The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Bas Luttik - One of the best experts on this subject based on the ideXlab platform.
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Unique parallel Decomposition for the pi calculus
arXiv: Logic in Computer Science, 2016Co-Authors: Matias David Lee, Bas LuttikAbstract:A (fragment of a) process algebra satisfies Unique parallel Decomposition if the definable behaviours admit a Unique Decomposition into indecomposable parallel components. In this paper we prove that finite processes of the pi-calculus, i.e. processes that perform no infinite executions, satisfy this property modulo strong bisimilarity and weak bisimilarity. Our results are obtained by an application of a general technique for establishing Unique parallel Decomposition using Decomposition orders.
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a Unique Decomposition theorem for ordered monoids with applications in process theory
Lecture Notes in Computer Science, 2003Co-Authors: Bas LuttikAbstract:We prove a Unique Decomposition theorem for a class of ordered commutative monoids. Then, we use our theorem to establish that every weakly normed process definable in \({\mathsf{ACP}{}^{{\mathalpha{\varepsilon}}}}\) with bounded communication can be expressed as the parallel composition of a multiset of weakly normed parallel prime processes in exactly one way.
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a Unique Decomposition theorem for ordered monoids with applications in process theory extended abstract
Mathematical Foundations of Computer Science, 2003Co-Authors: Bas LuttikAbstract:We prove a Unique Decomposition theorem for a class of ordered commutative monoids. Then, we use our theorem to establish that every weakly normed process definable in ACP e with bounded communication can be expressed as the parallel composition of a multiset of weakly normed parallel prime processes in exactly one way.
Sorin Popa - One of the best experts on this subject based on the ideXlab platform.
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a Unique Decomposition result for ht factors with torsion free core
Journal of Functional Analysis, 2007Co-Authors: Sorin PopaAbstract:We prove that II1 factors M have a Unique (up to unitary conjugacy) cross-product type Decomposition around “core subfactors” N⊂M satisfying the property HT of [S. Popa, On a class of type II1 factors with Betti numbers invariants, Ann. of Math. (2) 163 (2006) 809–899] and a certain “torsion freeness” condition. In particular, this shows that isomorphism of factors of the form Lαi(Z2)⋊Fni, i=1,2, for Fni⊂SL(2,Z) free groups of rank ni and αj=e2πitj, tj∉Q, implies n1=n2.
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a Unique Decomposition result for ht factors with torsion free core
arXiv: Operator Algebras, 2004Co-Authors: Sorin PopaAbstract:We prove that II$_1$ factors $M$ have a Unique (up to unitary conjugacy) cross-product type Decomposition around ``core subfactors'' $N \subset M$ satisfying the property HT and a certain ``torsion freeness'' condition. In particular, this shows that isomorphism of factors of the form $L_\alpha(\Bbb Z^2) \rtimes \Gamma$, for torsion free, non-amenable subgroups $\Gamma\subset SL(2, \Bbb Z)$ and $\alpha = e^{2\pi i t}$, $t \not\in \Bbb Q$, implies isomorphism of the corresponding groups $\Gamma$.
Joannes Schoukens - One of the best experts on this subject based on the ideXlab platform.
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Astronomical component estimation (ACE v.1) by time-variant sinusoidal modeling
Geoscientific Model Development, 2016Co-Authors: Matthias Sinnesael, Miroslav Zivanovic, David De Vleeschouwer, Philippe Claeys, Joannes SchoukensAbstract:Abstract. Accurately deciphering periodic variations in paleoclimate proxy signals is essential for cyclostratigraphy. Classical spectral analysis often relies on methods based on (fast) Fourier transformation. This technique has no Unique solution separating variations in amplitude and frequency. This characteristic can make it difficult to correctly interpret a proxy's power spectrum or to accurately evaluate simultaneous changes in amplitude and frequency in evolutionary analyses. This drawback is circumvented by using a polynomial approach to estimate instantaneous amplitude and frequency in orbital components. This approach was proven useful to characterize audio signals (music and speech), which are non-stationary in nature. Paleoclimate proxy signals and audio signals share similar dynamics; the only difference is the frequency relationship between the different components. A harmonic-frequency relationship exists in audio signals, whereas this relation is non-harmonic in paleoclimate signals. However, this difference is irrelevant for the problem of separating simultaneous changes in amplitude and frequency. Using an approach with overlapping analysis frames, the model (Astronomical Component Estimation, version 1: ACE v.1) captures time variations of an orbital component by modulating a stationary sinusoid centered at its mean frequency, with a single polynomial. Hence, the parameters that determine the model are the mean frequency of the orbital component and the polynomial coefficients. The first parameter depends on geologic interpretations, whereas the latter are estimated by means of linear least-squares. As output, the model provides the orbital component waveform, either in the depth or time domain. Uncertainty analyses of the model estimates are performed using Monte Carlo simulations. Furthermore, it allows for a Unique Decomposition of the signal into its instantaneous amplitude and frequency. Frequency modulation patterns reconstruct changes in accumulation rate, whereas amplitude modulation identifies eccentricity-modulated precession. The functioning of the time-variant sinusoidal model is illustrated and validated using a synthetic insolation signal. The new modeling approach is tested on two case studies: (1) a Pliocene–Pleistocene benthic δ18O record from Ocean Drilling Program (ODP) Site 846 and (2) a Danian magnetic susceptibility record from the Contessa Highway section, Gubbio, Italy.
