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Spin models are used in many studies of complex systems---be it condensed matter physics, neural networks, or economics---as they exhibit rich macroscopic behaviour despite their microscopic simplicity. Here we prove that all the physics of…

Statistical Mechanics · Physics 2016-06-15 Gemma De las Cuevas , Toby S. Cubitt

One of the theoretical pillars that sustain certain machine learning models are universal approximation theorems, which prove that they can approximate all functions from a function class to arbitrary precision. Independently, classical…

Disordered Systems and Neural Networks · Physics 2026-04-28 Tobias Reinhart , Gemma De les Coves

Unlike computation or the numerical analysis of differential equations, simulation does not have a well established conceptual and mathematical foundation. Simulation is an arguable unique union of modeling and computation. However,…

adap-org · Physics 2008-02-03 Steen Rasmussen , Christopher Barrett

Spin models are widely studied in the natural sciences, from investigating magnetic materials in condensed matter physics to studying neural networks. Previous work has demonstrated that there exist simple classical spin models that are…

Statistical Mechanics · Physics 2019-05-22 Tamara Kohler , Toby Cubitt

A universal Turing machine is a powerful concept - a single device can compute any function that is computable. A universal spin model, similarly, is a class of physical systems whose low energy behavior simulates that of any spin system.…

Computational Complexity · Computer Science 2024-06-25 Tomáš Gonda , Gemma De les Coves

With the rise of computers, simulation models have emerged beside the more traditional statistical and mathematical models as a third pillar for ecological analysis. Broadly speaking, a simulation model is an algorithm, typically…

Populations and Evolution · Quantitative Biology 2018-12-24 Florian Hartig

Computational models are quantitative representations of systems. By analyzing and comparing the outputs of such models, it is possible to gain a better understanding of the system itself. Though as the complexity of model outputs…

Machine Learning · Computer Science 2022-12-13 Colin G. Cess , Stacey D. Finley

We study mappings between distinct classical spin systems that leave the partition function invariant. As recently shown in [Phys. Rev. Lett. 100, 110501 (2008)], the partition function of the 2D square lattice Ising model in the presence…

Quantum Physics · Physics 2015-05-13 Gemma De las Cuevas , Wolfgang Dür , Maarten Van den Nest , Hans J. Briegel

From condensed matter to quantum chromodynamics, multidimensional spins are a fundamental paradigm, with a pivotal role in combinatorial optimization and machine learning. Machines formed by coupled parametric oscillators can simulate spin…

Optics · Physics 2022-11-29 Marcello Calvanese Strinati , Claudio Conti

In this note, we provide a unifying framework to investigate the computational complexity of classical spin models and give the full classification on spin models in terms of system dimensions, randomness, external magnetic fields and types…

Disordered Systems and Neural Networks · Physics 2019-11-12 Shi-Xin Zhang

Symmetries impose structure on the Hilbert space of a quantum mechanical model. The mathematical units of this structure are the irreducible representations of symmetry groups and I consider how they function as conceptual units of…

Quantum Physics · Physics 2018-01-29 N. L. Harshman

Recent work has characterised rigorously what it means for one quantum system to simulate another, and demonstrated the existence of universal Hamiltonians -- simple spin lattice Hamiltonians that can replicate the entire physics of any…

Quantum Physics · Physics 2021-10-26 Tamara Kohler , Stephen Piddock , Johannes Bausch , Toby Cubitt

We present general mappings between classical spin systems and quantum physics. More precisely, we show how to express partition functions and correlation functions of arbitrary classical spin models as inner products between quantum…

Quantum Physics · Physics 2009-08-27 R. Hübener , M. Van den Nest , W. Dür , H. J. Briegel

We prove that the 2D Ising model is complete in the sense that the partition function of any classical q-state spin model (on an arbitrary graph) can be expressed as a special instance of the partition function of a 2D Ising model with…

Quantum Physics · Physics 2008-03-18 M. Van den Nest , W. Dür , H. J. Briegel

Turing machines and spin models share a notion of universality according to which some simulate all others. Is there a theory of universality that captures this notion? We set up a categorical framework for universality which includes as…

Computational Complexity · Computer Science 2024-09-04 Tomáš Gonda , Tobias Reinhart , Sebastian Stengele , Gemma De les Coves

We show that the two dimensional Ising model is complete, in the sense that the partition function of any lattice model on any graph is equal to the partition function of the 2D Ising model with complex coupling. The latter model has all…

Quantum Physics · Physics 2013-05-30 V. Karimipour , M. H. Zarei

Integrable models are often constructed with real systems in mind. The exact solvability of the models leads to results which are unambiguous and provide the correct physical picture. In this review, we discuss the physical basis of some…

Condensed Matter · Physics 2007-05-23 Indrani Bose

Molecular spin clusters are mesoscopic systems whose structural and physical features can be tailored at the synthetic level. Besides, their quantum behavior is directly accessible in laboratory and their magnetic properties can be…

Mesoscale and Nanoscale Physics · Physics 2015-05-18 F. Troiani , V. Bellini , A. Candini , G. Lorusso , M. Affronte

In the many fields in which the Ising model is applied nowadays, the spin variables are often assumed to be of spin-class $\{-1,1\}$ or $\{0,1\}$, even though for any mix of binary real valued spin-classes a proper Ising model distribution…

Statistical Mechanics · Physics 2020-06-25 Joost Kruis

Simulation models are an absolute necessity in the human and social sciences, which can only very exceptionally use experimental science methods to construct their knowledge. Models enable the simulation of social processes by replacing the…

Computers and Society · Computer Science 2020-01-06 J. Raimbault , D. Pumain
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