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Kenneth Long

Publications and source records attributed to Kenneth Long.

16 recordsLinked to original sources
arXiv2026

Efficient binned profile likelihood minimization for precision measurements with RABBIT

Precision measurements at the LHC increasingly rely on binned profile maximum likelihood fits with thousands of bins and nuisance parameters, and the High-Luminosity LHC will push these numbers further. Fast and robust minimization of such likelihoods is crucial for timely analysis development and accurate inference. We present Rabbit (Rapid Automatic Bin-Based Inference Tool), a Python framework that exploits differentiable programming in TensorFlow 2 to perform this task on CPUs and GPUs. Automatic differentiation provides exact gradients and Hessian-vector products for a trust-region minimizer operating in Krylov subspaces, and just-intime compilation yields near-C++ execution speed. Rabbit implements flexible statistical models with analytic treatments where possible, supports symmetrization options that establish Gaussian approximations and a linearized likelihood formulation with deterministic solutions, and focuses on measuring physical observables through differentiable transformations of the model, including unfolded differential cross sections. Benchmarks on synthetic models demonstrate excellent scaling with the number of bins and parameters, outperforming established tools in challenging regimes where these fail to converge within reasonable time.

hep-ex↗
arXiv2023

When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA

Bayesian Neural Networks (BayesNNs) have demonstrated their capability of providing calibrated prediction for safety-critical applications such as medical imaging and autonomous driving. However, the high algorithmic complexity and the poor hardware performance of BayesNNs hinder their deployment in real-life applications. To bridge this gap, this paper proposes a novel multi-exit Monte-Carlo Dropout (MCD)-based BayesNN that achieves well-calibrated predictions with low algorithmic complexity. To further reduce the barrier to adopting BayesNNs, we propose a transformation framework that can generate FPGA-based accelerators for multi-exit MCD-based BayesNNs. Several novel optimization techniques are introduced to improve hardware performance. Our experiments demonstrate that our auto-generated accelerator achieves higher energy efficiency than CPU, GPU, and other state-of-the-art hardware implementations.

cs.LG↗
arXiv2022

End-to-end multi-particle reconstruction in high occupancy imaging calorimeters with graph neural networks

We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular calorimeters similar to that foreseen for the high-luminosity upgrade of the CMS detector. The algorithm exploits a distance-weighted graph neural network, trained with object condensation, a graph segmentation technique. Through a single-shot approach, the reconstruction task is paired with energy regression. We describe the reconstruction performance in terms of efficiency as well as in terms of energy resolution. In addition, we show the jet reconstruction performance of our method and discuss its inference computational cost. To our knowledge, this work is the first-ever example of single-shot calorimetric reconstruction of ${\cal O}(1000)$ particles in high-luminosity conditions with 200 pileup.

physics.ins-det↗
arXiv2022

Simulated Detector Performance at the Muon Collider

In this paper we report on the current status of studies on the expected performance for a detector designed to operate in a muon collider environment. Beam-induced backgrounds (BIB) represent the main challenge in the design of the detector and the event reconstruction algorithms. The current detector design aims to show that satisfactory performance can be achieved, while further optimizations are expected to significantly improve the overall performance. We present the characterization of the expected beam-induced background, describe the detector design and software used for detailed event simulations taking into account BIB effects. The expected performance of charged-particle reconstruction, jets, electrons, photons and muons is discussed, including an initial study on heavy-flavor jet tagging. A simple method to measure the delivered luminosity is also described. Overall, the proposed design and reconstruction algorithms can successfully reconstruct the high transverse-momentum objects needed to carry out a broad physics program.

hep-ex↗
arXiv2022

Promising Technologies and R&D Directions for the Future Muon Collider Detectors

Among the post-LHC generation of particle accelerators, the muon collider represents a unique machine with capability to provide very high energy leptonic collisions and to open the path to a vast and mostly unexplored physics programme. However, on the experimental side, such great physics potential is accompanied by unprecedented technological challenges, due to the fact that muons are unstable particles. Their decay products interact with the machine elements and produce an intense flux of background particles that eventually reach the detector and may degrade its performance. In this paper, we present technologies that have a potential to match the challenging specifications of a muon collider detector and outline a path forward for the future R&D efforts.

physics.ins-det↗
arXiv2022

Muon Collider Physics Summary

The perspective of designing muon colliders with high energy and luminosity, which is being investigated by the International Muon Collider Collaboration, has triggered a growing interest in their physics reach. We present a concise summary of the muon colliders potential to explore new physics, leveraging on the unique possibility of combining high available energy with very precise measurements.

hep-ph↗
arXiv2022

The physics case of a 3 TeV muon collider stage

In the path towards a muon collider with center of mass energy of 10 TeV or more, a stage at 3 TeV emerges as an appealing option. Reviewing the physics potential of such muon collider is the main purpose of this document. In order to outline the progression of the physics performances across the stages, a few sensitivity projections for higher energy are also presented. There are many opportunities for probing new physics at a 3 TeV muon collider. Some of them are in common with the extensively documented physics case of the CLIC 3 TeV energy stage, and include measuring the Higgs trilinear coupling and testing the possible composite nature of the Higgs boson and of the top quark at the 20 TeV scale. Other opportunities are unique of a 3 TeV muon collider, and stem from the fact that muons are collided rather than electrons. This is exemplified by studying the potential to explore the microscopic origin of the current $g$-2 and $B$-physics anomalies, which are both related with muons.

