ▼ Core Academic Curriculum Specialized Research Facilities Industry & Center Networks • Mandatory Quantum Computing. • National MagLab (High Fields). • Commercial Partnerships (IonQ). • 3 Advanced Technical Electives. • Interdisciplinary Research Bldg. • Hardware Integration (Qblox, Keysight). • QSE Research Seminars. • Cleanroom & Cryogenic Dilution. • Quantum Software Labs (Amazon). Program structure and institutional research assets include: Curriculum Requirements: A 14-credit-hour framework comprising a mandatory core course in Quantum Information and Computing (3 credits), three specialized STEM electives (9 credits), and two semesters of the Quantum Science & Engineering Seminar (2 credits). Research Infrastructure Access: Enrolled students gain direct access to the National High Magnetic Field Laboratory (MagLab) and the newly constructed Interdiscip

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Quantinuum, NVIDIA, and Pfizer Validate Generative Quantum AI (GenQAI) Framework for Pharmaceutical R&Dquantum-computing

Quantinuum, NVIDIA, and Pfizer Validate Generative Quantum AI (GenQAI) Framework for Pharmaceutical R&D

Quantinuum, NVIDIA, and Pfizer Validate Generative Quantum AI (GenQAI) Framework for Pharmaceutical R&D Researchers from Quantinuum, NVIDIA, and Pfizer Inc. have validated a Generative Quantum AI (GenQAI) framework designed to automate and accelerate quantum circuit synthesis for pharmaceutical research and electronic structure modeling. In their paper, “Learning to Prepare Molecular Ground States with Transformer Models“, the hybrid architecture combines classical High-Performance Computing (HPC), generative transformer models, and quantum processing units (QPUs) to compute ground-state preparation circuits for complex active pharmaceutical ingredients (APIs). The multi-institutional team introduced ADAPT-GQE, a generative AI model trained on quantum chemistry datasets generated via GPU-accelerated classical supercomputing. The model predicts complete ground-state quantum circuits for imipramine—a tricyclic antidepressant used as an industry benchmark for forced degradation and shelf-life stability studies—executing the resulting circuits on Quantinuum’s 98-qubit Helios-1 trapped-ion hardware. [ GenQAI / ADAPT-GQE Quantum Circuit Synthesis Pipeline ] │ ┌────────────────────────────────────────┼────────────────────────────────────────┐ ▼ ▼ ▼ HPC Data Generation (NVIDIA CUDA-Q) Generative AI Circuit Synthesis QPU Execution & Validation • GPU-Accelerated ADAPT-VQE Circuits. • Fine-Tuned NVIDIA Nemotron Models. • Quantinuum Helios-1 Processor. • OpenMM & MACE-OFF MD Conformers. • Gemma 3 / Nemotron-Nano Transformer. • InQuanto Chemistry Platform. • 12 to 16 Active-Space Qubit Maps. • 3-4 Orders of Magnitude Speedup. • Validated Imipramine Ground State. The experiment resolves a fundamental computational bottleneck in near-term variational quantum algorithms (VQEs): Bypassing Iterative Gradient Calculations: Standard adaptive algorithms like ADAPT-VQE require evaluating thousands of operator gradients and re-optimizing parameter landscapes at every step, ren

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SPLIT-Q: A Scalable Sequential Quantum Computing Framework for Coherent Controlled Islandingquantum-computing

SPLIT-Q: A Scalable Sequential Quantum Computing Framework for Coherent Controlled Islanding

