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2024 Snook Prize Problem: Ergodic Algorithms' Mixing Rates.
- Source :
- Computational Methods in Science & Technology; 2023, Vol. 29 Issue 1-4, p65-69, 4p
- Publication Year :
- 2023
-
Abstract
- In 1984 Shuichi Nosé invented an isothermal mechanics designed to generate Gibbs' canonical distribution for the coordinates {q} and momenta {p} of classical N-body systems [1, 2]. His approach introduced an additional timescaling variable s that could speed up or slow down the {q, p} motion in such a way as to generate the Gaussian velocity distribution ∝ e-p2/2mkT and the corresponding potential distribution, ∝ e-F(q)/kT. (For convenience here we choose Boltzmann's constant k and the particle massmboth equal to unity.) SoonWilliam Hoover pointed out that Nosé's approach fails for the simple harmonic oscillator [3]. Rather than generating the entire Gaussian canonical oscillator distribution, the Nosé-Hoover approach, which includes an additional friction coefficient ζ with distribution e-ζ2/2/v 2p, generates only a modest fractal chaotic sea, filling a small percentage of the canonical (q, p, ζ) distribution. In the decade that followed this thermostatted work a handful of ergodic algorithms were developed in both three- and four-dimensional phase spaces. These new approaches generated the entire canonical distribution, without holes. The 2024 Snook Prize problem is to study the efficiency of several such algorithms, such as the five ergodic examples described here, so as to assess their relative usefulness in attaining the canonical steady state for the harmonic oscillator. The 2024 Prize rewarding the best assessment is United States $1000, half of it a gift from ourselves with the balance from the Pozna'n Supercomputing and Networking Center. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15050602
- Volume :
- 29
- Issue :
- 1-4
- Database :
- Complementary Index
- Journal :
- Computational Methods in Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- 174964575
- Full Text :
- https://doi.org/10.12921/cmst.2023.0000022