3 papers
quant-ph2025
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…
quant-ph2024
Explicit quantum surrogates for quantum kernel models
Akimoto Nakayama, Hayata Morisaki, Kosuke Mitarai +2
Quantum machine learning (QML) leverages quantum states for data encoding, with key approaches being explicit models that use parameterized quantum circuits and implicit models tha…
quant-ph2023
A comprehensive survey on quantum computer usage: How many qubits are employed for what purposes?
Tsubasa Ichikawa, Hideaki Hakoshima, Koji Inui +18
Quantum computers (QCs), which work based on the law of quantum mechanics, are expected to be faster than classical computers in several computational tasks such as prime factoring…