Computer algebra is one of a key tools in modern physics research. In this talk I will give an overview of the main mathematical and programming concepts that lie in the basis of modern computer algebra tools and how they are applied for solving modern theoretical physics and some engineering problems. I will also give a sketch overview of modern computer algebra software, including general...
The extremely low flux of ultra-high energy cosmic rays
(UHECR) makes their direct observation by orbital experiments
practically impossible. For this reason all current and planning UHECR
experiments detect cosmic rays indirectly observing extensive air
showers (EAS) initiated by cosmic ray particles in the atmosphere.
Various types of shower observables are analysed in modern...
X-ray Free Electron Lasers (XFELs) are among the most complex accelerator projects in the world today. With large parameter spaces, sensitive dependence on beam quality, huge data rates, and challenging machine protection, there are diverse opportunities to apply machine learning (ML) to XFEL operation. This talk will summarize promising ML methods and highlight recent examples of successful...
We present a novel general Boltzmann machine with continuous visible
and discrete integer valued hidden states, yielding a parametric
density function involving a ratio of Riemann-Theta functions. After a
brief overview of the theory required to define this new ML
architecture, we show how the conditional expectation of a hidden
state for given visible states can be used as activation function...
When it comes to number-crunching, C++ is at the core of HENP’s software. But while C++17 is old news, many of us did not get to use it yet. And why would we? This presentation introduces some of the main reasons to move to C++17 - focusing on performant, readable code and robust interfaces.
Where C++17 has many new features that help, C++20 might come as “your next C++11”, a major step...
We report on multi-loop integral computations executed on a
PEZY/Exascaler large-scale (immersion cooling) computing system.
The programming model requires a host program written in C++
with an OpenCL kernel. However the kernel can be generated by
the Goose compiler interface, which allows parallelizing loops
according to compiler directives. As an advantage, the executable
derived from a...
In the High-Luminosity Large Hadron Collider (HL-LHC), one of the most challenging computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction. The methods currently in use at the LHC are based on the Kalman filter. Such methods have shown to be robust and to provide good physics performance, both in the trigger and offline. In order to...
NANOAOD is an event data format that has recently been commissioned by the CMS Collaboration to serve the needs of a substantial fraction of its physics analyses. The new format is about 20 times more compact than the MINIAOD format and only includes high level physics object information. NANOAOD is easily customisable for development activities, and supports standardised routines for content...
PyROOT is the name of ROOT’s Python bindings, which allow to access all the ROOT functionality implemented in C++ from Python. Thanks to the ROOT type system and the Cling C++ interpreter, PyROOT creates Python proxies for C++ entities on the fly, thus avoiding to generate static bindings beforehand.
PyROOT is in the process of being enhanced and modernised to meet the demands of the HEP...
The high-energy community recently witnessed the first attempts at leveraging machine (deep) learning techniques for improving the efficiency of the numerical Monte-Carlo integrations that lie at the core of most high-energy physics simulations.
The first part of my talk will characterise the various type of integrations necessary in these simulations as well as the type of improvements that...
To address the unprecedented scale of HL-LHC data, the HEP.TrkX project has been investigating a variety of machine learning approaches to particle track reconstruction. The most promising of these solutions, a graph neural network, processes the event as a graph that connects track measurements (detector hits corresponding to nodes) with candidate line segments between the hits (corresponding...
Massively parallel simulations generate increasing volumes of large data, whose exploitation requires large storage resources, efficient network and increasingly large post-processing facilities. In the coming era of exascale computations, there is an emerging need for new data analysis and visualization strategies.
Data manipulation, during the simulation and after, considerably slows down...
During the past two years ROOT's analysis tools underwent a major renovation,
embracing a declarative approach.
This contribution explores the most recent developments of the implementation of
such approach, some real-life examples from LHC experiments as well as present
and future R&D lines.
After an introduction of the tool offering access to declarative analysis,
RDataFrame, the newly...
Machine learning methods are integrated into the pipelined first level track trigger of the upgraded flavor physics experiment Belle II in Tsukuba, Japan. The novel triggering techniques cope with the severe background conditions coming along with the upgrade of the instantaneous luminosity by a factor of 40 to $\mathcal{L} = 8 \times 10^{35} \text{cm}^{−2} \text{s}^{−1}$. Using the precise...
For two decades, ROOT brought its own graphics system abstraction based
on a graphics model inspired by the popular graphics systems available
at that time. (X11, OpenGL, Cocoa ...)
With the emergence of modern C++ and recent graphics systems based on client/server
models, it was time to redefined completely ROOT graphics.
This has been been done in the context of ROOT 7 which provides the...
With the upgrade of the LHC to high luminosity, an increased rate of collisions will place a higher computational burden on track reconstruction algorithms. Typical algorithms such as the Kalman Filter and Hough-like Transformation scale worse than quadratically. However, the energy function of a traditional method for tracking, the geometric Denby-Peterson (Hopfield) network method, can be...
Modern data processing (acquisition, storage and analysis) requires modern tools.
One of the problems shared by existing scientific software is "scripting" approach, when user writes an imperative script which describes the stages in which data should be processed. The main deficiency of such approach is the lack of possibility to automate the process. For example one usually needs script to...
As a data-intensive computing application, high-energy physics requires storage and computing for large amounts of data at the PB level. Performance demands and data access imbalances in mass storage systems are increasing. Specifically, on one hand, traditional cheap disk storage systems have been unable to handle high IOPS demand services. On the other hand, a survey found that only a very...
A key ingredient in an automated evaluation of two-loop multileg processes is a
fast and numerically stable evaluation of scalar Feynman integrals. In this respect, the calculation of two-loop three- and four-point functions in the general complex mass case so far relies on multidimensional numerical integration through sector decomposition whereby a reliable result has a high computing cost,...
Finding tracks downstream of the magnet at the earliest LHCb trigger level is not part of the baseline plan of the Upgrade trigger, on account of the significant CPU time required to execute the search. Many long-lived particles, such as Ks and strange baryons, decay after the vertex track detector (VELO), so that their reconstruction efficiency is limited. We present a study of the...
DODAS stands for Dynamic On Demand Analysis Service and is a Platform as a Service toolkit built around several EOSC-hub services designed to instantiate and configure on-demand container-based clusters over public or private Cloud resources. It automates the whole workflow from service provisioning to the configuration and setup of software applications. Therefore, such solution allows to use...
