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Found 5 papers, 3 papers with code
A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications
Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate.
Bayesian Optimisation
High Energy Physics - Phenomenology
Computational Physics
Sampling the $μν$SSM for displaced decays of the tau left sneutrino LSP at the LHC
Within the framework of the $\mu\nu$SSM, a displaced dilepton signal is expected at the LHC from the decay of a tau left sneutrino as the lightest supersymmetric particle (LSP) with a mass in the range $45 - 100$ GeV.
High Energy Physics - Phenomenology High Energy Physics - Experiment
Event Generation and Statistical Sampling for Physics with Deep Generative Models and a Density Information Buffer
We present a study for the generation of events from a physical process with deep generative models.
High Energy Physics - Phenomenology High Energy Physics - Experiment Data Analysis, Statistics and Probability
Estimating QCD uncertainties in Monte Carlo event generators for gamma-ray dark matter searches
For the first time, we also derive a conservative set of uncertainties on the shower and hadronisation model parameters.
High Energy Physics - Phenomenology Cosmology and Nongalactic Astrophysics
Accelerating the BSM interpretation of LHC data with machine learning
The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators.
