Search results for "Matrix multiplication"

showing 10 items of 20 documents

Fast Approximated Discriminative Common Vectors Using Rank-One SVD Updates

2013

An efficient incremental approach to the discriminative common vector (DCV) method for dimensionality reduction and classification is presented. The proposal consists of a rank-one update along with an adaptive restriction on the rank of the null space which leads to an approximate but convenient solution. The algorithm can be implemented very efficiently in terms of matrix operations and space complexity, which enables its use in large-scale dynamic application domains. Deep comparative experimentation using publicly available high dimensional image datasets has been carried out in order to properly assess the proposed algorithm against several recent incremental formulations.

Kernel (linear algebra)Discriminative modelRank (linear algebra)Computer scienceDimensionality reductionSingular value decompositionSpace (mathematics)AlgorithmMatrix multiplicationImage (mathematics)
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Entanglement continuous unitary transformations

2016

Continuous unitary transformations are a powerful tool to extract valuable information out of quantum many-body Hamiltonians, in which the so-called flow equation transforms the Hamiltonian to a diagonal or block-diagonal form in second quantization. Yet, one of their main challenges is how to approximate the infinitely-many coupled differential equations that are produced throughout this flow. Here we show that tensor networks offer a natural and non-perturbative truncation scheme in terms of entanglement. The corresponding scheme is called "entanglement-CUT" or eCUT. It can be used to extract the low-energy physics of quantum many-body Hamiltonians, including quasiparticle energy gaps. We…

PhysicsQuantum PhysicsStrongly Correlated Electrons (cond-mat.str-el)High Energy Physics - Lattice (hep-lat)FOS: Physical sciencesGeneral Physics and AstronomyQuantum entanglement01 natural sciencesSecond quantizationMatrix multiplication010305 fluids & plasmasCondensed Matter - Strongly Correlated Electronssymbols.namesakeTheoretical physicsHigh Energy Physics - Lattice0103 physical sciencesThermodynamic limitsymbolsIsing modelQuantum Physics (quant-ph)010306 general physicsHamiltonian (quantum mechanics)QuantumPotts modelEPL (Europhysics Letters)
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Entanglement in Gaussian matrix-product states

2006

Gaussian matrix product states are obtained as the outputs of projection operations from an ancillary space of M infinitely entangled bonds connecting neighboring sites, applied at each of N sites of an harmonic chain. Replacing the projections by associated Gaussian states, the 'building blocks', we show that the entanglement range in translationally-invariant Gaussian matrix product states depends on how entangled the building blocks are. In particular, infinite entanglement in the building blocks produces fully symmetric Gaussian states with maximum entanglement range. From their peculiar properties of entanglement sharing, a basic difference with spin chains is revealed: Gaussian matrix…

PhysicsQuantum PhysicsStatistical Mechanics (cond-mat.stat-mech)GaussianFOS: Physical sciencesMathematical Physics (math-ph)Quantum entanglementQuantum PhysicsQuantum numberSquashed entanglementMultipartite entanglementAtomic and Molecular Physics and OpticsProjection (linear algebra)Matrix multiplicationsymbols.namesakeQuantum mechanicssymbolsQuantum Physics (quant-ph)Quantum information scienceCondensed Matter - Statistical MechanicsMathematical PhysicsOptics (physics.optics)Physics - Optics
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Reverse-safe data structures for text indexing

2021

We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optim…

050101 languages & linguisticsComputer sciencedata structure02 engineering and technologyprivacySet (abstract data type)combinatoric0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesPattern matchingSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionialgorithmSettore INF/01 - Informatica05 social sciencesSearch engine indexingINF/01 - INFORMATICAdata miningData structureMatrix multiplicationcombinatoricsExponent020201 artificial intelligence & image processingdata structure; algorithm; combinatorics; de Bruijn graph; data mining; privacyAlgorithmAdversary modelde Bruijn graphInteger (computer science)
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Simulation of matrix product states for dissipation and thermalization dynamics of open quantum systems

2020

Abstract We transform the system/reservoir coupling model into a one-dimensional semi-infinite discrete chain through unitary transformation to simulate the open quantum system numerically with the help of time evolving block decimation (TEBD) algorithm. We apply the method to study the dynamics of dissipative systems. We also generate the thermal state of a multimode bath using minimally entangled typical thermal state (METTS) algorithm, and investigate the impact of the thermal bath on an empty system. For both cases, we give an extensive analysis of the impact of the modeling and simulation parameters, and compare the numerics with the analytics.