In the transition to Run 3 in 2021, LHCb will undergo a major luminosity upgrade, going from 1.1 to 5.6 expected visible Primary Vertices (PVs) per event, and will adopt a purely software trigger. This has fueled increased interest in alternative highly-parallel and GPU friendly algorithms for tracking and reconstruction. We will present a novel prototype algorithm for vertexing in the LHCb...
A large amount of data is produced by large scale scientific facilities in high energy physics (HEP) field. And distributed computing technologies has been widely used to process these data. In traditional computing model such as grid computing, computing job is usually scheduled to the sites where the input data was pre-staged in. This model will lead to some problems includ-ing low CPU...
Storage have been identified as the main challenge for the future distributed computing infrastructures: Particle Physics (HL-LHC, DUNE, Belle-II), Astrophysics and Cosmology (SKA, LSST). In particular, the High Luminosity LHC (HL-LHC) will begin operations in the year of 2026 with expected data volumes to increase by at least an order of magnitude as compared with the present systems....
The Belle II experiment, beginning data taking with the full detector in early 2019, is expected to produce a volume of data fifty times that of its predecessor. With this dramatic increase in data comes the opportunity for studies of rare previously inaccessible processes. The investigation of such rare processes in a high data volume environment requires a correspondingly high volume of...
We present a novel framework that enables efficient probabilistic inference in large-scale scientific models by allowing the execution of existing domain-specific simulators as probabilistic programs, resulting in highly interpretable posterior inference. Our framework is general purpose and scalable, and is based on a cross-platform probabilistic execution protocol through which an inference...
Since 2013, ETH Zürich and University of Bologna have been working on the PULP project to develop energy efficient computing architectures suitable for a wide range of applications starting from the IoT domain where computations have to be done in a few milliWatts, all the way to the HPC domain where the goal is to extract the maximum number of calculations within a given power budget. For...
Complete one-loop electroweak radiative corrections to polarized Bhabha
scattering are presented. Higher order QED effects are evaluated in the leading
logarithmic approximation. Numerical results are shown for the conditions of future
circular and linear electron-positron colliders with polarized beams. Theoretical
uncertainties are estimated.
The LHCb Upgrade experiment will start operations in LHC Run 3 from 2021 onwards. Owing to the five-times higher instantaneous luminosity and higher foreseen trigger efficiency, the LHCb Upgrade will collect signal yields per unit time approximately ten times higher than that of the current experiment, with pileup increasing by a factor of six. This contribution presents the changes in the...
A new Monte Carlo event generator MCSANCee for simulation of processes at future e^+e^- colliders is presented. Complete one-loop electroweak radiative corrections and polarization of the initial beams are taken into account. The present generator includes the following processes: e^+e^- \to e^+e^- (mu^+mu^-, tau^+tau^-, ZH, Z\gamma, \gamma\gamma). Numerical results for all of these processes...
The LHCb experiment will be upgraded for data taking in Run 3 and beyond and the instantaneous luminosity will in particular increase by a factor five. The lowest level trigger of the current experiment, a hardware-based trigger that has a hard limit of 1 MHz in its event output rate, will be removed. and replaced with a full software trigger. This new
trigger needs to sustain rates up 30 MHz...
The HL-LHC program has seen numerous extrapolations of its needed computing resources that each indicate the need for substantial changes if the desired HL-LHC physics program is to be supported within the current level of computing resource budgets. Drivers include detector upgrades, large increases in event complexity (leading to increased processing time and analysis data size) and trigger...
The Grace system is an automatic system to calculate cross sections based on the standard model and MSSM including one-loop corrections.
I would like to report recent progress of the GRACE system including optimization of generated codes.
Generative models, and in particular generative adversarial networks, are gaining momentum in hep as a possible way to speed up the event simulation process. Traditionally, gan models applied to hep are designed to return images. On the other hand, many applications (e.g., analyses based on particle flow) are designed to take as input lists of particles. We investigate the possibility of using...
The Monte Carlo generator to simulate events of single-photon
annihilation to hadrons at center-of-mass energies below 2.5 GeV
is described. The generator is based on existing data on cross sections
of various exclusive channels of e+e- annihilation obtained in various
e+e- experiments by the scan and ISR methods. It is extensively used
in the software packages for analysis of experiments at...
The ATLAS experiment produced so far hundreds of petabytes of data and expects to have one order of magnitude more in the future. This data are spread among hundreds of computing Grid sites around the world. The EventIndex is the complete catalogue of all ATLAS events, real and simulated, keeping the references to all permanent files that contain a given event in any processing stage. It...
The increasing luminosities of future LHC runs and next generation of collider experiments will require an unprecedented amount of simulated events to be produced. Such large scale productions are extremely demanding in terms of computing resources. Thus new approaches to event generation and simulation of detector responses are needed. In LHCb the simulation of the RICH detector using the...
Network monitoring is of great importance for every data acquisition system (DAQ), it ensures stable and uninterrupted data flow. However, when using standard tools such as Icinga, often homogeneity of the DAQ hardware is not exploited.
We will present the application of machine learning techniques to detect anomalies among network devices as well as connection instabilities. The former...
An extensive upgrade programme has been developed for LHC and its experiments, which is crucial to allow the complete exploitation of the extremely high-luminosity collision data. The programme is staggered in two phases, so that the main interventions are foreseen in Phase II.
For this second phase, the main hadronic calorimeter of ATLAS (TileCal) will redesign its readout electronics but the...
The increasing LHC luminosity in Run III and, consequently, the increased number of simultaneous proton-proton collisions (pile-up) pose significant challenges for the CMS experiment. These challenges will affect not only the data taking conditions, but also the data processing environment of CMS, which requires an improvement in the online triggering system to match the required detector...
The first LHCb upgrade will take data at an instantaneous luminosity of 2E33cm^{-2}s^{-1} starting in 2021. Due to the high rate of beauty and charm signals LHCb has chosen as its baseline to read out the entire detector into a software trigger running on commodity x86 hardware at the LHC collision frequency of 30MHz, where a full offline-quality reconstruction will be performed. In this talk...
