Search results for "Theoretical Computer Science"
showing 10 items of 1151 documents
Quantum chemical meta-workflows in MoSGrid
2014
Quantum chemical workflows can be built up within the science gateway Molecular Simulation Grid. Complex workflows required by the end users are dissected into smaller workflows that can be combined freely to larger meta-workflows. General quantum chemical workflows are described here as well as the real use case of a spectroscopic analysis resulting in an end-user desired meta-workflow. All workflow features are implemented via Web Services Parallel Grid Runtime and Developer Environment and submitted to UNICORE. The workflows are stored in the Molecular Simulation Grid repository and ported to the SHIWA repository. © 2014 John Wiley & Sons, Ltd.
Lattice quantum hadrodynamics on a CRAY Y-MP
1992
Quantum corrections to the mean-field equation of state for nuclear matter are estimated in a lattice simulation of quantum hadrodynamics on a CRAY Y-MP. In contrast with lattice quantum chromodynamics, where coordinate space methods are the standard, the calculations are carried out in momentum space and on nonhypercubic (irregular) lattices. The quantum corrections to the known, mean-field equation of state were found to be considerable. The time frame of the project and the large computational needs of the program required the use of powerful supercomputers, like the CRAY Y-MP, which are capable of performing at a very high computing speed by using both vector and parallel hardware, the …
Quantum Computing with Trapped Charged Particles
2009
The concept of quantum computing has no clear cut origin. It emerged from combinations of information theory and quantum mechanical concepts. A decisive step was taken by Feynman [414, 415] who considered the possibility of universal simulation, a quantum system which could simulate the physical behavior of any other. Feynman gave arguments which suggested that quantum evolution could be used to compute certain problems more efficiently than any classical computer. His device may be considered as not sufficiently specified to be called a computer. The next important step was taken in 1985 by Deutsch [310]. His proposal is generally considered to represent the first blueprint for a quantum c…
Quantum query algorithms for certain functions and general algorithm construction techniques
2007
Quantum algorithms can be analyzed in a query model to compute Boolean functions where input is given in a black box, but the aim is to compute function value for arbitrary input using as few queries as possible. In this paper we concentrate on quantum query algorithm designing tasks. The main aim of research was to find new efficient algorithms and develop general algorithm designing techniques. We present several exact quantum query algorithms for certain problems that are better than classical counterparts. Next we introduce algorithm transformation methods that allow significant enlarging of sets of exactly computable functions. Finally, we propose quantum algorithm designing methods. G…
Quantum versus classical query complexity of relation
2011
This paper investigates the computability of mathematical relations in a quantum query model. The important task in complexity theory is to find examples with a large gap between classical and quantum algorithm complexity of the same computational problem. We present new results in quantum query algorithm design that allow achieving a large separation between classical and quantum query complexity of a specific relation. We demonstrate an example where quantum query algorithm for a finite relation needs more than two times fewer queries than the best possible classical analogue. We also show that relation can be extended to infinite family of relations with an input of general size N.
A NEURAL NETWORK PRIMER
1994
Neural networks are composed of basic units somewhat analogous to neurons. These units are linked to each other by connections whose strength is modifiable as a result of a learning process or algorithm. Each of these units integrates independently (in paral lel) the information provided by its synapses in order to evaluate its state of activation. The unit response is then a linear or nonlinear function of its activation. Linear algebra concepts are used, in general, to analyze linear units, with eigenvectors and eigenvalues being the core concepts involved. This analysis makes clear the strong similarity between linear neural networks and the general linear model developed by statisticia…
Inferring networks from high-dimensional data with mixed variables
2014
We present two methodologies to deal with high-dimensional data with mixed variables, the strongly decomposable graphical model and the regression-type graphical model. The first model is used to infer conditional independence graphs. The latter model is applied to compute the relative importance or contribution of each predictor to the response variables. Recently, penalized likelihood approaches have also been proposed to estimate graph structures. In a simulation study, we compare the performance of the strongly decomposable graphical model and the graphical lasso in terms of graph recovering. Five different graph structures are used to simulate the data: the banded graph, the cluster gr…
From time series to complex networks: the visibility graph
2008
In this work we present a simple and fast computational method, the visibility algorithm , that converts a time series into a graph. The constructed graph inherits several properties of the series in its structure. Thereby, periodic series convert into regular graphs, and random series do so into random graphs. Moreover, fractal series convert into scale-free networks, enhancing the fact that power law degree distributions are related to fractality, something highly discussed recently. Some remarkable examples and analytical tools are outlined to test the method's reliability. Many different measures, recently developed in the complex network theory, could by means of this new approach cha…
Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines
2021
Tsetlin Machines (TMs) capture patterns using conjunctive clauses in propositional logic, thus facilitating interpretation. However, recent TM-based approaches mainly rely on inspecting the full range of clauses individually. Such inspection does not necessarily scale to complex prediction problems that require a large number of clauses. In this paper, we propose closed-form expressions for understanding why a TM model makes a specific prediction (local interpretability). Additionally, the expressions capture the most important features of the model overall (global interpretability). We further introduce expressions for measuring the importance of feature value ranges for continuous feature…
Exact Response Time Analysis of Hierarchical Fixed-Priority Scheduling
2009
Hierarchical scheduling has recently been used to provide temporal isolation to embedded virtualised systems. Response time analysis is a common way to derive a schedulability test for these systems. This paper points out that response time analysis for hierarchical fixed-priority scheduling found in the literature is only exact for tasks of the highest priority domain. For the rest of the tasks is an upper bound. In our work, we provide the exact analysis and we compare it with previously published works.