Jonas Rembser

With the growing datasets of current and next-generation HighEnergy and Nuclear Physics (HEP/NP) experiments, statistical analysis has become more computationally demanding. These increasing demands elicit improvements and modernizations in existing statistical analysis software. One way to address these issues is to improve parameter estimation performance and numeric stability using Automatic Differentiation (AD). AD’s computational efficiency and accuracy are superior to the preexisting numerical differentiation techniques, and it offers significant performance gains when calculating the derivatives of functions with a large number of inputs, making it particularly appealing for statistical models with many parameters. For such models, many HEP/NP experiments use RooFit, a toolkit for statistical modeling and fitting that is part of ROOT. In this paper, we report on the effort to support the AD of RooFit likelihood functions. Our approach is to extend RooFit with a tool that generates overheadfree C++ code for a full likelihood function built from RooFit functional models. Gradients are then generated using Clad, a compiler-based source-codetransformation AD tool, using this C++ code. We present our results from applying AD to the entire minimization pipeline and profile likelihood calculations of several RooFit and HistFactory models at the LHC-experiment scale. We show significant reductions in calculation time and memory usage for the minimization of such likelihood functions. We also elaborate on this approach’s current limitations and explain our plans for the future.

The method of accelerating heavy particles in a helix wave-guide as repeatedly suggested in literature has been examined theoretically in detail. The first part of this article deals with the HF-characteristics of the wave-guide that were taken from known investigations based on the Pierce theory. A more accurate examination of the acceleration process for protons shows that the accelerating electric field strength on the axis of the helix is strongly reduced for proton energies larger than ca. 30 MeV, while for proton energies smaller than ca. 0.5 MeV the losses in the wave guide are considerably increasing. An acceleration, therefore, will only be advisable for a medium energy range, but here it is equivalent if not superior to other methods. In the case discussed here (acceleration of protons from 1 to 10 MeV) the optimum vacuum wave length was found to be ca. 1.5 m. With a HF-source output of 0.5 MW such an accelerator would have a length of ca. 12m, while the diameter of the shield would be 12 cm, the volume being about 0.15 m3.

RooFit is a toolkit for statistical modeling and fitting, and together with RooStats it is used for measurements and statistical tests by most experiments in particle physics, particularly the LHC experiments. As the LHC program progresses, physics analysis becomes more computationally demanding. Therefore, RooFit development in recent years is focused on modernizing RooFit, improving its ease of use, and on performance optimization. This paper presents the new RooFit vectorized computation mode, which supports calculations on the GPU. Additionally, we discuss new features in the upcoming ROOT 6.26 release, highlighting the new pythonizations in particular.

Abstract High-frequency financial market data is conceptually distinct from high energy physics (HEP) data. Market data is a time series generated by market participants, while HEP data is a set of independent events generated by collisions between particles. However, there are similarities within the data structure and required tools for data analysis, and both fields share a similar set of problems facing the increasing size of data generated. This paper describes some of the core concepts of financial markets, discusses the data similarities and differences with HEP, and provides an implementation to use ROOT, an open-source data analysis framework in HEP, with financial market data. This implementation makes it possible to take advantage of the rich set of features available in ROOT and extends research in finance.

RooFit is a toolkit for statistical modeling and fitting used by most experiments in particle physics. Just as data sets from next-generation experiments grow, processing requirements for physics analysis become more computationally demanding, necessitating performance optimizations for RooFit. One possibility to speed-up minimization and add stability is the use of Automatic Differentiation (AD). Unlike for numerical differentiation, the computation cost scales linearly with the number of parameters, making AD particularly appealing for statistical models with many parameters. In this paper, we report on one possible way to implement AD in RooFit. Our approach is to add a facility to generate C++ code for a full RooFit model automatically. Unlike the original RooFit model, this generated code is free of virtual function calls and other RooFit-specific overhead. In particular, this code is then used to produce the gradient automatically with Clad. Clad is a source transformation AD tool implemented as a plugin to the clang compiler, which automatically generates the derivative code for input C++ functions. We show results demonstrating the improvements observed when applying this code generation strategy to HistFactory and other commonly used RooFit models. HistFactory is the subcomponent of RooFit that implements binned likelihood models with probability densities based on histogram templates. These models frequently have a very large number of free parameters and are thus an interesting first target for AD support in RooFit.

The Compact Muon Solenoid (CMS) detector is one of the two multi-purpose experiments at the Large Hadron Collider (LHC) and has a broad physics program. Many aspects of this program depend on our ability to trigger, reconstruct and identify events with final state electrons, positrons, and photons with the CMS detector with excellent efficiency and high resolution. We present the full process of electron and photon reconstruction in CMS, starting from tracker hits and energy deposits in the electromagnetic calorimeter, the methods to achieve the ultimate precision in Run II energy measurements, the identification strategies (based both on cut-based approach and on multivariate analysis) to discriminate prompt electrons and photons from background, and the methods to estimate the associated systematic uncertainties. Finally the performance on benchmark channels (such as Z → e+e−) will be shown.

