7 papers · 1 filter
VQE-generated quantum circuit dataset for machine learning
Akimoto Nakayama, Kosuke Mitarai, Leonardo Placidi +2
Quantum machine learning has the potential to computationally outperform classical machine learning, but it is not yet clear whether it will actually be valuable for practical prob…
Classical variational optimization of PREPARE circuit for quantum phase estimation of quantum chemistry Hamiltonians
Hayata Morisaki, Kosuke Mitarai, Keisuke Fujii +1
We propose a method for constructing circuits for quantum phase estimation of a molecular Hamiltonian in quantum chemistry by using variational optimization of q…
A Polynomial Time Quantum Algorithm for Exponentially Large Scale Nonlinear Differential Equations via Hamiltonian Simulation
Yu Tanaka, Keisuke Fujii
Quantum computers have the potential to efficiently solve a system of nonlinear ordinary differential equations (ODEs), which play a crucial role in various industries and scientif…
Measuring Trotter error and its application to precision-guaranteed Hamiltonian simulations
Tatsuhiko N. Ikeda, Hideki Kono, Keisuke Fujii
Trotterization is the most common and convenient approximation method for Hamiltonian simulations on digital quantum computers, but estimating its error accurately is computational…
Variational quantum eigensolver with embedded entanglement using a tensor-network ansatz
Ryo Watanabe, Keisuke Fujii, Hiroshi Ueda
In this paper, we introduce a tensor network (TN) scheme into the entanglement augmentation process of the synergistic optimization framework by Rudolph et al. [arXiv:2208.13673] t…
Algorithmic error mitigation for quantum eigenvalues estimation
Adam Siegel, Kosuke Mitarai, Keisuke Fujii
When estimating the eigenvalues of a given observable, even fault-tolerant quantum computers will be subject to errors, namely algorithmic errors. These stem from approximations in…