詳細つりあいを満たさないモンテカルロ法(最近の研究から)  [in Japanese] Monte Carlo Method without Detailed Balance(Current Topics)  [in Japanese]

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Abstract

マルコフ連鎖モンテカルロ法は積分計算の汎用的数値手法であり,様々な分野で必要不可欠な解析手段となっている.1953年の発明以来,この手法は詳細つりない条件の枠の中で発展を続けてきた.しかし詳細つりあいは必要条件ではない.最近の研究により,この条件を破ることで,推定値の収束が大幅に改善されることが明らかになってきた.本稿では,モンテカルロ法の原理について解説した後,我々の新しいアルゴリズムを紹介する.

The Markov chain Monte Carlo method is a versatile numerical method for integral computation and is being extensively applied across the various disciplines as a vital tool. Since the invention in 1953, this method is constantly evolving within the paradigm of the detailed balance. However, the detailed balance condition is not necessary at all. Our recent study has revealed that the convergence of estimate values is greatly improved by breaking this condition. In this report, we present our novel algorithm free from the detailed balance after introducing the Monte Carlo method.

Journal

  • Butsuri

    Butsuri 66(5), 370-374, 2011

    The Physical Society of Japan

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Codes

  • NII Article ID (NAID)
    110008661943
  • NII NACSIS-CAT ID (NCID)
    AN00196952
  • Text Lang
    JPN
  • Article Type
    REV
  • ISSN
    0029-0181
  • NDL Article ID
    11059914
  • NDL Source Classification
    ZM35(科学技術--物理学)
  • NDL Call No.
    Z15-13
  • Data Source
    CJP  NDL  NII-ELS  J-STAGE 
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