Two independent research teams published peer-reviewed papers this week confirming that IBM's Nighthawk quantum processor can handle real problem classes at the frontier of two unrelated fields: ...
Abstract: The Quantum Approximate Optimization Algorithm (QAOA) is a leading candidate for solving combinatorial optimization problems on near-term quantum hardware. However, its practical deployment ...
Abstract: A promising approach to the practical application of the quantum approximate optimization algorithm (QAOA) is finding QAOA parameters classically in simulation and sampling the solutions ...
Microsoft and Quantinuum have demonstrated 12 logical qubits built from 97 physical qubits, running fault-tolerant algorithms that outperform the raw hardware beneath them. The achievement, detailed ...
The WIA-QUA-002 standard defines the computational framework for quantum algorithms, including quantum gates, circuits, Shor's algorithm, Grover's search, variational quantum eigensolver (VQE), ...
[Quantum Made in Japan #6] Japanese Quantum Optimization SaaS "Fixstars Amplify" Adds Quantum Computer as a Standard Feature—What Changes with the Integration of IonQ Trapped Ions? Fact: On June 22, ...
16 Jul 2026 02.00 PM - 03.00 PM MAS Executive Classroom 1 (SPMS-MAS-03-06) Current Students Add to Calendar ===== Abstract ===== Parameter optimization is widely regarded as one of the main classical ...
Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which optimization actually moved the needle.
A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...
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