OASIS: Optimal Analysis-Specific Importance Sampling for event generation

Matchev, Konstantin T.; Shyamsundar, Prasanth

doi:10.21468/SciPostPhys.10.2.034

SciPost Physics

OASIS: Optimal Analysis-Specific Importance Sampling for event generation

Konstantin T. Matchev, Prasanth Shyamsundar

SciPost Phys. 10, 034 (2021) · published 15 February 2021

doi: 10.21468/SciPostPhys.10.2.034
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Abstract

We propose a technique called Optimal Analysis-Specific Importance Sampling (OASIS) to reduce the number of simulated events required for a high-energy experimental analysis to reach a target sensitivity. We provide recipes to obtain the optimal sampling distributions which preferentially focus the event generation on the regions of phase space with high utility to the experimental analyses. OASIS leads to a conservation of resources at all stages of the Monte Carlo pipeline, including full-detector simulation, and is complementary to approaches which seek to speed-up the simulation pipeline.

TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhys.10.2.034
TI  - OASIS: Optimal Analysis-Specific Importance Sampling for event generation
PY  - 2021/02/15
UR  - https://scipost.org/SciPostPhys.10.2.034
JF  - SciPost Physics
JA  - SciPost Phys.
VL  - 10
IS  - 2
SP  - 034
A1  - Matchev, Konstantin T.
AU  - Shyamsundar, Prasanth
AB  - We propose a technique called Optimal Analysis-Specific Importance Sampling (OASIS) to reduce the number of simulated events required for a high-energy experimental analysis to reach a target sensitivity. We provide recipes to obtain the optimal sampling distributions which preferentially focus the event generation on the regions of phase space with high utility to the experimental analyses. OASIS leads to a conservation of resources at all stages of the Monte Carlo pipeline, including full-detector simulation, and is complementary to approaches which seek to speed-up the simulation pipeline.
ER  -

@Article{10.21468/SciPostPhys.10.2.034,
	title={{OASIS: Optimal Analysis-Specific Importance Sampling for event generation}},
	author={Konstantin T. Matchev and Prasanth Shyamsundar},
	journal={SciPost Phys.},
	volume={10},
	pages={034},
	year={2021},
	publisher={SciPost},
	doi={10.21468/SciPostPhys.10.2.034},
	url={https://scipost.org/10.21468/SciPostPhys.10.2.034},
}

Cited by 7

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¹ Konstantin T. Matchev,
¹ Prasanth Shyamsundar

¹ University of Florida [UF]

Funder for the research work leading to this publication

United States Department of Energy [DOE]