Search Results for author: Lena Funcke

Found 5 papers, 1 papers with code

Applications of Machine Learning to Lattice Quantum Field Theory

no code implementations10 Feb 2022 Denis Boyda, Salvatore Calì, Sam Foreman, Lena Funcke, Daniel C. Hackett, Yin Lin, Gert Aarts, Andrei Alexandru, Xiao-Yong Jin, Biagio Lucini, Phiala E. Shanahan

There is great potential to apply machine learning in the area of numerical lattice quantum field theory, but full exploitation of that potential will require new strategies.

BIG-bench Machine Learning

Reconstruction of the neutrino mass as a function of redshift

no code implementations26 Feb 2021 Christiane S. Lorenz, Lena Funcke, Matthias Löffler, Erminia Calabrese

We reconstruct the neutrino mass as a function of redshift, z, from current cosmological data using both standard binned priors and linear spline priors with variable knots.

Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology

Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models

no code implementations14 Jul 2020 Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima, Paolo Stornati

In this work, we demonstrate that applying deep generative machine learning models for lattice field theory is a promising route for solving problems where Markov Chain Monte Carlo (MCMC) methods are problematic.

BIG-bench Machine Learning

Distinguishing Dirac and Majorana neutrinos by their gravi-majoron decays

1 code implementation3 May 2019 Lena Funcke, Georg Raffelt, Edoardo Vitagliano

Neutrinos may acquire small Dirac or Majorana masses by new low-energy physics in terms of the chiral gravitational anomaly, as proposed by Dvali and Funcke (2016).

High Energy Physics - Phenomenology

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