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.
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.
quantum-computingQuantum Computing Companies In 2026
Quantum Computing Companies in 2026 The most comprehensive publicly available directory of quantum computing companies across hardware, software, security, sensing, components and services spanning dozens of countries. The quantum computing industry has crossed the billion-dollar revenue mark. Stock valuations for pure-play quantum companies have reached tens of billions. Governments on six continents have committed more than $40 billion in national quantum strategies. Google’s Willow chip demonstrated a 13,000x speedup over the world’s fastest supercomputer. Quantinuum secured a billion-dollar joint venture with Qatar. IonQ executed $2.5 billion in acquisitions across eighteen months. The Quantum Navigator tracks hundreds of organisations spanning dozens of countries. This article profiles the most significant players across every segment of the quantum technology stack. Every company links to its full profile on the Quantum Navigator. If your company is missing, get in touch and we will add you. Expand AllCollapse All ⚛️ Superconducting QubitsIBM, Google, Rigetti, IQM, OQC and superconducting circuit companies IBM QuantumNYSE: IBM🇺🇸 USLed by Jay Gambetta (VP, IBM Quantum), IBM has invested more in superconducting quantum computing than any other organisation. IBM operates the largest fleet of cloud-accessible quantum systems through IBM Quantum Network (300+ organisations). The 156-qubit Heron processor achieved 16x better performance over 2022 systems. In November 2025, the 120-qubit Nighthawk featured 218 next-generation tunable couplers enabling 30% more circuit complexity. IBM achieved a 10x speedup in QEC decoding, one year ahead of schedule. The IBM-Cisco partnership targets networked distributed quantum infrastructure by 2030. The roadmap extends to Kookaburra (2026, logical qubits + quantum memory) and Starling (2028, 200 logical qubits from ~10,000 physical qubits using LDPC codes that IBM claims require 90% fewer qubits than Google’s surface code). Qis
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quantum-computingAWS Quantum Technologies Releases Qiskit-Braket Provider v0.11, Now Compatible with Qiskit 2.0
AWS Quantum Technologies has released version 0.11 of the Qiskit-Braket provider on February 20, 2026, significantly enhancing how users access and utilize Amazon Braket’s quantum computing services through the popular Qiskit framework. This update introduces new “BraketEstimator” and “BraketSampler” primitives, mirroring Qiskit routines for improved performance and feature integration with Amazon Braket program sets. Importantly, the provider now fully supports Qiskit 2.0 while maintaining compatibility with versions as far back as v0.34.2, allowing users to “use a richer set of tools for executing quantum programs on Amazon Braket.” The release unlocks flexible compilation features, enabling circuits to be compiled directly for Braket devices using the to_braket function, accepting inputs from Qiskit, Braket, and OpenQASM3. Qiskit 2.0 Support and Backwards Compatibility A significant upgrade to the Qiskit-Braket provider now unlocks the power of Qiskit 2.0 for Amazon Braket users, while simultaneously maintaining compatibility with older versions—reaching back to v0.34.2. This dual approach ensures a smooth transition for existing workflows and allows researchers to immediately leverage the performance increases achieved through the refactoring of Qiskit 2.0. The latest release isn’t simply about compatibility; it’s about expanding the toolkit available for quantum program execution. The Qiskit-Braket provider facilitates flexible compilation features for Braket, utilizing standard Qiskit transpilation functionality through the to_braket function. This function is notably versatile, accepting inputs not only from Qiskit but also from Braket and OpenQASM3, and even supporting Qiskit Targets and common transpilation inputs. “You can now compile or transpile to Braket Circuit objects through the to_braket function, which can then be directly submitted to Braket devices,” explains the development team. Previously, these backends relied on simpler wrappers; now, these
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Quantum Advantage Tracker: the race to advantage - IBM
Quantum Advantage Tracker: the race to advantage IBM
