相关论文: Impact Probability Under Aleatory And Epistemic Un…
Entropic uncertainty relations are powerful tools, especially in quantum cryptography. They typically bound the amount of uncertainty a third-party adversary may hold on a measurement outcome as a result of the measurement overlap. However,…
The precision of measurements of the strong coupling constant using event-shape variables in e+e- annihilations is limited by theoretical systematic uncertainties. The uncertainties are related to missing higher orders in the perturbative…
We have calculated 90% confidence limits on the steady-state rate of catastrophic disruptions of main belt asteroids in terms of the absolute magnitude at which one catastrophic disruption occurs per year (HCL) as a function of the…
Close-proximity exploration of small celestial bodies is crucial for the comprehensive and accurate characterization of their properties. However, the complex and uncertain dynamical environment around them contributes to a rapid dispersion…
We provide context for Apophis' 2029 Earth passage by analyzing its possible source populations, in particular, the Flora family, which has a similar composition, corresponding to LL chondrite meteorites. Out of ${\sim}3380$ NEOs larger or…
Uncertainty can be classified as either aleatoric (intrinsic randomness) or epistemic (imperfect knowledge of parameters). The majority of frameworks assessing infectious disease risk consider only epistemic uncertainty. We only ever…
Based on a linearized model of the Yarkovsky effect, we investigate in this paper the dependence of the semimajor axis drift $\Delta a$ of a celestial body on its size, spinning obliquity, initial orbit and thermal parameters on its…
In this paper, we discuss the ambiguous chance constrained based portfolio optimization problems, in which the perturbations associated with the input parameters are stochastic in nature, but their distributions are not known precisely. We…
In this paper, we consider the problem of quantifying parametric uncertainty in classical empirical interatomic potentials (IPs) using both Bayesian (Markov Chain Monte Carlo) and frequentist (profile likelihood) methods. We interface these…
We study the computation of lower and upper probabilities of hitting a target set of states for imprecise Markov chains, where transition uncertainty is modelled by a convex set of transition matrices. In the precise case, hitting…
Among asteroids there exist ambiguities in their rotation period determinations. They are due to incomplete coverage of the rotation, noise and/or aliases resulting from gaps between separate lightcurves. To help to remove such…
Context. The close approach of the near-Earth asteroid (99942) Apophis to Earth in 2029 will provide a unique opportunity to examine how the physical properties of the asteroid could be changed due to the Earth's gravitational perturbation.…
Frequent significant deviations of the observed magnitude distribution of anthropogenic seismicity from the Gutenberg-Richter relation require alternative estimation methods for probabilistic seismic hazard assessments. We evaluate five…
This work demonstrates how the concept of the entropic potential of events -- a parameter quantifying the influence of discrete events on the expected future entropy of a system -- can enhance uncertainty quantification, decision-making,…
The quantification of aleatoric and epistemic uncertainty in terms of conditional entropy and mutual information, respectively, has recently become quite common in machine learning. While the properties of these measures, which are rooted…
We investigate the impact of nonaxisymmetric structure on estimates of galaxy inclinations and position angles. A new minimization technique is used to obtain estimates of inclination and position angle from a global fit to either…
We describe a probabilistic method of cross-identifying astrophysical sources in two catalogs from their positions and positional uncertainties. The probability that an object is associated with a source from the other catalog, or that it…
Classical probabilistic models of (noisy) quantum systems are not only relevant for understanding the non-classical features of quantum mechanics, but they are also useful for determining the possible advantage of using quantum resources…
Distributionally robust chance constrained programs minimize a deterministic cost function subject to the satisfaction of one or more safety conditions with high probability, given that the probability distribution of the uncertain problem…
In this paper, we present an analytical approach for the synthesis of ellipsoidal probabilistic reachable sets of saturated systems subject to unbounded additive noise. Using convex optimization methods, we compute a contraction factor of…