Jonathan Barrett - One of the best experts on this subject based on the ideXlab platform.
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Information processing in generalized probabilistic theories
Physical Review A - Atomic Molecular and Optical Physics, 2007Co-Authors: Jonathan BarrettAbstract:I introduce a framework in which a variety of probabilistic theories can be defined, including classical and quantum theories, and many others. From two simple assumptions, a tensor product rule for combining separate systems can be derived. Certain features, usually thought of as specifically quantum, turn out to be generic in this framework, meaning that they are present in all except classical theories. These include the non-Unique Decomposition of a mixed state into pure states, a theorem involving disturbance of a system on measurement (suggesting that the possibility of secure key distribution is generic), and a no-cloning theorem. Two particular theories are then investigated in detail, for the sake of comparison with the classical and quantum cases. One of these includes states that can give rise to arbitrary non-signalling correlations, including the super-quantum correlations that have become known in the literature as Nonlocal Machines or Popescu-Rohrlich boxes. By investigating these correlations in the context of a theory with well-defined dynamics, I hope to make further progress with a question raised by Popescu and Rohrlich, which is, why does quantum theory not allow these strongly nonlocal correlations? The existence of such correlations forces much of the dynamics in this theory to be, in a certain sense, classical, with consequences for teleportation, cryptography and computation. I also investigate another theory in which all states are local. Finally, I raise the question of what further axiom(s) could be added to the framework in order Uniquely to identify quantum theory, and hypothesize that quantum theory is optimal for computation.
Matthias Sinnesael - One of the best experts on this subject based on the ideXlab platform.
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Astronomical component estimation (ACE v.1) by time-variant sinusoidal modeling
Geoscientific Model Development, 2016Co-Authors: Matthias Sinnesael, Miroslav Zivanovic, David De Vleeschouwer, Philippe Claeys, Joannes SchoukensAbstract:Abstract. Accurately deciphering periodic variations in paleoclimate proxy signals is essential for cyclostratigraphy. Classical spectral analysis often relies on methods based on (fast) Fourier transformation. This technique has no Unique solution separating variations in amplitude and frequency. This characteristic can make it difficult to correctly interpret a proxy's power spectrum or to accurately evaluate simultaneous changes in amplitude and frequency in evolutionary analyses. This drawback is circumvented by using a polynomial approach to estimate instantaneous amplitude and frequency in orbital components. This approach was proven useful to characterize audio signals (music and speech), which are non-stationary in nature. Paleoclimate proxy signals and audio signals share similar dynamics; the only difference is the frequency relationship between the different components. A harmonic-frequency relationship exists in audio signals, whereas this relation is non-harmonic in paleoclimate signals. However, this difference is irrelevant for the problem of separating simultaneous changes in amplitude and frequency. Using an approach with overlapping analysis frames, the model (Astronomical Component Estimation, version 1: ACE v.1) captures time variations of an orbital component by modulating a stationary sinusoid centered at its mean frequency, with a single polynomial. Hence, the parameters that determine the model are the mean frequency of the orbital component and the polynomial coefficients. The first parameter depends on geologic interpretations, whereas the latter are estimated by means of linear least-squares. As output, the model provides the orbital component waveform, either in the depth or time domain. Uncertainty analyses of the model estimates are performed using Monte Carlo simulations. Furthermore, it allows for a Unique Decomposition of the signal into its instantaneous amplitude and frequency. Frequency modulation patterns reconstruct changes in accumulation rate, whereas amplitude modulation identifies eccentricity-modulated precession. The functioning of the time-variant sinusoidal model is illustrated and validated using a synthetic insolation signal. The new modeling approach is tested on two case studies: (1) a Pliocene–Pleistocene benthic δ18O record from Ocean Drilling Program (ODP) Site 846 and (2) a Danian magnetic susceptibility record from the Contessa Highway section, Gubbio, Italy.
