Search results for "FOS: Mathematics"

showing 10 items of 1448 documents

A Quantitative Analysis of Metrics on Rn with Almost Constant Positive Scalar Curvature, with Applications to Fast Diffusion Flows

2017

We prove a quantitative structure theorem for metrics on $\mathbf{R}^n$ that are conformal to the flat metric, have almost constant positive scalar curvature, and cannot concentrate more than one bubble. As an application of our result, we show a quantitative rate of convergence in relative entropy for a fast diffusion equation in $\mathbf{R}^n$ related to the Yamabe flow.

General MathematicsYamabe flow010102 general mathematicsMathematical analysisMetric Geometry (math.MG)01 natural sciencesMathematics - Analysis of PDEsMathematics - Metric Geometry0103 physical sciencesFOS: Mathematics010307 mathematical physics0101 mathematicsDiffusion (business)Constant (mathematics)Quantitative analysis Yamabe flow fast diffusion flowQuantitative analysis (chemistry)Analysis of PDEs (math.AP)MathematicsScalar curvature
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Removable singularities for div v=f in weighted Lebesgue spaces

2018

International audience; Let $w\in L^1_{loc}(\R^n)$ be apositive weight. Assuming that a doubling condition and an $L^1$ Poincar\'e inequality on balls for the measure $w(x)dx$, as well as a growth condition on $w$, we prove that the compact subsets of $\R^n$ which are removable for the distributional divergence in $L^{\infty}_{1/w}$ are exactly those with vanishing weighted Hausdorff measure. We also give such a characterization for $L^p_{1/w}$, $1<p<+\infty$, in terms of capacity. This generalizes results due to Phuc and Torres, Silhavy and the first author.

General Mathematics[MATH.MATH-CA]Mathematics [math]/Classical Analysis and ODEs [math.CA]Characterization (mathematics)[MATH.MATH-FA]Mathematics [math]/Functional Analysis [math.FA]01 natural sciencesMeasure (mathematics)functional analysisCombinatoricsMathematics - Analysis of PDEsWeightsRemovable setsClassical Analysis and ODEs (math.CA)FOS: Mathematics[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]Hausdorff measure0101 mathematicsLp spaceMathematicsremovable singularities010102 general mathematicsta111Divergence operatorMSC 2010: 28A12 42B37Functional Analysis (math.FA)Mathematics - Functional AnalysisMathematics - Classical Analysis and ODEsGravitational singularityweighted Lebesgue spacesfunktionaalianalyysiAnalysis of PDEs (math.AP)
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Mappings of Finite Distortion : Compactness of the Branch Set

2017

We show that an entire branched cover of finite distortion cannot have a compact branch set if its distortion satisfies a certain asymptotic growth condition. We furthermore show that this bound is strict by constructing an entire, continuous, open and discrete mapping of finite distortion which is piecewise smooth, has a branch set homeomorphic to an (n - 2)-dimensional torus and distortion arbitrarily close to the asymptotic bound. Peer reviewed

General Mathematicsbranch setsCOVERS01 natural sciencesfunktioteoriaSet (abstract data type)Mathematics - Geometric TopologyDimension (vector space)DistortionFOS: Mathematics111 Mathematicsfinite distortionComplex Variables (math.CV)topologia0101 mathematicsDIMENSIONMathematicsPartial differential equationMathematics - Complex Variables010102 general mathematicsMathematical analysisGeometric Topology (math.GT)TorusCompact spaceCover (topology)57M12 30C65PiecewiseLIGHT OPEN MAPSmonistotAnalysis
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Generalized Riesz systems and quasi bases in Hilbert space

2019

The purpose of this article is twofold. First of all, the notion of $(D, E)$-quasi basis is introduced for a pair $(D, E)$ of dense subspaces of Hilbert spaces. This consists of two biorthogonal sequences $\{ \varphi_n \}$ and $\{ \psi_n \}$ such that $\sum_{n=0}^\infty \ip{x}{\varphi_n}\ip{\psi_n}{y}=\ip{x}{y}$ for all $x \in D$ and $y \in E$. Secondly, it is shown that if biorthogonal sequences $\{ \varphi_n \}$ and $\{ \psi_n \}$ form a $(D ,E)$-quasi basis, then they are generalized Riesz systems. The latter play an interesting role for the construction of non-self-adjoint Hamiltonians and other physically relevant operators.