--> Quantum Physics arXiv:2608.12711 (quant-ph) [Submitted on 13 Aug 2026] Title:SPLIT-Q: A Scalable Sequential Quantum Computing Framework for Coherent Controlled Islanding Authors:Yuqi Jiang, Zhiding Liang, Qiang Guan, Yan Li, Ganesh Kumar Venayagamoorthy View a PDF of the paper titled SPLIT-Q: A Scalable Sequential Quantum Computing Framework for Coherent Controlled Islanding, by Yuqi Jiang and 4 other authors View PDF HTML (experimental) Abstract:Growing integration of distributed energy resources increases power-system variability and uncertainty. During disturbances, these effects can intensify generation-load imbalances and cascading failures. Controlled islanding limits their propagation by partitioning a compromised grid into connected, electrically sustainable islands. However, classical methods face rapidly growing computational costs as network size and island count increase. Quantum optimization offers an alternative for exploring this combinatorial partition space. Yet monolithic quantum formulations encode all assignment decisions in one circuit, causing qubit demand and circuit complexity to scale with network size. In this study, a qubit-bounded sequential distributed quantum approximate optimization algorithm (QAOA) framework is proposed to tackle coherent controlled islanding under limited quantum resources. It formulates the optimization as boundary-conditioned regional quadratic unconstrained binary optimization (QUBO) subproblems that are solved sequentially within a fixed qubit budget. Thus, circuit width remains independent of network size, with aggregate quantum workload scaling linearly on bounded-degree networks. Evaluation covers eleven IEEE systems from 9 to 300 buses using IBM quantum computing resources, with Gurobi and monolithic QAOA as references. Across all systems, the framework recovers feasible Gurobi-optimal partitions under noise, confirming the resilience of its solution quality. The results further show that the proposed met

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WarpSpeed Says its AI cuts quantum encryption cracking cost sharplyquantum-computing

WarpSpeed Says its AI cuts quantum encryption cracking cost sharply

WarpSpeed’s artificial intelligence has designed a quantum circuit that cracks a standard cryptographic challenge with significantly improved efficiency, the company says. The system achieved a 2.5 times more efficient circuit than Google’s in cracking the ECDSA challenge, a benchmark used to assess the security of digital signatures underpinning cryptocurrencies like Bitcoin and Ethereum, according to WarpSpeed. This improvement exceeds the median improvement on the benchmark over the last month by about two and a half orders of magnitude; according to WarpSpeed, its circuit consists of only 993,181 Toffoli gates and 1,205 qubits, certified by a zero-knowledge proof. Beyond circuit design, the company’s agents also found gaps combining cryptography, performance engineering, and software security within the benchmark’s verification processes, the firm reports. WarpSpeed AI Achieves 2.5x Efficiency in ECDSA Cracking WarpSpeed’s artificial intelligence delivered a quantum circuit that reduces the computational cost of cracking the Elliptic Curve Digital Signature Algorithm (ECDSA) by a substantial margin, achieving a 2.5 times more efficient circuit than Google Quantum AI’s previously published designs, WarpSpeed claims. This leap in performance was demonstrated on the publicly available ecdsa.fail benchmark, which Eigen Labs created from the Google paper. The system achieved these results through self-improvement, by the company’s account. The core of the challenge revolves around efficiently calculating point addition on elliptic curves, a fundamental operation within the ECDSA cryptographic scheme. Shor’s algorithm, the quantum method used to break this encryption, relies heavily on the cost of this single operation; therefore, optimizing point addition directly impacts the overall attack complexity. WarpSpeed’s circuit achieves a spacetime score of 1.20 × 10⁹, utilizing 993,181 Toffoli gates and 1,205 qubits, a figure certified by a zero-knowledge proof released a

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Xanadu and Alberta U. seek better cancer drugs with quantum chipsquantum-computing