The ATLAS experiment records data from the proton-proton collisions produced by the Large Hadron Collider (LHC). The Tile Calorimeter is the hadronic sampling calorimeter of ATLAS in the region |η| < 1.7. It uses iron absorbers and scintillators as active material. Jointly with the other calorimeters it is designed for reconstruction of hadrons, jets, tau-particles and missing transverse...
A high-precision calculation of the electron anomalous magnetic moment requires an evaluation of QED Feynman diagrams up to five independent loops. To make this calculation practically feasible it is necessary to remove all infrared and ultraviolet divergences before integration. A procedure of removing both infrared and ultraviolet divergences in each individual Feynman diagram will be...
The ATLAS software infrastructure has undergone several changes towards the adoption of Continuous Integration methodology to develop and test software. The users community can benefit from a CI environment in several ways: they can develop their custom analysis, build and test it using revision control services such as GitLab. By providing targeted official base images ATLAS enables users to...
We introduce a novel implementation of a reinforcement learning
algorithm which is adapted to the problem of jet grooming, a
crucial component of jet physics at hadron colliders. We show
that the grooming policies trained using a Deep Q-Network model
outperform state-of-the-art tools used at the LHC such as
Recursive Soft Drop, allowing for improved resolution of the mass
of boosted objects....
Resources required for high-throughput computing in large-scale particle physics experiments face challenging demands both now and in the future. The growing exploration of machine learning algorithms in particle physics offers new solutions to simulation, reconstruction, and analysis. These new machine learning solutions often lead to increased parallelization and faster reconstructions...
A large part of the success of deep learning in computer science can be attributed to the introduction of dedicated architectures exploiting the underlying structure of a given task. As deep learning methods are adopted for high energy physics, increasing attention is thus directed towards the development of new models incorporating physical knowledge.
In this talk, we present a network...
I describe a novel interactive virtual reality visualization of the Belle II detector at KEK and the animation therein of GEANT4-simulated event histories. Belle2VR runs on Oculus and Vive headsets (as well as in a web browser and on 2D computer screens, in the absence of a headset). A user with some particle-physics knowledge manipulates a gamepad or hand controller(s) to interact with and...
Women obtain more than half of U.S. undergraduate degrees in biology, chemistry, and mathematics, yet they earn less than 20% of computer science, engineering, and physics undergraduate degrees (NSF, 2014). Why are women represented in some STEM fields more than others? The STEM Paradox and the Gender Equality Paradox show that countries with greater gender equality have a lower percentage of...
Modern electronic general-purpose computing has been on an unparalleled path of exponential acceleration for more than 7 decades. From the 1970 onwards, this trend was driven by the success of integrated circuits based on silicon technology. The exponential growth has become a self-fulfilling (and economically driven) prophecy commonly referred to as Moore’s Law. The end of Moore’s law has...
Multivariate analyses in particle physics often reach a precision such that its uncertainties are dominated by systematic effects. While there are known strategies to mitigate systematic effects based on adversarial neural nets, the application of Boosted Decision Trees (BDT) so far had to ignore systematics in the training.
We present a method to incorporate systematic uncertainties into a...
The next generation of HPC and HTC facilities, such as Oak Ridge’s Summit, Lawrence Livermore’s Sierra, and NERSC's Perlmutter, show an increasing use of GPGPUs and other accelerators in order to achieve their high FLOP counts. This trend will only grow with exascale facilities such as A21. In general, High Energy Physics computing workflows have made little use of GPUs due to the relatively...
While the Higgs boson couplings to other particles are increasingly well-measured by LHC experiments, it has proven difficult to set constraints on the Higgs trilinear self-coupling $\lambda$, principally due to the very low cross-section of Higgs boson pair production. We present the results of NLO QCD corrections to Higgs pair production with full top-quark mass dependence, where the...
In this talk, we consider some of the computational aspects encountered in recent computations of double Higgs boson production in gluon fusion. We consider the NLO virtual amplitude in the high-energy limit, and the NNLO virtual amplitude in the low-energy (or large top quark mass) limit. We discuss various optimizations which were necessary to produce our results.
Analysis in high-energy physics usually deals with data samples populated from different sources. One of the most widely used ways to handle this is the sPlot technique. In this technique the results of a maximum likelihood fit are used to assign weights that can be used to disentangle signal from background. Some events are assigned negative weights, which makes it difficult to apply machine...
The ATLAS experiment at the Large Hadron Collider at CERN relies on a complex and highly distributed Trigger and Data Acquisition (TDAQ) system to gather and select particle collision data obtained at unprecedented energy and rates. The TDAQ Controls system is the component that guarantees the smooth and synchronous operations of all the TDAQ components and provides the means to minimize the...
Variable-dependent scale factors are commonly used in HEP to improve shape agreement of data and simulation. The choice of the underlying model is of great importance, but often requires a lot of manual tuning e.g. of bin sizes or fitted functions. This can be alleviated through the use of neural networks and their inherent powerful data modeling capabilities.
We present a novel and...
The ATLAS experiment at the LHC at CERN will move to use the Front-End Link eXchange (FELIX) system in a staged approach for LHC Run 3 (2021) and LHC Run 4 (2026). FELIX will act as the interface between the data acquisition; detector control and TTC (Timing, Trigger and Control) systems; and new or updated trigger and detector front-end electronics.
FELIX functions as a router between custom...
We present an algorithm which allows to solve analytically linear systems of differential equations which factorize to first order. The solution is given in terms of iterated integrals over an alphabet where its structure is implied by the coefficient matrix of the differential equations. These systems appear in a large variety of higher order calculations in perturbative Quantum Field...
Complex computer simulations are commonly required for accurate data modelling in many scientific disciplines, including experimental High Energy Physics, making statistical inference challenging due to the intractability of the likelihood evaluation for the observed data. Furthermore, sometimes one is interested on inference drawn over a subset of the generative model parameters while taking...
In this contribution I will discuss the practicalities of storing events from a NNLO calculation on disk with the view of "replaying" the simulation for a different analysis and under different conditions, such as a different PDF fit or a different scale setting.
ATLAS production system called ProdSys2 is used during Run2 to define
and to organize workflows and to schedule, submit and execute payloads
in a distributed computing infrastructure. We design ProdSys2 to manage
all ATLAS workflows: data (re)processing, MC simulation, physics groups
analysis objects production, High Level Trigger processing, SW release
building and user analysis. It...
