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View article: Analysis Facilities for the HL-LHC White Paper
Analysis Facilities for the HL-LHC White Paper Open
This white paper presents the current status of the R&D for Analysis Facilities (AFs) and attempts to summarize the views on the future direction of these facilities. These views have been collected through the High Energy Physics (HEP) So…
View article: Track reconstruction as a service for collider physics
Track reconstruction as a service for collider physics Open
Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant computational demands. Existing track reconstruction algorithms h…
View article: Refining Jets for CMS Run 3 using Fast Simulation
Refining Jets for CMS Run 3 using Fast Simulation Open
As the LHC moves into its high-luminosity phase, the CMS experiment must handle more complex data collected at much higher rates. While the Geant4-based simulation application (FullSim) provides highly accurate simulation to complement rea…
View article: R&D Adoption and Progress in Full Simulation of the CMS experiment
R&D Adoption and Progress in Full Simulation of the CMS experiment Open
In this work we report on evolution of usage of Geant4 within CMSSW and adaptation of the newest Geant4 11.2.1, which is expected to be used for CMS simulation production in 2025. Physics validation results and results on CPU performance a…
View article: Using containers to speed up development, to run integration tests and to teach about distributed systems
Using containers to speed up development, to run integration tests and to teach about distributed systems Open
GlideinWMS is a workload manager provisioning resources for many experiments including CMS and DUNE. The software is distributed both as native packages and specialized production containers. Following an approach used in other communities…
View article: Deployment of inference as a service at the US CMS Tier-2 data centers
Deployment of inference as a service at the US CMS Tier-2 data centers Open
Coprocessors, especially GPUs, will be a vital ingredient of data production workflows at the HL-LHC. At CMS, the GPU-as-a-service approach for production workflows is implemented by the SONIC project (Services for Optimized Network Infere…
View article: Simulating the CMS High Granularity Calorimeter with ML
Simulating the CMS High Granularity Calorimeter with ML Open
Detector simulation is a key component of physics analysis and related activities in CMS. In the upcoming High Luminosity LHC era, simulation will be required to use a smaller fraction of computing in order to satisfy resource constraints.…
View article: Searching for Strongly Coupled Dark Sectors with Unsupervised and Generative Learning
Searching for Strongly Coupled Dark Sectors with Unsupervised and Generative Learning Open
Recipient of the URA Early Career Award for groundbreaking searches for dark matter arising from strongly coupled dark sectors with the CMS detector, pioneering work in ML-based model-independent anomaly detection for collider and astrophy…
View article: Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server
Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server Open
View article: Dark QCD: the Next Frontier in Dark Matter
Dark QCD: the Next Frontier in Dark Matter Open
There has been a surge of interest in hidden valley models with new, strong forces, sometimes called "dark QCD". These models propose asymmetric, composite dark matter in the form of "dark hadrons" that would evade direct and indirect boun…
View article: Evolution of Generation and Simulation Techniques in the AI/ML Era
Evolution of Generation and Simulation Techniques in the AI/ML Era Open
As we probe rarer processes, explore more complicated models, and make more precise measurements: o Accuracy and computational speed increase in importance! 2
View article: Analysis Facilities White Paper
Analysis Facilities White Paper Open
This white paper presents the current status of the R&D for Analysis Facilities (AFs) and attempts to summarize the views on the future direction of these facilities. These views have been collected through the High Energy Physics (HEP) So…
View article: Full Simulation of CMS for Run-3 and Phase-2
Full Simulation of CMS for Run-3 and Phase-2 Open
In this contribution we report the status of the CMS Geant4 simulation and the prospects for Run-3 and Phase-2. Firstly, we report about our experience during the start of Run-3 with Geant4 10.7.2, the common software package DD4hep for ge…
View article: Gamma Irradiation as a Pretreatment Method for Microbial Fuel Cell Anode Substrate
Gamma Irradiation as a Pretreatment Method for Microbial Fuel Cell Anode Substrate Open
View article: Refining fast simulation using machine learning
Refining fast simulation using machine learning Open
At the CMS experiment, a growing reliance on the fast Monte Carlo application (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. The FastSim chain is roughly 10 times faster than the application base…
View article: Optimizing High Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server
Optimizing High Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server Open
With machine learning applications now spanning a variety of computational tasks, multi-user shared computing facilities are devoting a rapidly increasing proportion of their resources to such algorithms. Graph neural networks (GNNs), for …
View article: Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing Open
View article: Denoising diffusion models with geometry adaptation for high fidelity calorimeter simulation
Denoising diffusion models with geometry adaptation for high fidelity calorimeter simulation Open
Simulation is crucial for all aspects of collider data analysis, but the available computing budget in the High Luminosity LHC era will be severely constrained. Generative machine learning models may act as surrogates to replace physics-ba…
View article: Optimal mass variables for semivisible jets
Optimal mass variables for semivisible jets Open
Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with standard model hadrons in the form of semivisible jets. Classical mass reconstruction techniques may not be optim…
View article: Refining fast simulation using machine learning
Refining fast simulation using machine learning Open
At the CMS experiment, a growing reliance on the fast Monte Carlo application (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. The FastSim chain is roughly 10 times faster than the application base…
View article: Denoising diffusion models with geometry adaptation for high fidelity calorimeter simulation
Denoising diffusion models with geometry adaptation for high fidelity calorimeter simulation Open
Simulation is crucial for all aspects of collider data analysis, but the available computing budget in the High Luminosity LHC era will be severely constrained. Generative machine learning models may act as surrogates to replace physics-ba…
View article: Report on 2303.16253v3
Report on 2303.16253v3 Open
Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with standard model hadrons in the form of semivisible jets.Classical mass reconstruction techniques may not be optima…
View article: Report on 2303.16253v2
Report on 2303.16253v2 Open
Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with regular hadrons in the form of semivisible jets.Classical mass reconstruction techniques may not be optimal for t…
View article: Report on 2303.16253v2
Report on 2303.16253v2 Open
Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with regular hadrons in the form of semivisible jets.Classical mass reconstruction techniques may not be optimal for t…
View article: Fast & Accurate Calorimeter Simulation With Diffusion Models
Fast & Accurate Calorimeter Simulation With Diffusion Models Open
LHC increases, the scintillator tiles used in the CMS Hadronic Endcap calorimeter will lose their efficiency. This report outlines two possible radiation hard upgrade scenarios based on replacing the HE scintillators with quartz plates.
View article: Applications of Deep Learning to physics workflows
Applications of Deep Learning to physics workflows Open
Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing these datasets requires both sufficient compute power and …
View article: DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection Open
Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features. The…
View article: Optimal Mass Variables for Semivisible Jets
Optimal Mass Variables for Semivisible Jets Open
Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with standard model hadrons in the form of semivisible jets. Classical mass reconstruction techniques may not be optim…
View article: DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection Open
We present the data used in "DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection". It was also used in the conference paper presented in Machine Learning and the…
View article: GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter
GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter Open
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…