# Black-box optimization using factorization and Ising machines

https://mdr.nims.go.jp/datasets/35390592-429c-43f7-921d-0a8cdc67c489

## File

- [021307_1_5.0275450.pdf](https://mdr.nims.go.jp/filesets/cbe29e11-b578-4dd1-8137-3c1ff28f07b4/download) ([Detail](https://mdr.nims.go.jp/filesets/cbe29e11-b578-4dd1-8137-3c1ff28f07b4.md))

## Id

35390592-429c-43f7-921d-0a8cdc67c489

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2026-09-15T21:01:35.004381Z

## Updated at

2026-09-16T01:21:38.214267Z

## Published at

2026-09-16T03:27:17.163270Z

## Doi



## First published url

https://doi.org/10.1063/5.0275450

## Date published

2026-06-01

## Recorded date published

2026-6-1

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Black-box optimization using factorization and Ising machines
  title_type: original
  lang: en

## Description

- description: 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 this review, a factorization machine with quantum annealing
    or with quadratic-optimization annealing (FMQA) algorithm to realize fast computations
    of BBO using Ising machines (IMs) is discussed. The FMQA algorithm uses a factorization
    machine (FM) as a surrogate model for BBO. The FM model can be directly transformed
    into a quadratic unconstrained binary optimization model that can be solved using
    IMs. This makes it possible to optimize the acquisition function in BBO, which
    is a difficult task using conventional methods without IMs. Consequently, it has
    the advantage of handling large BBO problems. To be able to perform BBO with the
    FMQA algorithm immediately, we introduce the FMQA algorithm along with Python
    packages to run it. In addition, we review examples of applications of the FMQA
    algorithm in various fields, including physics, chemistry, materials science,
    and social sciences. These successful examples include binary and integer optimization
    problems, as well as more general optimization problems involving graphs, networks,
    and strings, using a binary variational autoencoder. We believe that BBO using
    the FMQA algorithm will become a key technology in IMs including quantum annealers.
  description_type: abstract
  lang: und

## Creator

- name: Ryo Tamura
  role: author
  orcid: https://orcid.org/0000-0002-0349-358X
- name: Yuya Seki
  role: author
  orcid: https://orcid.org/0000-0001-5393-2280
- name: Yuki Minamoto
  role: author
  orcid: https://orcid.org/0000-0002-6157-8370
- name: Koki Kitai
  role: author
- name: Yoshiki Matsuda
  role: author
- name: Shu Tanaka
  role: author
  orcid: https://orcid.org/0000-0002-0871-3836
- name: Koji Tsuda
  role: author
  orcid: https://orcid.org/0000-0002-4288-1606

## Contact agent



## Publisher

organization: AIP Publishing

## Managing organization



## Keyword

- subject: Ising machine
  schema: not_defined
- subject: Black-box optimization
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

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## Journal

- title: Applied Physics Reviews
  issn: '19319401'
  volume: '13'
  issue: '2'
  article_number: '021307'

## Conference



## Related item



## Funding

- identifier: JPMJPR24T8
  funder_name: Precursory Research for Embryonic Science and Technology
- identifier: JPMJCR21O2
  funder_name: Core Research for Evolutional Science and Technology
- identifier: JP23H05447
  funder_name: Japan Society for the Promotion of Science
- identifier: 25K07172
  funder_name: Japan Society for the Promotion of Science
- identifier: QST
  funder_name: Council for Science, Technology and Innovation
- identifier: JP- MJPF2221
  funder_name: Japan Science and Technology Agency
- identifier: JPNP23003
  funder_name: New Energy and Industrial Technology Development Organization

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## Fileset

- id: cbe29e11-b578-4dd1-8137-3c1ff28f07b4
  filename: 021307_1_5.0275450.pdf
  content_type: application/pdf
  size: 4153591
  md5: 1a45ed7c03a75238784a42bdda28db95

## Thumbnail

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filename: 021307_1_5.0275450.pdf