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Applications of Machine Learning to Lattice Quantum Field Theory
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.
Unusual Features of QCD Low-Energy Modes in IR Phase
We find similar structure at $\lambda_A$, and associate its adjacent thin layer ($d_{IR} >\approx 2$) with Anderson-like criticality.
High Energy Physics - Lattice Disordered Systems and Neural Networks High Energy Physics - Theory Nuclear Theory
Detecting flavor content of the vacuum using the Dirac operator spectrum
We show that we can resolve the flavor content of the sea quarks and constrain their masses using the Dirac spectral density.
High Energy Physics - Lattice High Energy Physics - Phenomenology
