5 papers
Adaptive identification of low-degree polynomials in quantum singular value transformation: application to nonlinear quantum properties estimation
Jumpei Kato, Akira Tanji, Hiroyuki Harada +3
Estimating properties of unknown quantum states via quantum singular value transformation (QSVT) often requires high-degree polynomials to handle small eigenvalues of density matri…
Random Access Codes: Explicit Constructions, Optimality, and Classical-Quantum Gaps
Ruho Kondo, Yuki Sato, Hiroshi Yano +3
A random access code (RAC) encodes an -bit string into a -bit message, , so that any requested bit can be recovered with high probability; a quantum RAC (QRAC) uses …
Learning from imperfect quantum data via unsupervised domain adaptation with classical shadows
Kosuke Ito, Akira Tanji, Hiroshi Yano +2
Learning from quantum data using classical machine learning models has emerged as a promising paradigm toward realizing quantum advantages. Despite extensive analyses on their perf…
Explicit block-encoding for partial differential equation-constrained optimization
Yuki Sato, Jumpei Kato, Hiroshi Yano +2
Partial differential equation (PDE)-constrained optimization, where an optimization problem is subject to PDE constraints, arises in various applications such as design, control, a…
Exponentially accurate open quantum simulation via randomized dissipation with minimal ancilla
Jumpei Kato, Kaito Wada, Kosuke Ito +1
Simulating open quantum systems is an essential technique for understanding complex physical phenomena and advancing quantum technologies. Some quantum algorithms simulate Lindblad…