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Detailed detector simulation and reconstruction of physics objects at the LHC are very CPU intensive and hence time consuming due to the high energy and multiplicity of the Monte-Carlo events and the complexity of the detectors. We present…

Computational Physics · Physics 2007-05-23 Stephan Wynhoff

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of…

High Energy Physics - Experiment · Physics 2024-11-25 ATLAS Collaboration

Radiation damage significantly impacts the performance of silicon tracking detectors in Large Hadron Collider (LHC) experiments such as ATLAS and CMS, with signal reduction being the most critical effect; adjusting sensor bias voltage and…

High Energy Physics - Experiment · Physics 2025-01-22 Keerthi Nakkalil , Marco Bomben

The CDF detector simulation framework is integrated into an AC++ application used to process events in the CDF experiment. The simulation framework is based on the GEANT3 package. It holds the detector element geometry descriptions, allows…

Computational Physics · Physics 2014-11-18 E. Gerchtein , M. Paulini

Detector simulation and reconstruction are a significant computational bottleneck in particle physics. We develop Particle-flow Neural Assisted Simulations (Parnassus) to address this challenge. Our deep learning model takes as input a…

Data Analysis, Statistics and Probability · Physics 2024-11-22 Etienne Dreyer , Eilam Gross , Dmitrii Kobylianskii , Vinicius Mikuni , Benjamin Nachman , Nathalie Soybelman

Cycle-level simulators such as gem5 are widely used in microarchitecture design, but they are prohibitively slow for large-scale design space explorations. We present Concorde, a new methodology for learning fast and accurate performance…

We uncover an effective and communicative set of agents working with MadGraph. Agentic installation, learning-by-doing training, and user support provide easy access to state-of-the-art simulations and accelerate LHC research. We show in…

High Energy Physics - Phenomenology · Physics 2026-04-08 Tilman Plehn , Daniel Schiller , Nikita Schmal

The use of machine learning algorithms is an attractive way to produce very fast detector simulations for scattering reactions that can otherwise be computationally expensive. Here we develop a factorised approach where we deal with each…

Data Analysis, Statistics and Probability · Physics 2022-07-26 D. Darulis , R. Tyson , D. G. Ireland , D. I. Glazier , B. McKinnon , P. Pauli

The fortran version of the AcerDET package has been published in [1], and used in the multiple publications on the predictions for physics at LHC. The package provides, starting from list of particles in the event, the list of reconstructed…

High Energy Physics - Phenomenology · Physics 2015-07-06 Patryk Mikos , Elzbieta Richter-Was

We present version 3.4 of the CalcHEP software package which is designed for effective evaluation and simulation of high energy physics collider processes at parton level. The main features of CalcHEP are the computation of Feynman…

High Energy Physics - Phenomenology · Physics 2015-06-05 Alexander Belyaev , Neil D. Christensen , Alexander Pukhov

In general-purpose particle detectors, the particle-flow algorithm may be used to reconstruct a comprehensive particle-level view of the event by combining information from the calorimeters and the trackers, significantly improving the…

Data Analysis, Statistics and Probability · Physics 2021-06-10 Joosep Pata , Javier Duarte , Jean-Roch Vlimant , Maurizio Pierini , Maria Spiropulu

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 based…

Instrumentation and Detectors · Physics 2025-01-15 Samuel Bein , Patrick Connor , Kevin Pedro , Peter Schleper , Moritz Wolf

SModelS is an automatised tool for the interpretation of simplified model results from the LHC. It allows to decompose models of new physics obeying a Z2 symmetry into simplified model components, and to compare these against a large…

We extend the Particle-flow Neural Assisted Simulations (Parnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative Artificial Intelligence (genAI) tools, continuous…

High Energy Physics - Experiment · Physics 2025-03-27 Etienne Dreyer , Eilam Gross , Dmitrii Kobylianskii , Vinicius Mikuni , Benjamin Nachman

Through the last three decades, accurate simulation of the interactions of particles with matter and modeling of detector geometries has proven to be of critical importance to the success of the international high-energy physics (HEP)…

High Energy Physics - Experiment · Physics 2017-08-17 V. Daniel Elvira

The high accuracy of detector simulation is crucial for modern particle physics experiments. However, this accuracy comes with a high computational cost, which will be exacerbated by the large datasets and complex detector upgrades…

In pursuit of precise and fast theory predictions for the LHC, we present an implementation of the MadNIS method in the MadGraph event generator. A series of improvements in MadNIS further enhance its efficiency and speed. We validate this…

High Energy Physics - Phenomenology · Physics 2024-07-31 Theo Heimel , Nathan Huetsch , Fabio Maltoni , Olivier Mattelaer , Tilman Plehn , Ramon Winterhalder

This is the manual for the version 2 of HackAnalysis, a powerful, lightweight, versatile and, most importantly, hackable, recasting tool. New features in this version include: compressed event format storage for ultra-fast development;…

High Energy Physics - Phenomenology · Physics 2024-06-17 Mark D. Goodsell

Process supervision, using a trained verifier to evaluate the intermediate steps generated by a reasoner, has demonstrated significant improvements in multi-step problem solving. In this paper, to avoid the expensive effort of human…

Artificial Intelligence · Computer Science 2024-10-16 Zihan Wang , Yunxuan Li , Yuexin Wu , Liangchen Luo , Le Hou , Hongkun Yu , Jingbo Shang

Driven by the increasing volume of recorded data, the demand for simulation from experiments based at the Large Hadron Collider will rise sharply in the coming years. Addressing this demand solely with existing computationally intensive…