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.
Plans to automate error correction and quantum–classical integration in stages, aiming for a unified development environment from Helios to Apollo (planned 2029).
Integrates over 400 mm² of computational area with control circuitry and inter‑chip connectivity to enable expansion of quantum computers via multiple chips.
They published resource estimates for Shor’s algorithm using cat qubits and LDPC‑cat codes, estimating RSA‑2048 could be broken in 3.14 days.
Combining SEEQC’s chip-based pre-decoder with NVIDIA Ising, simulations reduced decoding latency and logical error rate by about 50%.
Nord Quantique has won additional DARPA funding under the Quantum Benchmarking Initiative to continue evaluating and developing its bosonic quantum error‑correction approach.
IBM connected two superconducting quantum processors with four l-couplers, demonstrating an average 99% quantum state-transfer fidelity.
OptQC has published an arXiv paper proposing a photonic quantum-computing architecture that separates the offline resource-generation unit for error correction from the online computation unit.
Qblox integrated an NVIDIA DGX Spark with its quantum system controller via NVQLink, incorporating GPUs into the quantum control real-time loop.
They developed a method to iteratively correct correlated errors arising in cross-logical-qubit operations for trapped-ion systems, and compared logical error rates in large-scale simulations.
In the first phase of France’s PROQCIMA program, they tested cat‑qubit CNOT gates and a distance‑3 repetition code on hardware. The logical error rate remains above the error‑correction threshold.
Quantinuum recorded five logical errors per one million operations on its trapped‑ion quantum computer Helios using the color code.
Google Quantum AI demonstrated magic-state cultivation on the Willow quantum processor, achieving 99.99% logical fidelity for T states.
Diraq says quantum computers should be evaluated not by qubit count but by logical-operation throughput and cost per operation.
Riverlane re‑calibrated QEC decoder weights on GPUs, speeding a surface‑code training epoch 65× versus a single CPU core.
Alice & Bob performed a proof‑of‑concept decoding of LDPC‑cat codes on a GPU via NVIDIA NVQLink. The test used synthetic data and did not achieve real‑time decoding.
A neutral-atom approach to utility-scale quantum computing will undergo independent verification by DARPA.
IBM Quantum announced a new execution model, directed execution. The new primitive, Executor, lets clients inspect and modify error mitigation and circuit randomization from the client side.
D-Wave has launched a beta program for a gate-model quantum simulator based on dual-rail superconducting technology. Four organizations will develop applications with an eye toward future hardware.
Classiq has announced its Fault Tolerance Engine, which plans qubit placement and routing and estimates the physical resources required for fault-tolerant quantum computing.
Alice & Bob and ENS Lyon demonstrated a method to control two-photon dissipation in superconducting cat qubits using a tiny DC voltage instead of microwave drives.
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?
Infleqtion and Riverlane have signed a memorandum of understanding to evaluate integrating real-time quantum error correction with Infleqtion’s neutral-atom quantum computing platform.
Diraq has designed an 8‑qubit system being deployed in a commercial data center to run under 20 kW. For a future million‑qubit‑scale system, it assumes about 300 kW including classical compute components.
A seven-organization consortium led by QUDORA aims to build a trapped-ion demonstrator with more than 1,000 physical qubits and a QPU pilot line. The total project size is about €122 million.
They will jointly evaluate how the configuration of distributed quantum systems and error‑correction schemes affect required physical qubit counts, execution time, and system‑wide load.
IonQ evaluated real-time error decoding on a single CPU using circuits simulating up to 408 logical qubits and more than 31.5 million quantum operations. The reported increase in execution time was as little as 0.02%.
Riverlane plans to establish a U.S. headquarters with labs in Maryland and advance quantum error correction research and talent development in partnership with the University of Maryland.
Diraq and Dell Technologies are colocating quantum processors with HPC systems to test low-latency connections and hybrid computation control techniques.
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.