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Although spin is a core property in fermionic systems, its symmetry can be easily violated in a variational simulation, especially when strong correlation plays a vital role therein. In this study, we will demonstrate that the broken…

Chemical Physics · Physics 2023-10-09 Takashi Tsuchimochi , Yuto Mori , Seiichiro L. Ten-no

We investigate the universality of multi-spin systems in architectures of various symmetries of coupling type and topology. Explicit reachability sets under symmetry constraints are provided. Thus for a given (possibly symmetric)…

Quantum Physics · Physics 2009-05-17 U. Sander , T. Schulte-Herbrueggen

Standard Monte Carlo cluster algorithms have proven to be very effective for many different spin models, however they fail for frustrated spin systems. Recently a generalized cluster algorithm was introduced that works extremely well for…

Condensed Matter · Physics 2009-10-22 P. D. Coddington , L. Han

This article presents a general solution to the problem of computational complexity. First, it gives a historical introduction to the problem since the revival of the foundational problems of mathematics at the end of the 19th century.…

Computational Complexity · Computer Science 2023-12-25 Rami Zaidan

This paper presents some ideas to reduce the computational cost of evidence-based robust design optimization. Evidence Theory crystallizes both the aleatory and epistemic uncertainties in the design parameters, providing two quantitative…

Computational Engineering, Finance, and Science · Computer Science 2012-07-17 Massimiliano Vasile , Edmondo Minisci , Quirien Wijnands

The central object of this PhD thesis is known under different names in the fields of computer science and statistical mechanics. In computer science, it is called the Maximum Cut problem, one of the famous twenty-one Karp's original…

Machine Learning · Computer Science 2022-08-31 Mikhail Krechetov

"The Price of Robustness" by Bertsimas and Sim represented a breakthrough in the development of a tractable robust counterpart of Linear Programming Problems. However, the central modeling assumption that the deviation band of each…

Optimization and Control · Mathematics 2014-10-24 Christina Büsing , Fabio D'Andreagiovanni

Inferential models (IMs) offer provably reliable, data-driven, possibilistic statistical inference. But despite the IM framework's theoretical and foundational advantages, efficient computation is a challenge. This paper presents a simple…

Computation · Statistics 2025-07-09 Leonardo Cella , Ryan Martin

A countable set of quantum superintegrable systems for arbitrary spin is solved explicitly using tools of supersymmetric quantum mechanics. It is shown that these systems (introduced by Pronko, J. Phys. A: Math. Theor. 40 (2007) ) include…

Mathematical Physics · Physics 2015-06-03 A. G. Nikitin

Constraint Programming (CP) has proved an effective paradigm to model and solve difficult combinatorial satisfaction and optimisation problems from disparate domains. Many such problems arising from the commercial world are permeated by…

Artificial Intelligence · Computer Science 2018-08-08 Neil Yorke-Smith , Carmen Gervet

The high-performance scalable parallel algorithm for rigorous calculation of partition function of lattice systems with finite number Ising spins was developed. The parallel calculations run by C++ code with using of Message Passing…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-02-21 Alexey A. Peretyatko , Ivan A. Bogatyrev , Vitaliy Yu. Kapitan , Yury V. Kirienko , Konstantin V. Nefedev , Valery I. Belokon

Finding robust solutions of an optimization problem is an important issue in practice, and various concepts on how to define the robustness of a solution have been suggested. The idea of recoverable robustness requires that a solution can…

Optimization and Control · Mathematics 2016-04-07 Emilio Carrizosa , Marc Goerigk , Anita Schöbel

We compute the integral of a function or the expectation of a random variable with minimal cost and use, for our new algorithm and for upper bounds of the complexity, i.i.d. samples. Under certain assumptions it is possible to select a…

Numerical Analysis · Mathematics 2018-10-24 Robert J. Kunsch , Erich Novak , Daniel Rudolf

In classic robust optimization, it is assumed that a set of possible parameter realizations, the uncertainty set, is modeled in a previous step and part of the input. As recent work has shown, finding the most suitable uncertainty set is in…

Optimization and Control · Mathematics 2016-10-18 André Chassein , Marc Goerigk

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

Many tasks in our modern life, such as planning an efficient travel, image processing and optimizing integrated circuit design, are modeled as complex combinatorial optimization problems with binary variables. Such problems can be mapped to…

Ising machines can solve combinatorial optimization problems by representing them as energy minimization problems. A common implementation is the probabilistic Ising machine (PIM), which uses probabilistic (p-) bits to represent coupled…

In a model with no given probability measure, we consider asset pricing in the presence of frictions and other imperfections and characterize the property of coherent pricing, a notion related to (but much weaker than) the no arbitrage…

Mathematical Finance · Quantitative Finance 2016-09-12 Gianluca Cassese

While the Ising model remains essential to understand physical phenomena, its natural connection to combinatorial reasoning makes it also one of the best models to probe complex systems in science and engineering. We bring a computational…

Computational Physics · Physics 2022-12-27 Shaan A. Nagy , Roger Paredes , Jeffrey M. Dudek , Leonardo Dueñas-Osorio , Moshe Y. Vardi

Let G = ((A,B),E) be an instance of the stable marriage problem where every vertex ranks its neighbors in a strict order of preference. A matching M in G is popular if M does not lose a head-to-head election against any matching. Popular…

Data Structures and Algorithms · Computer Science 2020-05-06 Yuri Faenza , Telikepalli Kavitha