A large number of physics processes as seen by ATLAS at the LHC manifest as collimated, hadronic sprays of particles known as ‘jets’. Jets originating from the hadronic decay of a massive particle are commonly used in searches for both measurements of the Standard Model and searches for new physics. The ATLAS experiment has employed machine learning discriminants to the challenging task of...
The Level-0 Muon Trigger system of the ATLAS experiment will undergo a full upgrade for HL-LHC to stand the challenging performances requested with the increasing instantaneous luminosity. The upgraded trigger system foresees to send RPC raw hit data to the off-detector trigger processors, where the trigger algorithms run on new generation of Field-Programmable Gate Arrays (FPGAs). The FPGA...
We present the HepMC3 library designed to perform manipulations with
event records of High Energy Physics Monte Carlo Event Generators
(MCEGs). The library is a natural successor of HepMC and HepMC2
libraries used in the present and in the past. HepMC3 supports all
functionality of previous versions and significantly extends them.
In comparison to the previous versions, the default event...
The CMS experiment has been designed with a two-level trigger system: the Level 1 Trigger, implemented on custom-designed electronics, and the High Level Trigger (HLT), a streamlined version of the CMS offline reconstruction software running on a computer farm. A software trigger system requires a trade-off between the complexity of the algorithms running on the available computing resources,...
In radio-based physics experiments, sensitive analysis techniques are often required to extract signals at or below the level of noise. For a recent experiment at the SLAC National Accelerator Laboratory to test a radar-based detection scheme for high energy neutrino cascades, such a sensitive analysis was employed to dig down into a spurious background and extract a signal. This analysis...
The next LHC Runs, nominally RunIII and RunIV, pose problems to the offline and computing systems in CMS. RunIV in particular will needs completely different solutions, given the current estimates of LHC conditions and Trigger estimates. We want to report on the R&D process CMS has a whole has established, in order to gain insight on the needs and the possible solutions for the 2020+ CMS computing.
The Gambit collaboration is a new effort in the world of global BSM fitting -- the combination of the largest possible set of observational data from across particle, astro, and nuclear physics to gain a synoptic view of what experimental data has to say about models of new physics. Using a newly constructed, open source code framework, Gambit have released several state-of-the-art scans of...
I briefly review the recently finished 5-loop renormalization program of QCD, and explain the status and prospects of the computer-algebraic techniques involved.
We propose an algorithm to find a solution to an integro-differential equation of the DGLAP type for all the orders in the running coupling α with splitting functions given at a fixed order in α. Complex analysis is significantly used in the construction of the algorithm, we found a way to calculate the involved integrals over contours in the complex planes in more simple way than by any of...
Certifying the data recorded by the Compact Muon Solenoid (CMS) experiment at CERN which is usable for publication of physics results is a crucial and onerous task. Anomalies caused by detector malfunctioning or sub-optimal data processing are difficult to enumerate a priori and occur rarely, making it difficult to use classical supervised classification. We base out prototype towards the...
A common goal in the search for new physics is the determination of sets of New Physics models, typically parametrized by a number of parameters such as masses or couplings, that are either compatible with the observed data or excluded by it, where the determination into which category a given model belong requires expensive computation of the expected signal. This problem may be abstracted...
The hardware trigger L0 will be removed in LHCb upgrade I, and the software High Level Trigger have to process event at full LHC collision rate (30 MHz). This is a huge task, and delegating some low-level time-consuming tasks to FPGA accelerators can be very helpful in saving computing time that can be more usefully devoted to higher level tasks. In particular, the 2-D pixel geometry of the...
The Belle II experiment is an e+e- collider experiment in Japan, which
begins its main physics run in early 2019. The clean environment of e+e-
collisions together with the unique event topology of Belle II, in which
an Υ(4S) particle is produced and subsequently decays to a pair of B
mesons, allows a wide range of physics measurements to be performed
which are difficult or impossible at...
ROOT has several features which interact with libraries and require implicit header inclusion. This can be triggered by reading or writing data on disk, or user actions at the prompt. Often, the headers are immutable and reparsing is redundant. C++ Modules are designed to minimize the reparsing of the same header content by providing an efficient on-disk representation of C++ Code. ROOT has...
An important part of the LHC legacy will be precise limits on indirect effects of new physics, framed for instance in terms of an effective field theory. These measurements often involve many theory parameters and observables, which makes them challenging for traditional analysis methods. We discuss the underlying problem of “likelihood-free” inference and present powerful new analysis...
Abstract:
The HEP software ecosystem faces new challenges in 2020 with the approach of the High Luminosity LHC (HL-LHC) and the turn-on of a number of large new experiments. Current software development is organized around the experiments: No other field has attained this level of self-organization and collaboration in software development.
During 2017 the community produced a roadmap for...
The HL-LHC will see ATLAS and CMS see proton bunch collisions reaching track multiplicity up to 10.000 charged tracks per event. Algorithms need to be developed to harness the increased combinatorial complexity. To engage the Computer Science community to contribute new ideas, we organize a Tracking Machine Learning challenge (TrackML). Participants are provided events with 100k 3D points, and...
The anomalous magnetic moment of the electron $a_e$ and that of the muon $a_\mu$ occupy the special positions for precision tests of the Standard Model of elementary particles. Both have been precisely measured, 0.24 ppb for $a_e$ and 0.5 ppm for $a_\mu$, and new experiments of both $a_e$ and $a_\mu$ are on-going aiming to reduce the uncertainties. Theoretical calculations of $a_e$ and $a_\mu$...
In particle physics, workflow management systems are primarily used as tailored solutions in dedicated areas such as Monte Carlo production. However, physicists performing data analyses are usually required to steer their individual workflows manually which is time-consuming and often leads to undocumented relations between particular workloads.
We present the luigi analysis workflow (law)...
We investigate the problem of dark matter detection in emulsion detector. Previously we have shown, that it is very challenging but possible to use emulsion films of OPERA-like detector in SHiP experiment to separate electromagnetic showers from each other, thus hypothetically separating neutrino events from dark matter. In this study, we have investigated the possibility of usage of Target...
RooFit is the statistical modeling and fitting package used in many big particle physics experiments to extract physical parameters from reduced particle collision data, e.g. the Higgs boson experiments at the LHC.
RooFit aims to separate particle physics model building and fitting (the users' goals) from their technical implementation and optimization in the back-end.
In this talk, we...
Ground-based $\gamma$-ray astronomy relies on reconstructing primary particles' properties from the measurement of the induced air showers. Currently, template fitting is the state-of-the-art method to reconstruct air showers. CNNs represent promising means to improve on this method in both, accuracy and computational cost. Promoted by the availability of inexpensive hardware and open-source...
The LHCb detector will be upgraded in 2021, and due to the removal of the hardware-level trigger and the increase in the luminosity of the collisions, the conditions for a High Level Trigger 1 in software will become more challenging, requiring processing the full 30 MHz data-collision rate. The GPU High Level Trigger 1 is a framework that permits concurrent many-event execution targeting...
I give an update on recent developments in FeynArts, FormCalc, and LoopTools, and show how the new features were used in making the latest version of FeynHiggs.
In recent years, the astroparticle physics community has successfully adapted supervised learning algorithms for a wide range of tasks, including event reconstruction in cosmic ray observatories[1], photon identification at Cherenkov telescopes[2], and the extraction of gravitational wave signals from time traces[3]. In addition, first unsupervised learning approaches of generative models at...
Artificial neural networks are becoming a standard tool for data analysis, but their potential remains yet to be widely used for hardware-level trigger applications. Nowadays, high-end FPGAs, as they are also often used in low-level hardware triggers, offer enough performance to allow for the inclusion of networks of considerable size into these system for the first time. Nevertheless, in the...
The software framework SModelS, which has already been presented at the ACAT 2016 conference, allows for a very fast confrontation of arbitrary BSM models exhibiting a Z2 symmetry with an ever growing database of simplified models results from CMS and ATLAS. In this talk we shall present its newest features, like the extension to include searches for heavy stable charged particles (HSCPs), or...
FORM is a symbolic manipulation system, which is especially advantageous for handling gigantic expressions with many small terms. Because FORM has been developed in tackling real problems in perturbative quantum field theory, it has some features useful in such problems, although FORM applications are not restricted to any specific research field. In this talk, we discuss recent developments...
Nested data structures are critical for particle physics: it would be impossible to represent collision data as events containing arbitrarily many particles in a rectangular table (without padding or truncation, or without relational indirection). These data structures are usually constructed as class objects and arbitrary length sequences, such as vectors in C++ and lists in Python, and data...
From a breakthrough revolution, Deep Learning (DL) has grown to become a de-facto standard technique in the fields of artificial intelligence and computer vision. In particular Convolutional Neural Networks (CNNs) are shown to be a powerful DL technique to extract physics features from images: They were successfully applied to the data reconstruction and analysis of Liquid Argon Time...
Efficient random number generation with high quality statistical properties and exact reproducibility of Monte Carlo simulation are important requirements in many areas of computational science. VecRNG is a package providing pseudo-random number generation (pRNG) in the context of a new library VecMath. This library bundles up several general-purpose mathematical utilities, data structures...
PICO is a dark matter experiment using superheated bubble chamber technology. One of the main analysis challenges in PICO is to unambiguously distinguish between background events and nuclear recoil events from possible WIMP scatters. The conventional discriminator, acoustic parameter (AP), utilizes frequency analysis in Fourier space to compute the acoustic power, which is proven to be...
Improving the computing performance of particle transport simulation is an important goal to address the challenges of HEP experiments in the coming decades (i.e. HL-LHC), as well as the needs of other fields (i.e. medical imaging and radiotherapy).
The GeantV prototype includes a new transport engine, based on track level parallelization by grouping a large number of tracks in flight into...
The talk is devoted to the overview of Rings — an efficient lightweight library for commutative algebra written in Java and Scala languages. Polynomial arithmetic, GCDs, polynomial factorization and Gröbner bases are implemented with the use of modern asymptotically fast algorithms. Rings can be easily interacted or embedded in applications in high-energy physics and other research areas...
Deep Learning techniques have are being studied for different applications by the HEP community: in this talk, we discuss the case of detector simulation. The need for simulated events, expected in the future for LHC experiments and their High Luminosity upgrades, is increasing dramatically and requires new fast simulation solutions. We will describe an R&D activity within CERN openlab, aimed...
Over the last few years manipulating expressions with millions of terms has become common in particle physics. Form is the de facto tool for manipulations of extremely large expressions, but it comes with some downsides. In this talk I will discuss an effort to modernize aspects of Form, such as the language and workflow, and the introduction of bindings to C and Python. This new tool is...
Deep learning architectures in particle physics are often strongly dependent on the order of their input variables. We present a two-stage deep learning architecture consisting of a network for sorting input objects and a subsequent network for data analysis. The sorting network (agent) is trained through reinforcement learning using feedback from the analysis network (environment). A tree...
JANA2 is multi-threaded event reconstruction framework being developed for Experimental Nuclear Physics. It is an LDRD funded project that will be the successor of the original JANA framework. JANA2 is a near complete rewrite emphasizing C++ language features that have only become available since the C++11 standard. Successful and less-than-successful strategies employed in JANA and how they...
The Mathematica package STR (Star-Triangle Relations) is a recently developed tool designed to solve Feynman diagrams by means of the method of uniqueness in any (Euclidean) spacetime dimension D. The method of uniqueness is a powerful technique to solve multi-loop Feynman integrals in theories with conformal symmetry imposing some relations between D and the powers of propagators. In our...
Accurate particle identification (PID) is one of the most important aspects of the LHCb experiment. Modern machine learning techniques such as deep neural networks are efficiently applied to this problem and are integrated into the LHCb software. In this research, we discuss novel applications of neural network speed-up techniques to achieve faster PID in LHC upgrade conditions. We show that...
The Solenoidal Tracker at RHIC (STAR) is a multi-national supported experiment located at Brookhaven National Lab. The raw physics data captured from the detector is on the order of tens of PBytes per data acquisition campaign, which makes STAR fit well within the definition of a big data science experiment. The production of the data has typically run on standard nodes or on standard Grid...
Using variational autoencoders trained on known physics processes, we develop a one-side p-value test to isolate previously unseen event topologies as outlier events. Since the autoencoder training does not depend on any specific new physics signature, the proposed procedure has a weak dependence on underlying assumptions about the nature of new physics. An event selection based on this...
Beginning in 2021, the upgraded LHCb experiment will use a triggerless readout system collecting data at an event rate of 30 MHz. A software-only High Level Trigger will enable unprecedented flexibility for trigger selections. During the first stage (HLT1), a sub-set of the full offline track reconstruction for charged particles is run to select particles of interest based on single or...
