Matching conditional moments in PDF modelling of nonpremixed combustion

The rate of generation of fluctuations with respect to the scalar values conditioned on the mixture fraction, which significantly affects turbulent nonpremixed combustion processes, is examined. Simulation of the rate in a major mixing model is investigated and the derived equations can assist in selecting the model parameters so that the level of conditional fluctuations is better reproduced by the models. A more general formulation of the multiple mapping conditioning (MMC) model that distinguishes the reference and conditioning variables is suggested. This formulation can be viewed as a methodology of enforcing certain desired conditional properties onto conventional mixing models. Examples of constructing consistent MMC models with dissipation and velocity conditioning as well as of combining MMC with large eddy simulations (LES) are also provided. (c) 2005 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Conditional quantum-state engineering using ancillary squeezed-vacuum states

We investigate an optical scheme to conditionally engineer quantum states using a beam splitter, homodyne detection, and a squeezed vacuum as an ancillar state. This scheme is efficient in producing non-Gaussian quantum states such as squeezed single photons and superpositions of coherent states (SCSs). We show that a SCS with well defined parity and high fidelity can be generated from a Fock state of n

Entangled-state cycles from conditional quantum evolution

A system of cascaded qubits interacting via the one-way exchange of photons is studied. While for general operating conditions the system evolves to a superposition of Bell states (a dark state) in the long-time limit, under a particular resonance condition no steady state is reached within a finite time. We analyze the conditional quantum evolution (quantum trajectories) to characterize the asymptotic behavior under this resonance condition. A distinct bimodality is observed: for perfect qubit coupling, the system either evolves to a maximally entangled Bell state without emitting photons (the dark state) or executes a sustained entangled-state cycle-random switching between a pair of Bell states while emitting a continuous photon stream; for imperfect coupling, two entangled-state cycles coexist, between which a random selection is made from one quantum trajectory to another.

Statistical mechanics of low-density parity check error-correcting codes over Galois fields

A variation of low-density parity check (LDPC) error-correcting codes defined over Galois fields (GF(q)) is investigated using statistical physics. A code of this type is characterised by a sparse random parity check matrix composed of C non-zero elements per column. We examine the dependence of the code performance on the value of q, for finite and infinite C values, both in terms of the thermodynamical transition point and the practical decoding phase characterised by the existence of a unique (ferromagnetic) solution. We find different q-dependence in the cases of C = 2 and C ≥ 3; the analytical solutions are in agreement with simulation results, providing a quantitative measure to the improvement in performance obtained using non-binary alphabets.

Emulation of random output simulators

Computer models, or simulators, are widely used in a range of scientific fields to aid understanding of the processes involved and make predictions. Such simulators are often computationally demanding and are thus not amenable to statistical analysis. Emulators provide a statistical approximation, or surrogate, for the simulators accounting for the additional approximation uncertainty. This thesis develops a novel sequential screening method to reduce the set of simulator variables considered during emulation. This screening method is shown to require fewer simulator evaluations than existing approaches. Utilising the lower dimensional active variable set simplifies subsequent emulation analysis. For random output, or stochastic, simulators the output dispersion, and thus variance, is typically a function of the inputs. This work extends the emulator framework to account for such heteroscedasticity by constructing two new heteroscedastic Gaussian process representations and proposes an experimental design technique to optimally learn the model parameters. The design criterion is an extension of Fisher information to heteroscedastic variance models. Replicated observations are efficiently handled in both the design and model inference stages. Through a series of simulation experiments on both synthetic and real world simulators, the emulators inferred on optimal designs with replicated observations are shown to outperform equivalent models inferred on space-filling replicate-free designs in terms of both model parameter uncertainty and predictive variance.

