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Found 12 papers, 4 papers with code
Tensor networks and efficient descriptions of classical data
We investigate the potential of tensor network based machine learning methods to scale to large image and text data sets.
Enhancing Generative Models via Quantum Correlations
Generative modeling using samples drawn from the probability distribution constitutes a powerful approach for unsupervised machine learning.
Rényi free energy and variational approximations to thermal states
We propose the construction of thermodynamic ensembles that minimize the R\'enyi free energy, as an alternative to Gibbs states.
Quantum Physics Strongly Correlated Electrons
Generalization of group-theoretic coherent states for variational calculations
We introduce new families of pure quantum states that are constructed on top of the well-known Gilmore-Perelomov group-theoretic coherent states.
Quantum Physics Quantum Gases Strongly Correlated Electrons Mathematical Physics Mathematical Physics
Topological lower bound on quantum chaos by entanglement growth
A fundamental result in modern quantum chaos theory is the Maldacena-Shenker-Stanford upper bound on the growth of out-of-time-order correlators, whose infinite-temperature limit is related to the operator-space entanglement entropy of the evolution operator.
Quantum Physics Quantum Gases Statistical Mechanics Strongly Correlated Electrons
Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
Inspired by these developments, and the natural correspondence between tensor networks and probabilistic graphical models, we provide a rigorous analysis of the expressive power of various tensor-network factorizations of discrete multivariate probability distributions.
Computational speedups using small quantum devices
Suppose we have a small quantum computer with only M qubits.
From probabilistic graphical models to generalized tensor networks for supervised learning
We discuss the relationship between generalized tensor network architectures used in quantum physics, such as string-bond states, and architectures commonly used in machine learning.
Neural-Network Quantum States, String-Bond States, and Chiral Topological States
In particular we demonstrate that short-range Restricted Boltzmann Machines are Entangled Plaquette States, while fully connected Restricted Boltzmann Machines are String-Bond States with a nonlocal geometry and low bond dimension.
Entanglement in many-body quantum systems
Short review on entanglement, as seen from a quantum information perspective, and some simple applications to many-body quantum systems.
Quantum Physics Quantum Gases
Variational matrix product ansatz for dispersion relations
A variational ansatz for momentum eigenstates of translation invariant quantum spin chains is formulated.
Quantum Physics Statistical Mechanics Strongly Correlated Electrons
Time-dependent variational principle for quantum lattices
The algorithm is illustrated using both imaginary time and real-time examples.
Strongly Correlated Electrons Statistical Mechanics Quantum Physics
