SwePub
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Tosi Mia) "

Sökning: WFRF:(Tosi Mia)

  • Resultat 1-2 av 2
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Abercrombie, Daniel, et al. (författare)
  • Dark Matter benchmark models for early LHC Run-2 Searches : Report of the ATLAS/CMS Dark Matter Forum
  • 2020
  • Ingår i: Physics of the Dark Universe. - : Elsevier BV. - 2212-6864. ; 27
  • Tidskriftsartikel (refereegranskat)abstract
    • This document is the final report of the ATLAS-CMS Dark Matter Forum, a forum organized by the ATLAS and CMS collaborations with the participation of experts on theories of Dark Matter, to select a minimal basis set of dark matter simplified models that should support the design of the early LHC Run-2 searches. A prioritized, compact set of benchmark models is proposed, accompanied by studies of the parameter space of these models and a repository of generator implementations. This report also addresses how to apply the Effective Field Theory formalism for collider searches and present the results of such interpretations.
  •  
2.
  • Dorigo, Tommaso, et al. (författare)
  • Toward the end-to-end optimization of particle physics instruments with differentiable programming
  • 2023
  • Ingår i: Reviews in Physics. - 2405-4283. ; 10
  • Forskningsöversikt (refereegranskat)abstract
    • The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, “experience-driven” layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized through a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters. In this white paper, we lay down our plans for the design of a modular and versatile modeling tool for the end-to-end optimization of complex instruments for particle physics experiments as well as industrial and medical applications that share the detection of radiation as their basic ingredient. We consider a selected set of use cases to highlight the specific needs of different applications.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-2 av 2

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy