arXiv subjects

Saptaparna Bhattacharya

Publications and source records attributed to Saptaparna Bhattacharya.

15 recordsLinked to original sources

arXiv2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML), silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.

physics.ins-det↗

arXiv2026

Early Career Issues in Particle Physics

Particle physics stands at a crossroads. The discovery of the Higgs boson in 2012 completed the Standard Model, but it also opened a new set of fundamental questions about the nature of our universe. Answering these questions, from the hierarchy problem and the nature of dark matter to the origin of neutrino masses, will require a new generation of powerful and sophisticated experiments. The global community is currently engaged in a comprehensive, long-term planning process to determine the next big machine. These discussions are not merely technical. The decisions made in the coming years will shape the field until 2060 and beyond. This extended timeline has a direct and immediate impact on the lives and careers of the field's youngest members: the graduate students, postdoctoral fellows, and other early-career researchers (ECRs) who will be tasked with designing, building, and ultimately analyzing the data from these future facilities. This proceeding provides an overview of the key issues facing ECRs in particle physics today, based on a talk delivered on the subject. It begins by surveying the future collider landscape from an ECR perspective. It then delves into the critical feedback gathered directly from ECRs through large-scale surveys, focusing on their primary concerns and actionable recommendations. Following this, it presents an analysis of the academic job market, the important but often unrewarded role of science outreach, and the emerging dual-edged challenge and opportunity of artificial intelligence. The paper concludes by highlighting the indispensable support networks available to ECRs, which are vital for navigating this complex and uncertain career path.

hep-ex↗

arXiv2026

Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision

Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape cosmic evolution. This whitepaper presents a vision for how Artificial Intelligence (AI) can accelerate discovery in this field. We outline grand challenges that must be addressed to enable transformative breakthroughs and describe how current and planned experimental facilities can implement this vision to advance our understanding of the vast and complex physical world from the smallest to the largest scales. We show how facilities currently under construction, such as the HL-LHC, DUNE and soon EIC, can both benefit from and serve as proving grounds for this vision, while also enabling a longer-term goal for how future experiments -- like FCC-ee at CERN, IceCube-Gen2, a Muon Collider in the U.S., and smaller to mid-scale projects -- can be fully AI-native. We describe how a truly national-scale collaboration, jointly managed across large funding partners, and involving both DOE laboratories and universities, can make this happen.

hep-ex↗

arXiv2025

The Critical Importance of Software for HEP

Particle physics has an ambitious and broad global experimental programme for the coming decades. Large investments in building new facilities are already underway or under consideration. Scaling the present processing power and data storage needs by the foreseen increase in data rates in the next decade for HL-LHC is not sustainable within the current budgets. As a result, a more efficient usage of computing resources is required in order to realise the physics potential of future experiments. Software and computing are an integral part of experimental design, trigger and data acquisition, simulation, reconstruction, and analysis, as well as related theoretical predictions. A significant investment in computing and software is therefore critical. Advances in software and computing, including artificial intelligence (AI) and machine learning (ML), will be key for solving these challenges. Making better use of new processing hardware such as graphical processing units (GPUs) or ARM chips is a growing trend. This forms part of a computing solution that makes efficient use of facilities and contributes to the reduction of the environmental footprint of HEP computing. The HEP community already provided a roadmap for software and computing for the last EPPSU, and this paper updates that, with a focus on the most resource critical parts of our data processing chain.

hep-ex↗

arXiv2024

LHC EFT WG Note: SMEFT predictions, event reweighting, and simulation

This note gives an overview of the tools for predicting expectations in the Standard Model effective field theory (SMEFT) at the tree level and one loop available through event generators. Methods of event reweighting, the separate simulation of squared matrix elements, and the simulation of the full SMEFT process are compared in terms of statistical efficacy and potential biases.