The LHCb experiment is dedicated to the study of the c- and b-hadrons decays, including long living particles such as Ks and strange baryons (Lambda, Xi, etc... ). These kind of particles are difficult to reconstruct from LHCb tracking systems since they escape the detection in the first tracker. A new method to evaluate the performance in terms of efficiency and throughput of the different...
The scientific computing community is suffering from a lack of good development tool that can handle well the unique problems of coding for high performance computing. It is much more difficult for domain experts to parallelize inherited serial codes written in FORTRAN which are very common in CSE research field. An automatic parallel programming IDE is developed for rapid development of...
Triple-GEM detectors are a well known technology in high energy physics. In order to have a complete understanding of their behavior, in parallel with on-beam testing, a Monte Carlo code has to be developed to simulate their response to the passage of particles. The software must take into account all the physical processes involved from the primary ionization up to the signal formation,...
The ATLAS experiment at the LHC has a complex heterogeneous distributed
computing infrastructure, which is used to process and analyse exabytes of data. Metadata are collected and stored at all stages of physics analysis and data processing. All metadata could be divided into operational metadata to be used for the quasi on-line monitoring, and archival to study the systems’ behaviour over a...
A Tier-3g Facility within the computing resources of Istanbul Aydin
University has been planned and installed in collaboration with TR-ULAKBIM national
Tier-2 center. The facility is intended to provide an upgraded data analysis
infrastructure to CERN researchers considering the recent nation-wide projects of ATLAS and
CMS experiments. The fundamental design of Tier-3g has been detailed in...
MATHUSLA has been proposed as a second detector that sits over 100m from an LHC interaction point, on the surface, to look for ultra long-lived particles. A test stand was constructed with 2 layers of scintillator paddles and 3 layers of RPC's, on loan from the DZERO and Argo-YBJ. Downward and upward going tracks from cosmics and muons from the interaction point have been reconstructed. To...
The ATLAS experiment implemented an ensemble of neural networks
(NeuralRinger algorithm) dedicated to improve the performance of
filtering events containing electrons in the high-input rate online
environment of the Large Hadron Collider at CERN, Geneva.
This algorithm has been used online to select electrons with transverse energies
above 15 GeV since 2017 and is extended to electrons...
CernVM-FS is a solution to scalable, reliable and low-maintenance software distribution that is widely used in various High Energy Physics collaborations. The information that can be distributed by CernVM-FS is not limited to software but any other data. By default, the whole CernVM-FS repository containing all subdirectories and files is available to all users in read-only mode after...
Data-intensive end-user analyses in High Energy Physics requires high data throughput to reach short turnaround cycles.
This leads to enormous challenges for storage and network infrastructure, especially when facing the tremendously increasing amount of data to be processed during High-Luminosity LHC runs.
Including opportunistic resources with volatile storage systems into the traditional...
Linux containers have gained widespread use in High Energy Physics, be it for services using container engines such as containerd/kubernetes, for production jobs using container engines such as Singularity or Shifter, or for development workflows using Docker as a local container engine. Thus the efficient distribution of the container images, whose size usually ranges from a few hundred...
Tensor calculations are an important case in many natural sciences like mathematics and physics. To simplify such expressions, computer algebra is widely used. There are a number of approaches for solving this problem, namely, the component calculations, the calculations when tensor is considered as an abstract symbol with indices possessing some symmetry properties, and finally a pure...
The ATLAS experiment at the Large Hadron Collider (LHC) operated successfully from 2008 to 2018, which included Run 1 (2008-2013), a shutdown period and the Run 2 (2016-2018). In the course of the Run 2, the ATLAS data taking achieved an overall data taking efficiency of 97%, largely constraint by the irreducible dead-time introduced to accommodate the limitations of the detector read-out...
Nowadays, any physicist performing an analysis of the LHC data, needs to be well-versed in programming, at the level of both a system programmer and a software developer to handle the vast amounts of collision and simulation events. Even the simplest programming mistake in any of these areas can create big confusions on the analysis results. Moreover, a multitude of different analysis...
The detector description is an essential component in simulation, reconstruction and analysis of data resulting from particle collisions in high energy physics experiments. The main motivation behind DD4hep is to provide an integrated solution for all these stages and addresses detector description in a broad sense, including the geometry and the materials used in the device, and additional...
Decoding the nature of Dark Matter (DM) is one of the most important problems of particle physics. DM can potentially provide unique signatures at collider and non-collider experiments. Details of these signatures which we expect to observe in the near future would allow us to delineate the properties of DM and the respective underlying theory Beyond the Standard Model (BSM). While there...
The extensive physics program of the ATLAS experiment at the Large Hadron Collider (LHC) relies on large scale and high fidelity simulation of the detector response to particle interactions. Current full simulation techniques using Geant4 provide accurate modeling of the underlying physics processes, but are inherently resource intensive. In light of the high-luminosity upgrade of the LHC and...
Drift chamber is the main tracking detector for high energy physics experiment like BESIII. Due to the high luminosity and high beam intensity, drift chamber is suffer from the background from the beam and electronics which represent a computing challenge to the reconstruction software. Deep learning developments in the last few years have shown tremendous improvements in the analysis of data...
The NEWSdm (Nuclear Emulsions for WIMP Search directional measure) is an underground Direct detection Dark Matter (DM) search experiment. The usage of recent developments in the nuclear emulsions allows probing new regions in the WIMP parameter space. The prominent feature of this experiment is a potential of recording the signal direction, which gives a chance of overcoming the "neutrino...
We present recent work in deep learning for particle physics and cosmology at NERSC, the US Dept. of Energy mission HPC centre. We will describe activity in new methods and applications; distributed training across HPC resources; and plans for accelerated hardware for deep learning in NERSC-9 (Perlmutter) and beyond.
Some of the HEP methods and applications showcased include conditional...
The recent years have shown an exciting development in the scientific commmunity due to the interplay between new methods from data science and artificial intelligence, increasing computational resources and physics. The fundamental object of our theories of nature is the Lagrangian whose form is determined by the symmetries found already. A famous and well-motivated extension of the SM...