Xanadu and Alberta U. seek better cancer drugs with quantum chips

Xanadu (NASDAQ/TSX: XNDU) is investing in pharmaceutical research through a new partnership with the University of Alberta to accelerate the design of compounds for photodynamic therapy, a cancer treatment that avoids chemotherapy side effects. The collaboration unites Xanadu’s quantum computing framework with the published work of Professor Alex Brown on benchmarking photosensitizer simulations. “Current methodologies for developing effective photosensitizers are hampered by several hurdles,” said Dr. Christian Weedbrook, Founder and Chief Executive Officer of Xanadu, adding that leveraging quantum computers could make the technology a competitive method for drug discovery. This partnership aims to strengthen Xanadu’s workflow for drug design and address increasingly sophisticated challenges in photosensitizer development. Xanadu and Alberta U. Target Photosensitizer Challenges with Quantum Computing The collaboration focuses on accelerating the development of photosensitizers, light-activated compounds designed to selectively destroy tumor cells. Professor Brown’s research has identified limitations in current computational methods used to predict the effectiveness of these photosensitizers; standard techniques struggle to accurately model crucial interactions that determine their performance. Xanadu recently demonstrated the potential of quantum computers to simulate light-matter interactions within photosensitizers, revealing properties difficult to ascertain using classical approaches, including sensitivity to specific wavelengths and efficiency in triggering cell death. This builds on Xanadu’s existing open-source quantum computing platform, PennyLane, and represents an expansion of their quantum-based workflow for drug design. The partnership intends to address these hurdles by leveraging early fault-tolerant quantum computers to model complex light-matter interactions, potentially accelerating photodynamic drug discovery. Professor Brown emphasized the chall

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University of Guelph and Xanadu Sign MOU to Advance Quantum Education and Talent Developmentquantum-computing

University of Guelph and Xanadu Sign MOU to Advance Quantum Education and Talent Development

University of Guelph and Xanadu Sign MOU to Advance Quantum Education and Talent Development The University of Guelph (U of G) and photonic quantum computing developer Xanadu Quantum Technologies (NASDAQ/TSX: XNDU) have signed a Memorandum of Understanding (MOU) to collaborate on quantum computing education, curriculum integration, and workforce development. Extending through 2028, the partnership aligns U of G’s College of Computational, Mathematical, and Physical Sciences (CCMPS) with Xanadu’s technical stack to train the next generation of quantum software developers and researchers. The agreement addresses a key objective of Canada’s National Quantum Strategy: bridging the gap between academic physics/computer science programs and commercial quantum engineering requirements. As part of the collaboration, U of G will integrate practical quantum programming frameworks—centered on Xanadu’s open-source PennyLane software—into undergraduate and graduate coursework. [ U of G & Xanadu Workforce Pipeline Framework ] │ ┌───────────────────────────────────┼───────────────────────────────────┐ ▼ ▼ ▼ Academic Curriculum Integration PennyLane Software Training Industry Skill Readiness • Quantum Information Science. • Open-Source Quantum Framework. • Direct Workforce Pipeline. • Practical Algorithmic Labs. • Photonic Circuit Simulation. • Hands-On Quantum Hardware. • Interdisciplinary Research. • Hybrid Classical-QPU Models. • Industry-Academic Co-Design. Key objectives of the MOU include: Curriculum Co-Development: Creating hands-on educational modules that introduce students to practical quantum algorithms and photonic quantum computing paradigms. PennyLane Integration: Utilizing Xanadu’s open-source software stack as a primary instructional tool for quantum circuit design, optimization, and quantum machine learning. Workforce Development: Establishing collaborative research pathways and practical training opportunities to supply Canada’s expanding commercial quantum ec

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Xanadu and University of Alberta Partner to Accelerate Photodynamic Cancer Drug Discoveryquantum-computing

Xanadu and University of Alberta Partner to Accelerate Photodynamic Cancer Drug Discovery

