5,746 research outputs found
Measurements of top quark properties in top pair production and decay at the LHC using the CMS detector
AbstractMeasurements are presented of the properties of top quarks in pair production and decay from proton-proton collisions at the LHC. The data were collected at centre-of-mass energies of 7 and 8 TeV by the CMS experiment during the years 2011 and 2012. The top quark-antiquark charge asymmetry is measured using the difference of the absolute rapidities of the reconstructed top and anti-top kinematics, as well as from distributions of the top quark decay products. The measurements are performed in the decay channels of the tt‾ pair into both one and two leptons in the final state. The polarization of top quarks and top pair spin correlations are measured from the angular distributions of top quark decay products. The W-boson helicity fractions and angular asymmetries are extracted and limits on anomalous contributions to the Wtb vertex are determined. The flavor content in top-quark pair events is measured using the fraction of top quarks decaying into a W-boson and a b-quark relative to all top quark decays, R=B(t→Wb)/B(t→Wq), and the result is used to determine the CKM matrix element Vtb as well as the width of the top quark resonance. All of the results are found to be in good agreement with standard model predictions
FPGA-accelerated machine learning inference as a service for particle physics computing
New heterogeneous computing paradigms on dedicated hardware with increased
parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting
solutions with large potential gains. The growing applications of machine
learning algorithms in particle physics for simulation, reconstruction, and
analysis are naturally deployed on such platforms. We demonstrate that the
acceleration of machine learning inference as a web service represents a
heterogeneous computing solution for particle physics experiments that
potentially requires minimal modification to the current computing model. As
examples, we retrain the ResNet-50 convolutional neural network to demonstrate
state-of-the-art performance for top quark jet tagging at the LHC and apply a
ResNet-50 model with transfer learning for neutrino event classification. Using
Project Brainwave by Microsoft to accelerate the ResNet-50 image classification
model, we achieve average inference times of 60 (10) milliseconds with our
experimental physics software framework using Brainwave as a cloud (edge or
on-premises) service, representing an improvement by a factor of approximately
30 (175) in model inference latency over traditional CPU inference in current
experimental hardware. A single FPGA service accessed by many CPUs achieves a
throughput of 600--700 inferences per second using an image batch of one,
comparable to large batch-size GPU throughput and significantly better than
small batch-size GPU throughput. Deployed as an edge or cloud service for the
particle physics computing model, coprocessor accelerators can have a higher
duty cycle and are potentially much more cost-effective.Comment: 16 pages, 14 figures, 2 table
Two-particle Momentum Correlation in Jets at the Tevatron
Presented are the measurements of two-particle momentum correlations in jets produced in p-pbar collisions at center of mass frame energy 1.96 TeV. Studies were performed for charged particles within a restricted opening angle of 0.5 rad around the jet axis and for dijet events with various dijet masses. Comparison of the experimental results to the theoretical predictions obtained for partons within the framework of the resummed perturbative QCD (Next-to-Leading Log Approximation) shows that the parton momentum correlations do survive the hadronization stage of jet fragmentation, thus, giving further support to the hypothesis of Local Parton-Hadron Duality
Operational experience, improvements, and performance of the CDF Run II silicon vertex detector
The Collider Detector at Fermilab (CDF) pursues a broad physics program at
Fermilab's Tevatron collider. Between Run II commissioning in early 2001 and
the end of operations in September 2011, the Tevatron delivered 12 fb-1 of
integrated luminosity of p-pbar collisions at sqrt(s)=1.96 TeV. Many physics
analyses undertaken by CDF require heavy flavor tagging with large charged
particle tracking acceptance. To realize these goals, in 2001 CDF installed
eight layers of silicon microstrip detectors around its interaction region.
