Survey of Tensor Networks

ORAL

Abstract

Tensor networks have become a robust method over the past few decades to represent quantum systems and solve them efficiently. These numerical methods can optimize a system by keeping the most important degrees of freedom, allowing us to solve large systems more efficiently. We review the fundamentals of this field, including a deep connection with entanglement. Basic aspects of tensor networks and common algorithms are presented. Specifically, algorithms for classical spin systems are compared to study their effectiveness.

*S.D. graciously thanks the 2018 Institut Transdisciplinaire d'Information Quantique (INTRIQ) undergraduate internship project scholarship. T.E.B. thanks Institut quantique for funding through the postdoctoral fellowship program. G.E. thanks Institut quantique and the Département de physique. This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund (CFREF).

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Presenters

  • Samuel Desrosiers

    • Département de physique & Insitut quantique, Université de Sherbrooke

Authors

  • Samuel Desrosiers

    • Département de physique & Insitut quantique, Université de Sherbrooke

  • Glen Evenbly

    • Département de physique & Insitut quantique, Université de Sherbrooke

  • Thomas E Baker

    • Département de physique & Insitut quantique, Université de Sherbrooke
    • Département de physique, Université de Sherbrooke, Institut quantique