General Mathematicsquasi-basesMathematics::Number TheoryFOS: Physical sciences01 natural sciencesCombinatoricssymbols.namesakeRiesz systemSettore MAT/05 - Analisi MatematicaFOS: Mathematics0101 mathematicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsMathematicsMathematics::Functional AnalysisHigh Energy Physics::Phenomenology010102 general mathematicsHilbert spaceBasis (universal algebra)Mathematical Physics (math-ph)Linear subspaceFunctional Analysis (math.FA)010101 applied mathematicsMathematics - Functional AnalysisBiorthogonal systemsymbols
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Circular law for sparse random regular digraphs

2020

Fix a constant $C\geq 1$ and let $d=d(n)$ satisfy $d\leq \ln^{C} n$ for every large integer $n$. Denote by $A_n$ the adjacency matrix of a uniform random directed $d$-regular graph on $n$ vertices. We show that, as long as $d\to\infty$ with $n$, the empirical spectral distribution of appropriately rescaled matrix $A_n$ converges weakly in probability to the circular law. This result, together with an earlier work of Cook, completely settles the problem of weak convergence of the empirical distribution in directed $d$-regular setting with the degree tending to infinity. As a crucial element of our proof, we develop a technique of bounding intermediate singular values of $A_n$ based on studyi…

General Mathematicsregular graphsrandom matrices01 natural sciencesCombinatoricsMatrix (mathematics)FOS: Mathematics60B20 15B52 46B06 05C80Adjacency matrix0101 mathematicsrandom graphsMathematicsRandom graphlogarithmic potentialWeak convergenceDegree (graph theory)sparse matricesApplied MathematicsProbability (math.PR)010102 general mathematicsCircular lawSingular valueCircular lawintermediate singular valuesRandom matrixMathematics - ProbabilityJournal of the European Mathematical Society
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NUMERICAL ALGORITHMS

2013

For many systems of differential equations modeling problems in science and engineering, there are natural splittings of the right hand side into two parts, one non-stiff or mildly stiff, and the other one stiff. For such systems implicit-explicit (IMEX) integration combines an explicit scheme for the non-stiff part with an implicit scheme for the stiff part. In a recent series of papers two of the authors (Sandu and Zhang) have developed IMEX GLMs, a family of implicit-explicit schemes based on general linear methods. It has been shown that, due to their high stage order, IMEX GLMs require no additional coupling order conditions, and are not marred by order reduction. This work develops a …

General linear methodsMathematical optimizationIMEX methods; general linear methods; error analysis; order conditions; stability analysisIMEX methodsDifferential equationSCHEMESorder conditionsMathematics AppliedExtrapolationStability (learning theory)QUADRATIC STABILITYstability analysisPARABOLIC EQUATIONSSYSTEMSNORDSIECK METHODSFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisRUNGE-KUTTA METHODSMULTISTEP METHODSerror analysisMathematicsCONSTRUCTIONSeries (mathematics)Applied MathematicsNumerical analysisComputer Science - Numerical AnalysisStability analysisORDEROrder conditionsNumerical Analysis (math.NA)Computer Science::Numerical AnalysisRunge–Kutta methodsGeneral linear methodsError analysisORDINARY DIFFERENTIAL-EQUATIONSOrdinary differential equationgeneral linear methodsMathematics
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On the fractional probabilistic Taylor's and mean value theorems

2016

In order to develop certain fractional probabilistic analogues of Taylor's theorem and mean value theorem, we introduce the nth-order fractional equilibrium distribution in terms of the Weyl fractional integral and investigate its main properties. Specifically, we show a characterization result by which the nth-order fractional equilibrium distribution is identical to the starting distribution if and only if it is exponential. The nth-order fractional equilibrium density is then used to prove a fractional probabilistic Taylor's theorem based on derivatives of Riemann-Liouville type. A fractional analogue of the probabilistic mean value theorem is thus developed for pairs of nonnegative rand…

Generalized Taylor’s formulaMean value theoremSurvival bounded order01 natural sciencesStochastic ordering010104 statistics & probabilityCharacterization of exponential distribution; Fractional calculus; Fractional equilibrium distribution; Generalized Taylor’s formula; Mean value theorem; Survival bounded orderFOS: MathematicsCharacterization of exponential distributionApplied mathematics0101 mathematicsMathematicsComputer Science::Information RetrievalApplied MathematicsProbability (math.PR)010102 general mathematicsProbabilistic logic60E99 26A33 26A24Fractional calculusFractional equilibrium distributionFractional calculusExponential functionDistribution (mathematics)Bounded functionMean value theorem (divided differences)Random variableAnalysisMathematics - Probability
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Recovery of time-dependent coefficients from boundary data for hyperbolic equations

