16 papers
Generative Learning for Quantum Measurement Design
Jun Dai, Olivier Nahman-Lévesque, Guillaume Rabusseau +2
Extracting quantum information from a quantum state is a fundamental task of quantum computation, often requiring the estimation of many non-commuting observables under a finite me…
Provably Efficient Self-Calibrating Quantum Fault Tolerance
Weiyuan Gong, Hong-Ye Hu
Quantum error correction protects logical information only when every physical operation remains below the fault-tolerance threshold, a condition that must be maintained continuous…
Covariant Approximate Quantum Codes for Protected Analog Computation
Mariia Elovenkova, Hong-Ye Hu, Susanne F. Yelin
Quantum error correction compatible with continuous symmetries is a fundamental problem in quantum information and a possible route to robust analog quantum simulation. Because the…
Fast and Parallel High-Rate STAR Architecture for Megaquop Quantum Simulation
Refaat Ismail, Milan KornjaÄa, Hong-Ye Hu +4
Fault-tolerant quantum simulation is approaching a phase where encoding overhead, logical Clifford operations, magic-state preparation, and rotation synthesis must be optimized tog…
Learning Arbitrary Lindbladians with Quantum Error Correction
Nikita Romanov, Petr Ivashkov, Weiyuan Gong +4
We study ansatz-free Lindbladian learning, the problem of reconstructing the generator of an open quantum system without prior knowledge of its Hamiltonian or dissipator structures…
Opportunities and challenges in scaling quantum error detection on hardware
Yanis Le Fur, Ethan Egger, Hong-Ye Hu +3
Quantum error detection can produce unbiased expectation values that exponentially converge to noiseless results as the code distance is increased. Despite this, its performance as…