Generating function for tensor network diagrammatic summation

Autor(en)

Wei-Lin Tu, Huan-Kuang Wu, Norbert Schuch, Naoki Kawashima, Ji-Yao Chen

Abstrakt

The understanding of complex quantum many-body systems has been vastly boosted by tensor network (TN) methods. Among others, excitation spectrum and long-range interacting systems can be studied using TNs, where one however confronts the intricate summation over an extensive number of tensor diagrams. Here, we introduce a set of generating functions, which encode the diagrammatic summations as leading-order series expansion coefficients. Combined with automatic differentiation, the generating function allows us to solve the problem of TN diagrammatic summation. We illustrate this scheme by computing variational excited states and the dynamical structure factor of a quantum spin chain, and further investigating entanglement properties of excited states. Extensions to infinite-size systems and higher dimension are outlined.

Organisation(en)

Quantenoptik, Quantennanophysik und Quanteninformation, Institut für Mathematik

Externe Organisation(en)

University of Tokyo, University of Maryland, College Park, Max-Planck-Institut für Quantenoptik, Munich Center for Quantum Science and Technology (MCQST), Korea University

Journal

Physical Review B

Band

103

Seiten

205155-1 - 205155-6

Anzahl der Seiten

6

ISSN

2469-9950

DOI

https://doi.org/10.1103/PhysRevB.103.205155

Publikationsdatum

05-2021

Peer-reviewed

Ja

ÖFOS 2012

103015 Kondensierte Materie, 103018 Materialphysik

ASJC Scopus Sachgebiete

Electronic, Optical and Magnetic Materials, Condensed Matter Physics

Link zum Portal

https://ucrisportal.univie.ac.at/de/publications/9010f856-c403-4df7-921e-c86b1c27f218