973 research outputs found
Search for R-parity violating Supersymmetry using the CMS detector
In this talk, the latest results from CMS on R-parity violating Supersymmetry
are reviewed. We present results using up to 20/fb of data from the 8 TeV LHC
run of 2012. Interpretations of the experimental results in terms of production
of squarks, gluinos, charginos, neutralinos, and sleptons within R-parity
violating susy models are presented.Comment: talk presented at the LHCP 2013 Conference in Barcelona, Spain, May
13-18th, 201
Searching for Stopped Gluinos at CMS
We describe plans for a search for long-lived particles which will become
stopped by the CMS detector. We will look for the subsequent decay of these
particles during time intervals where there are no collisions in CMS:
during gaps between crossings in the LHC beam structure, and during inter-fill
periods between the beam being dumped and re-injection. Such long living
particles decays will be recorded with dedicated calorimeter triggers. For
models predicting these particles, such as split-susy gluinos, the large
cross-section combined with good stopping power of CMS, yields a significant
number of triggerable decays. If LHC instantaneous luminosity approaches 10^32
cm^-2 s^-1 in 2009-10, 5-sigma significance can be established in a matter of
days, since these decays occur on top of a negligible background.
Due to limited size, this paper concentrates on main idea and expected
results. More details are available in
https://twiki.cern.ch/twiki/bin/view/CMS/PhysicsResults.Comment: Talk given at the SUSY'09 conference, Boston, USA, June 5-10, 2009. 4
pages, 2 figure
Generative Adversarial Networks for LHCb Fast Simulation
LHCb is one of the major experiments operating at the Large Hadron Collider
at CERN. The richness of the physics program and the increasing precision of
the measurements in LHCb lead to the need of ever larger simulated samples.
This need will increase further when the upgraded LHCb detector will start
collecting data in the LHC Run 3. Given the computing resources pledged for the
production of Monte Carlo simulated events in the next years, the use of fast
simulation techniques will be mandatory to cope with the expected dataset size.
In LHCb generative models, which are nowadays widely used for computer vision
and image processing are being investigated in order to accelerate the
generation of showers in the calorimeter and high-level responses of Cherenkov
detector. We demonstrate that this approach provides high-fidelity results
along with a significant speed increase and discuss possible implication of
these results. We also present an implementation of this algorithm into LHCb
simulation software and validation tests.Comment: Proceedings for 24th International Conference on Computing in High
Energy and Nuclear Physic
Search for Stopped Gluinos in pp collisions at sqrt(s)=7 TeV at CMS
The results of the first search for long-lived gluinos produced in 7 TeV pp
collisions at the CERN Large Hadron Collider are presented. The search looks
for evidence of long-lived particles that stop in the CMS detector and decay in
the quiescent periods between beam crossings. In a dataset with a peak
instantaneous luminosity of 10^-32 /cm^2/s, an integrated luminosity of 10/pb,
and a search interval corresponding to 62 hours of LHC operation, no
significant excess above background was observed. Limits at the 95% confidence
level on gluino pair production over 13 orders of magnitude of gluino lifetime
are set. For a mass difference (m_gluino-m_neutralino)>100 GeV/c^2, and
assuming BR(gluino-> g neutralino)=100%, m_gluino < 370 GeV/c^2 are excluded
for lifetimes from 10^-6 s to 1000 s.Comment: 4 pages, to appear in the proceedings for the XXX Physics in
Collision International Symposium, Karlsruhe, Germany, September 1-4, 201
Cherenkov Detectors Fast Simulation Using Neural Networks
We propose a way to simulate Cherenkov detector response using a generative
adversarial neural network to bypass low-level details. This network is trained
to reproduce high level features of the simulated detector events based on
input observables of incident particles. This allows the dramatic increase of
simulation speed. We demonstrate that this approach provides simulation
precision which is consistent with the baseline and discuss possible
implications of these results.Comment: In proceedings of 10th International Workshop on Ring Imaging
Cherenkov Detector
Generative Models for Fast Calorimeter Simulation.LHCb case
Simulation is one of the key components in high energy physics. Historically
it relies on the Monte Carlo methods which require a tremendous amount of
computation resources. These methods may have difficulties with the expected
High Luminosity Large Hadron Collider (HL LHC) need, so the experiment is in
urgent need of new fast simulation techniques. We introduce a new Deep Learning
framework based on Generative Adversarial Networks which can be faster than
traditional simulation methods by 5 order of magnitude with reasonable
simulation accuracy. This approach will allow physicists to produce a big
enough amount of simulated data needed by the next HL LHC experiments using
limited computing resources.Comment: Proceedings of the presentation at CHEP 2018 Conferenc
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