Random distributed feedback fibre lasers

The concept of random lasers exploiting multiple scattering of photons in an amplifying disordered medium in order to generate coherent light without a traditional laser resonator has attracted a great deal of attention in recent years. This research area lies at the interface of the fundamental theory of disordered systems and laser science. The idea was originally proposed in the context of astrophysics in the 1960s by V.S. Letokhov, who studied scattering with "negative absorption" of the interstellar molecular clouds. Research on random lasers has since developed into a mature experimental and theoretical field. A simple design of such lasers would be promising for potential applications. However, in traditional random lasers the properties of the output radiation are typically characterized by complex features in the spatial, spectral and time domains, making them less attractive than standard laser systems in terms of practical applications. Recently, an interesting and novel type of one-dimensional random laser that operates in a conventional telecommunication fibre without any pre-designed resonator mirrors-random distributed feedback fibre laser-was demonstrated. The positive feedback required for laser generation in random fibre lasers is provided by the Rayleigh scattering from the inhomogeneities of the refractive index that are naturally present in silica glass. In the proposed laser concept, the randomly backscattered light is amplified through the Raman effect, providing distributed gain over distances up to 100km. Although an effective reflection due to the Rayleigh scattering is extremely small (~0.1%), the lasing threshold may be exceeded when a sufficiently large distributed Raman gain is provided. Such a random distributed feedback fibre laser has a number of interesting and attractive features. The fibre waveguide geometry provides transverse confinement, and effectively one-dimensional random distributed feedback leads to the generation of a stationary near-Gaussian beam with a narrow spectrum. A random distributed feedback fibre laser has efficiency and performance that are comparable to and even exceed those of similar conventional fibre lasers. The key features of the generated radiation of random distributed feedback fibre lasers include: a stationary narrow-band continuous modeless spectrum that is free of mode competition, nonlinear power broadening, and an output beam with a Gaussian profile in the fundamental transverse mode (generated both in single mode and multi-mode fibres).This review presents the current status of research in the field of random fibre lasers and shows their potential and perspectives. We start with an introductory overview of conventional distributed feedback lasers and traditional random lasers to set the stage for discussion of random fibre lasers. We then present a theoretical analysis and experimental studies of various random fibre laser configurations, including widely tunable, multi-wavelength, narrow-band generation, and random fibre lasers operating in different spectral bands in the 1-1.6μm range. Then we discuss existing and future applications of random fibre lasers, including telecommunication and distributed long reach sensor systems. A theoretical description of random lasers is very challenging and is strongly linked with the theory of disordered systems and kinetic theory. We outline two key models governing the generation of random fibre lasers: the average power balance model and the nonlinear Schrödinger equation based model. Recently invented random distributed feedback fibre lasers represent a new and exciting field of research that brings together such diverse areas of science as laser physics, the theory of disordered systems, fibre optics and nonlinear science. Stable random generation in optical fibre opens up new possibilities for research on wave transport and localization in disordered media. We hope that this review will provide background information for research in various fields and will stimulate cross-disciplinary collaborations on random fibre lasers. © 2014 Elsevier B.V.

Class Number Two for Real Quadratic Fields of Richaud-Degert Type

2000 Mathematics Subject Classification: Primary: 11D09, 11A55, 11C08, 11R11, 11R29; Secondary: 11R65, 11S40; 11R09.

An asymptotic test for the Conditional Value-at-Risk

Conditional Value-at-Risk (equivalent to the Expected Shortfall, Tail Value-at-Risk and Tail Conditional Expectation in the case of continuous probability distributions) is an increasingly popular risk measure in the fields of actuarial science, banking and finance, and arguably a more suitable alternative to the currently widespread Value-at-Risk. In my paper, I present a brief literature survey, and propose a statistical test of the location of the CVaR, which may be applied by practising actuaries to test whether CVaR-based capital levels are in line with observed data. Finally, I conclude with numerical experiments and some questions for future research.