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quantum-computingTII Opens Cloud Access to Its Superconducting QPUs
Insider Brief Technology Innovation Institute (TII) has launched a cloud service providing partners with access to its in-house superconducting quantum processing units (QPUs). The QPUs, developed by TII’s Quantum Computing Hardware Lab, range from 5 to 25 qubits and include locally fabricated chips with coherence times up to ten times longer than the lab’s first-generation prototypes. The platform integrates TII’s open-source Qibo framework to enable cloud-based execution of quantum and hybrid quantum-classical workloads. PRESS RELEASE — The Technology Innovation Institute (TII), the applied research pillar of Abu Dhabi’s Advanced Technology Research Council (ATRC), today announced the launch of a cloud service providing access to Quantum Processing Units (QPUs) developed by TII’s Quantum Computing Hardware Lab. Initially available to TII partners, the service enables users to run quantum workloads directly on TII’s physical quantum hardware in the cloud. Established four years ago, the Quantum Research Center’s Quantum Computing Hardware Lab has advanced from foundational capability-building to delivering cloud-accessible quantum systems based on superconducting devices. The lab currently operates multiple QPU systems ranging from 5 to 25 qubits, including in-house fabricated chips that demonstrate quantum coherence times up to ten times longer than TII’s first-generation prototypes. These advances reflect growing in-house expertise across quantum design, fabrication, and system-level integration. The launch is the result of a coordinated effort between the Quantum Computing Hardware Lab and TII’s Quantum Middleware team, with Qibo serving as the software layer for job submission and execution workflows. Qibo is TII’s open-source quantum software framework that enables users to build quantum circuits and hybrid quantum-classical workflows, and to execute them seamlessly across simulators and QPU backends through a unified interface. The platform is ava
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quantum-computingDigital Quantum Simulation of the Holstein-Primakoff Transformation on Noisy Qubits
--> Quantum Physics arXiv:2602.17806 (quant-ph) [Submitted on 19 Feb 2026] Title:Digital Quantum Simulation of the Holstein-Primakoff Transformation on Noisy Qubits Authors:Kelvin Yip, Alessandro Monteros, Sahel Ashhab, Lin Tian View a PDF of the paper titled Digital Quantum Simulation of the Holstein-Primakoff Transformation on Noisy Qubits, by Kelvin Yip and 3 other authors View PDF Abstract:Quantum simulation of many-body systems offers a powerful approach to exploring collective quantum dynamics beyond classical computational reach. Although spin and fermionic models have been extensively simulated on digital quantum computers, the simulation of bosonic systems on programmable quantum processors is often hindered by the intrinsically large Hilbert space of bosonic modes. In this work, we study the digital quantum simulation of bosonic modes using the Holstein-Primakoff (HP) transformation and implement this protocol on a cloud-based superconducting quantum processor. Two representative models are realized on quantum hardware: (i) the driven harmonic oscillator and (ii) the Jaynes-Cummings model. Using data obtained from the quantum simulations, we systematically examine the interplay between algorithmic and hardware-induced errors to identify optimal simulation parameters. The dominant algorithmic errors arise from the finite number of qubits used in the HP mapping and the finite number of Trotter steps in the time evolution, while hardware errors mainly originate from gate infidelity, decoherence, and readout errors. This study advances the digital quantum simulation of many-body systems involving bosonic degrees of freedom on currently available cloud quantum processors and provides a framework that can be extended to more complex spin-boson and multimode cavity models. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2602.17806 [quant-ph] (or arXiv:2602.17806v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2602.17806 F
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quantum-computingI achieved 97.8% average error recovery on IBM Quantum Torino hardware using classical post-processing. No calibration, no ancilla qubits, no hardware mods. Paper and data inside.