The inner drift chamber of the BESIII experiment is encountering an aging problem after running of several years. A Cylindrical Gas Electron Multiplier Inner Tracker (CGEM-IT) has been an important candidate for the upgrade of the inner drift chamber. In order to understand the specific detection behavior of CGEM-IT and to build a digitization model for it, a detailed simulation study with the...
All grid middleware require external packages to interact with computing elements, storage sites… In the case of the DIRAC middleware this was historically divided into two bundles, one called externals containing Python and standard binary libraries and the other called the LCGBundle containig libraries form the grid world (gfal, arc, etc). The externals were provided for several platforms...
We introduce two new loss functions designed to directly optimise the statistical significance of the expected number of signal events when training neural networks to classify events as signal or background in the scenario of a search for new physics at a particle collider. The loss functions are designed to directly maximise commonly used estimates of the statistical significance, s/√(s+b),...
In 2019 Belle II will start the planned physics runs with the entire detector installed. Compared to current collider experiments at the LHC, where all critical services are provided by the CERN as host lab and only storage and CPU resources are provided externally, Belle II and KEK chose a different, more distributed strategy. In particular, it provides easier access to existing expertise and...
Information concerning the operation, configuration and behaviour of the ATLAS experiment need to be reported, gathered and shared reliably with the whole ATLAS community which comprises over three thousand scientists geographically distributed all over the world. To provide such functionality, a logbook facility, Electronic Logbook for the information storage of ATLAS (ELisA), has been...
ROOT is a large code base with a complex set of build-time dependencies; there is a significant difference in compilation time between the “core” of ROOT and the full-fledged deployment. We present results on a “delayed build” for internal ROOT packages and external packages. This gives the ability to offer a “lightweight” core of ROOT, later extended by building additional modules to extend...
Maintaining the huge computing grid facilities for LHC
experiments and replacing their hardware every few years has been very
expensive. The California State University (CSU) ATLAS group just
received $250,000 AWS cloud credit from the CSU Chancellor’s Office to
build the first virtual US ATLAS Tier 3 to explore cloud solutions for
ATLAS. We will use this award to set up full ATLAS...
Deep learning has shown a promising future in physics’ data analysis and is anticipated to revolutionize LHC discoveries.
Designing an optimal algorithm may seem to be the most challenging task in machine learning progress especially in HEP due to the high dimensionality and extreme complexity of the data.
Physical knowledge can be employed in designing and modifying of the algorithm’s...
The German CMS community (DCMS) as a whole can benefit from the various compute resources, available to its different institutes. While Grid-enabled and National Analysis Facility resources are usually shared within the community, local and recently enabled opportunistic resources like HPC centers and cloud resources are not. Furthermore, there is no shared submission infrastructure...
The set of the four-loop numerical results for the relation between pole and running heavy quarks masses in QCD at fixed number of lighter flavors $3\leq n_l\leq 15$, which was obtained in Ref.[1] with help of the Lomonosov Supercomputer of Moscow State University, is analysed by the ordinary method of the least squares. We use its variant which allows to solve the overdetermined system of 13...
The Geant4 toolkit is used extensively in high energy physics to simulate the
passage of particles through matter and to estimate effects such as detector
responses, efficiencies and smearing. Geant4 uses many underlying models to predict
particle interaction kinematics, and uncertainty in these models leads to uncertainty in the interpretation of experiment measurements. The Geant4...
In High Energy Physics, tests of homogeneity are used primarily in two cases: for verification that data sample does not differ significantly from numerically produced Monte Carlo sample and for verifying separation of signal from background. Since Monte Carlo samples are usually weighted, it is necessary to modify classical homogeneity tests in order to apply them to weighted samples. In...
MPGD are the new frontier in gas trackers. Among this kind of
devices, the GEM chambers are widely used. The experimental signals acquired with the detector must obviously be reconstructed and analysed. In this
contribution, a new offline software to perform reconstruction,
alignment and analysis on the data collected with APV-25 and TIGER ASICs will
be presented. GRAAL (Gem Reconstruction And...
In recent years the usage of machine learning techniques within data-intensive sciences in general and high-energy physics in particular has rapidly increased, in part due to the availability of large datasets on which such algorithms can be trained as well as suitable hardware, such as graphics or tensor processing units which greatly accelerate the training and execution of such algorithms....
The ever growing amount of HEP data to be analyzed in the future requires as of today the allocation of additional, potentially only temporary available non-HEP dedicated resources. These so-called opportunistic resources are also well-suited to cover the typical unpredictable peak demands for computing resources in end-user analyses. However, their temporary availability requires a dynamic...
Amplitude analysis is an important tool for the research of the hadron spectrum, in which the maximum likelihood method is used to estimate the parameters of a probability density function. In each optimization step, the likelihood values of a huge number of events from both data and Monte-Carlo simulations are calculated and summed, which is the most time-consuming part of the whole...
The poster focuses on our experience in usage and extending of JupyterLab
in combination with EOS and CVMFS for HEP analysis within a local university group.
We started with a copy of CERN SWAN environment, after that our project evolved independently.
A major difference is that we switched from classic Jupyter Notebook
to JupyterLab, because our users are more insterested in text editor...
We present a new approach to identification of boosted neutral particles using electromagnetic calorimeters of the LHCb detector. The identification of photons and neutral pions is currently based on expected properties of the objects reconstructed in the calorimeter. This allows to distinguish single photons in the electromagnetic calorimeter from overlapping photons produced from high...
Particle identification is a key ingredient of most of LHCb results. Muon identification in particular is used at every stage of the LHCb triggers. The objective of the muon identification is to distinguish muons from the rest of the particles using only information from the Muon subdetector under strict timing constraints. We use state-of-the-art gradient boosting algorithm and real data with...
The Compact Muon Solenoid (CMS) is one of the general-purpose detectors at the CERN Large Hadron Collider (LHC) which collects enormous amounts of physics data. Before the final physics analysis can proceed, data has to be checked for quality (certified) by passing a number of automatic (like physics objects reconstruction, histogram preparation) and manual (checking, comparison and decision...
In this work are presented the result of the comparing two versions of GEANT4 by the use of experimental data of experiment HARP. The comparison is performed with help of a new method of statistical comparison of data sets. The method provides more information for data analysis than methods based on the chi-squared distribution.
micrOMEGAs is a package for the calculation of the relic density of Dark Matter and of different observables related with Dark Matter searches. The talk will present the general structure of the package and several recent developments including freeze-in relic abundance calculation, interface with different packages that compute collider observables, and recent improvements in direct detection signals.
