141 citations · 659 across the 34 of their papers we have counts for
6 papers · 1 filter
Adaptive Interpolating Quantum Transform: A Quantum-Native Framework for Efficient Transform Learning
Gekko Budiutama, Shunsuke Daimon, Hirofumi Nishi +3
Machine learning on quantum computers has attracted attention for its potential to deliver computational speedups in different tasks. However, deep variational quantum circuits req…
Entanglement entropy dynamics of non-Gaussian states in free boson systems: Random sampling approach
Ryui Kaneko, Daichi Kagamihara, Ippei Danshita
We develop a random sampling method for calculating the time evolution of the Rényi entanglement entropy after a quantum quench from an insulating state in free boson systems. Beca…
Forecasting long-time dynamics in quantum many-body systems by dynamic mode decomposition
Ryui Kaneko, Masatoshi Imada, Yoshiyuki Kabashima +1
Reliable numerical computation of quantum dynamics is a fundamental challenge when the long-ranged quantum entanglement plays essential roles as in the cases governed by quantum cr…
Channel Attention for Quantum Convolutional Neural Networks
Gekko Budiutama, Shunsuke Daimon, Hirofumi Nishi +3
Quantum convolutional neural networks (QCNNs) have gathered attention as one of the most promising algorithms for quantum machine learning. Reduction in the cost of training as wel…
Evaluating thermal expectation values by almost ideal sampling with Trotter gates
Shimpei Goto, Ryui Kaneko, Ippei Danshita
We investigate the sampling efficiency for the simulations of quantum many-body systems at finite temperatures when initial sampling states are generated by applying Trotter gates…
Rényi entanglement entropy after a quantum quench starting from insulating states in a free boson system
Daichi Kagamihara, Ryui Kaneko, Shion Yamashika +4
We investigate the time-dependent Rényi entanglement entropy after a quantum quench starting from the Mott-insulating and charge-density-wave states in a one-dimensional free boson…