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…
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…
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…
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…