A group of Early-Career Researchers (ECRs) has been given a mandate from the European Committee for Future Accelerators (ECFA) to debate the topics of the current European Strategy Update (ESU) for Particle Physics and to summarise the outcome in a brief document [1]. A full-day debate with 180 delegates was held at CERN, followed by a survey collecting quantitative input. During the debate, the ECRs discussed future colliders in terms of the physics prospects, their implications for accelerator and detector technology as well as computing and software. The discussion was organised into several topic areas. From these areas two common themes were particularly highlighted by the ECRs: sociological and human aspects; and issues of the environmental impact and sustainability of our research.

The proton spectrum in a cylindrical neutron collision counter with hydrogen-rich filler gas was calculated for a monochromatic neutron beam parallel to the axis. The numericai discrepancies between the results of Rossi and Staub (Ionization Chambers and Counters, p.155, New York, McGraw-Hill, 1949) and those of Skyrme, Tunnicliffe, and Ward (Rev. Sci. Instr. 23, 204(1952)) on the wall and end effects in cylindrical counters are explained. It was proposed to utilize the boundary effects in a long collision counter for energy measurement of fast neutrons. (tr-auth)

This document discusses the state, roadmap, and risks of the foundational components of ROOT with respect to the experiments at the HL-LHC (Run 4 and beyond). As foundational components, the document considers in particular the ROOT input/output (I/O) subsystem. The current HEP I/O is based on the TFile container file format and the TTree binary event data format. The work going into the new RNTuple event data format aims at superseding TTree, to make RNTuple the production ROOT event data I/O that meets the requirements of Run 4 and beyond.

ROOT is high energy physics' software for storing and mining data in a statistically sound way, to publish results with scientific graphics. It is evolving since 25 years, now providing the storage format for more than one exabyte of data; virtually all high energy physics experiments use ROOT. With another significant increase in the amount of data to be handled scheduled to arrive in 2027, ROOT is preparing for a massive upgrade of its core ingredients. As part of a review of crucial software for high energy physics, the ROOT team has documented its R&D plans for the coming years.

This document discusses the state, roadmap, and risks of the foundational components of ROOT with respect to the experiments at the HL-LHC (Run 4 and beyond). As foundational components, the document considers in particular the ROOT input/output (I/O) subsystem. The current HEP I/O is based on the TFile container file format and the TTree binary event data format. The work going into the new RNTuple event data format aims at superseding TTree, to make RNTuple the production ROOT event data I/O that meets the requirements of Run 4 and beyond.

ROOT is high energy physics' software for storing and mining data in a statistically sound way, to publish results with scientific graphics. It is evolving since 25 years, now providing the storage format for more than one exabyte of data; virtually all high energy physics experiments use ROOT. With another significant increase in the amount of data to be handled scheduled to arrive in 2027, ROOT is preparing for a massive upgrade of its core ingredients. As part of a review of crucial software for high energy physics, the ROOT team has documented its R&D plans for the coming years.

As the field of high energy physics moves to an era of precision measurements its models become ever more complex and so do the challenges for computational frameworks that intend to fit these models to data. This report describes two computational optimizations with which RooFit intends to address this challenge: parallelization and batched computations. For the former, a problem-agnostic parallelization framework was devised with generality in mind such that it could be seamlessly applied at various stages of the existing Minuit2 minimization routine. In the results shown in this report parallelization was applied at the gradient calculation stage. The batched computations approach on the other hand required an overhaul of the current manner in which RooFit prepares its computatational graph for the evaluation of likelihoods. This report includes initial benchmarks of the batched computations strategy run on a CPU with vector instructions. Both strategies show significant performance improvements and the parallelization approach at its current state also proves to be robust enough to consistently fit state of the art physics models to real LHC data. Future developments are targeted towards combining both technologies in RooFit in a production-ready state in a ROOT release in the near future.

The second workshop on the HEP Analysis Ecosystem took place 23-25 May 2022 at IJCLab in Orsay, to look at progress and continuing challenges in scaling up HEP analysis to meet the needs of HL-LHC and DUNE, as well as the very pressing needs of LHC Run 3 analysis. The workshop was themed around six particular topics, which were felt to capture key questions, opportunities and challenges. Each topic arranged a plenary session introduction, often with speakers summarising the state-of-the art and the next steps for analysis. This was then followed by parallel sessions, which were much more discussion focused, and where attendees could grapple with the challenges and propose solutions that could be tried. Where there was significant overlap between topics, a joint discussion between them was arranged. In the weeks following the workshop the session conveners wrote this document, which is a summary of the main discussions, the key points raised and the conclusions and outcomes. The document was circulated amongst the participants for comments before being finalised here.

The main topics discussed at the 17th Annual Conference of the IAEA in Vienna were budget problems, arising from the latest price increases and from the decline of the dollar rate, which have a considerable effect also on the most important future tasks of the IAEA, namely technical assistance and safeguards operations. Another item on the agenda was the market study on the construction of nuclear power plants for and in developing countries. Following the extension of the Board of Governors, the German Federal Republic now has a permanent seat in this body as one of the nine most developed countries. (GE)