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1.
Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning / Shanahan, Phiala (MIT) ; Terao, Kazuhiro (SLAC) ; Whiteson, Daniel (UC, Irvine) ; Aarts, Gert (Swansea U. ; ECT, Trento ; Fond. Bruno Kessler, Trento) ; Adelmann, Andreas (Northeastern U. ; PSI, Villigen) ; Akchurin, N. (Texas Tech.) ; Alexandru, Andrei (George Washington U. ; Maryland U.) ; Amram, Oz (Johns Hopkins U.) ; Andreassen, Anders (Google Inc.) ; Apresyan, Artur (Fermilab) et al.
The rapidly-developing intersection of machine learning (ML) with high-energy physics (HEP) presents both opportunities and challenges to our community. [...]
arXiv:2209.07559 ; FERMILAB-CONF-22-719-ND-PPD-QIS-SCD.
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Fermilab Library Server - eConf - Fulltext - Fulltext
2.
Snowmass2021 theory frontier white paper: Astrophysical and cosmological probes of dark matter / Boddy, Kimberly K. (Texas U.) ; Lisanti, Mariangela (Princeton U. ; Flatiron Inst., New York) ; McDermott, Samuel D. (Fermilab) ; Rodd, Nicholas L. (CERN) ; Weniger, Christoph (Amsterdam U. ; U. Amsterdam, GRAPPA) ; Ali-Haïmoud, Yacine (New York U., CCPP) ; Buschmann, Malte (Princeton U.) ; Cholis, Ilias (Oakland U.) ; Croon, Djuna (Durham U., IPPP) ; Erickcek, Adrienne L. (North Carolina U.) et al.
While astrophysical and cosmological probes provide a remarkably precise and consistent picture of the quantity and general properties of dark matter, its fundamental nature remains one of the most significant open questions in physics. Obtaining a more comprehensive understanding of dark matter within the next decade will require overcoming a number of theoretical challenges: the groundwork for these strides is being laid now, yet much remains to be done. [...]
arXiv:2203.06380; FERMILAB-CONF-22-151-T.- 2022-06-22 - 27 p. - Published in : JHEAp 35 (2022) 112-138 Fulltext: jt - PDF; 2203.06380 - PDF; Fulltext from Publisher: PDF; External links: Fermilab Library Server; eConf
In : 2021 Snowmass Summer Study, Seattle, WA, United States, 11 - 20 July 2021, pp.112-138
3.
Snowmass2021 Cosmic Frontier White Paper: Puzzling Excesses in Dark Matter Searches and How to Resolve Them / Leane, Rebecca K. (SLAC ; KIPAC, Menlo Park) ; Shin, Seodong (Jeonbuk Natl. U.) ; Yang, Liang (UC, San Diego) ; Adhikari, Govinda (UC, San Diego) ; Alhazmi, Haider (Jazan U.) ; Aramaki, Tsuguo (Northeastern U.) ; Baxter, Daniel (Fermilab) ; Calore, Francesca (Annecy, LAPTH) ; Caputo, Regina (NASA, Goddard) ; Cholis, Ilias (Oakland U.) et al.
Intriguing signals with excesses over expected backgrounds have been observed in many astrophysical and terrestrial settings, which could potentially have a dark matter origin. [...]
arXiv:2203.06859 ; FERMILAB-CONF-22-191-PPD-T.
- 57 p.
Fermilab Library Server - eConf - Fulltext - Fulltext
4.
Dark Matter Science in the Era of LSST / Bechtol, Keith (Wisconsin U., Madison) ; Drlica-Wagner, Alex (Chicago U., Astron. Astrophys. Ctr. ; Chicago U., KICP ; Fermilab) ; Abazajian, Kevork N. (UC, Irvine) ; Abidi, Muntazir (Cambridge U., DAMTP) ; Adhikari, Susmita (KIPAC, Menlo Park) ; Ali-Haïmoud, Yacine (New York U.) ; Annis, James (Fermilab) ; Ansarinejad, Behzad (Durham U.) ; Armstrong, Robert (LLNL, Livermore) ; Asorey, Jacobo (Queensland U. ; Unlisted, AU) et al.
Astrophysical observations currently provide the only robust, empirical measurements of dark matter. [...]
arXiv:1903.04425.
- 2019. - 11 p.
Fulltext

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