I'm an independent researcher and I've developed a new approach to quantum error mitigation. The core idea: quantum decoherence acts as a diffusion process on measurement probability distributions, and you can reverse it using Richardson-Lucy deconvolution with self-calibrating asymmetric noise estimation. Results on IBM Quantum Torino (real hardware, 20,000 shots per circuit): GHZ 4 qubits: 100% recovery GHZ 8 qubits: 99.7% recovery GHZ 12 qubits: 99.8% recovery W-state 3 qubits: 99.8% recovery Bernstein-Vazirani 5 qubits: 87.6% recovery 3 Bell pairs 6 qubits: 99.6% recovery Average: 97.8% fidelity recovery across all circuits. The method self-calibrates from measurement data alone. Zero calibration circuits. Zero ancilla qubits. Runs in under 1 second on a laptop. Full paper with theory, math, and all experimental results: https://zenodo.org/records/18724718 Patent pending. Happy to answer questions and discuss. Also looking for an arXiv quant-ph endorsement if anyone is willing. Open to feedback and criticism. I want to learn as much as I can from this community. submitted by /u/nicazecenzo [link] [comments]
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quantum-computingQuandela Unveils MerLin, Reproducing 18 State-of-the-Art Photonic QML Models
Quandela Quantique Inc. has unveiled MerLin, a new open-source framework designed as a discovery engine for photonic and hybrid quantum machine learning. Available as of February 11, 2026, MerLin integrates optimized quantum simulation into standard machine learning workflows, enabling the training of quantum layers and systematic benchmarking. As an initial demonstration, the framework successfully reproduces eighteen state-of-the-art photonic and hybrid QML models, spanning diverse architectures like kernel methods and convolutional networks. By embedding photonic quantum models within established machine learning ecosystems, MerLin allows practitioners to leverage existing tooling for comparisons and hybrid workflows, “establishing a shared experimental baseline consistent with empirical benchmarking methodologies widely adopted in modern artificial intelligence.” This positions MerLin as a tool for linking algorithms, benchmarks, and future quantum hardware. Photonic Quantum Computing Advantages for Machine Learning Photonic quantum computing is proving particularly promising due to its scalability, robustness, compatibility with optical communication technologies, and energy efficiency. This convergence of quantum computing and machine learning is accelerating advances in both fields, with quantum machine learning (QML) offering the potential to extend the capabilities of classical algorithms. Unlike many approaches, photonic QML “exploits the bosonic nature of light and high-dimensional multi-mode interference to implement and train machine learning models directly on this unconventional photonic quantum computation model, enabling intrinsic parallelism and efficient exploration of large Hilbert spaces.” Realizing this potential necessitates software frameworks that bridge abstract QML models with execution on emerging quantum hardware. The need for such tools is highlighted by the current fragmented software landscape, where frameworks like Qiskit, Cirq, Puls
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quantum-computingScaleway & AQT Launch European Quantum Computing Partnership, February 2026
Alpine Quantum Technologies (AQT) and Scaleway announced today, February 20, 2026, a partnership to deliver European quantum computing through cloud access. AQT is integrating its trapped-ion quantum computer, IBEX Q1, directly into Scaleway’s cloud platform, creating a new sovereign quantum infrastructure designed to bolster digital resilience and technological independence. The collaboration will provide access to quantum processing units via Scaleway’s Quantum as a Service (QaaS) platform, available Tuesdays and Wednesdays from 10:00 to 17:00 CET. “Together with Scaleway, AQT offers our customers hands-on access to the best quantum computers in Europe,” said Felix Rohde, Director of Cloud Partnerships and Business Development at AQT. This move significantly expands Europe’s capacity for secure, independent quantum computing and opens new avenues for innovation in fields ranging from logistics to financial modeling. AQT IBEX Q1 Integrates with Scaleway’s European Quantum as a Service The arrival of the IBEX Q1 trapped-ion quantum computer within Scaleway’s cloud infrastructure marks a significant step toward a fully sovereign quantum ecosystem in Europe, offering unprecedented access to advanced quantum processing capabilities. Crucially, the IBEX Q1 can be accessed and programmed using familiar quantum software packages like Qiskit, Cirq, and Pennylane, lowering the barrier to entry for those eager to explore quantum computation. Availability is specifically scheduled for Tuesdays and Wednesdays between 10:00 and 17:00 CET, accommodating the working hours of European-based customers. This strategic timing reflects a commitment to practical usability and seamless integration into existing workflows. Valentin Macheret, Engineering Manager, Quantum Technologies at Scaleway, highlights the technical advantages of the collaboration, noting that AQT’s approach “offers remarkable fidelity and unique all-to-all connectivity, which are critical for running complex and dee
