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Experimental High Energy Physics has entered an era of precision measurements. However, measurements of many of the accessible processes assume that the final states' underlying kinematic distribution is the same as the Standard Model prediction. This assumption introduces an implicit model-dependency into the measurement, rendering the reinterpretation of the experimental analysis complicated without reanalysing the underlying data. We present a novel reweighting method in order to perform reinterpretation of particle physics measurements. It makes use of reweighting the Standard Model templates according to kinematic signal distributions of alternative theoretical models, prior to performing the statistical analysis. The generality of this method allows us to perform statistical inference in the space of theoretical parameters, assuming different kinematic distributions, according to a beyond Standard Model prediction. We implement our method as an extension to the pyhf software and interface it with the EOS software, which allows us to perform flavor physics phenomenology studies. Furthermore, we argue that, beyond the pyhf or HistFactory likelihood specification, only minimal information is necessary to make a likelihood model-agnostic and hence easily reinterpretable. We showcase that publishing such likelihoods is crucial for a full exploitation of experimental results.

Given the urgency to reduce fossil fuel energy production to make climate tipping points less likely, we call for resource-aware knowledge gain in the research areas on Universe and Matter with emphasis on the digital transformation. A portfolio of measures is described in detail and then summarized according to the timescales required for their implementation. The measures will both contribute to sustainable research and accelerate scientific progress through increased awareness of resource usage. This work is based on a three-days workshop on sustainability in digital transformation held in May 2023., Comment: 20 pages, 2 figures, publication following workshop 'Sustainability in the Digital Transformation of Basic Research on Universe & Matter', 30 May to 2 June 2023, Meinerzhagen, Germany, https://indico.desy.de/event/37480

When measuring rare processes at Belle II, a huge luminosity is required, which means a large number of simulations are necessary to determine signal efficiencies and background contributions. However, this process demands high computation costs while most of the simulated data, in particular in case of background, are discarded by the event selection. Thus, filters using graph neural networks are introduced at an early stage to save the resources for the detector simulation and reconstruction of events discarded at analysis level. In our work, we improved the performance of the filters using graph attention and investigated statistical methods including sampling and reweighting to deal with the biases introduced by the filtering., Comment: to be published in ACAT 2022 proceedings in the Journal Of Physics: Conference Series

The pixel vertex detector (PXD) is an essential part of the Belle II detector recording particle positions. Data from the PXD and other sensors allow us to reconstruct particle tracks and decay vertices. The effect of background hits on track reconstruction is simulated by adding measured or simulated background hit patterns to the hits produced by simulated signal particles. This model requires a large set of statistically independent PXD background noise samples to avoid a systematic bias of reconstructed tracks. However, data from the fine-grained PXD requires a substantial amount of storage. As an efficient way of producing background noise, we explore the idea of an on-demand PXD background generator using conditional Generative Adversarial Networks (GANs) with contrastive learning, adapted by the number of PXD sensors in order to both increase the image fidelity and produce sensor-dependent PXD hitmaps., Comment: 25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)

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.

A workflow describes the entirety of processing steps in an analysis, such as employed in many fields of physics. Workflow management makes the dependencies between individual steps of a workflow and their computational requirements explicit, such that entire workflows can be executed in a stand-alone manner. Though the use of workflow management is widely recommended in the interest of transparency, reproducibility and data preservation, choosing among the large variety of available workflow management tools can be overwhelming. We compare selected workflow management tools concerning all relevant criteria and make recommendations for different use cases.

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases -- including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits -- we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results., Comment: 60 pages, 15 figures

We introduce a Python package that provides simply and unified access to a collection of datasets from fundamental physics research - including particle physics, astroparticle physics, and hadron- and nuclear physics - for supervised machine learning studies. The datasets contain hadronic top quarks, cosmic-ray induced air showers, phase transitions in hadronic matter, and generator-level histories. While public datasets from multiple fundamental physics disciplines already exist, the common interface and provided reference models simplify future work on cross-disciplinary machine learning and transfer learning in fundamental physics. We discuss the design and structure and line out how additional datasets can be submitted for inclusion. As showcase application, we present a simple yet flexible graph-based neural network architecture that can easily be applied to a wide range of supervised learning tasks. We show that our approach reaches performance close to dedicated methods on all datasets. To simplify adaptation for various problems, we provide easy-to-follow instructions on how graph-based representations of data structures, relevant for fundamental physics, can be constructed and provide code implementations for several of them. Implementations are also provided for our proposed method and all reference algorithms., Comment: 14 pages, 3 figures, 5 tables - Version accepted by Computing and Software for Big Science

