Search results for "Mathematical physics"

showing 10 items of 2687 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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Multi-GPU Accelerated Multi-Spin Monte Carlo Simulations of the 2D Ising Model

2010

A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468–4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message P…

FOS: Computer and information sciencesComputer scienceMonte Carlo methodGraphics processing unitFOS: Physical sciencesGeneral Physics and AstronomyMathematical Physics (math-ph)Parallel computingGPU clusterComputational Physics (physics.comp-ph)Graphics (cs.GR)Computational scienceCUDAComputer Science - GraphicsHardware and ArchitectureIsing modelCentral processing unitGeneral-purpose computing on graphics processing unitsMassively parallelPhysics - Computational PhysicsMathematical Physics
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The quantum query complexity of certification

2009

We study the quantum query complexity of finding a certificate for a d-regular, k-level balanced NAND formula. Up to logarithmic factors, we show that the query complexity is Theta(d^{(k+1)/2}) for 0-certificates, and Theta(d^{k/2}) for 1-certificates. In particular, this shows that the zero-error quantum query complexity of evaluating such formulas is O(d^{(k+1)/2}) (again neglecting a logarithmic factor). Our lower bound relies on the fact that the quantum adversary method obeys a direct sum theorem.

FOS: Computer and information sciencesDiscrete mathematicsQuantum Physics0209 industrial biotechnologyNuclear and High Energy PhysicsQuantum queryComputer scienceDirect sumFOS: Physical sciencesGeneral Physics and AstronomyStatistical and Nonlinear Physics0102 computer and information sciences02 engineering and technologyCertificationComputational Complexity (cs.CC)Certificate01 natural sciencesTheoretical Computer ScienceComputer Science - Computational Complexity020901 industrial engineering & automationComputational Theory and Mathematics010201 computation theory & mathematicsQuantum Physics (quant-ph)QuantumMathematical PhysicsQuantum Information and Computation
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Exact quantum algorithms have advantage for almost all Boolean functions

2014

It has been proved that almost all $n$-bit Boolean functions have exact classical query complexity $n$. However, the situation seemed to be very different when we deal with exact quantum query complexity. In this paper, we prove that almost all $n$-bit Boolean functions can be computed by an exact quantum algorithm with less than $n$ queries. More exactly, we prove that ${AND}_n$ is the only $n$-bit Boolean function, up to isomorphism, that requires $n$ queries.

FOS: Computer and information sciencesNuclear and High Energy Physics81P68 03D15Parity functionBoolean circuitGeneral Physics and AstronomyFOS: Physical sciencesBoolean algebras canonically definedComputational Complexity (cs.CC)Theoretical Computer ScienceCombinatoricsBoolean expressionBoolean functionMathematical PhysicsComputer Science::DatabasesMathematicsDiscrete mathematicsSymmetric Boolean functionQuantum PhysicsProduct termComputer Science::Information RetrievalStatistical and Nonlinear PhysicsComputer Science - Computational ComplexityComputational Theory and MathematicsMaximum satisfiability problemQuantum Physics (quant-ph)
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Quantum lower bound for inverting a permutation with advice

2014

Given a random permutation $f: [N] \to [N]$ as a black box and $y \in [N]$, we want to output $x = f^{-1}(y)$. Supplementary to our input, we are given classical advice in the form of a pre-computed data structure; this advice can depend on the permutation but \emph{not} on the input $y$. Classically, there is a data structure of size $\tilde{O}(S)$ and an algorithm that with the help of the data structure, given $f(x)$, can invert $f$ in time $\tilde{O}(T)$, for every choice of parameters $S$, $T$, such that $S\cdot T \ge N$. We prove a quantum lower bound of $T^2\cdot S \ge \tilde{\Omega}(\epsilon N)$ for quantum algorithms that invert a random permutation $f$ on an $\epsilon$ fraction of…

FOS: Computer and information sciencesNuclear and High Energy PhysicsComputer Science - Cryptography and SecurityGeneral Physics and AstronomyFOS: Physical sciencesOne-way functionComputational Complexity (cs.CC)Upper and lower boundsTheoretical Computer ScienceCyclic permutationCombinatoricsPermutationMathematical PhysicsMathematicsDiscrete mathematicsQuantum PhysicsBit-reversal permutationStatistical and Nonlinear PhysicsRandom permutationComputer Science - Computational ComplexityComputational Theory and MathematicsQuantum algorithmQuantum Physics (quant-ph)Advice (complexity)Cryptography and Security (cs.CR)MathematicsofComputing_DISCRETEMATHEMATICS
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A novel exact representation of stationary colored Gaussian processes (fractional differential approach)

2010

A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output of a set of linear fractional stochastic differential equations whose solution is a weighted sum of fractional Brownian motions. The exact form of the weighting coefficients is given and it is shown that it is related to the fractional moments of the target spectral density of the colored noise.

