5 papers
Extracting average properties of disordered spin chains with translationally invariant tensor networks
Kevin Vervoort, Wei Tang, Nick Bultinck
We develop a tensor network-based method for calculating disorder-averaged expectation values in random spin chains without having to explicitly sample over disorder configurations…
Accelerating two-dimensional tensor network optimization by preconditioning
Xing-Yu Zhang, Qi Yang, Philippe Corboz +2
We revisit gradient-based optimization for infinite projected entangled pair states (iPEPS), a tensor network ansatz for simulating many-body quantum systems. This approach is hind…
Numerical study of boson mixtures with multi-component continuous matrix product states
Wei Tang, Benoît Tuybens, Jutho Haegeman
The continuous matrix product state (cMPS) ansatz is a promising numerical tool for studying quantum many-body systems in continuous space. Although it provides a clean framework t…
Gauging the variational optimization of projected entangled-pair states
Wei Tang, Laurens Vanderstraeten, Jutho Haegeman
Projected entangled-pair states (PEPS) constitute a powerful variational ansatz for capturing ground state physics of two-dimensional quantum systems. However, accurately computing…
Matrix product state fixed points of non-Hermitian transfer matrices
Wei Tang, Frank Verstraete, Jutho Haegeman
The contraction of tensor networks is a central task in the application of tensor network methods to the study of quantum and classical many body systems. In this paper, we investi…