Belle II is a rapidly growing collaboration with members from one hundred and nineteen institutes spread around the globe. The software development team of the experiment, as well as the software users, are very much decentralised. Together with the active development of the software, such decentralisation makes the adoption of the latest software releases by users an essential, but quite challenging task. To ensure the relevance of the documentation, we adopted the policy of in-code documentation and configured a website that allows us to tie the documentation to given releases. To prevent tutorials from becoming outdated, we covered them by unit-tests. For the user support, we use a question and answer service that not only reduces repetition of the same questions but also turned out to be a place for discussions among the experts. A prototype of a metasearch engine for the different sources of documentation has been developed. For training of the new users, we organise centralised StarterKit workshops attached to the collaboration meetings. The materials of the workshops are later used for self-education and organisation of local training sessions.

This paper describes the track-finding algorithm that is used for event reconstruction in the Belle II experiment operating at the SuperKEKB B-factory in Tsukuba, Japan. The algorithm is designed to balance the requirements of a high efficiency to find charged particles with a good track parameter resolution, a low rate of spurious tracks, and a reasonable demand on CPU resources. The software is implemented in a flexible, modular manner and employs a diverse selection of global and local track-finding algorithms to achieve an optimal performance.

The Belle II experiment is designed to collect 50 times more data than its predecessor. For a smooth collection of high-quality data, a robust and automated data transport and processing pipeline has been established. We describe the basic software components employed by the high level trigger. It performs a reconstruction of all events using the same algorithms as offline, classifies the events according to physics criteria, and provides monitoring information. The improved system described in this paper has been deployed successfully since 2019.

New Physics can manifest itself in kinematic distributions of particle decays. The parameter space defining the shape of such distributions can be large which is challenging for both theoretical and experimental studies. Using clustering algorithms, the parameter space can however be dissected into subsets (clusters) which correspond to similar kinematic distributions. Clusters can then be represented by benchmark points, which allow for less involved studies and a concise presentation of the results. We demonstrate this concept using the Python package ClusterKinG, an easy to use framework for the clustering of distributions that particularly aims to make these techniques more accessible in a High Energy Physics context. As an example we consider $\bar B\to D^{(*)}\tau^-\bar\nu_\tau$ distributions and discuss various clustering methods and possible implications for future experimental analyses., Comment: 25 pages, 10 figures, 2 tables; corrected implementation of chi2 metric with correlated random variables and corrected number of degrees of freedom; added toy study to validate statistical treatment

The GENFIT toolkit, initially developed at the Technische Universitaet Muenchen, has been extended and modified to be more general and user-friendly. The new GENFIT, called GENFIT2, provides track representation, track-fitting algorithms and graphic visualization of tracks and detectors, and it can be used for any experiment that determines parameters of charged particle trajectories from spacial coordinate measurements. Based on general Kalman filter routines, it can perform extrapolations of track parameters and covariance matrices. It also provides interfaces to Millepede II for alignment purposes, and RAVE for the vertex finder. Results of an implementation of GENFIT2 in basf2 and PandaRoot software frameworks are presented here., Comment: 41 pages 24 figures, 1 table. Paper submitted to NIM

Data processing frameworks are an essential part of HEP experiments' software stacks. Frameworks provide a means by which code developers can undertake the essential tasks of physics data processing, accessing relevant inputs and storing their outputs, in a coherent way without needing to know the details of other domains. Frameworks provide essential core services for developers and help deliver a configurable working application to the experiments' production systems. Modern HEP processing frameworks are in the process of adapting to a new computing landscape dominated by parallel processing and heterogeneity, which pose many questions regarding enhanced functionality and scaling that must be faced without compromising the maintainability of the code. In this paper we identify a program of work that can help further clarify the key concepts of frameworks for HEP and then spawn R&D activities that can focus the community's efforts in the most efficient manner to address the challenges of the upcoming experimental program.

We describe the conversion of simulated and recorded data by the Belle experiment to the Belle~II format with the software package \texttt{b2bii}. It is part of the Belle~II Analysis Software Framework. This allows the validation of the analysis software and the improvement of analyses based on the recorded Belle dataset using newly developed analysis tools.