Xanadu and University of Alberta Partner to Accelerate Photodynamic Cancer Drug Discovery Photonic quantum computing developer Xanadu Quantum Technologies Limited (NASDAQ/TSX: XNDU) has announced a strategic research partnership with the University of Alberta to engineer novel quantum algorithms for oncology and pharmaceutical drug design. Led by Xanadu’s algorithms team and Professor Alex Brown, Chair of the Department of Chemistry at the University of Alberta, the project focuses on modeling complex light-matter interactions in photosensitizers—light-activated chemical compounds utilized in targeted photodynamic cancer therapy (PDT). Photodynamic therapy uses light-activated compounds to selectively destroy localized tumor cells while minimizing systemic damage associated with traditional chemotherapy. However, designing photosensitizer molecules classically presents a severe computational bottleneck: predicting excited-state dynamics, wavelength sensitivity, and singlet oxygen generation efficiency requires modeling non-adiabatic light-matter coupling that traditional density functional theory (DFT) and classical quantum chemistry approximations struggle to resolve. [ Xanadu & UAlberta Photodynamic Quantum Workflow ] │ ┌────────────────────────────────────┼────────────────────────────────────┐ ▼ ▼ ▼ Photosensitizer Target Systems Photonic Quantum Simulation Stack Early Fault-Tolerant Application • Excited-State Photodynamics. • PennyLane Quantum Software Stack. • Quantum Photodynamic Algorithms. • Wavelength Sensitivity Mapping. • Light-Matter Coupling Solvers. • Accelerates PDT Oncology Pipeline. • Singlet Oxygen Efficiency. • Photonic Fault-Tolerant Roadmaps. • Bypasses Classical Simulation Limits. The collaboration pairs Xanadu’s fault-tolerant algorithm pipeline and PennyLane open-source software stack with Professor Brown’s benchmarking expertise in computational photodynamics: Light-Matter Simulation: Developing fault-tolerant quantum algorithms capable

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SDT Joins Canadian Non-Profit Open Quantum Design as Official Manufacturing Partnerquantum-computing

SDT Joins Canadian Non-Profit Open Quantum Design as Official Manufacturing Partner

SDT Joins Canadian Non-Profit Open Quantum Design as Official Manufacturing Partner South Korean quantum equipment developer and systems integrator SDT has joined Canadian non-profit organization Open Quantum Design (OQD) as a primary hardware manufacturing partner. Announced at Quantum Korea 2026, the strategic agreement tasks SDT with translating OQD’s open-source hardware blueprints into physical trapped-ion quantum processing units (QPUs) and integrating their supporting control infrastructure. OQD develops full-stack, open-source trapped-ion quantum computers—publishing complete schematics for ultra-high vacuum (UHV) chambers, microfabricated surface ion-trap electrodes, laser control optics, and open software stacks. As the designated manufacturing partner, SDT will fabricate and assemble complete QPU hardware modules, build control electronics, and co-develop user-interface software to make open-source quantum computers commercially reproducible for global universities, research laboratories, and defense agencies. [ OQD & SDT Open-Source Trapped-Ion Ecosystem ] │ ┌──────────────────────────────────┴──────────────────────────────────┐ ▼ ▼ OQD Open-Source Hardware & Software Blueprints SDT System Integration & Manufacturing • Public UHV Chamber & Electrode Designs. • Precision Fabrication of Vacuum & Ion Traps. • Open Control Electronics Schematics. • Free-Space Optical Assembly & Laser Systems. • Open-Source Software Stack & Drivers. • QuREKA QCaaS Cloud & Interface Integration. Additionally, SDT has joined the preferred-supplier network for LightFlow, a cloud-based design and manufacturing platform for free-space optical systems, securing its role in producing optical subsystems and ion-trap assemblies for OQD systems. Concurrently, SDT is deploying its QuREKA Quantum Computing as a Service (QCaaS) platform to support hybrid CPU-GPU-QPU research across South Korea’s bio-pharmaceutical sector. Operating out of its Quantum-AI Hyb

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ORIENTOM and Fondazione LINKS Form Research Partnership for Financial Quantum Computingquantum-computing

ORIENTOM and Fondazione LINKS Form Research Partnership for Financial Quantum Computing