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quantum-computingIBM’s Duality Accelerator Drives Quantum Software Growth with SQK (2023) & QodeX Quantum
IBM is fueling the next generation of quantum software companies with new investments in startups SQK and QodeX Quantum, announced today, February 20, 2026. Selected for phase two of the Alchemist Chicago accelerator’s inaugural cohort, these early-stage companies are pioneering quantum applications in healthcare and machine learning, representing a push toward “transformative solutions for industry.” Seattle-based SQK, founded in 2023, is developing hybrid quantum-classical algorithms for medical image reconstruction, while Chicago’s QodeX Quantum, established in 2025, aims to build a platform for quantum-native AI models. According to IBM, these investments are part of a broader strategy to “accelerate the growth of the software ecosystem” and unlock the potential of quantum computers, solidifying Illinois as a global hub for quantum innovation. SQK and QodeX Quantum: Pioneering Healthcare & AI Solutions “By addressing one of healthcare’s most pressing needs, improving accuracy and efficiency in imaging, SQK is positioned to make a meaningful impact,” IBM states. IBM intends to empower QodeX with access to its quantum technology and customer ecosystems, fostering sustainable growth. This support is part of IBM’s broader strategy to accelerate the quantum software ecosystem, including a two-phase program with the University of Chicago’s Polsky Center. “Building a robust quantum ecosystem…brings the promise of useful quantum computing closer to reality,” according to IBM, with Illinois becoming a central hub for this innovation. Alchemist Chicago Accelerator Drives Quantum Startup Growth Phase one of the program concentrated on customer discovery and proof-of-concept development, leveraging IBM’s mentorship and access to its quantum systems. Currently, the accelerator is in phase two, providing venture investment and business acceleration to selected startups, including SQK and QodeX Quantum, both participants in the inaugural cohort. Chicago’s QodeX Quantum, es
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quantum-computingQiskit-Braket provider v0.11: New Primitives and Flexible Circuit Compilation
Qiskit-Braket provider v0.11: New Primitives and Flexible Circuit Compilation We recently released v0.11 of the Qiskit-Braket provider, which brings more Qiskit features to Amazon Braket users, improves access to Braket backends through Qiskit, and also enables compilation on the Braket SDK or with OpenQASM Programs. With v0.11, the Qiskit-Braket provider now: Supports flexible compilation features for Braket using common Qiskit transpile functionality through the to_braket function Contains new BraketEstimator and BraketSampler primitives, which mirror routines found in similar Qiskit primitives, and includes several features aimed at running with Amazon Braket program sets. Supports Qiskit 2.0, and is fully back compatible to v0.34.2. With the latest upgrades to the Qiskit-Braket provider, you can use a richer set of tools for executing quantum programs on Amazon Braket. Updated support for Qiskit 2.0 The Qiskit-Braket-provider now supports Qiskit 2.0, which introduced new functionality and deprecated several old classes, compared to Qiskit 1.x. Additionally, performance increases seen in the refactoring of Qiskit 2.0 can now be leveraged using the Qiskit-Braket provider. The Qiskit-Braket provider is also back compatible to v0.34.2. For a full list of 2.0 changes, see Qiskit’s release summary, as well as recent releases (0.7.0 and beyond) in the Qiskit-Braket provider. Unlocking compilation for Braket circuits The Qiskit-Braket provider can now be used to easily unlock compilation on Braket circuits. You can now compile or transpile to Braket Circuit objects through the to_braket function, which can then be directly submitted to Braket devices: from qiskit_braket_provider import to_braket from braket.circuits import Circuit from braket.aws import AwsDevice from braket.devices import Devices device = AwsDevice(Devices.IQM.Garnet) ghz_4 = Circuit().h(0).cnot(0,1).cnot(1,2).cnot(2,3) ghz_4_native = to_braket(ghz_4, braket_device = device) # result = device.run(ghz_4