2019

We study uniqueness of the recovery of a time-dependent magnetic vector-valued potential and an electric scalar-valued potential on a Riemannian manifold from the knowledge of the Dirichlet to Neumann map of a hyperbolic equation. The Cauchy data is observed on time-like parts of the space-time boundary and uniqueness is proved up to the natural gauge for the problem. The proof is based on Gaussian beams and inversion of the light ray transform on Lorentzian manifolds under the assumptions that the Lorentzian manifold is a product of a Riemannian manifold with a time interval and that the geodesic ray transform is invertible on the Riemannian manifold.

GeodesicDirichlet-to-Neumann maplight ray transformmagnetic potentialBoundary (topology)CALDERON PROBLEM01 natural sciencesGaussian beamMathematics - Analysis of PDEsFOS: Mathematics111 Mathematics[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]Uniqueness0101 mathematicsMathematics::Symplectic GeometryMathematical PhysicsMathematicsX-ray transformSTABILITYinverse problemsMathematical analysisStatistical and Nonlinear PhysicsRiemannian manifoldX-RAY TRANSFORMWave equationMathematics::Geometric TopologyManifoldTENSOR-FIELDS010101 applied mathematicsUNIQUE CONTINUATIONGeometry and TopologyMathematics::Differential GeometryWAVE-EQUATIONSHyperbolic partial differential equationAnalysis of PDEs (math.AP)
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Exact simulation of first exit times for one-dimensional diffusion processes

2019

International audience; The simulation of exit times for diffusion processes is a challenging task since it concerns many applications in different fields like mathematical finance, neuroscience, reliability horizontal ellipsis The usual procedure is to use discretization schemes which unfortunately introduce some error in the target distribution. Our aim is to present a new algorithm which simulates exactly the exit time for one-dimensional diffusions. This acceptance-rejection algorithm requires to simulate exactly the exit time of the Brownian motion on one side and the Brownian position at a given time, constrained not to have exit before, on the other side. Crucial tools in this study …

Girsanov theoremand phrases: Exit timeDiscretizationsecondary: 65N75Exit time Brownian motion diffusion processes Girsanov’s transformation rejection sampling exact simulation randomized algorithm conditioned Brownian motion.MSC 65C05 65N75 60G40Exit time01 natural sciencesGirsanov’s transformationrandomized algorithm010104 statistics & probabilityrejection samplingGirsanov's transformationexact simulationFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsConvergent seriesBrownian motion60G40MathematicsNumerical AnalysisApplied MathematicsMathematical financeRejection samplingProbability (math.PR)diffusion processesNumerical Analysis (math.NA)conditioned Brownian motionRandomized algorithm010101 applied mathematics[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Computational MathematicsModeling and Simulationconditioned Brownian motion 2010 AMS subject classifications: primary 65C05Brownian motionRandom variableMathematics - ProbabilityAnalysis[MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
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Radio Labelings of Distance Graphs

2013

A radio $k$-labeling of a connected graph $G$ is an assignment $c$ of non negative integers to the vertices of $G$ such that $$|c(x) - c(y)| \geq k+1 - d(x,y),$$ for any two vertices $x$ and $y$, $x\ne y$, where $d(x,y)$ is the distance between $x$ and $y$ in $G$. In this paper, we study radio labelings of distance graphs, i.e., graphs with the set $\Z$ of integers as vertex set and in which two distinct vertices $i, j \in \Z$ are adjacent if and only if $|i - j| \in D$.

Graph labeling05C12 05C78Edge-graceful labeling0211 other engineering and technologies0102 computer and information sciences02 engineering and technology[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]01 natural sciencesCombinatoricsIndifference graphChordal graphradio k-labeling numberFOS: MathematicsDiscrete Mathematics and CombinatoricsMathematics - CombinatoricsGraph toughnessMathematicsDiscrete mathematicsResistance distanceApplied Mathematicsgraph labeling021107 urban & regional planning[ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM]distance graph[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]010201 computation theory & mathematicsIndependent setdistance graph.Combinatorics (math.CO)MSC 05C12 05C78Distance
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