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The study of generic properties of quantum states has led to an abundance of insightful results. A meaningful set of states that can be efficiently prepared in experiments are ground states of gapped local Hamiltonians, which are well…

Quantum Physics · Physics 2022-05-03 Jonas Haferkamp , Christian Bertoni , Ingo Roth , Jens Eisert

Matrix Product States (MPS) are a particular type of one dimensional tensor network states, that have been applied to the study of numerous quantum many body problems. One of their key features is the possibility to describe and encode…

Quantum Physics · Physics 2017-11-02 Ilya Kull , Andras Molnar , Erez Zohar , J. Ignacio Cirac

We present an implementation of an efficient algorithm for the calculation of the spectrum of one-dimensional quantum systems with periodic boundary conditions. This algorithm is based on a matrix product representation for quantum states…

Statistical Mechanics · Physics 2016-12-05 Michael Weyrauch , Mykhailo V. Rakov

Matrix product states (MPS) are a standard tensor-network representation for ground states of one-dimensional quantum many-body systems, and they underpin widely used simulation tools such as DMRG. However, while quantum model checking has…

Quantum Physics · Physics 2026-05-15 Ming Xu , Yihao Chen , Ji Guan

We solve the nonequilibrium dynamical mean-field theory (DMFT) using matrix product states (MPS). This allows us to treat much larger bath sizes and by that reach substantially longer times (factor $\sim$ 2 -- 3) than with exact…

Strongly Correlated Electrons · Physics 2014-12-22 F. Alexander Wolf , Ian P. McCulloch , Ulrich Schollwöck

We generalize the Matrix Product States method using the chiral vertex operators of Conformal Field Theory and apply it to study the ground states of the XXZ spin chain, the J1-J2 model and random Heisenberg models. We compute the overlap…

Statistical Mechanics · Physics 2013-05-29 J. Ignacio Cirac , German Sierra

Consistency models are a class of generative models that enable few-step generation for diffusion and flow matching models. While consistency models have achieved promising results on Euclidean domains like images, their applications to…

Machine Learning · Computer Science 2025-11-04 Chaoran Cheng , Yusong Wang , Yuxin Chen , Xiangxin Zhou , Nanning Zheng , Ge Liu

We demonstrate that the optimal states in lossy quantum interferometry may be efficiently simulated using low rank matrix product states. We argue that this should be expected in all realistic quantum metrological protocols with…

Quantum Physics · Physics 2013-06-18 Marcin Jarzyna , Rafal Demkowicz-Dobrzanski

We investigate the relation between the scaling of block entropies and the efficient simulability by Matrix Product States (MPS), and clarify the connection both for von Neumann and Renyi entropies (see Table I). Most notably, even states…

Quantum Physics · Physics 2009-11-13 Norbert Schuch , Michael M. Wolf , Frank Verstraete , J. Ignacio Cirac

Tensor network methods have progressed from variational techniques based on matrix-product states able to compute properties of one-dimensional condensed-matter lattice models into methods rooted in more elaborate states such as projected…

Strongly Correlated Electrons · Physics 2021-08-23 C. Krumnow , L. Veis , J. Eisert , Ö. Legeza

We propose a framework to design concurrently a frustration-free quantum many-body Hamiltonian and its numerically exact ground states on a sufficiently large finite-size cluster in one and two dimensions using an elementary matrix product…

Strongly Correlated Electrons · Physics 2024-12-17 Hidehiro Saito , Chisa Hotta

Tensor network methods have proved to be highly effective in addressing a wide variety of physical scenarios, including those lacking an intrinsic one-dimensional geometry. In such contexts, it is possible for the problem to exhibit a weak…

We introduce the Riemannian Motion Policy (RMP), a new mathematical object for modular motion generation. An RMP is a second-order dynamical system (acceleration field or motion policy) coupled with a corresponding Riemannian metric. The…

Robotics · Computer Science 2018-07-26 Nathan D. Ratliff , Jan Issac , Daniel Kappler , Stan Birchfield , Dieter Fox

Gaussian fermionic matrix product states (GfMPS) form a class of ansatz quantum states for 1d systems of noninteracting fermions. We show, for a simple critical model of free hopping fermions, that: (i) any GfMPS approximation to its ground…

Quantum Physics · Physics 2022-12-28 Adrián Franco-Rubio , J. Ignacio Cirac

Response functions $\langle A_x(t) B_y(0)\rangle$ for one-dimensional strongly correlated quantum many-body systems can be computed with matrix product state (MPS) techniques. Especially, when one is interested in spectral functions or…

Strongly Correlated Electrons · Physics 2019-03-21 Moritz Binder , Thomas Barthel

The variational method is a powerful approach to solve many-body quantum problems non perturbatively. However, in the context of relativistic quantum field theory (QFT), it needs to meet 3 seemingly incompatible requirements outlined by…

Quantum Physics · Physics 2021-11-24 Antoine Tilloy

The experimental realisation of large scale many-body systems has seen immense progress in recent years, rendering full tomography tools for state identification inefficient, especially for continuous systems. In order to work with these…

We introduce a family of quantum spin chains with nearest-neighbor interactions that can serve to clarify and refine the classification of gapped quantum phases of such systems. The gapped ground states of these models can be described as a…

Strongly Correlated Electrons · Physics 2012-08-29 Sven Bachmann , Bruno Nachtergaele

Characterizing criticality in quantum many-body systems of dimension $\ge 2$ is one of the most important challenges of the contemporary physics. In principle, there is no generally valid theoretical method that could solve this problem. In…

Strongly Correlated Electrons · Physics 2017-08-25 Cheng Peng , Shi-Ju Ran , Maciej Lewenstein , Gang Su

In this work, we investigate the universal representation capacity of the Matrix Product States (MPS) from the perspective of boolean functions and continuous functions. We show that MPS can accurately realize arbitrary boolean functions by…

Machine Learning · Statistics 2025-10-16 Erdong Guo , David Draper
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