Search results for "Mathematical proof"
showing 10 items of 61 documents
Mathematical properties of nested residues and their application to multi-loop scattering amplitudes
2021
Journal of high energy physics 02(2), 112 (2021). doi:10.1007/JHEP02(2021)112
Rebuttal to “Comment on “Evidence of electrical activity on Titan drawn from the Schumann resonances sent by Huygens probe” by J.A. Morente, J.A. Por…
2009
Abstract Hamelin et al. criticize some conclusions of our paper [Morente, J.A., Porti, J.A., Salinas, A., Navarro, E.A., 2008. Icarus 195, 802–811]. This rebuttal is our response to their criticism. In our view, their comments are contradictory and not based on scientific argument. Our paper presents a comprehensible methodology for extracting weak resonances from the late-time response of systems with high losses and our conclusions are derived from and supported by this methodology, which was first checked using an analytical function and later with the data from a numerical simulation of Titan’s atmosphere. Conversely, the Comment of Hamelin et al. does not contain any mathematical proof…
On some inequalities for the identric, logarithmic and related means
2015
We offer new proofs, refinements as well as new results related to classical means of two variables, including the identric and logarithmic means.
An Ehrenfeucht-Fraïssé Approach to Collapse Results for First-Order Queries over Embedded Databases
2001
We present a new proof technique for collapse results for first-order queries on databases which are embedded in N or R>o. Our proofs are by means of an explicitly constructed winning strategy for Duplicator in an Ehrenfeucht-FraissE game, and can deal with certain infinite databases where previous, highly involved methods fail. Our main result is that first-order logic has the natural-generic collapse over {N,≤ ,+} for arbitrary (i.e., possibly infinite) databases. Furthermore, a first application of this result shows the natural-generic collapse of first-order logic over {R>o,≤,+} for a certain kind of databases over R>o which consist of a possibly infinite number of regions.
The Duality of Entropy/Extropy, and Completion of the Kullback Information Complex
2018
The refinement axiom for entropy has been provocative in providing foundations of information theory, recognised as thoughtworthy in the writings of both Shannon and Jaynes. A resolution to their concerns has been provided recently by the discovery that the entropy measure of a probability distribution has a dual measure, a complementary companion designated as &ldquo
Solving Two-Person Zero-Sum Stochastic Games With Incomplete Information Using Learning Automata With Artificial Barriers
2021
Learning automata (LA) with artificially absorbing barriers was a completely new horizon of research in the 1980s (Oommen, 1986). These new machines yielded properties that were previously unknown. More recently, absorbing barriers have been introduced in continuous estimator algorithms so that the proofs could follow a martingale property, as opposed to monotonicity (Zhang et al., 2014), (Zhang et al., 2015). However, the applications of LA with artificial barriers are almost nonexistent. In that regard, this article is pioneering in that it provides effective and accurate solutions to an extremely complex application domain, namely that of solving two-person zero-sum stochastic games that…
A formal proof of the e-optimality of discretized pursuit algorithms
2015
Learning Automata (LA) can be reckoned to be the founding algorithms on which the field of Reinforcement Learning has been built. Among the families of LA, Estimator Algorithms (EAs) are certainly the fastest, and of these, the family of discretized algorithms are proven to converge even faster than their continuous counterparts. However, it has recently been reported that the previous proofs for ??-optimality for all the reported algorithms for the past three decades have been flawed. We applaud the researchers who discovered this flaw, and who further proceeded to rectify the proof for the Continuous Pursuit Algorithm (CPA). The latter proof examines the monotonicity property of the proba…
The minimal model of Hahn for the Calvin cycle.
2018
There are many models of the Calvin cycle of photosynthesis in the literature. When investigating the dynamics of these models one strategy is to look at the simplest possible models in order to get the most detailed insights. We investigate a minimal model of the Calvin cycle introduced by Hahn while he was pursuing this strategy. In a variant of the model not including photorespiration it is shown that there exists exactly one positive steady state and that this steady state is unstable. For generic initial data either all concentrations tend to infinity at lates times or all concentrations tend to zero at late times. In a variant including photorespiration it is shown that for suitable v…
The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality
2016
The fundamental phenomenon that has been used to enhance the convergence speed of learning automata (LA) is that of incorporating the running maximum likelihood (ML) estimates of the action reward probabilities into the probability updating rules for selecting the actions. The frontiers of this field have been recently expanded by replacing the ML estimates with their corresponding Bayesian counterparts that incorporate the properties of the conjugate priors. These constitute the Bayesian pursuit algorithm (BPA), and the discretized Bayesian pursuit algorithm. Although these algorithms have been designed and efficiently implemented, and are, arguably, the fastest and most accurate LA report…
Solving the Discrete Multiple Criteria Problem using Convex Cones
1984
An interactive method employing pairwise comparisons of attainable solutions is developed for solving the discrete, deterministic multiple criteria problem assuming a single decision maker who has an implicit quasi-concave increasing utility (or value) function. The method chooses an arbitrary set of positive multipliers to generate a proxy composite linear objective function which is then maximized over the set of solutions. The maximizing solution is compared with several solutions using pairwise judgments asked of the decision maker. Responses are used to eliminate alternatives using convex cones based on expressed preferences, and then a new set of weights is found that satisfies the i…