Real time monitoring of Compact Muon Solenoid (CMS) trigger system is a vital task to ensure the quality of all physics results published by the collaboration. Today, the trigger monitoring software reports on potential problems given the time evolution of the reported rates. The anomalous rates are identified given the deviation from the prediction which is calculated using a regression model...
Data Quality Monitoring (DQM) is a very significant component of all high-
energy physics (HEP) experiments. Data recorded by Data Acquisition (DAQ) sensors and devices are sampled to perform live monitoring of the status of each detector during data collection. This gives to the system and scientists the ability to identify problems with extremely low latency, minimizing the amount of data...
The overlapping grid technique can be used to solve partial differential equations defined on complex computational domains. However, large-scale realistic applications using overlapping grid technique under distributed memory systems are not easy. The grid points do not meet point by point and interpolation is needed. Applications with millions of grid points may consist of many blocks. A...
HEP computing is a typical data intensive computing. Performance of distributed storage system, can largely defines the efficiency of HEP data processing and analysis. There is a large number of parameters that can be adjusted in a distributed storage system. The setting of these parameters has a great influence on the performance. At present, these parameters are either set with static values...
An efficient phase space integration is important for most calculations for collider experiments. We are developing a phase space integration that distribute phase space points according to the singular limit of QCD, Using the Altarelli-Parisi splitting functions as the underlying probability for a splitting, by developing and applying theoretical and computational tools
Although the standard model of particle physics is successful in describing physics as we know it, it is known to be incomplete. Many models have been developed to extend the standard model, none of which have been experimentally verified. One of the main hurdles in this effort is the dimensionality of these models, yielding problems in analysing, visualising and communicating results. Because...
Mitigation of the effect of the multiple parasitic proton collisions produced during bunch crossing at the LHC is a major endeavor towards the realization of the physics program at the collider. The pileup affects many physics observable derived during the online and offline reconstruction. We propose a graph neural network machine learning model, based on the PUPPI approach, for identifying...
The mass Monte Carlo data production is the most CPU intensive process in the data analysis of for the high energy physics. The use of large scale computational resources at HPC in China is expected to increase substantially the cost-efficiency of the processing. TianheII, the second fastest HPC in China, which used to ranks first in the TOP500. We report on the technical challenges and...
A large class of statistical models in high energy physics can be expressed a simultaneous measurement of binned observables. A popular framework for such binned analysis is HistFactory. So far the only implementation of the model has been within the ROOT ecosystem, limiting adoption and extensibility. We present a complete and extensible implementation of the HistFactory class of models in...
The LHC’s Run3 will push the envelope on data-intensive workflows and, at the lowest level, this data is managed using the ROOT software framework. At the beginning of Run 1, all data was compressed with the ZLIB algorithm: ROOT has since added support for multiple new algorithms (such as LZMA and LZ4), each with unique strengths. Work is continuing as industry introduces new techniques -...
Increasing data rates opens up new opportunities for astroparticle physics by improving the precision of data analysis and by deploying advanced analysis techniques that demand relatively large data volumes, e.g. deep learning . One of the ways to increase statistics is to combine data from different experimental setups for joint analysis. Moreover, such data integration provides us with an...
Distinct HEP workflows have distinct I/O needs; while ROOT I/O excels at serializing complex C++ objects common to reconstruction, analysis workflows typically have simpler objects and can sustain higher event rates. To meet these workflows, we have developed a “bulk I/O” interface, allowing multiple events’ data to be returned per library call. This reduces ROOT-related overheads and...
BESIII experiment studies physics in the tau-charm energy region. Since 2009, BESIII has collected large scale data samples and many important physics results have been achieved based on these samples. Gaudi is used as BESIII offline software underlying framework, for both data production and data analysis. As data set accumulated year by year, efficiency of data analysis becomes more and more...
We show how Interaction Networks could be used for jet tagging at the Large Hadron Collider.
We take as an example the problem of identifying high-pT H->bb decays exploiting both jet substructure and secondary vertices from b quarks. We consider all tracks produced in the hadronization of the two b’s and represent the jet both as a track-to-track and a track-to-vertex interaction. The...
We describe a little in detail some techniques used in the calculation of
4-loop QED contributions to some quantities like g-2,
slope of the Dirac form factor, renormalization constants;
in particular, some different approaches to the parallelization of some
parts of the calculations. Some recent results will be also presented.
The design and performance of the ATLAS Inner Detector (ID) trigger algorithms running online on the high level trigger (HLT) processor farm for 13 TeV LHC collision data with high pile-up are discussed.
The HLT ID tracking is a vital component in all physics signatures in the ATLAS trigger for the precise selection of the rare or interesting events necessary for physics analysis...
The SND detector has been operating at the VEPP-2000 collider (BINP, Russia) for several years unveiling amazing knowledge. Being a scientific facility it experiences constant improvements. One of the improvements worth mentioning is the DQM system for the SND detector.
First, information is collected automatically by DQM scripts and then could be corrected/confirmed by the detector operators...
Track finding and fitting are amongst the most complex part of
event reconstruction in high-energy physics, and dominates usually
the computing time in high luminosity environment. A central part of
track reconstruction is the transport of a given track parameterisation
(i.e. the parameter estimation and associated covariances) through the
detector, respecting the magnetic field setup and the...
The LHCb experiment is dedicated to the study of the c- and b-hadrons decays, including long living particles such as Ks and strange baryons (Lambda, Xi, etc... ). These kind of particles are difficult to reconstruct from LHCb tracking systems since they escape the detection in the first tracker. A new method to evaluate the performance in terms of efficiency and throughput of the different...
In software development Continuous Integration (CI), the practice of bringing together multiple developers’ code modifications into a single repository, and Continuous Delivery (CD), the practice of automatedly creating and testing releases are well known. CI/CD pipelines are available in many automation tools (such as GitLab) and act to enhance and speed up software development.
Continuous...
Probability distribution functions (PDFs) are very used in modeling random
processes and physics simulations. It can be demonstrated that the relation-
ships between PDFs are linked through functional parameters. Improving the
performance of the generation of many random numbers to be used as input
by the PDFs is often a very challenging task as it involves algorithms with
acceptance-rejection...