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quantum-computingTower Semiconductor and Xanadu Industrialize Silicon Photonic Quantum Stack
Tower Semiconductor and Xanadu Industrialize Silicon Photonic Quantum Stack Tower Semiconductor and Xanadu have expanded their partnership to develop a manufacturable silicon photonics platform for fault-tolerant quantum computing. This collaboration utilizes Tower’s high-volume foundry infrastructure to industrialize Xanadu’s photonic circuit designs, transitioning hardware from prototype to demonstrator systems. The joint engineering effort focuses on a custom production flow for a specialized material stack designed to maintain optical performance and scalability as system complexity increases. Technical developments center on the optimization of ultra-low loss silicon nitride (SiN) waveguides and integrated photodiodes within standard product flows. These components are critical for measurement-based quantum computing (MBQC) architectures, which require the generation and entanglement of thousands of qubits on a single photonic chip. By validating these designs on an established 200mm manufacturing platform, the partnership aims to meet the precise tolerances and high-yield requirements of large-scale quantum information processing. This manufacturing-aligned approach leverages Tower Semiconductor’s PH18 silicon photonics platform to provide a foundation for commercial-scale hardware. The expansion secures a dedicated fabrication route for Xanadu’s custom material stack, ensuring compatibility with industrial semiconductor processes. This technical alignment is intended to facilitate the deployment of photonic quantum modules that integrate with existing telecommunications and data center infrastructure. For further technical specifications, consult the official documentation from Tower Semiconductor here, review Xanadu’s photonic hardware architecture here, explore the Tower SiPho technology platform here, or access research on PennyLane here. February 19, 2026 Mohamed Abdel-Kareem2026-02-19T16:48:10-08:00 Leave A Comment Cancel replyComment Type in the text di
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quantum-computingAQT Integrates IBEX Q1 Trapped-Ion QPU into Scaleway Sovereign Cloud
AQT Integrates IBEX Q1 Trapped-Ion QPU into Scaleway Sovereign Cloud Alpine Quantum Technologies (AQT) and Scaleway have established a partnership to integrate the IBEX Q1 trapped-ion quantum processing unit (QPU) into Scaleway’s Quantum-as-a-Service (QaaS) platform. This deployment provides industrial and research organizations with access to universal quantum hardware hosted on European sovereign cloud infrastructure. The integration is designed to support high-performance computing (HPC) and quantum computing hybrid workflows, utilizing AQT’s hardware in coordination with Scaleway’s classical computing resources. The IBEX Q1 system utilizes trapped-ion technology characterized by all-to-all qubit connectivity and high gate fidelity. The hardware is accessible through standard open-source frameworks, including Qiskit, Cirq, and Pennylane, requiring no prior reservations for execution during specified operational windows. Currently, the device is available for cloud-based processing on Tuesdays and Wednesdays between 10:00 and 17:00 CET, targeting users within European time zones to minimize latency in development cycles. This infrastructure is positioned to address computational requirements in optimization, materials simulation, and financial modeling. By concentrating both hardware and cloud management within European jurisdictions, the partnership meets specific regulatory and data residency standards for public and private sector entities. The platform remains open for further integration with third-party solution developers focusing on the development of market-ready quantum applications within a secure, independent ecosystem. For additional technical information, consult the official partnership announcement here, the AQT cloud partner directory here, the Scaleway QaaS platform details here, or the IBEX Q1 system specifications here. February 19, 2026 Mohamed Abdel-Kareem2026-02-19T16:34:45-08:00 Leave A Comment Cancel replyComment Type in the text displayed
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quantum-computingIBM Ventures Invests in Two Quantum Software Startups to Accelerate Quantum innovation - The Quantum Insider
IBM Ventures Invests in Two Quantum Software Startups to Accelerate Quantum innovation The Quantum Insider
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quantum-computingIBM Ventures Invests in Two Quantum Software Startups to Accelerate Quantum innovation
Insider Brief IBM has invested in quantum software startups SQK and QodeX Quantum as part of its strategy to expand the quantum software ecosystem. SQK is applying hybrid quantum-classical algorithms to medical image reconstruction, while QodeX Quantum is developing quantum-native AI models integrated into machine learning workflows. IBM is also supporting quantum software development in Illinois through a partnership with the University of Chicago’s Polsky Center and participation in the Alchemist Chicago accelerator. Picture by IBM. IBM announced new investments in quantum software startups SQK and QodeX Quantum, stating that the company is committed to developing quantum software and maintaining the Qiskit open-source quantum software development kit while partnering with and investing in startups to accelerate adoption and impact. The company said it has invested in SQK and QodeX Quantum, two early-stage startups in the Duality quantum startup accelerator program that were selected for phase two of the Alchemist Chicago accelerator’s inaugural cohort. These companies were chosen for their work addressing challenges in healthcare and machine learning. SQK, a Seattle-based startup founded in 2023, is applying hybrid quantum-classical algorithms to medical image reconstruction. The company stated that this capability could affect diagnostics in oncology, cardiovascular health, and neuroscience. IBM will also provide SQK with resources, mentorship, and strategic connections to support its growth. QodeX Quantum, a Chicago-based startup founded in 2025, is developing quantum-native AI models and building a platform designed to integrate quantum computing into machine learning workflows. IBM will support QodeX by providing access to IBM’s quantum technology, networks, and customer ecosystems to help enable long-term growth. IBM’s Quantum Strategy in Illinois Part of IBM’s quantum strategy is to accelerate the growth of the software ecosystem to explore algorithms and a
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quantum-computingAQT and Scaleway Launch European Quantum Cloud Access
Insider Brief Alpine Quantum Technologies (AQT) is integrating its IBEX Q1 trapped-ion quantum computer into Scaleway’s cloud platform to provide sovereign Quantum-as-a-Service access in Europe. The partnership combines European quantum hardware and cloud infrastructure to support digital sovereignty, hybrid quantum-classical applications, and broader access for enterprises, researchers, and public institutions. The IBEX Q1 system will be accessible via Scaleway’s platform using frameworks such as Qiskit, Cirq, and Pennylane, with scheduled availability for users in European time zones. PRESS RELEASE — A new cloud partnership strengthens digital sovereignty and expands access to quantum computing – Alpine Quantum Technologies (“AQT”) is integrating its trapped-ion quantum computer into Scaleway’s cloud. This collaboration enables: A new sovereign quantum infrastructure made in Europe, combining European cloud and quantum hardware to support digital resilience and technological independence A stronger AQT presence within the French quantum ecosystem, fostering closer collaboration with research, industry, and innovation stakeholders. The development of hybrid applications, by pairing AQT’s quantum systems with Scaleway’s classical computing resources. An enhanced cloud offering from Scaleway, featuring digital, universal quantum hardware integrated directly into its platform. The trapped-ion quantum computer IBEX Q1 by AQT (Innsbruck, Austria) will be available via Scaleway’s (HQ: France) Quantum-as-a-Service (QaaS) platform, which gives industrial companies, research institutions, public authorities, educational institutions and developers access to quantum processing units (QPUs) via its sovereign cloud infrastructure. AQT’s quantum computer can be accessed and programmed without reservation needed from Qiskit, Cirq and Pennylane packages. The device is available T
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quantum-computingWiMi Hologram Cloud Unveils Quantum-Classical AI Model for Image Classification
WiMi Hologram Cloud Inc. has unveiled a novel approach to image classification, proposing a hybrid quantum-classical Inception neural network model. The Beijing-based Holographic Augmented Reality technology provider aims to overcome limitations in current image classification models by integrating the power of quantum computing with established classical deep learning techniques. This new architecture utilizes Inception-style parallel feature channels to achieve “triple improvements in performance, efficiency, and robustness.” WiMi’s research focuses on redesigning the parallel structure of quantum networks, moving beyond single-path designs to unlock the full potential of quantum computing for image analysis and lay the foundation for future hybrid quantum AI research. WiMi’s Hybrid Quantum-Classical Inception Network for Image Classification This isn’t simply