PIRSA:17040035

Solving Non-relativistic Quantum Field Theories with continuous Matrix Product States

APA

Ganahl, M. (2017). Solving Non-relativistic Quantum Field Theories with continuous Matrix Product States. Perimeter Institute for Theoretical Physics. https://pirsa.org/17040035

MLA

Ganahl, Martin. Solving Non-relativistic Quantum Field Theories with continuous Matrix Product States. Perimeter Institute for Theoretical Physics, Apr. 18, 2017, https://pirsa.org/17040035

BibTex

          @misc{ scivideos_PIRSA:17040035,
            doi = {10.48660/17040035},
            url = {https://pirsa.org/17040035},
            author = {Ganahl, Martin},
            keywords = {Quantum Matter, Quantum Fields and Strings, Quantum Gravity, Quantum Information},
            language = {en},
            title = {Solving Non-relativistic Quantum Field Theories with continuous Matrix Product States},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2017},
            month = {apr},
            note = {PIRSA:17040035 see, \url{https://scivideos.org/index.php/pirsa/17040035}}
          }
          

Martin Ganahl Sandbox AQ

Talk numberPIRSA:17040035

Abstract

Since its proposal in the breakthrough paper [F. Verstraete, J.I. Cirac, Phys. Rev. Lett. 104, 190405(2010)], continuous Matrix Product States (cMPS) have emerged as a powerful tool for obtaining non-perturbative ground state and excited state properties of interacting quantum field theories (QFTs) in (1+1)d. At the heart of the cMPS lies an efficient parametrization of manybody wavefunctionals directly in the continuum, that enables one to obtain ground states of QFTs via imaginary time evolution. In the first part of my talk I will give a general introduction to the cMPS formalism. In the second part, I will then discuss a new method for cMPS optimization, based on energy gradient instead of the usual imaginary time evolution. This new method overcomes several problems associated with imaginary time evolution, and allows to perform calculations at much lower cost / higher accuracy than previously possible.