Search results for "K matrix"

showing 10 items of 20 documents

Implementing the three-particle quantization condition including higher partial waves

2019

We present an implementation of the relativistic three-particle quantization condition including both $s$- and $d$-wave two-particle channels. For this, we develop a systematic expansion about threshold of the three-particle divergence-free K matrix, $\mathcal{K}_{\mathrm{df,3}}$, which is a generalization of the effective range expansion of the two-particle K matrix, $\mathcal{K}_2$. Relativistic invariance plays an important role in this expansion. We find that $d$-wave two-particle channels enter first at quadratic order. We explain how to implement the resulting multichannel quantization condition, and present several examples of its application. We derive the leading dependence of the …

Nuclear and High Energy PhysicsNuclear TheoryAtomic Physics (physics.atom-ph)Relativistic invarianceFOS: Physical sciencesLattice QCD01 natural sciencesPhysics - Atomic PhysicsNuclear Theory (nucl-th)Quantization (physics)High Energy Physics - LatticeHigh Energy Physics - Phenomenology (hep-ph)0103 physical sciencesBound statelcsh:Nuclear and particle physics. Atomic energy. RadioactivityQuadratic orderScattering Amplitudes010306 general physicsNuclear theoryCondensed Matter - Statistical MechanicsK matrixMathematical physicsPhysicsLattice Quantum Field TheoryStatistical Mechanics (cond-mat.stat-mech)010308 nuclear & particles physicsHigh Energy Physics - Lattice (hep-lat)Lattice QCDScattering amplitudeHigh Energy Physics - Phenomenologylcsh:QC770-798Journal of High Energy Physics
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Order optimal preconditioners for fully implicit Runge-Kutta schemes applied to the bidomain equations

2010

The partial differential equation part of the bidomain equations is discretized in time with fully implicit Runge–Kutta methods, and the resulting block systems are preconditioned with a block diagonal preconditioner. By studying the time-stepping operator in the proper Sobolev spaces, we show that the preconditioned systems have bounded condition numbers given that the Runge–Kutta scheme is A-stable and irreducible with an invertible coefficient matrix. A new proof of order optimality of the preconditioners for the one-leg discretization in time of the bidomain equations is also presented. The theoretical results are verified by numerical experiments. Additionally, the concept of weakly po…

Numerical AnalysisPartial differential equationDiscretizationPreconditionerApplied MathematicsMathematical analysisBlock matrixComputer Science::Numerical AnalysisMathematics::Numerical Analysislaw.inventionSobolev spaceComputational MathematicsRunge–Kutta methodsInvertible matrixlawCoefficient matrixAnalysisMathematicsNumerical Methods for Partial Differential Equations
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Reduced scaling in electronic structure calculations using Cholesky decompositions

2003

The small numerical rank of the two-electron integral matrix for large molecular systems and large basis sets was demonstrated. Though, the current implementation still requires some improvements on the calculations done in the inner most loop of the decomposition do not exploit the parsity in the Cholesky vectors. With respect to the practical applicability of the presented method an efficient approach to geometrical derivatives was imperative. Such an approach was obtained including certain derivative product functions and decomposing an expanded integral matrix.

PhysicsMolecular electronic statesMolecular electronic states ; Quantum chemistryIntegral matrixGeneral Physics and AstronomyElectronic structureQuantum chemistryUNESCO::FÍSICA::Química físicaPhysics and Astronomy (all)Computational chemistryFock matrixApplied mathematicsDensity fittingPhysical and Theoretical Chemistry:FÍSICA::Química física [UNESCO]ScalingQuantum chemistryCholesky decomposition
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Clues for the existence of twoK1(1270)resonances

2007

The axial-vector meson ${K}_{1}(1270)$ was studied within the chiral unitary approach, where it was shown that it has a two-pole structure. We reanalyze the high-statistics WA3 experiment ${K}^{\ensuremath{-}}p\ensuremath{\rightarrow}{K}^{\ensuremath{-}}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}p$ at 63 GeV, which established the existence of both ${K}_{1}(1270)$ and ${K}_{1}(1400)$, and we show that it clearly favors our two-pole interpretation. We also reanalyze the traditional $K$-matrix interpretation of the WA3 data and find that the good fit of the data obtained there comes from large cancellations of terms of unclear physical interpretation.

PhysicsNuclear and High Energy PhysicsParticle physicsParticle decayChiral perturbation theoryPair productionBethe–Salpeter equationMesonUnitarityK matrixInterpretation (model theory)Physical Review D
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High selective H-plane TE dual mode cavity filter design by using nonresonating nodes

2013

The design of H-plane TE dual mode cavity filters using models containing nonresonating nodes is presented. From the models a coupling matrix is derived and decomposed into submatrices, each representing a subcircuit. The optimization and cascading of subcircuits represents a good starting point for the global optimization. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:161–166, 2014

