Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
139 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Lamarr: LHCb ultra-fast simulation based on machine learning models deployed within Gauss (2303.11428v3)

Published 20 Mar 2023 in hep-ex, cs.LG, and physics.ins-det

Abstract: About 90% of the computing resources available to the LHCb experiment has been spent to produce simulated data samples for Run 2 of the Large Hadron Collider at CERN. The upgraded LHCb detector will be able to collect larger data samples, requiring many more simulated events to analyze the data to be collected in Run 3. Simulation is a key necessity of analysis to interpret signal, reject background and measure efficiencies. The needed simulation will far exceed the pledged resources, requiring an evolution in technologies and techniques to produce these simulated data samples. In this contribution, we discuss Lamarr, a Gaudi-based framework to speed-up the simulation production parameterizing both the detector response and the reconstruction algorithms of the LHCb experiment. Deep Generative Models powered by several algorithms and strategies are employed to effectively parameterize the high-level response of the single components of the LHCb detector, encoding within neural networks the experimental errors and uncertainties introduced in the detection and reconstruction phases. Where possible, models are trained directly on real data, statistically subtracting any background components by applying appropriate reweighing procedures. Embedding Lamarr in the general LHCb Gauss Simulation framework allows to combine its execution with any of the available generators in a seamless way. The resulting software package enables a simulation process independent of the detailed simulation used to date.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (28)
  1. Alves Jr A A et al. (LHCb) 2008 JINST 3 S08005
  2. Aaij R et al. (LHCb) 2015 Int. J. Mod. Phys. A 30 1530022 (Preprint 1412.6352)
  3. Clemencic M et al. (LHCb) 2011 J. Phys. Conf. Ser. 331 032023
  4. Barrand G et al. 2001 Comput. Phys. Commun. 140 45–55
  5. Sjostrand T, Mrenna S and Skands P Z 2008 Comput. Phys. Commun. 178 852–867 (Preprint 0710.3820)
  6. Lange D J 2001 Nucl. Instrum. Meth. A 462 152–155
  7. Allison J et al. 2006 IEEE Trans. Nucl. Sci. 53 270
  8. Mazurek M, Corti G and Müller D 2021 Comput. Inform. 40 815–832 (Preprint 2112.04789)
  9. Mazurek M, Clemencic M and Corti G 2023 PoS ICHEP2022 225
  10. Rama M and Vitali G (LHCb) 2019 EPJ Web Conf. 214 02040
  11. Maevskiy A et al. (LHCb) 2020 J. Phys. Conf. Ser. 1525 012097 (Preprint 1905.11825)
  12. Ratnikov F and Rogachev A 2021 EPJ Web Conf. 251 03043
  13. Rogachev A and Ratnikov F 2023 J. Phys. Conf. Ser. 2438 012086 (Preprint 2207.06329)
  14. Anderlini L et al. 2023 PoS ICHEP2022 233
  15. Müller D et al. 2018 Eur. Phys. J. C 78 1009 (Preprint 1810.10362)
  16. Ratnikov F et al. 2023 Nucl. Instrum. Meth. A 1046 167591
  17. Anderlini L et al. (LHCb) 2023 J. Phys. Conf. Ser. 2438 012088 (Preprint 2210.09767)
  18. Anderlini L et al. (LHCb) 2023 J. Phys. Conf. Ser. 2438 012130 (Preprint 2204.09947)
  19. Goodfellow I et al. 2014 NeurIPS’14 pp 2672–2680 (Preprint 1406.2661)
  20. Mirza M and Osindero S 2014 (Preprint 1411.1784)
  21. Graziani G et al. 2022 JINST 17 P02018 (Preprint 2110.10259)
  22. Mariani S et al. 2023 J. Phys. Conf. Ser. 2438 012107
  23. He K et al. 2016 CVPR’16 pp 770–778 (Preprint 1512.03385)
  24. Terjék D 2020 ICLR’20 (Preprint 1907.05681)
  25. Aaij R et al. 2019 EPJ Tech. Instrum. 6 1 (Preprint 1803.00824)
  26. Borisyak M and Kazeev N 2019 JINST 14 P08020 (Preprint 1905.11719)
  27. Anderlini L and Barbetti M 2022 PoS CompTools2021 034
  28. Barbetti M and Anderlini L 2023 ACAT’22 (Preprint 2301.05522)
Citations (3)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com