3 papers
quant-ph2026
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…
quant-ph2026
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…
quant-ph2026
Quantum phase classification via partial tomography-based quantum hypothesis testing
Akira Tanji, Hiroshi Yano, Naoki Yamamoto
Quantum phase classification is a fundamental problem in quantum many-body physics, traditionally approached using order parameters or quantum machine learning techniques such as q…