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↗
arXiv2021

Multi-particle reconstruction in the High Granularity Calorimeter using object condensation and graph neural networks

The high-luminosity upgrade of the LHC will come with unprecedented physics and computing challenges. One of these challenges is the accurate reconstruction of particles in events with up to 200 simultaneous proton-proton interactions. The planned CMS High Granularity Calorimeter offers fine spatial resolution for this purpose, with more than 6 million channels, but also poses unique challenges to reconstruction algorithms aiming to reconstruct individual particle showers. In this contribution, we propose an end-to-end machine-learning method that performs clustering, classification, and energy and position regression in one step while staying within memory and computational constraints. We employ GravNet, a graph neural network, and an object condensation loss function to achieve this task. Additionally, we propose a method to relate truth showers to reconstructed showers by maximising the energy weighted intersection over union using maximal weight matching. Our results show the efficiency of our method and highlight a promising research direction to be investigated further.

physics.ins-det↗
arXiv2021

Vector Boson Scattering Processes: Status and Prospects

Insight into the electroweak (EW) and Higgs sectors can be achieved through measurements of vector boson scattering (VBS) processes. The scattering of EW bosons are rare processes that are precisely predicted in the Standard Model (SM) and are closely related to the Higgs mechanism. Modifications to VBS processes are also predicted in models of physics beyond the SM (BSM), for example through changes to the Higgs boson couplings to gauge bosons and the resonant production of new particles. In this review, experimental results and theoretical developments of VBS at the Large Hadron Collider, its high luminosity upgrade, and future colliders are presented.

hep-ph↗
arXiv2020

Muon Colliders: Opening New Horizons for Particle Physics

Particle colliders have arguably been the most important instruments for particle physics over the past 50 years. As they became more powerful, they were used to push the frontier of our knowledge into previously uncharted territory. The LHC, the highest energy collider to date, at which the Higgs boson was discovered, is a prime example. To continue along the road into the Terra Promissa beyond the Standard Model requires colliders with energy reach even greater than that of the LHC. Beams of muons offer enormous potential for the exploration of the energy frontier. Since the muon is a fundamental particle, its full energy is available in collisions in contrast to protons which are composed of quarks and gluons. However, muon beams decay rapidly, which presents a special challenge for a collider. Recent research indicates that the technologies required to overcome this challenge are within our grasp and may offer a cost-effective and energy-efficient option to continue our explorations. A new international collaboration is forming to bring together the diverse expertise and complementary capabilities from around the world to realize the muon collider as the next-generation energy-frontier discovery machine.

physics.acc-ph↗
arXiv2020

New physics at nuSTORM

In this work we investigate the usefulness of nuSTORM as a probe of two new-physics scenarios which are sterile neutrinos and non-unitarity of the neutrino mixing matrix. For the sterile neutrino we show the importance of the neutral current events when combined with the charged current events to constrain the effective mixing angle, $\theta_{\mu \mu}$, and the sterile mixing angles $\theta_{14}$ and $\theta_{24}$. We also study the role nuSTORM will play in the study of neutrino oscillation physics if the three generation neutrino mixing matrix is non-unitary. In this context we elucidate the role of nuSTORM, considering both charged current and neutral current events, in constraining the various non-unitarity parameters such as $\alpha_{11}$, $|\alpha_{21}|$ and $\alpha_{22}$.

hep-ph↗
arXiv2020

Beyond the Standard Model in Vector Boson Scattering Signatures

The high-energy scattering of massive electroweak bosons, known as vector boson scattering (VBS), is a sensitive probe of new physics. VBS signatures will be thoroughly and systematically investigated at the LHC with the large data samples available and those that will be collected in the near future. Searches for deviations from Standard Model (SM) expectations in VBS facilitate tests of the Electroweak Symmetry Breaking (EWSB) mechanism. Current state-of-the-art tools and theory developments, together with the latest experimental results, and the studies foreseen for the near future are summarized. A review of the existing Beyond the SM (BSM) models that could be tested with such studies as well as data analysis strategies to understand the interplay between models and the effective field theory paradigm for interpreting experimental results are discussed. This document is a summary of the EU COST network "VBScan" workshop on the sensitivity of VBS processes for BSM frameworks that took place December 4-5, 2019 at the LIP facilities in Lisbon, Portugal. In this manuscript we outline the scope of the workshop, summarize the different contributions from theory and experiment, and discuss the relevant findings.

hep-ph↗
arXiv2018

Future Opportunities in Accelerator-based Neutrino Physics

This document summarizes the conclusions of the Neutrino Town Meeting held at CERN in October 2018 to review the neutrino field at large with the aim of defining a strategy for accelerator-based neutrino physics in Europe. The importance of the field across its many complementary components is stressed. Recommendations are presented regarding the accelerator based neutrino physics, pertinent to the European Strategy for Particle Physics. We address in particular i) the role of CERN and its neutrino platform, ii) the importance of ancillary neutrino cross-section experiments, and iii) the capability of fixed target experiments as well as present and future high energy colliders to search for the possible manifestations of neutrino mass generation mechanisms.

hep-ex↗
arXiv2017

Multi-boson Measurements in CMS

Recent results from the CMS experiment on the production of multiple vector bosons in proton-proton collisions at the CERN LHC are presented. Measurements of WZ and ZZ production with fully leptonic decays, Z$(\nu\nu)\gamma$, and WV (V $=$ W,Z $\rightarrow q\bar{q}$) production at 8 and 13 TeV are discussed. Selected cross section measurements, unfolded differential measurements, and limits on anomalous triple gauge couplings are presented and compared with theoretical predictions.

hep-ex↗