相关论文: Model-Independent Searches Using Matrix Element Ra…
Matrices are said to behave as free non-commuting random variables if the action which governs their dynamics constrains only their eigenvalues, i.e. depends on traces of powers of individual matrices. The authors use recently developed…
The ATLAS and CMS experiments at LHC have great physics potential in discovering many possible new particles, from Standard Model (SM) Higgs boson to supersymmetric (SUSY) and other beyond the SM new particles over a very large mass range…
We present theoretical and experimental preparations for an indirect search for new physics using the rare decay $\bar B_d \to \bar K^* l^+ l^-$. We design new observables with very small theoretical uncertainties and good experimental…
LHC searches for new physics focus on combinations of hard physics objects. In this work we propose a qualitatively different soft signal for new physics at the LHC - the "anomalous underlying event". Every hard LHC event will be…
We consider a model-based approach to perform batch off-policy evaluation in reinforcement learning. Our method takes a mixture-of-experts approach to combine parametric and non-parametric models of the environment such that the final value…
In this new era of large data, it is important to make sure we do not miss any signs of new physics. Using the publicly-available open data collected by the arXiv.org experiment in the \texttt{hep-ph} channel, corresponding to a raw total…
A new approach to precise determination of atomic matrix elements is described whereby measurement of spectral locations of zeros in the Rayleigh scattering cross-section allows frequency-domain extraction of matrix elements in terms of a…
Indications of a possible composition-dependent fifth force, based on a reanalysis of the E\"{o}tv\"{o}s experiment, have not been supported by a number of modern experiments. Here, we argue that searching for a composition-dependent fifth…
Intensity Frontier experiments are often evaluated by the smallest coupling it can probe, irrespective of what particle can be found or the scientific significance of its detection. In this work, we propose a new framework that determines…
The cleanest way to discover a new particle is generally the "bump-hunt" methodology: looking for a localised excess in a mass (or related) distribution. However, if the mass of the particle being discovered is not known the procedure of…
Non-leptonic $B^0_s \rightarrow D_s^{\pm} K^{\mp}$ transitions are particularly interesting processes to test the Standard Model. As these decays occur via pure tree diagrams, they allow a theoretically clean determination of the angle…
Flavour physics plays a central role in the search for physics beyond the Standard Model, posing fundamental questions whose answers may point to new physics scales far above the electroweak scale. The flavour structure of the Standard…
In this work we consider partially observable environments with sparse rewards. We present a self-supervised representation learning method for image-based observations, which arranges embeddings respecting temporal distance of…
This paper attempts to classify various blinding strategies used in particle physics. It argues that the blinding technique is not used consistently throughout searches for new physics. More importantly, the blinding technique, in its…
Models for what may lie behind the Standard Model often require non-perturbative calculations in strongly coupled field theory. This creates opportunities for lattice methods, to obtain quantities of phenomenological interest as well as to…
The FASER{\nu} experiment has detected the first neutrino events coming from LHC. Near future high-statistic neutrino samples will allow us to search for new physics within the neutrino sector. Motivated by the forthcoming promising…
This paper presents an algorithm for the unsupervised learning of latent variable models from unlabeled sets of data. We base our technique on spectral decomposition, providing a technique that proves to be robust both in theory and in…
The CKM matrix and its unitarity is analyzed by disentangling experimental information obtained from three different particle systems of neutrons, mesons, and nuclei. New physics beyond the Standard Model is supported under the new…
Detecting influential features in non-linear and/or high-dimensional data is a challenging and increasingly important task in machine learning. Variable selection methods have thus been gaining much attention as well as post-selection…
Extending the Standard Model (SM) by a $U(1)_{L_\mu-L_\tau}$ group gives potentially significant new contributions to $g_\mu-2$, allows the construction of realistic neutrino mass matrices, incorporates lepton universality violation, and…