FOS: Computer and information sciencesStatistics and ProbabilityDifferential equationFOS: Physical sciencesGeneral Physics and AstronomyStatistics - ComputationStochastic differential equationsymbols.namesakeSpectral MomentsApplied mathematicsStationary processeGaussian processCondensed Matter - Statistical MechanicsComputation (stat.CO)Mathematical PhysicsMathematicsGeneralized functionStatistical Mechanics (cond-mat.stat-mech)Statistical and Nonlinear PhysicsMathematical Physics (math-ph)White noiseClosed and exact differential formsColors of noiseGaussian noiseFractional CalculuModeling and SimulationsymbolsSettore ICAR/08 - Scienza Delle Costruzioni
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Time and space efficient quantum algorithms for detecting cycles and testing bipartiteness

2016

We study space and time efficient quantum algorithms for two graph problems -- deciding whether an $n$-vertex graph is a forest, and whether it is bipartite. Via a reduction to the s-t connectivity problem, we describe quantum algorithms for deciding both properties in $\tilde{O}(n^{3/2})$ time and using $O(\log n)$ classical and quantum bits of storage in the adjacency matrix model. We then present quantum algorithms for deciding the two properties in the adjacency array model, which run in time $\tilde{O}(n\sqrt{d_m})$ and also require $O(\log n)$ space, where $d_m$ is the maximum degree of any vertex in the input graph.

FOS: Computer and information sciencesVertex (graph theory)Quantum PhysicsNuclear and High Energy PhysicsReduction (recursion theory)Two-graphFOS: Physical sciencesGeneral Physics and AstronomyStatistical and Nonlinear PhysicsTheoretical Computer ScienceCombinatoricsComputational Theory and MathematicsComputer Science - Data Structures and AlgorithmsBipartite graphGraph (abstract data type)Adjacency listData Structures and Algorithms (cs.DS)Quantum algorithmAdjacency matrixQuantum Physics (quant-ph)Mathematical PhysicsMathematicsofComputing_DISCRETEMATHEMATICSMathematicsQuantum Information and Computation
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Dirac equation as a quantum walk over the honeycomb and triangular lattices

2018

A discrete-time Quantum Walk (QW) is essentially an operator driving the evolution of a single particle on the lattice, through local unitaries. Some QWs admit a continuum limit, leading to well-known physics partial differential equations, such as the Dirac equation. We show that these simulation results need not rely on the grid: the Dirac equation in $(2+1)$--dimensions can also be simulated, through local unitaries, on the honeycomb or the triangular lattice. The former is of interest in the study of graphene-like materials. The latter, we argue, opens the door for a generalization of the Dirac equation to arbitrary discrete surfaces.

FOS: Computer and information sciences[ INFO ] Computer Science [cs]Differential equationFOS: Physical sciencestriangulation01 natural sciences010305 fluids & plasmassymbols.namesakeHigh Energy Physics - Lattice[PHYS.QPHY]Physics [physics]/Quantum Physics [quant-ph]Lattice (order)Mesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciences[ PHYS.PHYS.PHYS-GEN-PH ] Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]unitaritysurface[INFO]Computer Science [cs]Quantum walkHexagonal latticeDirac equationcontinuum limit010306 general physicsQuantumComputingMilieux_MISCELLANEOUSlatticeMathematical physicsPhysicsQuantum PhysicsPartial differential equationCondensed Matter - Mesoscale and Nanoscale PhysicsUnitarity[PHYS.HLAT]Physics [physics]/High Energy Physics - Lattice [hep-lat]High Energy Physics - Lattice (hep-lat)[ PHYS.HLAT ] Physics [physics]/High Energy Physics - Lattice [hep-lat]differential equations[PHYS.PHYS.PHYS-GEN-PH]Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]Computer Science - Distributed Parallel and Cluster ComputingDirac equationsymbolsDistributed Parallel and Cluster Computing (cs.DC)Quantum Physics (quant-ph)Physical Review A
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Quantum Toda Lattice: a Challenge for Representation Theory

2021

Quantum Toda lattice may solved by means of the Representation Theory of semisimple Lie groups, or alternatively by using the technique of the Quantum Inverse Scattering Method. A comparison of the two approaches, which is the purpose of the present review article, sheds a new light on Representation Theory and leads to a number of challenging questions.

FOS: MathematicsFOS: Physical sciences16T25 17B35 17B37 22E46 33B15 33C15Mathematical Physics (math-ph)[MATH] Mathematics [math]Representation Theory (math.RT)Mathematics - Representation TheoryMathematical PhysicsProceedings of Symposia in Pure Mathematics
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Free boundary methods and non-scattering phenomena

2021

We study a question arising in inverse scattering theory: given a penetrable obstacle, does there exist an incident wave that does not scatter? We show that every penetrable obstacle with real-analytic boundary admits such an incident wave. At zero frequency, we use quadrature domains to show that there are also obstacles with inward cusps having this property. In the converse direction, under a nonvanishing condition for the incident wave, we show that there is a dichotomy for boundary points of any penetrable obstacle having this property: either the boundary is regular, or the complement of the obstacle has to be very thin near the point. These facts are proved by invoking results from t…

FOS: MathematicsFOS: Physical sciencesMathematical Physics (math-ph)Analysis of PDEs (math.AP)
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