Related papers: Reframing Jet Physics with New Computational Metho…
We present data-driven methods for the full reconstruction of jets in heavy ion collisions, for inclusive and co-incidence jet measurements at both RHIC and LHC. The complex structure of heavy ion events generates a large background of…
We investigate the behaviour of jets at high-multiplicity using analytic techniques. We consider in detail the rates, areas and the intermediate splitting scales as a function of the number of jets. In each case, we are able to characterise…
This paper proposes new methods for analyzing dynamic images registered by multichannel, highly sensitive detectors with low spatial but high temporal resolution. The principal characteristic of the approach is the absence of factorization…
In this talk, we discuss the speed-up of numerical calculations of jet observables by replacing the usual sum over all helicity amplitudes with an integral over a parametrisation for the parton polarisations called random polarisations.…
A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from…
In particle simulations, the weights of particles determine how many physical particles they represent. Adaptively adjusting these weights can greatly improve the efficiency of the simulation, without creating severe nonphysical artifacts.…
Global optimization is an active area of research in atomistic simulations, and many algorithms have been proposed to date. A prominent example is basin hopping Monte Carlo, which performs a modified Metropolis Monte Carlo search to explore…
Particle and ensemble filters are increasingly utilized for inference, optimization, and forecast; however, both filtering methods use discrete distributions to simulate continuous state space, a drawback that can lead to degraded…
Metaheuristic algorithms are powerful tools for global optimization, particularly for non-convex and non-differentiable problems where exact methods are often impractical. Particle-based optimization methods, inspired by swarm intelligence…
We study the impact of selection biases on jet structure and substructure observables and separate these effects from effects caused by jet quenching. We use the angular separation $\Delta R$ of the hardest splitting in a jet as the primary…
We review recent developments related to jet clustering algorithms and jet finding. These include fast implementations of sequential recombination algorithms, new IRC safe algorithms, quantitative determination of jet areas and quality…
The theory of stochastic resetting asserts that restarting a search process at certain times may accelerate the finding of a target. In the case of a classical diffusing particle trapped in a potential well, stochastic resetting may…
We develop a formulation for molecular dynamics, Langevin, and hybrid Monte Carlo algorithms in the recently proposed generalized ensemble that is based on a physically motivated realisation of Tsallis weights. The effectiveness of the…
To precisely measure jets over a large background such as pile up in high luminosity p+p collisions at LHC, a new generation of jet reconstruction algorithms is developed. These algorithms are also applicable to reconstruct jets in the…
The modification of jet substructure in relativistic heavy-ion collisions is studied using JETSCAPE, a publicly available software package containing a framework for Monte Carlo event generators. Multi-stage jet evolution in JETSCAPE…
We present numerical simulations investigating the interaction of AGN jets with galaxy clusters, for the first time taking into account the dynamic nature of the cluster gas and detailed cluster physics. The simulations successfully…
We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such…
Jets can be used to probe the physical properties of the high energy density matter created in collisions at the Relativistic Heavy Ion Collider (RHIC). Measurements of strong suppression of inclusive hadron distributions and di-hadron…
Probabilistic predictions are probability distributions over the set of possible outcomes. Such predictions quantify the uncertainty in the outcome, making them essential for effective decision making. By combining multiple predictions, the…
We make the connection between certain deep learning architectures and the renormalisation group explicit in the context of QCD by using a deep learning network to construct a toy parton shower model. The model aims to describe…