Quantum field-theoretic machine learning The precise equivalence between discretized Euclidean field theories and Markov random fields, as established by the Hammersley-Clifford theorem, opens up the opportunity to investigate machine learning from the perspective of quantum field theory. In this talk I will discuss a variety of interconnected topics: Markov properties for quantum fields, the derivation
Schwinger effect in superconductors From the sixties a deep connection has followed the development of superconductivity and quantum field theory. The Anderson-Higgs mechanism and the similarities between the Dirac and Bogoliubov-de Gennes equations are the most intriguing examples. In this last analogy, the massive Dirac particle is identified with a quasiparticle excitation and the fermion
"Digital Quantum Simulation of the Schwinger Model with Topological Term In this talk, I would present our recent work (arXiv:2001.00485) on digital quantum simulation of 1+1 dimensional quantum electrodynamics (Schwinger model) with the topological term, using adiabatic state preparation. This, in turn, allows us to compute an expectation value of the fermion mass operator with