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Generative modeling with projected entangled-pair states
We argue and demonstrate that projected entangled-pair states (PEPS) outperform matrix product states significantly for the task of generative modeling of datasets with an intrinsic two-dimensional structure such as images.
Efficient MPS methods for extracting spectral information on rings and cylinders
Despite the explicit breaking of translation symmetry by the MPS representation, we show that momentum emerges as a good quantum number, and can be exploited for labeling excitations on top of MPS ground states.
Strongly Correlated Electrons Quantum Physics
A scaling hypothesis for projected entangled-pair states
We introduce a new paradigm for scaling simulations with projected entangled-pair states (PEPS) for critical strongly-correlated systems, allowing for reliable extrapolations of PEPS data with relatively small bond dimensions $D$.
Quantum Physics
Solving frustrated Ising models using tensor networks
Motivated by the recent success of tensor networks to calculate the residual entropy of spin ice and kagome Ising models, we develop a general framework to study frustrated Ising models in terms of infinite tensor networks %, i. e. tensor networks that can be contracted using standard algorithms for infinite systems.
Tensor Networks
Statistical Mechanics
Quantum Physics