ORIENTOM and Fondazione LINKS Form Research Partnership for Financial Quantum Computing Seoul-based quantum software developer ORIENTOM and Italian research institution Fondazione LINKS (Links Foundation) have signed a Memorandum of Understanding (MoU) to advance quantum computing, quantum-inspired algorithms, and High-Performance Computing (HPC) integration across the finance, banking, and insurance sectors. The strategic collaboration will verify technical feasibility and develop Proof of Concept (PoC) frameworks and operational prototypes tailored for commercial financial institutions. The joint initiative combines ORIENTOM’s hardware-agnostic Quantum Middleware platform with Fondazione LINKS’ HPC infrastructure and quantum research environment (supported by local research partners including Politecnico di Torino and the Italian National Institute for Metrology – INRiM). [ ORIENTOM & Fondazione LINKS Research Framework ] │ ┌───────────────────────────────────┼───────────────────────────────────┐ ▼ ▼ ▼ Derivatives & Options Pricing Portfolio & Risk Management Banking & Insurance QML • Quantum Amplitude Estimation. • Constrained Combinatorial Opt. • Fraud & Anomaly Detection. • Quantum Monte Carlo Speedup. • Optimal Liquidation & Execution. • Quantum Machine Learning (QML). • High-Dimensional Valuation. • Tail Risk & Stress Analysis. • Personalisation & Recommendation. The collaboration focuses on three primary domain use cases: Derivatives and Options Pricing: Accelerating high-dimensional stochastic pricing models by coupling classical Monte Carlo methods with Quantum Amplitude Estimation (QAE). Portfolio Optimization and Risk Management: Applying quantum and quantum-inspired algorithms to complex, constrained combinatorial optimization problems—including portfolio liquidation, order execution, and real-time risk analysis. Banking and Insurance Machine Learning: Exploring Quantum Machine Learning (QML) and Quantum-Inspired Machine

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Yonsei University to Upgrade On-Premises IBM Quantum System One to Next-Generation Nighthawk QPUquantum-computing

Yonsei University to Upgrade On-Premises IBM Quantum System One to Next-Generation Nighthawk QPU

Yonsei University to Upgrade On-Premises IBM Quantum System One to Next-Generation Nighthawk QPU The Yonsei Quantum Initiative at Yonsei University (Songdo Campus, Incheon, South Korea) has announced an operational hardware upgrade for its on-premises IBM Quantum System One facility. Scheduled for November 2026, the university will replace its current 127-qubit IBM Eagle quantum processing unit (QPU) with IBM’s 120-qubit Nighthawk QPU, making Yonsei the second facility globally—after IBM Miami—to host a Nighthawk-based quantum computer. The upgrade marks a transition in physical topology and interconnect design: Square Lattice Topology: Moving from Eagle’s heavy-hex layout (where qubits average ~2.5 neighboring connections) to Nighthawk’s square lattice structure gives each qubit 4 direct connections via 218 tunable couplers. 40% Computational Capacity Gain: By quadrupling adjacent connectivity, Nighthawk eliminates a substantial number of intermediate SWAP gates during circuit execution, reducing gate depth overhead and enabling ~40% more computational throughput at equivalent fidelity levels. Hybrid Quantum-HPC Workloads: Yonsei is actively deploying its QPU in a hybrid workflow with RIKEN’s Fugaku supercomputer (Japan) to study target mechanisms for Leigh syndrome, a severe genetic neurological disorder. The hybrid division of labor—using the QPU to filter key chemical candidate spaces before offloading heavy classical processing—is projected to compress long-term simulation timelines from decades to days. [ Yonsei IBM System One Upgrade Architecture ] │ ┌─────────────────────────────────────┴─────────────────────────────────────┐ ▼ ▼ Previous On-Premises QPU (IBM Eagle) Upgraded On-Premises QPU (IBM Nighthawk) • 127 Superconducting Qubits (Heavy-Hex Layout). • 120 Superconducting Qubits (Square Lattice). • ~2.5 Average Neighbor Connections / Qubit. • 4 Direct Neighbor Connections / Qubit (218 Couplers). • Higher SWAP-Gate Overhead in Complex Circuits. • ~40% Com

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