Search results for "Symbolic"

showing 10 items of 449 documents

RationalizeRoots: Software Package for the Rationalization of Square Roots

2019

The computation of Feynman integrals often involves square roots. One way to obtain a solution in terms of multiple polylogarithms is to rationalize these square roots by a suitable variable change. We present a program that can be used to find such transformations. After an introduction to the theoretical background, we explain in detail how to use the program in practice.

FOS: Computer and information sciencesComputer Science - Symbolic ComputationHigh Energy Physics - TheoryHigh energy particleFeynman integralComputationGeneral Physics and AstronomyFOS: Physical sciencesengineering.materialSymbolic Computation (cs.SC)Rationalization (economics)01 natural sciences010305 fluids & plasmasHigh Energy Physics - Phenomenology (hep-ph)Square root0103 physical sciencesComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONAlgebraic number010306 general physicsMathematical PhysicsVariable (mathematics)MapleMathematical Physics (math-ph)AlgebraHigh Energy Physics - PhenomenologyHigh Energy Physics - Theory (hep-th)Hardware and ArchitectureengineeringComputer Science - Mathematical SoftwareMathematical Software (cs.MS)
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A novel approach to integration by parts reduction

2015

Integration by parts reduction is a standard component of most modern multi-loop calculations in quantum field theory. We present a novel strategy constructed to overcome the limitations of currently available reduction programs based on Laporta's algorithm. The key idea is to construct algebraic identities from numerical samples obtained from reductions over finite fields. We expect the method to be highly amenable to parallelization, show a low memory footprint during the reduction step, and allow for significantly better run-times.

FOS: Computer and information sciencesComputer Science - Symbolic ComputationHigh Energy Physics - TheoryPhysicsNuclear and High Energy Physics010308 nuclear & particles physicsFOS: Physical sciencesConstruct (python library)Symbolic Computation (cs.SC)01 natural scienceslcsh:QC1-999Computational scienceReduction (complexity)High Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Finite fieldHigh Energy Physics - Theory (hep-th)Component (UML)0103 physical sciencesKey (cryptography)Memory footprintIntegration by partsAlgebraic number010306 general physicslcsh:PhysicsPhysics Letters B
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Conceptual Spaces for Cognitive Architectures: A lingua franca for different levels of representation

2017

During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [Laird (2012)]) adopt a classical symbolic approach, some (e.g. LEABRA [O'Reilly and Munakata (2000)]) are based on a purely connectionist model, while others (e.g. CLARION [Sun (2006)] adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and reasoning are also available [Kurup and Chandrasekaran (2007)]. In this p…

FOS: Computer and information sciencesConceptual SpaceCognitive Architectures; Cognitive modeling; Conceptual Spaces; Knowledge representation; Experimental and Cognitive Psychology; Cognitive Neuroscience; Artificial IntelligenceComputer Science - Artificial IntelligenceComputer scienceCognitive NeuroscienceExperimental and Cognitive Psychology02 engineering and technology050105 experimental psychologyCognitive modelingCognitive ArchitecturesConnectionismArtificial IntelligenceConceptual Spaces0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesSoarCognitive ArchitectureRepresentation (mathematics)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCognitive scienceKnowledge level05 social sciencesCommon groundCognitionCLARIONDiagrammatic reasoningArtificial Intelligence (cs.AI)Knowledge representation020201 artificial intelligence & image processingThe SymbolicBiologically Inspired Cognitive Architectures
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REDUCTION OF CONSTRAINT SYSTEMS

1993

Geometric modeling by constraints leads to large systems of algebraic equations. This paper studies bipartite graphs underlaid by systems of equations. It shows how these graphs make possible to polynomially decompose these systems into well constrained, over-, and underconstrained subsystems. This paper also gives an efficient method to decompose well constrained systems into irreducible ones. These decompositions greatly speed up the resolution in case of reducible systems. They also allow debugging systems of constraints.

FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)bipartite graphsmatchingperfect matching[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]maximum matching[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]geometric modelingComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONFOS: Mathematics[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]Mathematics - CombinatoricsCombinatorics (math.CO)constraintsComputer Science - Discrete Mathematics
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Symbolic integration of hyperexponential 1-forms

2019

Let $H$ be a hyperexponential function in $n$ variables $x=(x_1,\dots,x_n)$ with coefficients in a field $\mathbb{K}$, $[\mathbb{K}:\mathbb{Q}] <\infty$, and $\omega$ a rational differential $1$-form. Assume that $H\omega$ is closed and $H$ transcendental. We prove using Schanuel conjecture that there exist a univariate function $f$ and multivariate rational functions $F,R$ such that $\int H\omega= f(F(x))+H(x)R(x)$. We present an algorithm to compute this decomposition. This allows us to present an algorithm to construct a basis of the cohomology of differential $1$-forms with coefficients in $H\mathbb{K}[x,1/(SD)]$ for a given $H$, $D$ being the denominator of $dH/H$ and $S\in\mathbb{K}[x…

