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Joosep Pata

Researcher at California Institute of Technology

Publications -  748
Citations -  32013

Joosep Pata is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Large Hadron Collider & Lepton. The author has an hindex of 75, co-authored 606 publications receiving 26161 citations. Previous affiliations of Joosep Pata include University of Trento & ETH Zurich.

Papers
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Measurement of the azimuthal anisotropy of and mesons in PbPb collisions at sNN=5.02TeV

Albert M. Sirunyan, +2309 more
- 10 Aug 2021 - 
TL;DR: In this article, the second-order Fourier coefficients (v 2 ) characterizing the azimuthal distributions of and mesons produced in PbPb collisions at s NN = 5.02 TeV are studied.

Measurement of b hadron lifetimes in pp collisions at √s = 8 TeV

Albert M. Sirunyan, +2230 more
TL;DR: In this paper, the authors measured the lifetime of the B^0 meson in two decay modes, with contributions from different amounts of the heavy and light eigenstates, with a precision of 454.1 ± 1.4 and 443.8 ± 2.8, respectively.
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Measurements of triple-differential cross sections for inclusive isolated-photon+jet events in pp collisions at $\sqrt{s} =$ 8 TeV

Albert M. Sirunyan, +2278 more
TL;DR: Measurements are presented of the triple-differential cross section for inclusive isolated-photon+jet events in p p collisions at s = 8 TeV as a function of photon transverse momentum, photon pseudorapidity, and jet pseudorAPidity.
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Study of dijet events with a large rapidity gap between the two leading jets in pp collisions at s = 7 TeV

Albert M. Sirunyan, +2208 more
TL;DR: In this article, events with no charged particles produced between the two leading jets were studied in proton-proton collisions at $\sqrt{s}=7$ $\,\text {TeV}$.
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Machine Learning for Particle Flow Reconstruction at CMS

TL;DR: A possible evolution of particle flow towards heterogeneous computing platforms such as GPUs using a graph neural network is studied and the machine-learned PF model reconstructs particle candidates based on the full list of tracks and calorimeter clusters in the event.