adding quantum components to existing structures; WiMi’s approach fundamentally redesigns the architecture to integrate quantum computing with classical deep learning via Inception-style parallel feature channels. The core objective, as the company explains, is to “solve the expressiveness bottleneck of image classification models” by leveraging quantum computing’s ability to represent high-dimensional features while maintaining practical engineering feasibility. Previous quantum neural network research, WiMi notes, has largely focused on embedding variational quantum circuits into traditional neural networks, yielding incremental gains but failing to fully unlock quantum potential. The WiMi research team determined that a redesign of the parallel structure was essential, specifically needing to move beyond the limitations of single-path quantum networks. Their solution utilizes three parallel feature paths: quantum feature extraction, classical feature extraction, and a hybrid quantum-classical path. This Inception module concatenates outputs from these paths, creating a feature tensor for the classifier. “
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quantum-computingD-Wave (NYSE: QBTS) Schedules Q4 & FY2025 Earnings Release
D-Wave Quantum Inc. (NYSE: QBTS) announced it will release its fourth quarter and full fiscal year 2025 financial results on February 26, 2026, before market open. The company, uniquely positioned as the only provider of both annealing and gate-model quantum computing systems, will detail its performance for the period ended December 31, 2025. A conference call at 8:00 a.m. (Eastern Time) featuring Chief Executive Officer Dr. Alan Baratz and Chief Financial Officer John Markovich will follow the release, discussing both financial results and the company’s future outlook. D-Wave, serving over 100 organizations across commercial, government, and research, continues to lead in delivering enterprise-grade quantum solutions, including its Leap™ quantum cloud service boasting 99.9% availability. D-Wave Announces February 26, 2026 Financial Results Release D-Wave Quantum Inc. The company, a pioneer in quantum computing, reports its financial year ended December 31, 2025, at this time, making it a key date for investors tracking the burgeoning quantum landscape. D-Wave distinguishes itself as the “only dual-platform quantum computing company,” offering both annealing and gate-model systems alongside associated software and services. The financial release will be accessible via the D-Wave Investor Relations website at https://ir.dwavesys.com/. A conference call is scheduled for 8:00 a.m. (Eastern Time) on February 26, 2026, to elaborate on the results and future outlook, with dial-in numbers 1-844-826-3035 (domestic) and 1-412-317-5195 (international) available, or a link for instant access. Chief Executive Officer Dr. Dual-Platform Quantum Computing Systems & Leap™ Cloud Service D-Wave Quantum Inc. distinguishes itself by offering a unique approach to quantum computing, providing both annealing and gate-model systems—a capability no other company currently matches. This dual-platform strategy allows users to explore different quantum paradigms, potentially optimizing so
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quantum-computingIBM Ventures Invests in SQK and QodeX Quantum for Specialized Software Development
IBM Ventures Invests in SQK and QodeX Quantum for Specialized Software Development IBM Ventures has announced new investments in SQK and QodeX Quantum, two early-stage startups participating in the Alchemist Chicago deep tech accelerator. These investments represent a strategic move by IBM to bolster the quantum software ecosystem by supporting founders who are transitioning theoretical breakthroughs into industrial applications. Both startups were selected from the Duality accelerator program to advance into the second phase of Alchemist Chicago, a business acceleration stage that provides venture capital and intensive mentorship for enterprise scaling. SQK, based in Seattle, is developing hybrid quantum-classical algorithms specifically for medical image reconstruction. The company’s technology aims to improve the diagnostic accuracy and speed of imaging in fields like oncology, cardiovascular health, and neuroscience—addressing a critical computational bottleneck in modern healthcare. Meanwhile, QodeX Quantum, a Chicago-native startup, is focused on enabling quantum-native AI models. Their platform integrates quantum processing directly into machine learning workflows to enhance enterprise analytics and predictive modeling beyond the limits of classical architectures. These investments are part of IBM’s broader regional strategy in Illinois, centered on the Illinois Quantum and Microelectronics Park (IQMP). IBM plans to deploy its next-generation IBM Quantum System Two at the park to anchor the newly established National Quantum Algorithm Center. By providing startups like SQK and QodeX with technical access to utility-scale hardware (including the 156-qubit IBM Heron processor) and the Qiskit software stack, IBM aims to create a “front door” for industry partners to discover and deploy useful quantum algorithms for real-world enterprise challenges. For further technical details, view the official announcement from IBM here. February 18, 2026 Mohamed Abdel-Kareem
