A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications
Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophy...
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
13 May 2021
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| In: |
Journal of high energy physics
Year: 2021, Heft: 5, Pages: 1-44 |
| ISSN: | 1029-8479 |
| DOI: | 10.1007/JHEP05(2021)108 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/JHEP05(2021)108
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| Verfasserangaben: | The DarkMachines High Dimensional Sampling Group, Csaba Balázs, Melissa van Beekveld, Sascha Caron, Barry M. Dillon, Ben Farmer, Andrew Fowlie, Eduardo C. Garrido-Merchán, Will Handley, Luc Hendriks, Guðlaugur Jóhannesson, Adam Leinweber, Judita Mamužić, Gregory D. Martinez, Sydney Otten, Roberto Ruiz de Austri, Pat Scott, Zachary Searle, Bob Stienen, Joaquin Vanschoren, and Martin White |
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| 245 | 0 | 2 | |a A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications |c The DarkMachines High Dimensional Sampling Group, Csaba Balázs, Melissa van Beekveld, Sascha Caron, Barry M. Dillon, Ben Farmer, Andrew Fowlie, Eduardo C. Garrido-Merchán, Will Handley, Luc Hendriks, Guðlaugur Jóhannesson, Adam Leinweber, Judita Mamužić, Gregory D. Martinez, Sydney Otten, Roberto Ruiz de Austri, Pat Scott, Zachary Searle, Bob Stienen, Joaquin Vanschoren, and Martin White |
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| 520 | |a Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms. | ||
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