Physicsopen quantum systemthermal bathDynamics (mechanics)General Physics and AstronomyDissipationtime-evolving block decimation algorithm01 natural sciences114 Physical sciencesMatrix multiplication010305 fluids & plasmasOpen quantum systemThermalisationQuantum mechanicsalgoritmit0103 physical sciencesminimally entangled typical thermal stateskvanttifysiikka010306 general physicsQuantum
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Higher order matrix differential equations with singular coefficient matrices

2015

In this article, the class of higher order linear matrix differential equations with constant coefficient matrices and stochastic process terms is studied. The coefficient of the highest order is considered to be singular; thus, rendering the response determination of such systems in a straightforward manner a difficult task. In this regard, the notion of the generalized inverse of a singular matrix is used for determining response statistics. Further, an application relevant to engineering dynamics problems is included.

Stochastic partial differential equationMatrix (mathematics)Constant coefficientsSingular solutionComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONMathematical analysisMathematicsofComputing_NUMERICALANALYSISMatrix analysisCoefficient matrixDifferential algebraic equationMatrix multiplicationMathematicsAIP Conference Proceedings
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Versatile Direct and Transpose Matrix Multiplication with Chained Operations: An Optimized Architecture Using Circulant Matrices

2016

With growing demands in real-time control, classification or prediction, algorithms become more complex while low power and small size devices are required. Matrix multiplication (direct or transpose) is common for such computation algorithms. In numerous algorithms, it is also required to perform matrix multiplication repeatedly, where the result of a multiplication is further multiplied again. This work describes a versatile computation procedure and architecture: one of the matrices is stored in internal memory in its circulant form, then, a sequence of direct or transpose multiplications can be performed without timing penalty. The architecture proposes a RAM-ALU block for each matrix c…

Cycles per instructionBlock matrix020206 networking & telecommunications02 engineering and technologyParallel computingMatrix chain multiplicationMatrix multiplication020202 computer hardware & architectureTheoretical Computer ScienceMatrix (mathematics)Computational Theory and MathematicsHardware and ArchitectureTranspose0202 electrical engineering electronic engineering information engineeringMultiplicationHardware_ARITHMETICANDLOGICSTRUCTURESArithmeticCirculant matrixSoftwareMathematicsIEEE Transactions on Computers
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Fast Matrix Multiplication

2015

Until a few years ago, the fastest known matrix multiplication algorithm, due to Coppersmith and Winograd (1990), ran in time O(n2.3755). Recently, a surge of activity by Stothers, Vassilevska-Williams, and Le~Gall has led to an improved algorithm running in time O(n2.3729). These algorithms are obtained by analyzing higher and higher tensor powers of a certain identity of Coppersmith and Winograd. We show that this exact approach cannot result in an algorithm with running time O(n2.3725), and identify a wide class of variants of this approach which cannot result in an algorithm with running time $O(n^{2.3078}); in particular, this approach cannot prove the conjecture that for every e > 0, …

Class (set theory)Conjecturepeople.profession0102 computer and information sciences02 engineering and technology01 natural sciencesIdentity (music)Matrix multiplicationRunning timeCombinatorics010201 computation theory & mathematicsTensor (intrinsic definition)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingCoppersmithpeopleMathematicsCoppersmith–Winograd algorithmProceedings of the forty-seventh annual ACM symposium on Theory of Computing
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Empirical Autotuning of Two-level Parallel Linear Algebra Routines on Large cc-NUMA Systems

2012

In large cc-NUMA systems the efficient use of the different levels of the memory hierarchy is not an easy task, and the performance of multithreading implementations of the libraries decreases when the number of cores used increases, so producing an important lost of efficiency. To alleviate this problem, routines with multilevel parallelism can be developed by combining OpenMP and BLAS parallelism. In that way, higher performance can be achieved, but it is necessary to develop some autotuning technique for the appropriate selection of the number of threads to use at each level. The selection can be made through theoretical models of the execution time or some installation methodology. This…

Task (computing)Selection (relational algebra)Memory hierarchyComputer scienceMultithreadingLinear algebraParallelism (grammar)Parallel computingTemporal multithreadingMatrix multiplication2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications
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Response determination of linear dynamical systems with singular matrices: A polynomial matrix theory approach

2017

Abstract An approach is developed based on polynomial matrix theory for formulating the equations of motion and for determining the response of multi-degree-of-freedom (MDOF) linear dynamical systems with singular matrices and subject to linear constraints. This system modeling may appear for reasons such as utilizing redundant DOFs, and can be advantageous from a computational cost perspective, especially for complex (multi-body) systems. The herein developed approach can be construed as an alternative to the recently proposed methodology by Udwadia and coworkers, and has the significant advantage that it circumvents the use of pseudoinverses in determining the system response. In fact, ba…

Multibody system0209 industrial biotechnologyMathematical optimizationPolynomialApplied Mathematics02 engineering and technologyLinear constrained structural/mechanical systemPolynomial matrix theoryMatrix multiplicationPolynomial matrixMatrix polynomialLinear dynamical systemMatrix (mathematics)020303 mechanical engineering & transports020901 industrial engineering & automation0203 mechanical engineeringMatrix splittingModeling and SimulationApplied mathematicsMatrix analysisClosed form solutionSingular matrixMathematics
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