134 citations · 285 across the 22 of their papers we have counts for
22 papers
Stage-dependent integer-binary encoding in factorization-machine black-box optimization
Ryo Ogawa, Mayumi Nakano, Yuya Seki +1
Black-box optimization (BBO) deals with problems where objective functions lack explicit analytical forms and are expensive to evaluate. Factorization machine with quadratic-optimi…
Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding
Taiga Hayashi, Yuya Seki, Kotaro Terada +3
Factorization machine with quadratic-optimization annealing (FMQA) is a black-box optimization method that combines a factorization machine (FM) surrogate with QUBO-based search by…
Black-box optimization using factorization and Ising machines
Ryo Tamura, Yuya Seki, Yuki Minamoto +4
Black-box optimization (BBO) is used in materials design, drug discovery, and hyperparameter tuning in machine learning. The world is experiencing several of these problems. In thi…
SWIFT-FMQA: Enhancing Factorization Machine with Quadratic-Optimization Annealing via Sliding Window
Mayumi Nakano, Yuya Seki, Shuta Kikuchi +1
Black-box (BB) optimization problems aim to identify an input that maximizes or minimizes the output of a function (the BB function) whose input-output relationship is unknown. Fac…
Can Constrained Quantum Annealing Be Effective in Noisy Quantum Annealers?
Ryoya Igata, Myonsok I, Yuya Seki +2
We investigate the performance of penalty-based quantum annealing (PQA) and constrained quantum annealing (CQA) in solving the graph partitioning problem under various noise models…
Initialization Method for Factorization Machine Based on Low-Rank Approximation for Constructing a Corrected Approximate Ising Model
Yuya Seki, Hyakka Nakada, Shu Tanaka
This paper presents an initialization method that can approximate a given approximate Ising model with a high degree of accuracy using a factorization machine (FM), a machine learn…
Machine learning supported annealing for prediction of grand canonical crystal structures
Yannick Couzinie, Yuya Seki, Yusuke Nishiya +4
This study investigates the application of Factorization Machines with Quantum Annealing (FMQA) to address the crystal structure problem (CSP) in materials science. FMQA is a black…
Towards optimization of photonic-crystal surface-emitting lasers via quantum annealing
Takuya Inoue, Yuya Seki, Shu Tanaka +3
Photonic-crystal surface-emitting lasers (PCSELs), which utilize a two-dimensional (2D) optical resonance inside a photonic crystal for lasing, feature various outstanding function…
Quantum annealing with symmetric subspaces
Takashi Imoto, Yuya Seki, Yuichiro Matsuzaki
Quantum annealing (QA) is a promising approach for not only solving combinatorial optimization problems but also simulating quantum many-body systems such as those in condensed mat…
Black-box optimization for integer-variable problems using Ising machines and factorization machines
Yuya Seki, Ryo Tamura, Shu Tanaka
Black-box optimization has potential in numerous applications such as hyperparameter optimization in machine learning and optimization in design of experiments. Ising machines are…
Preparing ground states of the XXZ model using the quantum annealing with inductively coupled superconducting flux qubits
Takashi Imoto, Yuya Seki, Yuichiro Matsuzaki
Preparing ground states of Hamiltonians is important in the condensed matter physics and the quantum chemistry. The interaction Hamiltonians typically contain not only diagonal but…
Quantum annealing with twisted fields
Takashi Imoto, Yuya Seki, Yuichiro Matsuzaki and +1
Quantum annealing is a promising method for solving combinational optimization problems and performing quantum chemical calculations. The main sources of errors in quantum annealin…
Improving the accuracy of the energy estimation by combining quantum annealing with classical computation
Takashi Imoto, Yuya Seki, Yuichiro Matsuzaki +1
Quantum chemistry calculations are important applications of quantum annealing. For practical applications in quantum chemistry, it is essential to estimate a ground state energy o…
Quantum remote sensing under the effect of dephasing
Hideaki Okane, Hideaki Hakoshima, Yuki Takeuchi +2
The quantum remote sensing (QRS) is a scheme to add security about the measurement results of a qubit-based sensor. A client delegates a measurement task to a remote server that ha…
Direct estimation of the energy gap between the ground state and excited state with quantum annealing
Yuichiro Matsuzaki, Hideaki Hakoshima, Kenji Sugisaki +2
Quantum chemistry is one of the important applications of quantum information technology. Especially, an estimation of the energy gap between a ground state and excited state of a…
Boltzmann machine learning with a variational quantum algorithm
Yuta Shingu, Yuya Seki, Shohei Watabe +5
Boltzmann machine is a powerful tool for modeling probability distributions that govern the training data. A thermal equilibrium state is typically used for Boltzmann machine learn…
Excited state search using quantum annealing
Yuya Seki, Yuichiro Matsuzaki, Shiro Kawabata
Quantum annealing (QA) is one of the ways to search the ground state of the problem Hamiltonian. Here, we propose the QA scheme to search arbitrary excited states of the problem Ha…
Quantum annealing with capacitive-shunted flux qubits
Yuichiro Matsuzaki, Hideaki Hakoshima, Yuya Seki +1
Quantum annealing (QA) provides us with a way to solve combinatorial optimization problems. In the previous demonstration of the QA, a superconducting flux qubit (FQ) was used. How…
Enhancing quantum annealing performance by a degenerate two-level system
Shohei Watabe, Yuya Seki, Shiro Kawabata
Quantum annealing is an innovative idea and method for avoiding the increase of the calculation cost of the combinatorial optimization problem. Since the combinatorial optimization…
Quantum Phase Transition in Fully-Connected Quantum Wajnflasz-Pick Model
Yuya Seki, Shu Tanaka, Shiro Kawabata
We construct a quantum Wajnflasz-Pick model that is a generalized quantum Ising model, and investigate a nature of quantum phase transitions of the model with infinite-range intera…
Quantum Annealing with Antiferromagnetic Transverse Interactions for the Hopfield Model
Yuya Seki, Hidetoshi Nishimori
We investigate quantum annealing with antiferromagnetic transverse interactions for the generalized Hopfield model with -body interactions. The goal is to study the effectivenes…
Quantum annealing with antiferromagnetic fluctuations
Yuya Seki, Hidetoshi Nishimori
We introduce antiferromagnetic quantum fluctuations into quantum annealing in addition to the conventional transverse-field term. We apply this method to the infinite-range ferroma…