Introduction

The Density Matrix Renormalization Group (DMRG) and its generalizations in the form of Tensor Network States have made significant contributions across a wide range of fields, including condensed matter physics, statistical physics, quantum chemistry, nuclear physics, quantum information, and machine learning.

The Tensor Network States: Algorithms and Applications (TNSAA) workshops were established to highlight these developments, providing a platform for presenting new algorithmic advances and their applications in uncovering novel physics.

Continuing this tradition, TNSAA 2026 will bring together researchers working on tensor network states, numerical methods, quantum many-body systems, quantum information, machine learning, and related areas. In addition to invited talks, the workshop will include contributed oral and poster presentations.

The workshop aims to encourage discussions across disciplines and stimulate new collaborations and research directions.

Date

December 15–18, 2026

Venue

RIKEN Center for Computational Science (R-CCS)
Kobe, Japan

Topics

Topics include, but are not limited to:

  • Tensor network algorithms
  • Quantum many-body systems
  • Quantum information and computation
  • Numerical methods for strongly correlated systems
  • Tensor networks and machine learning
  • Quantum simulation
  • Applications in physics, chemistry, and related fields

Previous Workshops