The Full Event Interpretation is presented: a new exclusive tagging algorithm used by the high-energy physics experiment Belle II. The experimental setup of Belle II allows the precise measurement of otherwise inaccessible $B$ meson decay-modes. The Full Event Interpretation algorithm enables many of these measurements. The algorithm relies on machine learning to automatically identify plausible $B$ meson decay chains based on the data recorded by the detector. Compared to similar algorithms employed by previous experiments, the Full Event Interpretation provides a greater efficiency, yielding a larger effective sample size usable in the measurement., Comment: 11 pages, 7 figures, 1 table

The High Energy Phyiscs community has developed and needs to maintain many tens of millions of lines of code and to integrate effectively the work of thousands of developers across large collaborations. Software needs to be built, validated, and deployed across hundreds of sites. Software also has a lifetime of many years, frequently beyond that of the original developer, it must be developed with sustainability in mind. Adequate recognition of software development as a critical task in the HEP community needs to be fostered and an appropriate publication and citation strategy needs to be developed. As part of the HEP Softare Foundation's Community White Paper process a working group on Software Development, Deployment and Validation was formed to examine all of these issues, identify best practice and to formulare recommendations for the next decade. Its report is presented here.

Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.

One of the key assumptions of the Standard Model of fundamental particles is that the interactions of the charged leptons, namely electrons, muons, and taus, differ only because of their different masses. While precision tests comparing processes involving electrons and muons have not revealed any significant violation of this assumption, recent studies involving the higher-mass tau lepton have resulted in observations that challenge lepton universality at the level of four standard deviations. A confirmation of these results would point to new particles or interactions, and could have profound implications for our understanding of particle physics., Comment: 10 pages, 7 figures. Accepted for publication in Nature

We present a software framework for Belle II that reconstructs B mesons in many decay modes with minimal user intervention. It does so by reconstructing particles in user-supplied decay channels, and then in turn using these reconstructed particles in higher-level decays. This hierarchical reconstruction allows one to cover a relatively high fraction of all B decays by specifying a limited number of particle decays. Multivariate classification methods are used to achieve a high signal-to-background ratio in each individual channel. The entire reconstruction, including the application of pre-cuts and classifier trainings, is automated to a high degree and will allow users to retrain to account for analysis-specific signal-side selections., Comment: 5 pages, 3 figures. To appear in the proceedings of the 16th International workshop on Advanced Computing and Analysis Techniques in physics research (ACAT 2014)

The decay Bs -> mu+mu- is very sensitive to contributions from new physics processes. Thus the Tevatron and LHC experiments are hunting for an observation of a Bs -> mu+mu- signal. In this article the updated search for Bs -> mu+mu- and B0 -> mu+mu- by the CDF experiment is presented. The CDF result was received with great interest because an excess over the background expectation is seen, although of modest statistical significance and still consistent with the prediction of a standard model signal and other experimental results., Comment: To appear in the proceedings of the 2011 Europhysics Conference on High Energy Physics-HEP 2011, July 21-27, 2011, Grenoble, France

The Tevatron experiments CDF and D0 have filled many empty spots in the spectrum of heavy baryons over the last few years. The most recent results are described in this article: The first direct observation of the Xi_b^0, improved measurements of Sigma_b properties, a new measurement of the Lambda_b -> J/psi Lambda branching ratio, and a high-statistics study of charm baryons., Comment: To appear in the proceedings of the XIV International Conference on Hadron Spectroscopy (Hadron 2011), June 13-17, 2011, Munich, Germany

While B0 and B+ mesons are well studied, mainly by the B factories, less is known about Bs mesons. Specifically large new physics effects may still be present in the Bs system. This unexplored region is studied by the CDF, D0, and Belle experiments. In this article their recent measurements on the Bs physics sector are presented., Comment: To appear in the proceedings of XXX. Physics in Collision, September 1-4, 2010, Karlsruhe, Germany

We describe a new B-meson full reconstruction algorithm designed for the Belle experiment at the B-factory KEKB, an asymmetric e+e- collider that collected a data sample of 771.6 x 10^6 BBbar pairs during its running time. To maximize the number of reconstructed B decay channels, it utilizes a hierarchical reconstruction procedure and probabilistic calculus instead of classical selection cuts. The multivariate analysis package NeuroBayes was used extensively to hold the balance between highest possible efficiency, robustness and acceptable consumption of CPU time. In total, 1104 exclusive decay channels were reconstructed, employing 71 neural networks altogether. Overall, we correctly reconstruct one B+/- or B0 candidate in 0.28% or 0.18% of the BBbar events, respectively. Compared to the cut-based classical reconstruction algorithm used at the Belle experiment, this is an improvement in efficiency by roughly a factor of 2, depending on the analysis considered. The new framework also features the ability to choose the desired purity or efficiency of the fully reconstructed sample freely. If the same purity as for the classical full reconstruction code is desired ~25%, the efficiency is still larger by nearly a factor of 2. If, on the other hand, the efficiency is chosen at a similar level as the classical full reconstruction, the purity rises from ~25% to nearly 90%.

