no code implementations • 24 Aug 2023 • Steve Abel, Juan Carlos Criado, Michael Spannowsky
The training of neural networks (NNs) is a computationally intensive task requiring significant time and resources.
no code implementations • 23 May 2022 • Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky
We use a Convolutional Neural Network (CNN) to identify the relevant features in the thermodynamical phases of chiral magnets, including (anti-)skyrmions, bimerons, and helical and ferromagnetic states.
1 code implementation • 7 Apr 2022 • Juan Carlos Criado, Michael Spannowsky
We present a general method, called Qade, for solving differential equations using a quantum annealer.
1 code implementation • 26 Mar 2021 • Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky
We present Elvet, a Python package for solving differential equations and variational problems using machine learning methods.
no code implementations • 26 Feb 2021 • Juan Carlos Criado, Abdelhak Djouadi, Niko Koivunen, Martti Raidal, Hardi Veermäe
Using an effective field theory approach for higher-spin fields, we derive the interactions of colour singlet and electrically neutral particles with a spin higher than unity, concentrating on the spin-3/2, spin-2, spin-5/2 and spin-3 cases.
High Energy Physics - Phenomenology High Energy Physics - Experiment High Energy Physics - Theory Nuclear Theory
no code implementations • 14 Dec 2020 • Juan Carlos Criado, Valentin V. Khoze, Michael Spannowsky
Skyrmions are extended field configurations, initially proposed to describe baryons as topological solitons in an effective field theory of mesons.
High Energy Physics - Phenomenology High Energy Physics - Experiment High Energy Physics - Theory
1 code implementation • 11 Jan 2019 • Juan Carlos Criado
BasisGen is a Python package for the automatic generation of bases of operators in effective field theories.
High Energy Physics - Phenomenology