PhysicsPlane (geometry)NRNsDual modeBlock matrixCoupling matrixCondensed Matter PhysicsTopologyDual-mode filterAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsFilter designSynthesisControl theoryTEORIA DE LA SEÑAL Y COMUNICACIONESPoint (geometry)Elliptic filterElliptic filterElectrical and Electronic EngineeringH-plane filterGlobal optimizationMicrowave
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Method specific Cholesky decomposition : Coulomb and exchange energies

2008

We present a novel approach to the calculation of the Coulomb and exchange contributions to the total electronic energy in self consistent field and density functional theory. The numerical procedure is based on the Cholesky decomposition and involves decomposition of specific Hadamard product matrices that enter the energy expression. In this way, we determine an auxiliary basis and obtain a dramatic reduction in size as compared to the resolution of identity (RI) method. Although the auxiliary basis is determined from the energy expression, we have complete control of the errors in the gradient or Fock matrix. Another important advantage of this method specific Cholesky decomposition is t…

PhysicsPotential energy functionsBasis (linear algebra)General Physics and AstronomyMinimum degree algorithmUNESCO::FÍSICA::Química físicaPhysics and Astronomy (all)Computational chemistryFock matrixDensity functional theoryHadamard productApplied mathematicsSCF calculationsDensity functional theoryDensity functional theory ; Hadamard matrices ; Potential energy functions ; SCF calculationsHadamard matricesPhysical and Theoretical Chemistry:FÍSICA::Química física [UNESCO]ScalingCholesky decompositionSparse matrix
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A construction of equivariant bundles on the space of symmetric forms

2021

We construct stable vector bundles on the space of symmetric forms of degree d in n+1 variables which are equivariant for the action of SL_{n+1}(C), and admit an equivariant free resolution of length 2. For n=1, we obtain new examples of stable vector bundles of rank d-1 on P^d, which are moreover equivariant for SL_2(C). The presentation matrix of these bundles attains Westwick's upper bound for the dimension of vector spaces of matrices of constant rank and fixed size.

Pure mathematicsRank (linear algebra)General MathematicsVector bundlestable vector bundlesSpace (mathematics)Mathematics - Algebraic GeometryMatrix (mathematics)symmetric formsDimension (vector space)FOS: MathematicsRepresentation Theory (math.RT)Algebraic Geometry (math.AG)Mathematics::Symplectic Geometryhomogeneous varietyMathematicsequivariant resolution14J60quiver representationconstant rank matrixhomogeneous bundleEquivariant mapgroup actionStable vector bundles; symmetric forms; group action; equivariant resolution; constant rank matrix; homogeneous bundle; homogeneous variety; quiver representationMathematics - Representation TheoryResolution (algebra)Vector spaceRevista Matemática Iberoamericana
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Structure of eigenvectors of random regular digraphs

2018

Let $d$ and $n$ be integers satisfying $C\leq d\leq \exp(c\sqrt{\ln n})$ for some universal constants $c, C>0$, and let $z\in \mathbb{C}$. Denote by $M$ the adjacency matrix of a random $d$-regular directed graph on $n$ vertices. In this paper, we study the structure of the kernel of submatrices of $M-z\,{\rm Id}$, formed by removing a subset of rows. We show that with large probability the kernel consists of two non-intersecting types of vectors, which we call very steep and gradual with many levels. As a corollary, we show, in particular, that every eigenvector of $M$, except for constant multiples of $(1,1,\dots,1)$, possesses a weak delocalization property: its level sets have cardin…

Random graphDegree (graph theory)Applied MathematicsGeneral MathematicsProbability (math.PR)010102 general mathematicsBlock matrix16. Peace & justice01 natural sciencesCombinatoricsCircular lawFOS: MathematicsRank (graph theory)60B20 15B52 46B06 05C80Adjacency matrix0101 mathematicsRandom matrixEigenvalues and eigenvectorsMathematics - ProbabilityMathematics
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Manager’s and citizen’s perspective of positive and negative risks for small probabilities

2011

So far „risk‟ has been mostly defined as the expected value of a loss, mathematically PL, being P the probability of an adverse event and L the loss incurred as a consequence of the event. The so called risk matrix is based on this definition. Also for favorable events one usually refers to the expected gain PG, being G the gain incurred as a consequence of the positive event. These “measures” are generally violated in practice. The case of insurances (on the side of losses, negative risk) and the case of lotteries (on the side of gains, positive risk) are the most obvious. In these cases a single person is available to pay a higher price than that stated by the mathematical expected valu…

Risk matrix Risk sustainability Managerial perspective Social perspectiveSettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E Tecnologica
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Rethinking the risk matrix

2011

So far risk has been mostly defined as the expected value of a loss, mathematically PL (being P the probability of an adverse event and L the loss incurred as a consequence of the adverse event). The so called risk matrix follows from such definition. This definition of risk is justified in a long term “managerial” perspective, in which it is conceivable to distribute the effects of an adverse event on a large number of subjects or a large number of recurrences. In other words, this definition is mostly justified on frequentist terms. Moreover, according to this definition, in two extreme situations (high-probability/low-consequence and low-probability/high-consequence), the estimated risk…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaRisk matrix Risk & sustainability Managerial perspective of risk Social perspective of risk
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