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pro vyhledávání: '"Lester, Christopher"'
We use machine learning methods to search for parity violations in the Large-Scale Structure (LSS) of the Universe, motivated by recent claims of chirality detection using the 4-Point Correlation Function (4PCF), which would suggest new physics durin
Externí odkaz:
http://arxiv.org/abs/2410.16030
Hypothesis testing in high dimensional data is a notoriously difficult problem without direct access to competing models' likelihood functions. This paper argues that statistical divergences can be used to quantify the difference between the populati
Externí odkaz:
http://arxiv.org/abs/2405.06397
Publikováno v:
JHEP08(2022)231
Non-Standard-Model parity violation may be occurring in LHC collisions. Any such violation would go unseen, however, as searches are for it are not currently performed. One barrier to searches for parity violation is the lack of model-independent met
Externí odkaz:
http://arxiv.org/abs/2205.09876
Autor:
Tombs, Rupert, Lester, Christopher G.
Publikováno v:
JINST 2022 vol 17 number 8 pages P08024
Symmetries are key properties of physical models and of experimental designs, but any proposed symmetry may or may not be realized in nature. In this paper, we introduce a practical and general method to test such suspected symmetries in data, with m
Externí odkaz:
http://arxiv.org/abs/2111.05442
Autor:
Lester, Christopher G.
Searches for parity violation at particle physics collider experiments without polarised initial states or final-state polarimeters lack a formal framework within which some of their methods and results can be efficiently described. This document def
Externí odkaz:
http://arxiv.org/abs/2111.00623
Autor:
Lester, Christopher G., Tombs, Rupert
Publikováno v:
Transactions on Machine Learning Research, 2022
Testing whether data breaks symmetries of interest can be important to many fields. This paper describes a simple way that machine learning algorithms (whose outputs have been appropriately symmetrised) can be used to detect symmetry breaking. The or
Externí odkaz:
http://arxiv.org/abs/2111.00616
Publikováno v:
International Journal of Modern Physics, Volume No. 37, Issue No. 16, Article No. 2250093, Year 2022
Comparisons of the positive and negative halves of the distributions of parity-odd event variables in particle-physics experimental data can provide sensitivity to sources of non-standard parity violation. Such techniques benefit from lacking first-o
Externí odkaz:
http://arxiv.org/abs/2008.05206
A theorem of Weyl tells us that the Lorentz (and parity) invariant polynomials in the momenta of $n$ particles are generated by the dot products. We extend this result to include the action of an arbitrary permutation group $P \subset S_n$ on the par
Externí odkaz:
http://arxiv.org/abs/2003.05487
Stochastic simulation algorithms (SSAs) are widely used to numerically investigate the properties of stochastic, discrete-state models. The Gillespie Direct Method is the pre-eminent SSA, and is widely used to generate sample paths of so-called agent
Externí odkaz:
http://arxiv.org/abs/2001.07247
Publikováno v:
JHEP12(2019)120
The Standard Model violates parity, but only by mechanisms which are invisible to Large Hadron Collider (LHC) experiments (on account of the lack of initial state polarisation or spin-sensitivity in the detectors). Nonetheless, new physical processes
Externí odkaz:
http://arxiv.org/abs/1904.11195