Related papers: Computational Particle Physics for Event Generator…
High-quality simulated data is crucial for particle physics discoveries. Therefore, parton shower algorithms are a major building block of the data synthesis in event generator programs. However, the core algorithms used to generate parton…
We present a general method of associating next-to-leading order weights to leading order phase space configurations at hadron colliders. The method relies on a re-organization of phase space for the real radiation contributions, defining a…
In this paper we describe the present status and our plans for the realization of next phases of the CalcPHEP project aimed at the theoretical support of experiments at modern and future accelerators: TEVATRON, LHC, electron Linear…
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…
We present a novel probabilistic programming framework that couples directly to existing large-scale simulators through a cross-platform probabilistic execution protocol, which allows general-purpose inference engines to record and control…
Searches for new physics in high-energy physics (HEP) experiments commonly rely on interactions with materials. A burgeoning direction is the accurate calculation and design of materials for HEP applications. In this Snowmass contribution,…
A common feature of wall-bounded turbulent particle-laden flows is enhanced particle concentrations in a thin layer near the wall due to a phenomenon known as turbophoresis. Even at relatively low bulk volume fractions, particle-particle…
The Higgs particle is a new elementary particle predicted in the Standard Model of the elementary particle physics. It plays a special role in the theory of mass generation of quarks, leptons, and gauge bosons. In this article, theoretical…
We propose a method to organize experimental data from particle collision experiments in a general format which can enable a simple visualisation and effective classification of collision data using machine learning techniques. The method…
In this publication, uncertainties in and differences between the MC@NLO and POWHEG methods for matching next-to-leading order QCD calculations with parton showers are discussed. Implementations of both algorithms within the event generator…
Theoretical predictions for scattering processes with multi-particle final states at next-to-leading order (NLO) in perturbative QCD are essential to fully exploit the physics potential of present and future high-energy colliders. The…
PHASE is a new event generator dedicated to the study of Standard Model processes with six fermions in the final state at the LHC. The code is intended for analyses of vector boson scattering, Higgs search, three gauge boson production, and…
Experimental High-Energy Physics (HEP), especially the Large Hadron Collider (LHC) programme at the European Organization for Nuclear Research (CERN), is one of the most computationally intensive activities in the world. This demand is set…
Physics event generators are essential components of the data analysis software chain of high energy physics experiments, and important consumers of their CPU resources. Improving the software performance of these packages on modern…
The Matrix Element Method is a promising multi-variate analysis tool which offers an optimal approach to compare theory and experiment according to the Neyman-Pearson lemma. However, until recently its usage has been limited by the fact…
We illustrate how the Matrix Element Method at Next-to-Leading Order (MEM@NLO) can be used to discriminate between events arising from the production of a Higgs boson, which subsequently decays to a final state consisting of…
We study a phenomenological ansatz for merging next-to-next-to-leading order (NNLO) calculations with Monte Carlo event generators. We reweight them to match bin-integrated NNLO differential distributions. To test this procedure, we study…
Point processes offer a versatile framework for sequential event modeling. However, the computational challenges and constrained representational power of the existing point process models have impeded their potential for wider…
Photonic Quantum Computers provides several benefits over the discrete qubit-based paradigm of quantum computing. By using the power of continuous-variable computing we build an anomaly detection model to use on searches for New Physics.…
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…