Fri·Nov 18, 2022Friday·November 18, 2022

1. 01*

   Composite dynamics in Sp($2N$) gauge theories

   Jong-Wan Lee🇰🇷 · Ed Bennett🇬🇧 · Deog Ki Hong🇰🇷 · Ho Hsiao🇹🇼 · C. -J. David Lin🇹🇼 · Biagio Lucini🇬🇧 · Maurizio Piai🇬🇧 · Davide Vadacchino🇬🇧

   Sp($2N$) gauge theories with fermonic matter provide an ideal laboratory to build extensions of the standard model based on novel composite dynamics. Examples include composite Higgs along with top partial compositeness and composite dark matter. Without fermions, their study also complements those based on SU($N_c$) gauge theories with which they share a common sector in the large $N_c=2N$ limit. We report on our recent progress in the numerical studies of Sp($2N$) gauge theories discretised on a four-dimensional Euclidean lattice. In particular, we present preliminary results for the low-lying mass spectra of mesons and chimera baryons in the theories with $N=2$. We also compute the topological susceptibility for various values of $N$, extrapolate the results to the large $N$ limit, and discuss certain universal properties in Yang-Mills theories.

   hep-lathep-phhep-thEPJ Web Conf.(2022)·3 citations
2. 02*

   Multi-Representation Dynamics of SU(4) Composite Higgs Models: Chiral Limit and Spectral Reconstructions

   Luigi Del Debbio🇬🇧 · Alessandro Lupo🇬🇧 · Marco Panero🇮🇹 · Nazario Tantalo🇮🇹

   We present a lattice study of the $SU(4)$ gauge theory with two Dirac fermions in the fundamental and two in the two-index antisymmetric representation, a model close to a theory of partial compositeness. Focus of this work are the methodologies behind the computation of the spectrum and the extrapolation of the chiral point for a theory with matter in multiple representations. While being still technical, this study provides important steps towards a non-perturbative understanding of the spectrum of theories of partial compositeness, which present a richer dynamics compared to single-representation theories. The multi-representation features are studied first in perturbation theory, and then non-perturbatively by adopting a dual outlook on lattice data through a joint analysis of time-momentum correlation functions and smeared spectral densities.

   hep-lathep-phEPJC(2023)·38 citations
3. 03*

   Mitigating the Hubbard Sign Problem. A Novel Application of Machine Learning

   Marcel Rodekamp🇩🇪 · Christoph Gäntgen🇩🇪

   Many fascinating systems suffer from a severe (complex action) sign problem preventing us from calculating them with Markov Chain Monte Carlo simulations. One promising method to alleviate the sign problem is the transformation of the integration domain towards Lefschetz Thimbles. Unfortunately, this suffers from poor scaling originating in numerically integrating of flow equations and evaluation of an induced Jacobian. In this proceedings we present a new preliminary Neural Network architecture based on complex-valued affine coupling layers. This network performs such a transformation efficiently, ultimately allowing simulation of systems with a severe sign problem. We test this method within the Hubbard Model at finite chemical potential, modelling strongly correlated electrons on a spatial lattice of ions.

   ↳ cond-mat.str-elhep-latPoS(2023)·3 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.