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The reconstruction of charged particle trajectories is a crucial challenge of particle physics experiments as it directly impacts particle reconstruction and physics performances. To reconstruct these trajectories, different reconstruction algorithms are used sequentially. Each of these algorithms uses many configuration parameters that must be fine-tuned to properly account for the detector/experimental setup, the available CPU budget and the desired physics performance. Examples of such parameters are cut values limiting the algorithm's search space, approximations accounting for complex phenomenons, or parameters controlling algorithm performance. Until now, these parameters had to be optimised by human experts, which is inefficient and raises issues for the long-term maintainability of such algorithms. Previous experience using machine learning for particle reconstruction (such as the TrackML challenge) has shown that they can be easily adapted to different experiments by learning directly from the data. We propose to bring the same approach to the classic track reconstruction algorithms by connecting them to an agent-driven optimiser, allowing us to find the best input parameters using an iterative tuning approach. We have so far demonstrated this method on different track reconstruction algorithms within A Common Tracking Software (ACTS) framework using the Open Data Detector (ODD). These algorithms include the trajectory seed reconstruction and selection, the particle vertex reconstruction and the generation of simplified material maps used for trajectory reconstruction., Comment: 6 pages, 2 figures, Talk presented at the 21st International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2022)

The reconstruction of particle trajectories is a key challenge of particle physics experiments, as it directly impacts particle identification and physics performances while also representing one of the main CPU consumers of many high-energy physics experiments. As the luminosity of particle colliders increases, this reconstruction will become more challenging and resource-intensive. New algorithms are thus needed to address these challenges efficiently. One potential step of track reconstruction is ambiguity resolution. In this step, performed at the end of the tracking chain, we select which tracks candidates should be kept and which must be discarded. The speed of this algorithm is directly driven by the number of track candidates, which can be reduced at the cost of some physics performance. Since this problem is fundamentally an issue of comparison and classification, we propose to use a machine learning-based approach to the Ambiguity Resolution. Using a shared-hits-based clustering algorithm, we can efficiently determine which candidates belong to the same truth particle. Afterwards, we can apply a Neural Network (NN) to compare those tracks and decide which ones are duplicates and which ones should be kept. This approach is implemented within A Common Tracking Software (ACTS) framework and tested on the Open Data Detector (ODD), a realistic virtual detector similar to a future ATLAS one. This new approach was shown to be 15 times faster than the default ACTS algorithm while removing 32 times more duplicates down to less than one duplicated track per event., Comment: 8 pages, 3 figures, 1 table, Talk presented at the 26th International Conference on Computing in High Energy & Nuclear Physics (CHEP 2023)

Particle tracking is among the most sophisticated and complex part of the full event reconstruction chain. A number of reconstruction algorithms work in a sequence to build these trajectories from detector hits. These algorithms use many configuration parameters that need to be fine-tuned to properly account for the detector/experimental setup, the available CPU budget and the desired physics performance. The most popular method to tune these parameters is hand-tuning using brute-force techniques. These techniques can be inefficient and raise issues for the long-term maintainability of such algorithms. The open-source track reconstruction software framework known as "A Common Tracking Framework (ACTS)" offers an alternative solution to these parameter tuning techniques through the use of automatic parameter optimization algorithms. ACTS comes equipped with an auto-tuning suite that provides necessary setup for performing optimization of input parameters belonging to track reconstruction algorithms. The user can choose the tunable parameters in a flexible way and define a cost/benefit function for optimizing the full reconstruction chain. The fast execution speed of ACTS allows the user to run several iterations of optimization within a reasonable time bracket. The performance of these optimizers has been demonstrated on different track reconstruction algorithms such as trajectory seed reconstruction and selection, particle vertex reconstruction and generation of simplified material map, and on different detector geometries such as Generic Detector and Open Data Detector (ODD). We aim to bring this approach to all aspects of trajectory reconstruction by having a more flexible integration of tunable parameters within ACTS.

The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned., Comment: 27 pages

Common and community software packages, such as ROOT, Geant4 and event generators have been a key part of the LHC's success so far and continued development and optimisation will be critical in the future. The challenges are driven by an ambitious physics programme, notably the LHC accelerator upgrade to high-luminosity, HL-LHC, and the corresponding detector upgrades of ATLAS and CMS. In this document we address the issues for software that is used in multiple experiments (usually even more widely than ATLAS and CMS) and maintained by teams of developers who are either not linked to a particular experiment or who contribute to common software within the context of their experiment activity. We also give space to general considerations for future software and projects that tackle upcoming challenges, no matter who writes it, which is an area where community convergence on best practice is extremely useful., Comment: 40 pages contribution to Snowmass 2021

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.

