27,015 research outputs found
The artificial retina processor for track reconstruction at the LHC crossing rate
We present results of an R&D study for a specialized processor capable of
precisely reconstructing, in pixel detectors, hundreds of charged-particle
tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel
pattern-recognition algorithm, inspired by studies of the processing of visual
images by the brain as it happens in nature, and describe in detail an
efficient hardware implementation in high-speed, high-bandwidth FPGA devices.
This is the first detailed demonstration of reconstruction of offline-quality
tracks at 40 MHz and makes the device suitable for processing Large Hadron
Collider events at the full crossing frequency.Comment: 4th draft of WIT proceedings modified according to JINST referee's
comments. 10 pages, 6 figures, 2 table
Theoretical and computational analysis of second- and third-harmonic generation in periodically patterned graphene and transition-metal dichalcogenide monolayers
Remarkable optical and electrical properties of two-dimensional (2D)
materials, such as graphene and transition-metal dichalcogenide (TMDC)
monolayers, offer vast technological potential for novel and improved
optoelectronic nanodevices, many of which relying on nonlinear optical effects
in these 2D materials. This article introduces a highly effective numerical
method for efficient and accurate description of linear and nonlinear optical
effects in nanostructured 2D materials embedded in periodic photonic structures
containing regular three-dimensional (3D) optical materials, such as
diffraction gratings and periodic metamaterials. The proposed method builds
upon the rigorous coupled-wave analysis and incorporates the nonlinear optical
response of 2D materials by means of modified electromagnetic boundary
conditions. This allows one to reduce the mathematical framework of the
numerical method to an inhomogeneous scattering matrix formalism, which makes
it more accurate and efficient than previously used approaches. An overview of
linear and nonlinear optical properties of graphene and TMDC monolayers is
given and the various features of the corresponding optical spectra are
explored numerically and discussed. To illustrate the versatility of our
numerical method, we use it to investigate the linear and nonlinear
multiresonant optical response of 2D-3D heteromaterials for enhanced and
tunable second- and third-harmonic generation. In particular, by employing a
structured 2D material optically coupled to a patterned slab waveguide, we
study the interplay between geometric resonances associated to guiding modes of
periodically patterned slab waveguides and plasmon or exciton resonances of 2D
materials.Comment: 28 pages, 21 figure
A Specialized Processor for Track Reconstruction at the LHC Crossing Rate
We present the results of an R&D study of a specialized processor capable of
precisely reconstructing events with hundreds of charged-particle tracks in
pixel detectors at 40 MHz, thus suitable for processing LHC events at the full
crossing frequency. For this purpose we design and test a massively parallel
pattern-recognition algorithm, inspired by studies of the processing of visual
images by the brain as it happens in nature. We find that high-quality tracking
in large detectors is possible with sub-s latencies when this algorithm is
implemented in modern, high-speed, high-bandwidth FPGA devices. This opens a
possibility of making track reconstruction happen transparently as part of the
detector readout.Comment: Presented by G.Punzi at the conference on "Instrumentation for
Colliding Beam Physics" (INSTR14), 24 Feb to 1 Mar 2014, Novosibirsk, Russia.
Submitted to JINST proceeding
Practical Gauss-Newton Optimisation for Deep Learning
We present an efficient block-diagonal ap- proximation to the Gauss-Newton
matrix for feedforward neural networks. Our result- ing algorithm is
competitive against state- of-the-art first order optimisation methods, with
sometimes significant improvement in optimisation performance. Unlike
first-order methods, for which hyperparameter tuning of the optimisation
parameters is often a labo- rious process, our approach can provide good
performance even when used with default set- tings. A side result of our work
is that for piecewise linear transfer functions, the net- work objective
function can have no differ- entiable local maxima, which may partially explain
why such transfer functions facilitate effective optimisation.Comment: ICML 201
TPC tracking and particle identification in high-density environment
Track finding and fitting algorithm in the ALICE Time projection chamber
(TPC) based on Kalman-filtering is presented. Implementation of particle
identification (PID) using d/d measurement is discussed. Filtering and
PID algorithm is able to cope with non-Gaussian noise as well as with ambiguous
measurements in a high-density environment. The occupancy can reach up to 40%
and due to the overlaps, often the points along the track are lost and others
are significantly displaced. In the present algorithm, first, clusters are
found and the space points are reconstructed. The shape of a cluster provides
information about overlap factor. Fast spline unfolding algorithm is applied
for points with distorted shapes. Then, the expected space point error is
estimated using information about the cluster shape and track parameters.
Furthermore, available information about local track overlap is used. Tests are
performed on simulation data sets to validate the analysis and to gain
practical experience with the algorithm.Comment: 9 pages, 5 figure
Hybridizing Non-dominated Sorting Algorithms: Divide-and-Conquer Meets Best Order Sort
Many production-grade algorithms benefit from combining an asymptotically
efficient algorithm for solving big problem instances, by splitting them into
smaller ones, and an asymptotically inefficient algorithm with a very small
implementation constant for solving small subproblems. A well-known example is
stable sorting, where mergesort is often combined with insertion sort to
achieve a constant but noticeable speed-up.
We apply this idea to non-dominated sorting. Namely, we combine the
divide-and-conquer algorithm, which has the currently best known asymptotic
runtime of , with the Best Order Sort algorithm, which
has the runtime of but demonstrates the best practical performance
out of quadratic algorithms.
Empirical evaluation shows that the hybrid's running time is typically not
worse than of both original algorithms, while for large numbers of points it
outperforms them by at least 20%. For smaller numbers of objectives, the
speedup can be as large as four times.Comment: A two-page abstract of this paper will appear in the proceedings
companion of the 2017 Genetic and Evolutionary Computation Conference (GECCO
2017
Massively Parallel Computing and the Search for Jets and Black Holes at the LHC
Massively parallel computing at the LHC could be the next leap necessary to
reach an era of new discoveries at the LHC after the Higgs discovery.
Scientific computing is a critical component of the LHC experiment, including
operation, trigger, LHC computing GRID, simulation, and analysis. One way to
improve the physics reach of the LHC is to take advantage of the flexibility of
the trigger system by integrating coprocessors based on Graphics Processing
Units (GPUs) or the Many Integrated Core (MIC) architecture into its server
farm. This cutting edge technology provides not only the means to accelerate
existing algorithms, but also the opportunity to develop new algorithms that
select events in the trigger that previously would have evaded detection. In
this article we describe new algorithms that would allow to select in the
trigger new topological signatures that include non-prompt jet and black
hole--like objects in the silicon tracker.Comment: 15 pages, 11 figures, submitted to NIM
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