IBM and AMD build live quantum error‑correction research platform to support Starling in 2029
An IBM quantum processor is colocated with ORNL’s HPC equipped with AMD GPUs and CPUs to validate low‑latency quantum error‑correction processing.
An IBM quantum processor is colocated with ORNL’s HPC equipped with AMD GPUs and CPUs to validate low‑latency quantum error‑correction processing.
D-Wave updated the core algorithm of its Stride hybrid solver and began offering the improved version on the Leap quantum cloud. In internal comparisons on problems such as the traveling salesman problem, it reported improvements in solution quality and solve time.
Qblox and HPE will collaborate on developing a classical–quantum hybrid platform, using an integrated testbed to evaluate interoperability and system-level performance.
Combining SEEQC’s chip-based pre-decoder with NVIDIA Ising, simulations reduced decoding latency and logical error rate by about 50%.
They will evaluate the performance and technical challenges of a solver that combines quantum computing and HPC for linear equations in thermal-fluid analysis.
Qblox integrated an NVIDIA DGX Spark with its quantum system controller via NVQLink, incorporating GPUs into the quantum control real-time loop.
IBM introduced a mechanism to call Qiskit’s Rust core directly via the C API, enabling integration of quantum processing into existing HPC and scientific computing code.
Quantinuum and the University of Western Australia have signed an MOU on developing quantum talent and industry use cases. They plan to provide cloud access to quantum infrastructure, including Helios.
Competition in quantum computing won’t be decided by QPU performance alone. As QEC, real‑time control, and hybrid computation increase the need for low‑latency feedback between QPUs and classical systems, NVIDIA is expanding an integrated stack around CUDA‑Q and NVQLink, while AMD and Xanadu counter with the open heterogeneous platform Backline. Will QPU vendors or platform companies that bind QPUs together lead the quantum computing infrastructure?
A method that approximates a quantum state as a combination of basis functions and reconstructs it with fewer measurements than conventional methods was demonstrated in numerical simulations.
They built a quantum–classical hybrid workflow to search operational configurations of a natural-gas network and ran a reduced-size problem on IonQ Forte‑1.
IonQ announced a joint research plan to install its Superion 256 quantum computer at NVIDIA’s research center and connect it directly to NVIDIA’s GPU infrastructure.
IonQ and SDT announced a multi‑year partnership. They will introduce quantum computers and quantum memory in South Korea and expand collaboration into manufacturing, integration, and hybrid data‑center development.
Diraq and Dell Technologies are colocating quantum processors with HPC systems to test low-latency connections and hybrid computation control techniques.
IonQ and Synopsys incorporated quantum algorithms into pre-processing for engineering simulations, reducing end-to-end runtimes by 5.9–14.6%.
Alice & Bob and CEA have begun work to integrate software for cat qubits into HPC environments and to research many-body algorithms aimed at early fault-tolerant quantum computing.
IQM has signed a delivery contract with Brazil’s Eldorado Research Institute. The IQM Spark will be installed in Q1 2027, and remote access to a 54‑qubit cloud system will also be provided.
A single program written in CUDA‑Q was executed across real qubits, a PPU, GPU and CPU. Quantum‑to‑classical information exchange took about 1 microsecond.
IQM plans a staged deployment of a quantum computer for the LUMI AI Factory beginning in 2027, aiming to enable real-time quantum error correction and up to 9 logical qubits.
Alice & Bob and Hyperion Research recommended latency testing, software standardization, and joint workflow design to integrate HPC, quantum, and AI.
A quantum–HPC coupled simulation of a 12,635‑atom protein system and automation of the computational workflow were recognized.
RIKEN’s JHPC-quantum has adopted QunaSys’ development kit. The environment will link HPCs such as Fugaku with IBM and Quantinuum quantum computers.
QOBLIB, which compares quantum and classical optimization methods under common conditions, has been expanded through a published paper and the launch of a dedicated website.
Quantinuum will install its trapped-ion quantum computer Helios in OCI, offering a hybrid computing environment that combines HPC and GPUs with quantum processing.
They will begin a joint proof of concept comparing classical computing, quantum‑inspired computing, and quantum computing for defense logistics, resource allocation and related decisions.
IQM’s H1 2026 revenue was €8.9 million, with an operating loss of €60.5 million. Full-year revenue is forecast at €42–47 million.
JIJ has raised approximately ¥840 million through a third‑party allocation of shares. The funds will be used to expand its mathematical optimization business, advance “JijZept AI”, develop middleware for gate‑model quantum computing, and support overseas expansion.
D-Wave and Nasdaq Verafin will launch a proof of concept applying quantum–classical hybrid techniques to financial crime detection. They will analyze hundreds of data signals to explore their use in predictive models for anomalous account behavior.
planqc, Saarland University, BMW and Infineon have launched an industrial optimization research project that combines quantum-driven problem reduction with classical algorithms.
Q-CTRL outlines the conditions needed to commercialize quantum computers, using integration examples at RIKEN and Elevate Quantum to highlight the importance of HPC integration, operational automation, and workforce development.