In modern High Energy Physics (HEP) experiments visualization of experimental data has a key role in many activities and tasks across the whole data chain: from detector development to monitoring, from event generation to reconstruction of physics objects, from detector simulation to data analysis, and all the way to outreach and education. In this paper, the definition, status, and evolution of data visualization for HEP experiments will be presented. Suggestions for the upgrade of data visualization tools and techniques in current experiments will be outlined, along with guidelines for future experiments. This paper expands on the summary content published in the HSF \emph{Roadmap} Community White Paper~\cite{HSF-CWP-2017-01}

This paper proposes a quantitative model of the circulation of foreign news based on a gravity-like model of spatial interaction disaggregated by time, media and countries of interest. The analysis of international RSS news stories published by 31 daily newspapers in 2015 demonstrates, first, that many of the laws of circulation of international news predicted half a century ago by Galtung and Ruge and by {\"O}stgaard are still valid. The salience of countries in media remains strongly determined by size effects (area, population), with prominent coverage of rich countries (GDP/capita) with elite status (permanent members of UNSC, the Holy See). The effect of geographical distance and a common language remains a major factor of media coverage in newsrooms. Contradicting the flat world hypothesis, global journalism remains an exception, and provincialism is the rule. The disaggregation of the model by media demonstrates that newspapers are not following exactly the same rules and are more or less sensitive to distance, a common language or elite status. The disaggregation of the model by week suggests that the rules governing foreign news can also be temporarily modified by exceptional events that eliminate the usual effects of salience and relatedness, producing short periods of 'global consensus' that can benefit small, poor and remote countries. This paper concludes by recommending the use of a sample of carefully chosen diversified media rather than a large aggregation of data for global studies.

This article describes the generation of elastic shear waves in a soft medium using a laser beam. Our experiments show two different regimes depending on laser energy. Physical modeling of the underlying phenomena reveals a thermoelastic regime caused by a local dilatation resulting from temperature increase, and an ablative regime caused by a partial vaporization of the medium by the laser. Computed theoretical displacements are close to experimental measurements. A numerical study based on the physical modeling gives propagation patterns comparable to those generated experimentally. These results provide a physical basis for the feasibility of a shear wave elastography technique (a technique which measures a soft solid stiffness from shear wave propagation) by using a laser beam.

Elasticity is a fundamental cellular property that is related to the anatomy, functionality and pathological state of cells and tissues. However, current techniques based on cell deformation, atomic force microscopy or Brillouin scattering are rather slow and do not always accurately represent cell elasticity. Here, we have developed an alternative technique by applying shear wave elastography to the micrometer scale. Elastic waves were mechanically induced in live mammalian oocytes using a vibrating micropipette. These audible frequency waves were observed optically at 200,000 frames per second and tracked with an optical flow algorithm. Whole cell elasticity was then mapped using an elastography method inspired by the seismology field. Using this approach, we show that the elasticity of mouse oocyte is decreased when the oocyte cytoskeleton is disrupted with cytochalasin B. The technique is fast (less than 1 ms for data acquisition), precise (spatial resolution of a few micrometers), able to map internal cell structures, robust, and thus represents a tractable novel option for interrogating biomechanical properties of diverse cell types.

Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments over the next 10 years will require the HEP community to address a number of challenges in the area of software and computing. For this reason, the HEP software community has engaged in a planning process over the past two years, with the objective of identifying and prioritizing the research and development required to enable the next generation of HEP detectors to fulfill their full physics potential. The aim is to produce a Community White Paper which will describe the community strategy and a roadmap for software and computing research and development in HEP for the 2020s. The topics of event reconstruction and software triggers were considered by a joint working group and are summarized together in this document., Comment: Editors: Vladimir Gligorov and David Lange

Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments over the next 10 years will require the HEP community to address a number of challenges in the area of software and computing. For this reason, the HEP software community has engaged in a planning process over the past two years, with the objective of identifying and prioritizing the research and development required to enable the next generation of HEP detectors to fulfill their full physics potential. The aim is to produce a Community White Paper which will describe the community strategy and a roadmap for software and computing research and development in HEP for the 2020s. The topics of event reconstruction and software triggers were considered by a joint working group and are summarized together in this document., Comment: Editors Vladimir Vava Gligorov and David Lange

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.

This study presents the first observation of shear wave induced remotely within soft tissues. It was performed through the combination of a transcranial magnetic stimulation device and a permanent magnet. A physical model based on Maxwell and Navier equations was developed. Experiments were performed on a cryogel phantom and a chicken breast sample. Using an ultrafast ultrasound scanner, shear waves of respective amplitude of 5 and 0.5 micrometers were observed. Experimental and numerical results were in good agreement. This study constitutes the framework of an alternative shear wave elastography method.

We investigate the conductance of a Normal-Normal'-Superconductor (NN'S) junction, in which current injection destroys superconductivity in a small region N' of the superconductor, with a size varying with the applied voltage V. Voltage-dependent de Gennes-Saint James (dGSJ) bound states appearing in the N' slab lead to two distinct sets of conductance oscillations. We show that this effect significantly alters the conductance of systems for which $\kappa^2v_F \sim 10^9$ m/s such as pnictides ($\kappa$ and $v_F$ being the Ginzburg number and the Fermi velocity, respectively), and we discuss their consequences on the identification of the bosonic modes of strongly coupled superconductors.

