5 citations · 8 across the 10 of their papers we have counts for
10 papers
Discretization-Aware Fine-Tuning for Quantum Machine Learning with Chemical Foundation Models
Shunji Matsuura, Sonika Johri
A key challenge in practical quantum machine learning (QML), particularly for discriminative tasks such as classification, is the limited capacity of near-term quantum devices to e…
Krylov Break Times from an Inhomogeneous Lieb--Robinson Light Cone
Shunji Matsuura, Yoji Kawamura, Joseph Salfi +1
Krylov and Lanczos approximations are used in quantum dynamics, quantum subspace methods, and Hamiltonian learning. A practical question is how long an -dimensional Krylov trunc…
Learning Quantum Operator Dynamics from Short-Time Data
Jinyang Li, Satoshi Iso, Shunji Matsuura +2
Real-time dynamics of quantum observables provide direct access to excitation spectra and correlation functions in quantum many-body systems, but currently available quantum device…
Gauge Symmetry in Quantum Simulation
Masanori Hanada, Shunji Matsuura, Andreas Schafer +1
Quantum simulation of non-Abelian gauge theories requires careful handling of gauge redundancy. We address this challenge by presenting universal principles for treating gauge symm…
Quantum Machine Learning for Identifying Transient Events in X-ray Light Curves
Taiki Kawamuro, Shinya Yamada, Shigehiro Nagataki +3
We investigate whether a novel method of quantum machine learning (QML) can identify anomalous events in X-ray light curves as transient events and apply it to detect such events f…
Universal framework with exponential speedup for the quantum simulation of quantum field theories including QCD
Jad C. Halimeh, Masanori Hanada, Shunji Matsuura
We present a quantum simulation framework universally applicable to a wide class of quantum systems, including quantum field theories such as quantum chromodynamics (QCD). Specific…