no code implementations • 11 Mar 2021 • Sirui Lu, Márton Kanász-Nagy, Ivan Kukuljan, J. Ignacio Cirac
We investigate the potential of tensor network based machine learning methods to scale to large image and text data sets.
no code implementations • 20 Jan 2021 • Xun Gao, Eric R. Anschuetz, Sheng-Tao Wang, J. Ignacio Cirac, Mikhail D. Lukin
Generative modeling using samples drawn from the probability distribution constitutes a powerful approach for unsupervised machine learning.
1 code implementation • 23 Dec 2020 • Giacomo Giudice, Aslı Çakan, J. Ignacio Cirac, Mari Carmen Bañuls
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
no code implementations • 22 Dec 2020 • Tommaso Guaita, Lucas Hackl, Tao Shi, Eugene Demler, J. Ignacio Cirac
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
no code implementations • 4 Dec 2020 • Zongping Gong, Lorenzo Piroli, J. Ignacio Cirac
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
1 code implementation • 8 Jul 2019 • Ivan Glasser, Ryan Sweke, Nicola Pancotti, Jens Eisert, J. Ignacio Cirac
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.
no code implementations • 24 Jul 2018 • Vedran Dunjko, Yimin Ge, J. Ignacio Cirac
Suppose we have a small quantum computer with only M qubits.
no code implementations • 15 Jun 2018 • Ivan Glasser, Nicola Pancotti, J. Ignacio Cirac
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.
no code implementations • 11 Oct 2017 • Ivan Glasser, Nicola Pancotti, Moritz August, Ivan D. Rodriguez, J. Ignacio Cirac
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.
no code implementations • 16 May 2012 • J. Ignacio Cirac
Short review on entanglement, as seen from a quantum information perspective, and some simple applications to many-body quantum systems.
Quantum Physics Quantum Gases
1 code implementation • 11 Mar 2011 • Jutho Haegeman, Bogdan Pirvu, David J. Weir, J. Ignacio Cirac, Tobias J. Osborne, Henri Verschelde, Frank Verstraete
A variational ansatz for momentum eigenstates of translation invariant quantum spin chains is formulated.
Quantum Physics Statistical Mechanics Strongly Correlated Electrons
1 code implementation • 4 Mar 2011 • Jutho Haegeman, J. Ignacio Cirac, Tobias J. Osborne, Iztok Pizorn, Henri Verschelde, Frank Verstraete
The algorithm is illustrated using both imaginary time and real-time examples.
Strongly Correlated Electrons Statistical Mechanics Quantum Physics