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quantum-computingQuantum Error Models Commonly Assume Smooth Changes, but New Analysis Reveals This Isn’t Always True
Researchers are increasingly focused on accurately modelling errors in quantum systems, and a new study by Alireza Seif, Moein Malekakhlagh, and Swarnadeep Majumder, all from IBM Quantum at IBM T. J. Watson Research Center, investigates the often-assumed Markovian nature of Pauli channels. These channels are fundamental to describing noise, particularly when utilising Pauli twirling, yet a systematic examination of this assumption has been lacking. This work employs CP-indivisibility to assess non-Markovianity within multi-qubit Pauli channels, revealing that while the channel structure aligns with standard Pauli-Lindblad models, the associated rates can frequently be negative or complex. The findings demonstrate that random Pauli channels are almost invariably non-Markovian, and importantly, that even physically realistic noise models exhibit this behaviour, even when originating from Markovian processes. By extending probabilistic error amplification and cancellation to accommodate non-Markovian generators, the team quantifies the resulting sampling overhead and validates their approach with experiments on superconducting qubits, showing improved predictive accuracy when allowing negative rates in noise models. Scientists have uncovered a fundamental limitation in how quantum errors are typically modelled, revealing that commonly used assumptions about the behaviour of quantum systems may be flawed. This discovery has significant implications for building practical quantum computers, as current error correction strategies rely heavily on the Markovian assumption. The study focuses on Pauli channels, a standard way to represent errors in quantum computers, particularly when using a technique called Pauli twirling to simplify noise characteristics. By rigorously examining these channels, the team found that while the structure of the generator often resembles the expected form, the rates governing error evolution are often negative or even complex numbers. The proba
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quantum-computingQuantum Walks Boost Security on Early Computers
Scientists are increasingly focused on developing quantum cryptographic protocols compatible with near-term, noisy intermediate-scale quantum (NISQ) devices. Aditi Rath, Dinesh Kumar Panda, and Colin Benjamin, all from the National Institute of Science Education and Research, Bhubaneswar, Homi Bhabha National Institute, detail a novel scheme leveraging discrete-time quantum walks and Parrondo dynamics on cyclic graphs. This research is significant because it constructs a practical quantum circuit specifically tailored for NISQ architectures and rigorously assesses its security against common attacks, modelling intercept-resend and man-in-the-middle scenarios. Through numerical simulations and analysis of hardware feasibility, the authors demonstrate how connectivity and state-transfer strategies critically impact fidelity and performance, offering valuable insights into the trade-offs inherent in deploying quantum cryptography on contemporary processors. Scientists are edging closer to unhackable communications with a quantum cryptography method designed for today’s limited quantum computers. This advance tackles a critical challenge by working with imperfect, noisy hardware than waiting for fully-fledged quantum machines. The technique promises secure data transmission even before large-scale quantum networks become a reality. Compatibility with noisy intermediate-scale quantum (NISQ) devices is paramount for realising practical quantum cryptographic protocols. This work investigates a novel cryptographic scheme founded on discrete-time quantum walks (DTQWs) on cyclic graphs, harnessing the intriguing Parrondo dynamics, a phenomenon where periodic behaviour arises from a sequence of individually chaotic operations. Researchers have constructed a dedicated quantum circuit design optimised for NISQ architectures and rigorously analysed its performance using numerical simulations within the Qiskit framework, both under idealised conditions and with realistic noise mod
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