1 citations · 1 across the 3 of their papers we have counts for
3 papers
Learning functions of Hamiltonians with Hamiltonian Fourier features
Yuto Morohoshi, Akimoto Nakayama, Hidetaka Manabe +1
We propose a quantum machine learning task that is provably easy for quantum computers and arguably hard for classical ones. The task involves predicting quantities of the form $\m…
Quantum expectation value estimation by doubling the number of qubits
Hiroshi Yano, Masaya Kohda, Shoichiro Tsutsui +4
Expectation value estimation is ubiquitous in quantum algorithms. The expectation value of a Hamiltonian, which is essential in various practical applications, is often estimated b…
Pricing multi-asset derivatives by variational quantum algorithms
Kenji Kubo, Koichi Miyamoto, Kosuke Mitarai +1
Pricing a multi-asset derivative is an important problem in financial engineering, both theoretically and practically. Although it is suitable to numerically solve partial differen…