| Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
|---|---|---|
| Article Number | 06019 | |
| Number of page(s) | 8 | |
| Section | T6 - Machine learning & analysis | |
| DOI | https://doi.org/10.1051/epjconf/201921406019 | |
| Published online | 17 September 2019 | |
https://doi.org/10.1051/epjconf/201921406019
Study of Neural Network Size Requirements for Approximating Functions Relevant to HEP
1
College of the Holy Cross
2
University of Notre Dame
* e-mail: jstietze@nd.edu
** e-mail: klannon@nd.edu
Published online: 17 September 2019
A new event data format has been designed and prototyped by the CMS collaboration to satisfy the needs of a large fraction of physics analyses (at least 50%) with a per event size of order 1 kB. This new format is more than a factor of 20 smaller than the MINIAOD format and contains only top level information typically used in the last steps of the analysis. The talk will review the current analysis strategy from the point of view of event format in CMS (both skims and formats such as RECO, AOD, MINIAOD, NANOAOD) and will describe the design guidelines for the new NANOAOD format.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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