FOS: Computer and information sciencesMathematics - Differential GeometryComputer Science - Symbolic ComputationPure mathematicsMathematics::Commutative Algebra010102 general mathematics68W30Field (mathematics)010103 numerical & computational mathematicsFunction (mathematics)[MATH] Mathematics [math]Symbolic Computation (cs.SC)16. Peace & justiceFunctional decomposition01 natural sciencesDifferential Geometry (math.DG)FOS: MathematicsComputer Science::Symbolic Computation0101 mathematics[MATH]Mathematics [math]Symbolic integrationMathematics
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Constructing Antidictionaries in Output-Sensitive Space

2021

A word $x$ that is absent from a word $y$ is called minimal if all its proper factors occur in $y$. Given a collection of $k$ words $y_1,y_2,\ldots,y_k$ over an alphabet $\Sigma$, we are asked to compute the set $\mathrm{M}^{\ell}_{y_{1}\#\ldots\#y_{k}}$ of minimal absent words of length at most $\ell$ of word $y=y_1\#y_2\#\ldots\#y_k$, $\#\notin\Sigma$. In data compression, this corresponds to computing the antidictionary of $k$ documents. In bioinformatics, it corresponds to computing words that are absent from a genome of $k$ chromosomes. This computation generally requires $\Omega(n)$ space for $n=|y|$ using any of the plenty available $\mathcal{O}(n)$-time algorithms. This is because a…

FOS: Computer and information sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniOutput sensitive algorithmsString algorithmsPhysicsAntidictionarieSettore INF/01 - InformaticaOutput sensitive algorithm0102 computer and information sciencesAbsent wordsSpace (mathematics)01 natural sciencesAntidictionariesCombinatorics010201 computation theory & mathematicsTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYData compressionComputer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)Computer Science::Symbolic Computation[INFO]Computer Science [cs]Absent wordAlphabetWord (group theory)2019 Data Compression Conference (DCC)
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Determinantal sets, singularities and application to optimal control in medical imagery

2016

International audience; Control theory has recently been involved in the field of nuclear magnetic resonance imagery. The goal is to control the magnetic field optimally in order to improve the contrast between two biological matters on the pictures. Geometric optimal control leads us here to analyze mero-morphic vector fields depending upon physical parameters , and having their singularities defined by a deter-minantal variety. The involved matrix has polynomial entries with respect to both the state variables and the parameters. Taking into account the physical constraints of the problem, one needs to classify, with respect to the parameters, the number of real singularities lying in som…

FOS: Computer and information sciences[INFO.INFO-SC]Computer Science [cs]/Symbolic Computation [cs.SC]Computer Science - Symbolic Computation0209 industrial biotechnologyPolynomialRank (linear algebra)010102 general mathematicsBoundary (topology)Field (mathematics)02 engineering and technologySymbolic Computation (cs.SC)Optimal control01 natural sciencesPolynomial system solvingReal geometryPolynomial matrix[ INFO.INFO-SC ] Computer Science [cs]/Symbolic Computation [cs.SC]Set (abstract data type)Matrix (mathematics)020901 industrial engineering & automationApplications0101 mathematicsAlgorithmMathematics
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The infinite dihedral group

2022

We describe the infinite dihedral group as automaton group. We collect basic results and give full proofs in details for all statements.

FOS: Mathematics20F65 (Primary) 05C25 20E08 68Q70 13F25 (Secondary)Computer Science::Symbolic ComputationGroup Theory (math.GR)Nonlinear Sciences::Cellular Automata and Lattice GasesMathematics - Group TheoryComputer Science::Formal Languages and Automata Theory
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Group-Analytic Family Psychotherapy: A Transcultural Perspective

1997

Group-analytic family psychotherapy is a methodology based on a development of Group-analytic theory. The family is defined as a mental field formed by the symbolic plot of `us' in a double relationship: with the cultural history of the family group on one side, and with external groups on the other. The symbolic plot thus has a tribal characteristic which connects the genealogical trees to the ancestral foundation of the group. In cases of psychotic and borderline patients, Group-analytic family psychotherapy has indicated two types of family: those that are embedded in the past, or families that are cut off from the past. After outlining the circumstances of Italian families, this articl…

Family therapyPsychoanalysisPsychotherapistCultural historySocial PsychologyCultural anthropologyPerspective (graphical)Ethnic groupPsychiatry and Mental healthClinical PsychologyGroup analysisThe SymbolicPlot (narrative)PsychologyGroup Analysis
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A uniform quantificational logic for algebraic notions ofcontext

2002

A quantificational framework of formal reasoning is proposed, which emphasises the pattern of entering and exiting context. Contexts are modelled by an algebraic structure which reflects the order and manner in which context is entered into and exited from. The equations of the algebra partitions context terms into equivalence classes. A formal semantics is defined, containing models that map equivalence classes of certain context terms to sets of first order structures. The corresponding Hilbert system incorporates the algebraic equations as axioms asserted in context. In this way a uniform logic for arbitrary algebras of context is obtained. Soundness and completeness are proved. In semig…

Formalization of contextComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONVDP::Matematikk og naturvitenskap: 400::Matematikk: 410::Algebra/algebraisk analyse: 414Algebras of contextsLogic of contextual assertionsVDP::Humaniora: 000::Filosofiske fag: 160::Logikk: 163
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