12 citations · 18 across the 8 of their papers we have counts for
8 papers
Beyond Optimization: Harnessing Quantum Annealer Dynamics for Machine Learning
Akitada Sakurai, Aoi Hayashi, Tadayoshi Matsumori +3
Quantum annealing is typically regarded as a tool for combinatorial optimization, but its coherent dynamics also offer potential for machine learning. We present a model that encod…
Quantum Random Features: A Spectral Framework for Quantum Machine Learning
Akitada Sakurai, Aoi Hayashi, William John Munro +1
Quantum machine learning (QML) models often require deep, parameterized circuits to capture complex frequency components, limiting their scalability and near-term implementation. W…
Modular quantum extreme reservoir computing
Hon Wai Lau, Aoi Hayashi, Akitada Sakurai +2
Quantum reservoir computing employs fixed quantum dynamics as a feature map for machine learning. Integrating multiple quantum reservoirs, however, raises a key question: how few i…
Simple Hamiltonian dynamics is a powerful quantum processing resource
Akitada Sakurai, Aoi Hayashi, William John Munro +1
A quadrillion dimensional Hilbert space hosted by a quantum processor with over 50 physical qubits has been expected to be powerful enough to perform computational tasks ranging fr…
Equilibration of Non-interacting Photons and Quantum Signatures of Chaos
V. M. Bastidas, H. L. Nourse, A. Sakurai +4
Equilibration plays a fundamental role in our understanding of statistical mechanics and the long-time dynamics of many-body systems. In quantum systems, the route to equilibration…
Gauge dependence of the Aharonov-Bohm phase in a quantum electrodynamics framework
A. Hayashi
The Aharonov-Bohm (AB) phase is usually associated with a line integral of the electromagnetic vector potential generated by an external current source, such as a solenoid. Accordi…
Impact of the form of weighted networks on the quantum extreme reservoir computation
Aoi Hayashi, Akitada Sakurai, Shin Nishio +2
The quantum extreme reservoir computation (QERC) is a versatile quantum neural network model that combines the concepts of extreme machine learning with quantum reservoir computati…
Competing insulating phases of dipolar bosons in a dimerized optical lattice
Aoi Hayashi, Suman Mondal, Tapan Mishra +1
We study the ground state properties of dipolar bosons in a one dimensional dimerized optical lattice. In the limit of strong onsite repulsion i.e. hardcore bosons, and strong dipo…