These detectors were designed for 2--5 years of operation, radiation doses up
to 2 Mrad (0.02 Gy), and were expected to be replaced in 2004. The sensors were
not replaced, and the Tevatron run was extended for several years beyond its
design, exposing the sensors and electronics to much higher radiation doses
than anticipated. In this paper we describe the operational challenges
encountered over the past 10 years of running the CDF silicon detectors, the
preventive measures undertaken, and the improvements made along the way to
ensure their optimal performance for collecting high quality physics data. In
addition, we describe the quantities and methods used to monitor radiation
damage in the sensors for optimal performance and summarize the detector
performance quantities important to CDF's physics program, including vertex
resolution, heavy flavor tagging, and silicon vertex trigger performance.Comment: Preprint accepted for publication in Nuclear Instruments and Methods
A (07/31/2013
A high-performance track fitter for use in ultra-fast electronics
This article describes a new charged-particle track fitting algorithm
designed for use in high-speed electronics applications such as hardware-based
triggers in high-energy physics experiments. Following a novel technique
designed for fast electronics, the positions of the hits on the detector are
transformed before being passed to a linearized track parameter fit. This
transformation results in fitted track parameters with a very linear dependence
on the hit positions. The approach is demonstrated in a representative detector
geometry based on the CMS detector at the Large Hadron Collider. The fit is
implemented in FPGA chips and optimized for track fitting throughput and
obtains excellent track parameter performance. Such an algorithm is potentially
useful in any high-speed track-fitting application
Fast convolutional neural networks on FPGAs with hls4ml
We introduce an automated tool for deploying ultra low-latency, low-power
deep neural networks with convolutional layers on FPGAs. By extending the
hls4ml library, we demonstrate an inference latency of s using
convolutional architectures, targeting microsecond latency applications like
those at the CERN Large Hadron Collider. Considering benchmark models trained
on the Street View House Numbers Dataset, we demonstrate various methods for
model compression in order to fit the computational constraints of a typical
FPGA device used in trigger and data acquisition systems of particle detectors.
In particular, we discuss pruning and quantization-aware training, and
demonstrate how resource utilization can be significantly reduced with little
to no loss in model accuracy. We show that the FPGA critical resource
consumption can be reduced by 97% with zero loss in model accuracy, and by 99%
when tolerating a 6% accuracy degradation.Comment: 18 pages, 18 figures, 4 table
Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron
We study the underlying event in proton-antiproton collisions by examining
the behavior of charged particles (transverse momentum pT > 0.5 GeV/c,
pseudorapidity |\eta| < 1) produced in association with large transverse
momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the
Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV
center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan
production) or the leading jet (in high-pT jet production) in each event to
define three regions of \eta-\phi space; toward, away, and transverse, where
\phi is the azimuthal scattering angle. For Drell-Yan production (excluding the
leptons) both the toward and transverse regions are very sensitive to the
underlying event. In high-pT jet production the transverse region is very
sensitive to the underlying event and is separated into a MAX and MIN
transverse region, which helps separate the hard component (initial and
final-state radiation) from the beam-beam remnant and multiple parton
interaction components of the scattering. The data are corrected to the
particle level to remove detector effects and are then compared with several
QCD Monte-Carlo models. The goal of this analysis is to provide data that can
be used to test and improve the QCD Monte-Carlo models of the underlying event
that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.
Search for the Higgs boson in events with missing transverse energy and b quark jets produced in proton-antiproton collisions at s**(1/2)=1.96 TeV
We search for the standard model Higgs boson produced in association with an
electroweak vector boson in events with no identified charged leptons, large
imbalance in transverse momentum, and two jets where at least one contains a
secondary vertex consistent with the decay of b hadrons. We use ~1 fb-1
integrated luminosity of proton-antiproton collisions at s**(1/2)=1.96 TeV
recorded by the CDF II experiment at the Tevatron. We find 268 (16) single
(double) b-tagged candidate events, where 248 +/- 43 (14.4 +/- 2.7) are
expected from standard model background processes. We place 95% confidence
level upper limits on the Higgs boson production cross section for several
Higgs boson masses ranging from 110 GeV/c2 to 140 GeV/c2. For a mass of 115
GeV/c2 the observed (expected) limit is 20.4 (14.2) times the standard model
prediction.Comment: 8 pages, 2 figures, submitted to Phys. Rev. Let
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