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Found 3 papers, 1 papers with code
Quantum adiabatic machine learning with zooming
The significant improvement of quantum annealing algorithms for machine learning and the use of a discrete quantum algorithm on a continuous optimization problem both opens a new class of problems that can be solved by quantum annealers and suggests the approach in performance of near-term quantum machine learning towards classical benchmarks.
Charged particle tracking with quantum annealing-inspired optimization
At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for analysis are expected to face challenges due to scaling with track density.
Demonstration of fidelity improvement using dynamical decoupling with superconducting qubits
Quantum computers must be able to function in the presence of decoherence.
Quantum Physics