hep-ph↗

arXiv2024

EFT Workshop at Notre Dame

The LPC EFT workshop was held April 25-26, 2024 at the University of Notre Dame. The workshop was organized into five thematic sessions: "how far beyond linear" discusses issues of truncation and validity in interpretation of results with an eye towards practicality; "reconstruction-level results" visits the question of how best to design analyses directly targeting inference of EFT parameters; "logistics of combining likelihoods" addresses the challenges of bringing a diverse array of measurements into a cohesive whole; "unfolded results" tackles the question of designing fiducial measurements for later use in EFT interpretations, and the benefits and limitations of unfolding; and "building a sample library" addresses how best to generate simulation samples for use in data analysis. This document serves as a summary of presentations, subsequent discussions, and actionable items identified over the course of the workshop.

hep-ex↗

arXiv2023

A sensitivity study of triboson production processes to dimension-6 EFT operators at the LHC

We present the first parton-level study of anomalous effects in triboson production in both fully and semi-leptonic channels in proton-proton collisions at 13 TeV at the Large Hadron Collider (LHC). The sensitivity to anomalies induced by a minimal set of bosonic dimension-6 operators from the Warsaw basis is evaluated with specific analyses for each final state. A likelihood-based strategy is employed to assess the most sensitive kinematic observables per channel, where the contribution of Effective Field Theory operators is parameterized at either the linear or quadratic level. The impact of the mutual interference terms of pairs of operators on the sensitivity is also examined. This benchmark study explores the complementarity and overlap in sensitivity between different triboson measurements and paves the way for future analyses at the LHC experiments. The statistical combination of the considered final states allows setting stringent bounds on five bosonic Wilson coefficients.

hep-ph↗

arXiv2022

Report of the Topical Group on Electroweak Precision Physics and Constraining New Physics for Snowmass 2021

The precise measurement of physics observables and the test of their consistency within the standard model (SM) are an invaluable approach, complemented by direct searches for new particles, to determine the existence of physics beyond the standard model (BSM). Studies of massive electroweak gauge bosons (W and Z bosons) are a promising target for indirect BSM searches, since the interactions of photons and gluons are strongly constrained by the unbroken gauge symmetries. They can be divided into two categories: (a) Fermion scattering processes mediated by s- or t-channel W/Z bosons, also known as electroweak precision measurements; and (b) multi-boson processes, which include production of two or more vector bosons in fermion-antifermion annihilation, as well as vector boson scattering (VBS) processes. The latter categories can test modifications of gauge-boson self-interactions, and the sensitivity is typically improved with increased collision energy. This report evaluates the achievable precision of a range of future experiments, which depend on the statistics of the collected data sample, the experimental and theoretical systematic uncertainties, and their correlations. In addition it presents a combined interpretation of these results, together with similar studies in the Higgs and top sector, in the Standard Model effective field theory (SMEFT) framework. This framework provides a model-independent prescription to put generic constraints on new physics and to study and combine large sets of experimental observables, assuming that the new physics scales are significantly higher than the EW scale.

hep-ph↗

arXiv2022

A standard convention for particle-level Monte Carlo event-variation weights

Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.

hep-ph↗

arXiv2022

GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter

We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used is based on Graph Neural Networks (GNNs) and directly analyzes the hits in each HGCAL endcap. The ML algorithm is trained to predict clusters of hits originating from the same incident particle by labeling the hits with the same cluster index. We impose simple criteria to assess whether the hits associated as a cluster by the prediction are matched to those hits resulting from any particular individual incident particles. The algorithm is studied by simulating two tau leptons in each of the two HGCAL endcaps, where each tau may decay according to its measured standard model branching probabilities. The simulation includes the material interaction of the tau decay products which may create additional particles incident upon the calorimeter. Using this varied multiparticle environment we can investigate the application of this reconstruction technique and begin to characterize energy containment and performance.