Ultrasound speckle is a granular texture pattern appearing in ultrasound imaging. It can be used to distinguish tissues and identify pathologies. Lorentz force electrical impedance tomography is an ultrasound-based medical imaging technique of the tissue electrical conductivity. It is based on the application of an ultrasound wave in a medium placed in a magnetic field and on the measurement of the induced electric current due to Lorentz force. Similarly to ultrasound imaging, we hypothesized that a speckle could be observed with Lorentz force electrical impedance tomography imaging. In this study, we first assessed the theoretical similarity between the measured signals in Lorentz force electrical impedance tomography and in ultrasound imaging modalities. We then compared experimentally the signal measured in both methods using an acoustic and electrical impedance interface. Finally, a bovine muscle sample was imaged using the two methods. Similar speckle patterns were observed. This indicates the existence of an "acousto-electrical speckle" in the Lorentz force electrical impedance tomography with spatial characteristics driven by the acoustic parameters but due to electrical impedance inhomogeneities instead of acoustic ones as is the case of ultrasound imaging.

The ability of the Lorentz force to link a mechanical displacement to an electrical current presents a strong interest for medical acoustics, and three applications were studied in this thesis. In the first part of this work, a hydrophone was developed for mapping the particle velocity of an acoustic field. This hydrophone was constructed using a thin copper wire and an external magnetic field. A model was elaborated to determine the relationship between the acoustic pressure and the measured electrical current, which is induced by Lorentz force when the wire vibrates in the acoustic field of an ultrasound transducer. The built prototype was characterized and its spatial resolution, frequency response, sensitivity, robustness and directivity response were investigated. An imaging method called Lorentz Force Electrical Impedance Tomography was also studied. In this method, a biological tissue is vibrated by ultrasound in a magnetic field, which induces an electrical current by Lorentz force. The electrical impedance of the tissue can be deduced from the measurement of the current. This technique was applied for imaging a gelatin phantom, a beef muscle sample, and a thermal lesion in a chicken breast sample. This showed the method may be useful for providing additional contrast to conventional ultrasound imaging. Finally, this thesis demonstrated that shear waves can be generated in soft tissues using Lorentz force. This work was performed by applying an electrical current with two electrodes in a soft solid placed in a magnetic field. Shear waves were observed in gelatin phantom and liver sample. The speed of the shear waves were used to compute elasticity and their source to map the electrical conductivity of the samples., Comment: PhD thesis, in French

This study presents the first observation of elastic shear waves generated in soft solids using a dynamic electromagnetic field. The first and second experiments of this 5 study showed that Lorentz force can induce a displacement in a soft phantom and that this displacement was detectable by an ultrasound scanner using speckle-tracking algorithms. For a 100 mT magnetic field and a 10 ms, 100 mA peak-to-peak electrical burst, the displacement reached a magnitude of 1 um. In the third experiment, we showed that Lorentz force can induce shear waves in a phantom. A physical model 10 using electromagnetic and elasticity equations was proposed. Computer simulations were in good agreement with experimental results. The shear waves induced by Lorentz force were used in the last experiment to estimate the elasticity of a swine liver sample.

A Lorentz-force hydrophone consists of a thin wire placed inside a magnetic field. When under the influence of an ultrasound pulse, the wire vibrates and an electrical signal is induced by the Lorentz force that is proportional to the pulse amplitude. In this study a compact prototype of such a hydrophone is introduced and characterized, and the hydrodynamic model previously developed is refined. It is shown that the wire tension has a negligible effect on the measurement of pressure. The frequency response of the hydrophone reaches 1 MHz for wires with a diameter ranging between 70 and 400 \micro m. The hydrophone exhibits a directional response such that the signal amplitude differs by less than 3dB as the angle of the incident ultrasound pulse varies from -20$^o$ and +20$^o$. The linearity of the measured signal is confirmed across the 50 kPa to 10 MPa pressure range, and an excellent resistance to cavitation is observed. This hydrophone is of interest for high pressure ultrasound measurements including High Intensity Focused Ultrasound (HIFU) and ultrasonic measurements in difficult environments.

This article describes a method called Lorentz Force Electrical Impedance Tomography. The electrical conductivity of biological tissues can be measured through their sonication in a magnetic field: the vibration of the tissues inside the field induces an electrical current by Lorentz force. This current, detected by electrodes placed around the sample, is proportional to the ultrasonic pressure, to the strength of the magnetic field and to the electrical conductivity gradient along the acoustic axis. By focusing at different places inside the sample, a map of the electrical conductivity gradient can be established. In this study experiments were conducted on a gelatin phantom and on a beef sample, successively placed in a 300 mT magnetic field and sonicated with an ultrasonic transducer focused at 21 cm emitting 500 kHz bursts. Although all interfaces are not visible, in this exploratory study a good correlation is observed between the electrical conductivity image and the ultrasonic image. This method offers an alternative to detecting pathologies invisible to standard ultrasonography.