High precision flavor physics measurements are an essential complement to the direct searches for new physics at the LHC. Such measurements can be performed at an upgraded KEKB accelerator. The status of the SuperKEKB collider and Belle II detector is presented in this article., Comment: Presented at Flavor Physics and CP Violation - FPCP 2010, Turin, Italy, May 25-29, 2010

Measurements of production cross sections and polarizations are essential inputs for a theoretical understanding of heavy vector meson production. In this article the CDF measurement of the Y(1S) polarization in the kinematic range |y|<0.6 and 2 < pT [GeV/c] < 40 using a data sample of 2.9/fb is described. Compared to the CDF Run I measurement, with which it agrees, it extends the covered pT range, allowing for a better comparison to predictions in the perturbative regime. The observed trend towards longitudinal polarization at high transverse momentum disagrees with predictions based on non-relativistic QCD., Comment: To appear in the proceedings of XVIII International Workshop on Deep-Inelastic Scattering and Related Subjects, April 19 -23, 2010, Florence, Italy

Since the discovery of the X(3872) in 2003 the B-factory experiments BaBar and Belle have been driving forces in the spectroscopy of new charmonium-like states. In this article the latest results on the decays X(3872) -> D0 D*0bar and X(3872) -> psi gamma, where psi stands for J/psi or psi(2S), are presented and analyses of Z(4430)+ -> psi pi+ and Z(4050/4250)+ -> chi_c1 pi+ are discussed., Comment: to be published in the proceedings of DIS-2009, XVIIth. International Workshop on Deep-Inelastic Scattering and Related Subjects, Madrid, Spain, April 26-30, 2009

While B0 and B+ mesons are well studied at B-factories, large samples of B0s mesons are only available at the Tevatron so far. Since the B0s meson consists of quarks of the second and third generation it provides a complementary probe for searches for new physics effects. Results of the CDF and D0 experiments on the decays B0s -> mu+ mu- and B0s -> mu+ mu- phi as well as on CP violation in B0s mixing and in interference between mixing and decay are presented., Comment: to be published in the proceedings of DIS-2009, XVIIth. International Workshop on Deep-Inelastic Scattering and Related Subjects, Madrid, Spain, April 26-30, 2009

The measurements of rare decays are highly sensitive to physics beyond the standard model. In this article limits on the branching ratios of the decays B0s -> mu+mu-, D0 -> mu+mu- and D+ -> pi+mu+mu- are presented. Furthermore the first measurement of the branching fraction and CP asymmetry of Lambda_b -> p pi- and Lambda_b -> p K- decays is described. Data samples with an integrated luminosity of up to 2/fb collected at the Tevatron ppbar-collider at sqrt(s)=1.96 TeV were used in these analyses. The results are consistent with the standard model predictions and tighten the constraints on new physics models., Comment: To appear in the proceedings of 43rd Rencontres de Moriond on QCD and Hadronic Interactions, La Thuile, Italy, 8-15 Mar 2008

The Bs meson is an interesting particle to study because a sizable mixing induced CP violation in the Bs-Bsbar system would be an indication for physics beyond the Standard Model. In this paper we present a measurement of the lifetime difference DeltaGamma between the Bs mass eigenstates and the CP violating phase in the decay Bs -> J/psi phi. In 1.7 fb^-1 of data collected with the CDF II detector at the Tevatron ppbar collider we measure DeltaGamma = 0.076 +0.059-0.063 (stat.) +- 0.006 (syst.) ps^-1, well consistent with the Standard Model prediction, and a mean Bs lifetime of ctau_s = 456 +-13 (stat.) +- 7 (syst.) m^-6. We find no evidence for CP violation., Comment: Submitted for the SUSY07 proceedings, 4 pages, LaTeX, 9 eps figures