physics.ins-det↗

arXiv2019

Bayesian Block Histogramming for High Energy Physics

The Bayesian Block algorithm, originally developed for applications in astronomy, can be used to improve the binning of histograms in high energy physics. The visual improvement can be dramatic, as shown here with two simple examples. More importantly, this algorithm and the histogram is produces is a non-parametric density estimate, providing a description of background distributions that does not suffer from the arbitrariness of ad hoc analytical functions. The statistical power of an hypothesis test based on Bayesian Blocks is nearly as good as that obtained by fitting analytical functions. Two examples are provided: a narrow peak on a smoothly-falling background, and an excess in the tail of a background that falls rapidly over several orders of magnitude. These examples show the usefulness of the binning provided by the Bayesian Blocks algorithm both for presentation of data and when searching for new physics.

physics.data-an↗

arXiv2013

Search for Exotic Top Partners at sqrt(s) = 8 TeV

We present searches for heavy top and bottom quark partners at CMS using data collected at sqrt(s) = 8 TeV. Such partners, if vector-like, occur in models such as the Little Higgs and Large Extra Dimensions. Fermionic top partners could also occur in composite Higgs models. The searches presented here span a wide range of final states, from lepton plus jets to multi-leptonic, and exclusion limits are set on mass and production cross sections as a function of branching ratios of the heavy quarks to their decay products.

hep-ex↗

arXiv2013

Prospects for a Heavy Vector-Like Charge 2/3 Quark T search at the LHC with \sqrt{s}=14 TeV and 33 TeV. "A Snowmass 2013 Whitepaper"

We present the prospects for the discovery or exclusion of heavy vector-like charge 2/3 quarks, T, in proton-proton collisions at two center-of-mass energies, 14 and 33 TeV at the LHC. In this note, the pair production of T quark and its antiparticle, with decays to W boson and a b quark (Wb), a top quark and the Higgs boson (tH), and a top quark and Z boson (tZ) are investigated. Higgs boson decays to $b\bar b$ and $W^+W^-$ final states are selected for this study.

hep-ex↗

arXiv2011

Efficiency measurement of b-tagging algorithms developed by the CMS experiment

Identification of jets originating from b quarks (b-tagging) is a key element of many physics analyses at the LHC. Various algorithms for b-tagging have been developed by the CMS experiment to identify b-tagged jets with a typical efficiency between 40% and 70% while keeping the rate of misidentified light quark jets between 0.1% and 10%. An important step, in order to be able to use these tools in physics analysis, is the determination of the efficiency for tagging b-jets. Several methods to measure the efficiencies of the lifetime based b-tagging algorithms are presented. Events that have jets with muons are used to enrich a jet sample in heavy flavor content. The efficiency measurement relies on the transverse momentum of the muon relative to the jet axis or on solving a system of equations which incorporate two uncorrelated taggers. Another approach uses the number of b-tagged jets in top pair events to estimate the efficiency. The results obtained in 2010 data and the uncertainties obtained with the different techniques are reported. The rate of misidentified light quarks have been measured using the "negative" tagging technique.

hep-ex↗

arXiv2010

Czochralski Silicon as a Detector Material for S-LHC Tracker Volumes

With an expected ten-fold increase in luminosity in S-LHC, the radiation environment in the tracker volumes will be considerably harsher for silicon-based detectors than the already harsh LHC environment. Since 2006, a group of CMS institutes, using a modified CMS DAQ system, has been exploring the use of Magnetic Czochralski silicon as a detector element for the strip tracker layers in S-LHC experiments. Both p+/n-/n+ and n+/p-/p+ sensors have been characterized, irradiated with proton and neutron sources, assembled into modules, and tested in a CERN beamline. There have been three beam studies to date and results from these suggest that both p+/n-/n+ and n+/p-/p+ Magnetic Czochralski silicon are sufficiently radiation hard for the $R>25$ cm regions of S-LHC tracker volumes. The group has also explored the use of forward biasing for heavily irradiated detectors, and although this mode requires sensor temperatures less than -50\,$^\circ$C, the charge collection efficiency appears to be promising.

physics.ins-det↗