GPS inferred velocity and strain rate fields in eastern Canada

La vallée du fleuve Saint-Laurent, dans l’est du Canada, est l’une des régions sismiques les plus actives dans l’est de l’Amérique du Nord et est caractérisée par de nombreux tremblements de terre intraplaques. Après la rotation rigide de la plaque tectonique, l’ajustement isostatique glaciaire est de loin la plus grande source de signal géophysique dans l’est du Canada. Les déformations et les vitesses de déformation de la croûte terrestre de cette région ont été étudiées en utilisant plus de 14 ans d’observations (9 ans en moyenne) de 112 stations GPS fonctionnant en continu. Le champ de vitesse a été obtenu à partir de séries temporelles de coordonnées GPS quotidiennes nettoyées en appliquant un modèle combiné utilisant une pondération par moindres carrés. Les vitesses ont été estimées avec des modèles de bruit qui incluent les corrélations temporelles des séries temporelles des coordonnées tridimensionnelles. Le champ de vitesse horizontale montre la rotation antihoraire de la plaque nord-américaine avec une vitesse moyenne de 16,8±0,7 mm/an dans un modèle sans rotation nette (no-net-rotation) par rapport à l’ITRF2008. Le champ de vitesse verticale confirme un soulèvement dû à l’ajustement isostatique glaciaire partout dans l’est du Canada avec un taux maximal de 13,7±1,2 mm/an et un affaissement vers le sud, principalement au nord des États-Unis, avec un taux typique de −1 à −2 mm/an et un taux minimum de −2,7±1,4 mm/an. Le comportement du bruit des séries temporelles des coordonnées GPS tridimensionnelles a été analysé en utilisant une analyse spectrale et la méthode du maximum de vraisemblance pour tester cinq modèles de bruit: loi de puissance; bruit blanc; bruit blanc et bruit de scintillation; bruit blanc et marche aléatoire; bruit blanc, bruit de scintillation et marche aléatoire. Les résultats montrent que la combinaison bruit blanc et bruit de scintillation est le meilleur modèle pour décrire la partie stochastique des séries temporelles. Les amplitudes de tous les modèles de bruit sont plus faibles dans la direction nord et plus grandes dans la direction verticale. Les amplitudes du bruit blanc sont à peu près égales à travers la zone d’étude et sont donc surpassées, dans toutes les directions, par le bruit de scintillation et de marche aléatoire. Le modèle de bruit de scintillation augmente l’incertitude des vitesses estimées par un facteur de 5 à 38 par rapport au modèle de bruit blanc. Les vitesses estimées de tous les modèles de bruit sont statistiquement cohérentes. Les paramètres estimés du pôle eulérien de rotation pour cette région sont légèrement, mais significativement, différents de la rotation globale de la plaque nord-américaine. Cette différence reflète potentiellement les contraintes locales dans cette région sismique et les contraintes causées par la différence des vitesses intraplaques entre les deux rives du fleuve Saint-Laurent. La déformation de la croûte terrestre de la région a été étudiée en utilisant la méthode de collocation par moindres carrés. Les vitesses horizontales interpolées montrent un mouvement cohérent spatialement: soit un mouvement radial vers l’extérieur pour les centres de soulèvement maximal au nord et un mouvement radial vers l’intérieur pour les centres d’affaissement maximal au sud, avec une vitesse typique de 1 à 1,6±0,4 mm/an. Cependant, ce modèle devient plus complexe près des marges des anciennes zones glaciaires. Basées selon leurs directions, les vitesses horizontales intraplaques peuvent être divisées en trois zones distinctes. Cela confirme les conclusions d’autres chercheurs sur l’existence de trois dômes de glace dans la région d’étude avant le dernier maximum glaciaire. Une corrélation spatiale est observée entre les zones de vitesses horizontales intraplaques de magnitude plus élevée et les zones sismiques le long du fleuve Saint-Laurent. Les vitesses verticales ont ensuite été interpolées pour modéliser la déformation verticale. Le modèle montre un taux de soulèvement maximal de 15,6 mm/an au sud-est de la baie d’Hudson et un taux d’affaissement typique de 1 à 2 mm/an au sud, principalement dans le nord des États-Unis. Le long du fleuve Saint-Laurent, les mouvements horizontaux et verticaux sont cohérents spatialement. Il y a un déplacement vers le sud-est d’une magnitude d’environ 1,3 mm/an et un soulèvement moyen de 3,1 mm/an par rapport à la plaque l’Amérique du Nord. Le taux de déformation verticale est d’environ 2,4 fois plus grand que le taux de déformation horizontale intraplaque. Les résultats de l’analyse de déformation montrent l’état actuel de déformation dans l’est du Canada sous la forme d’une expansion dans la partie nord (la zone se soulève) et d’une compression dans la partie sud (la zone s’affaisse). Les taux de rotation sont en moyenne de 0,011°/Ma. Nous avons observé une compression NNO-SSE avec un taux de 3.6 à 8.1 nstrain/an dans la zone sismique du Bas-Saint-Laurent. Dans la zone sismique de Charlevoix, une expansion avec un taux de 3,0 à 7,1 nstrain/an est orientée ENE-OSO. Dans la zone sismique de l’Ouest du Québec, la déformation a un mécanisme de cisaillement avec un taux de compression de 1,0 à 5,1 nstrain/an et un taux d’expansion de 1.6 à 4.1 nstrain/an. Ces mesures sont conformes, au premier ordre, avec les modèles d’ajustement isostatique glaciaire et avec la contrainte de compression horizontale maximale du projet World Stress Map, obtenue à partir de la théorie des mécanismes focaux (focal mechanism method).

Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks

International audience

Disorder-induced light localisation:from random to artificial

Light localisation in one-dimensional (1D) randomly disordered medium is usually characterized by randomly distributed resonances with fluctuating transmission values, instead of selectively distributed resonances with close-to-unity transmission values that are needed in real application fields. By a resonance tuning scheme developed recently, opening of favorable resonances or closing of unfavorable resonances are achieved by disorder micro-modification, both on the layered medium and the fibre Bragg grating (FBG) array. And furthermore, it is shown that those disorder-induced resonances are independently tunable. Therefore, selected resonances and arranged light localisation can be achieved via artificial disorder, and thus meet the demand of various application fields.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Conditional entropy and predictability for non-reversible Markov systems

The purpose of this thesis is to clarify the role of non-equilibrium stationary currents of Markov processes in the context of the predictability of future states of the system. Once the connection between the predictability and the conditional entropy is established, we provide a comprehensive approach to the definition of a multi-particle Markov system. In particular, starting from the well-known theory of random walk on network, we derive the non-linear master equation for an interacting multi-particle system under the one-step process hypothesis, highlighting the limits of its tractability and the prop- erties of its stationary solution. Lastly, in order to study the impact of the NESS on the predictability at short times, we analyze the conditional entropy by modulating the intensity of the stationary currents, both for a single-particle and a multi-particle Markov system. The results obtained analytically are numerically tested on a 5-node cycle network and put in correspondence with the stationary entropy production. Furthermore, because of the low dimensionality of the single-particle system, an analysis of its spectral properties as a function of the modulated stationary currents is performed.

Biased Random-key Genetic Algorithms For The Winner Determination Problem In Combinatorial Auctions.

Abstract In this paper, we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer-linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.

Synthesis and structural characterization of block and random low molecular weight copolymers composed of L-lactic acid and isosorbide succinate moieties

Isosorbide succinate moieties were incorporated into poly(L-lactide) (PLLA) backbone in order to obtain a new class of biodegradable polymer with enhanced properties. This paper describes the synthesis and characterization of four types of low molecular weight copolymers. Copolymer I was obtained from monomer mixtures of L-lactide, isosorbide, and succinic anhydride; II from oligo(L-lactide) (PLLA), isosorbide, and succinic anhydride; III from oligo(isosorbide succinate) (PIS) and L-lactide; and IV from transesterification reactions between PLLA and PIS. MALDI-TOFMS and 13C-NMR analyses gave evidence that co-oligomerization was successfully attained in all cases. The data suggested that the product I is a random co-oligomer and the products II-IV are block co-oligomers.