248 research outputs found

    Sequential design of computer experiments for the estimation of a probability of failure

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    This paper deals with the problem of estimating the volume of the excursion set of a function f:Rd→Rf:\mathbb{R}^d \to \mathbb{R} above a given threshold, under a probability measure on Rd\mathbb{R}^d that is assumed to be known. In the industrial world, this corresponds to the problem of estimating a probability of failure of a system. When only an expensive-to-simulate model of the system is available, the budget for simulations is usually severely limited and therefore classical Monte Carlo methods ought to be avoided. One of the main contributions of this article is to derive SUR (stepwise uncertainty reduction) strategies from a Bayesian-theoretic formulation of the problem of estimating a probability of failure. These sequential strategies use a Gaussian process model of ff and aim at performing evaluations of ff as efficiently as possible to infer the value of the probability of failure. We compare these strategies to other strategies also based on a Gaussian process model for estimating a probability of failure.Comment: This is an author-generated postprint version. The published version is available at http://www.springerlink.co

    Measurement of the neutron magnetic form factor from inclusive quasielastic scattering of polarized electrons from polarized 3He

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    We report a measurement of the asymmetry in spin-dependent quasielastic scattering of longitudinally polarized electrons from a polarized 3He target. The neutron magnetic form factor GMn has been extracted from the measured asymmetry based on recent PWIA calculations using spin-dependent spectral functions. Our determination of GMn at Q2=0.19 (GeV/c)2 agrees with the dipole parametrization. This experiment represents the first measurement of the neutron magnetic form factor using spin-dependent electron scattering

    Active Brownian Particles. From Individual to Collective Stochastic Dynamics

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    We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

    A proof of the Geroch-Horowitz-Penrose formulation of the strong cosmic censor conjecture motivated by computability theory

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    In this paper we present a proof of a mathematical version of the strong cosmic censor conjecture attributed to Geroch-Horowitz and Penrose but formulated explicitly by Wald. The proof is based on the existence of future-inextendible causal curves in causal pasts of events on the future Cauchy horizon in a non-globally hyperbolic space-time. By examining explicit non-globally hyperbolic space-times we find that in case of several physically relevant solutions these future-inextendible curves have in fact infinite length. This way we recognize a close relationship between asymptotically flat or anti-de Sitter, physically relevant extendible space-times and the so-called Malament-Hogarth space-times which play a central role in recent investigations in the theory of "gravitational computers". This motivates us to exhibit a more sharp, more geometric formulation of the strong cosmic censor conjecture, namely "all physically relevant, asymptotically flat or anti-de Sitter but non-globally hyperbolic space-times are Malament-Hogarth ones". Our observations may indicate a natural but hidden connection between the strong cosmic censorship scenario and the Church-Turing thesis revealing an unexpected conceptual depth beneath both conjectures.Comment: 16pp, LaTeX, no figures. Final published versio

    The differential diagnosis of chronic daily headaches: an algorithm-based approach

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    Chronic daily headaches (CDHs) refers to primary headaches that happen on at least 15 days per month, for 4 or more hours per day, for at least three consecutive months. The differential diagnosis of CDHs is challenging and should proceed in an orderly fashion. The approach begins with a search for “red flags” that suggest the possibility of a secondary headache. If secondary headaches that mimic CDHs are excluded, either on clinical grounds or through investigation, the next step is to classify the headaches based on the duration of attacks. If the attacks last less than 4 hours per day, a trigeminal autonomic cephalalgia (TAC) is likely. TACs include episodic and chronic cluster headache, episodic and chronic paroxysmal hemicrania, SUNCT, and hypnic headache. If the duration is ≥4 h, a CDH is likely and the differential diagnosis encompasses chronic migraine, chronic tension-type headache, new daily persistent headache and hemicrania continua. The clinical approach to diagnosing CDH is the scope of this review
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