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F. Bucci

Researcher at University of Geneva

Publications -  520
Citations -  45259

F. Bucci is an academic researcher from University of Geneva. The author has contributed to research in topics: Large Hadron Collider & Lepton. The author has an hindex of 103, co-authored 510 publications receiving 43474 citations. Previous affiliations of F. Bucci include West University of Timișoara & Istanbul Technical University.

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Search for Flavor-Changing Neutral-Current Charm Decays

Bernard Aubert, +609 more
TL;DR: In this article, the authors search for rare FCNC charm decays of the form $X_c+\to h^+\llp, where X_c^+$ is a charm hadron, $h$ are a pion, kaon or proton, and $\ell^{(}{'}^{)}$ is an electron or a muon.
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Riccati-based solution to the optimal control of linear evolution equations with finite memory

TL;DR: In this article , the optimal control problem with quadratic functionals for a linear Volterra integro-differential equation in Hilbert spaces was studied, and a closed-loop form of the unique optimal control via certain operators that are shown to solve a coupled system of quad-ratic differential equations was obtained.
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Status of the NA62 ring imaging Cherenkov detector

TL;DR: The ring imaging Cherenkov detector of the NA62 experiment at the CERN SPS is a key element of particle identification in the NA 62 experimental strategy as mentioned in this paper, which fulfills different conditions: to distinguish pions from muons with a muon rejection factor of O(10 2 ) in the NE momentum range of operation, between 15 and 35 GeV/c.
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Physics beyond the standard model with kaons at NA62

Paolo Massarotti, +188 more
TL;DR: The NA62 experiment at CERN Super Proton Synchrotron was designed to measure BR(K+ → π+νv¯) with an in-fight technique, never used before for this measurement.
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Search for K+ decays to a lepton and invisible particles

Nicolas Lurkin, +225 more
TL;DR: The NA62 experiment at CERN reports searches for K + → e + N , K + + → µ + N and K+ → µ+ X decays, where N and X are massive invisible particles, using the 2016-2018 data set as mentioned in this paper .