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Geometric programming (GP) provides a power tool for solving a variety of optimization problems. In the real world, many applications of geometric programming (GP) are engineering design problems in which some of the problem parameters are…

Numerical Analysis · Computer Science 2010-02-08 A. K. Ojha , A. K. Das

In this thesis massive higher derivative gravity theories are analyzed in some detail. One-particle scattering amplitude between two covariantly conserved sources mediated by a graviton exchange is found at tree-level in $D$ dimensional…

General Relativity and Quantum Cosmology · Physics 2012-02-01 Ibrahim Gullu

We explore the energy content of superpositions of current states. Specifically, we focus on the maximum energy that can be extracted from them through local unitary transformations. The figure of merit we employ is the local ergotropy. We…

Quantum Physics · Physics 2025-06-17 Francesco Perciavalle , Davide Rossini , Juan Polo , Luigi Amico

In this paper we consider estimating the number of solutions to multiplicative equations in finite fields when the variables run through certain sets with high additive structure. In particular, we consider estimating the multiplicative…

Number Theory · Mathematics 2019-03-22 Bryce Kerr

In this paper we present a new efficient variant to compute strong Gr\"obner basis over quotients of principal ideal domains. We show an easy lifting process which allows us to reduce one computation over the quotient $R/nR$ to two…

Commutative Algebra · Mathematics 2019-06-21 Christian Eder , Tommy Hofmann

We obtain a representation of pairing energies in phase space, for the Lipkin-Meshkov-Glick and general boson Bardeen-Cooper-Schrieffer pairing models. This is done by means of a probability distribution of the quantum state in phase space.…

Quantum Physics · Physics 2014-11-14 M. Calixto , O. Castaños , E. Romera

We present an effective method for computing parametric primary decomposition via comprehensive Gr\"obner systems. In general, it is very difficult to compute a parametric primary decomposition of a given ideal in the polynomial ring with…

Symbolic Computation · Computer Science 2024-08-29 Yuki Ishihara , Kazuhiro Yokoyama

A strongly polynomial algorithm is given for the generalized flow maximization problem. It uses a new variant of the scaling technique, called continuous scaling. The main measure of progress is that within a strongly polynomial number of…

Data Structures and Algorithms · Computer Science 2016-03-01 László A. Végh

We show how the localization landscape, originally introduced to bound low energy eigenstates of disordered wave media and many-body quantum systems, can form the basis for hardware-efficient quantum algorithms for solving binary…

Quantum Physics · Physics 2023-07-06 Benjamin Y. L. Tan , Beng Yee Gan , Daniel Leykam , Dimitris G. Angelakis

In this paper, we present a generic parametrization of generically zero-dimensional parametric polynomial systems. More specifically, we study the specialization properties of the Rational Univariate Representation and derive bounds on the…

Symbolic Computation · Computer Science 2026-02-09 Florent Corniquel

Polymorphism rationalizes how processing can control the final structure of a material. The rugged free-energy landscape and exceedingly slow kinetics in the solid state have so far hampered computational investigations. We report for the…

Soft Condensed Matter · Physics 2020-07-24 Chan Liu , Jan Gerit Brandenburg , Omar Valsson , Kurt Kremer , Tristan Bereau

We consider polynomials of a few linear forms and show how exploit this type of sparsity for optimization on some particular domains like the Euclidean sphere or a polytope. Moreover, a simple procedure allows to detect this form of…

Optimization and Control · Mathematics 2022-04-05 Jean-Bernard Lasserre

Minimal problems in computer vision raise the demand of generating efficient automatic solvers for polynomial equation systems. Given a polynomial system repeated with different coefficient instances, the traditional Gr\"obner basis or…

Computer Vision and Pattern Recognition · Computer Science 2020-04-27 Bo Li , Viktor Larsson

The advent of plant phenomics, coupled with the wealth of genotypic data generated by next-generation sequencing technologies, provides exciting new resources for investigations into and improvement of complex traits. However, these new…

Genomics · Quantitative Biology 2019-04-30 Gota Morota , Diego Jarquin , Malachy T. Campbell , Hiroyoshi Iwata

We explore whether the topology of energy landscapes in chemical systems obeys any rules and what these rules are. To answer this and related questions we use several tools: (i)Reduced energy surface and its density of states, (ii)…

Materials Science · Physics 2015-05-14 Artem R. Oganov , Mario Valle

We characterize the approximation spaces of a broad class of bases - which includes almost greedy bases - in terms of weighted Lorentz spaces. For those bases, we also find necessary and sufficient conditions under which the approximation…

Functional Analysis · Mathematics 2025-02-17 Miguel Berasategui , Pablo M. Berná , Andrea García

We propose two efficient algorithms for configurational sampling of systems with rough energy landscape. The first one is a new method for the determination of the multicanonical weight factor. In this method a short replica-exchange…

Statistical Mechanics · Physics 2009-10-31 Yuji Sugita , Yuko Okamoto

This paper presents an alternative approach to simplify the proofs of some important results related to polynomial mappings in Computational Algebraic Geometry such as Polynomial Implicitization, Image Closure and some properties of the…

Algebraic Geometry · Mathematics 2011-11-30 Yongbi Li

We address the problem of constructing accurate mathematical models of the dynamics of complex systems projected on a collective variable. To this aim we introduce a conceptually simple yet effective algorithm for estimating the parameters…

Statistical Mechanics · Physics 2022-09-28 Karen Palacio-Rodriguez , Fabio Pietrucci

We study the equilibrium states of energy functions involving a large set of real variables, defined on the links of sparsely connected networks, and interacting at the network nodes, using the cavity and replica methods. When applied to…

Disordered Systems and Neural Networks · Physics 2009-11-11 K. Y. Michael Wong , David Saad