Banuls Group

The focus of my research is the development and application of Tensor Network methods for the numerical simulation of quantum many body systems.

Tensor Networks for quantum many-body physics

Tensor networks can help us investigating lattice gauge theories

The term Tensor Network States (TNS) has become a common one in the context of numerical studies of quantum many-body problems. It refers to a number of families that represent different approaches for the efficient description of the state of a quantum many-body system. The paradigmatic application of these techniques, in the context of condensed matter physics, has been the solution of one dimensional spin problems using Matrix Product States (MPS). This family of states lies at the basis of the Density Matrix Renormalization Group method, which has become the most precise tool for the study of one dimensional quantum many-body systems in regimes where analytical tools cannot be used. But the potential of TNS extends far beyond such problems, and promising extensions include the natural generalization of MPS to higher dimensions and the applications to dynamics.


TNS and non-equilibrium dynamics

Time dependent observables described by tensor networks

One significant research direction is the development of Tensor Network tools for the investigation of non-equilibrium dynamical problems. Even in one spatial dimension, the physics of systems out-of-equilibrium holds unsolved fundamental questions, for instance about thermalization. The applicability of analytical techniques is limited, and non-perturbative methods are necessary to study the most general scenarios. Although the most standard MPS algorithms suffer also from severe limitations in these scenarios, the Tensor Network toolbox allows us to overcome some of the problems and to look at time dependent quantities in novel ways. As a particular example, the description of operators, as opposed to states, as tensor networks has provided us with a new method to study long-time properties without simulating the full dynamics. This technique can be applied now to explore the many body localization scenario.

Selected publications

  • Matrix Product States for Dynamical Simulation of Infinite Chains, Phys. Rev. Lett. 102, 240603 (2009);
  • Slowest local operators in quantum spin chains, Phys. Rev. E 92, 012128 (2015);

TNS and lattice gauge theories

Simulation of SU(2) string breaking (cf. JHEP 07 (2015) 130)

Another research direction that has proven fruitful in the last few years is the application of the tensor network toolbox to quantum many-body problems outside the realm of condensed matter physics. In particular, we have used MPS and related tools to perform extremely accurate numerical calculations of quantum gauge theories, following the strategy of lattice gauge theory (LGT) computations, for spectral properties, thermal equilibrium states and dynamics.


Selected publications

  • Density Induced Phase Transitions in the Schwinger Model: A Study with Matrix Product States, Phys. Rev. Lett. 118, 071601 (2017);
  • The mass spectrum of the Schwinger model with Matrix Product States, JHEP 11 (2013) 158;

Dr. Mari-Carmen Banuls



Max Planck Institute for Quantum Optics

Hans-Kopfermann-Str 1

D-85748 Garching