Enhanced x-ray phase determination by three-beam diffraction

For decades, solving the phase problem of x-ray scattering has been a goal that, in principle, could be achieved by means of n-beam diffraction (n-BD). However, the phases extracted by the actual n-BD phasing techniques are not very precise, mainly due to systematic errors that are difficult to estimate. We present an innovative theoretical approach and experimental procedure that, combined, eliminate two major sources of error. It is a high precision phasing technique that provides the triplet-phase angle with an error of about 2 degrees.     

Mössbauer investigation of iron disulphide (marcasite)

Mössbauer absorption of Fe⁵⁷ in naturally occuring and synthetic crystals of FeS₂, marcasite, has been studied in the ideal absorber thickness in the transmission geometry from a Co⁵⁷/Rh and Co⁵⁷/LiNbO₃ source. The recoilles fraction at room temperature, 298 K, has been obtained to be 0.2 and the mean square displacement < r² > was found to be 13×10^-19 cm² at room temperature, 298 K. Because of the small size of marcasite crystals it has not been possible to record good spectra of the monocrystals as a function of the orientation of the incident gamma rays from Co⁵⁷/LiNbO₃ source.     

The constrained compartmentalized knapsack problem: mathematical models and solution methods

The constrained compartmentalized knapsack problem can be seen as an extension of the constrained knapsack problem. However, the items are grouped into different classes so that the overall knapsack has to be divided into compartments, and each compartment is loaded with items from the same class. Moreover, building a compartment incurs a fixed cost and a fixed loss of the capacity in the original knapsack, and the compartments are lower and upper bounded. The objective is to maximize the total value of the items loaded in the overall knapsack minus the cost of the compartments. This problem has been formulated as an integer non-linear program, and in this paper, we reformulate the non-linear model as an integer linear master problem with a large number of variables. Some heuristics based on the solution of the restricted master problem are investigated. A new and more compact integer linear model is also presented, which can be solved by a branch-and-bound commercial solver that found most of the optimal solutions for the constrained compartmentalized knapsack problem. On the other hand, heuristics provide good solutions with low computational effort.     

A Monte Carlo study of finite temperature λφ 2, 3 4 ⋆

Zeitschrift für Physik C Particles and Fields - We study the finite temperature behaviour of λφ4 theory in two and three dimensions, using Monte Carlo simulations. We renormalize the...     

Statistical maps and generalized random walks

We continue our study of statistical maps (equivalently, fuzzy random variables in the sense of Gudder and Bugajski). In the realm of fuzzy probability theory, statistical maps describe the transportation of probability measures on one measurable space into probability measures on another measurable space. We show that for discrete probability spaces each statistical map can be represented via a special matrix the rows of which are probability functions related to conditional probabilities and the columns are related to fuzzy n-partitions of the domain. Discrete statistical maps sending a probability measure p to a probability measure q can be represented via conditional distributions and correspond to joint probabilities on the product. The composition of statistical maps provide a tool to describe and to study generalized random walks and Markov chains.     

Random walks with different directions

As an extension of Polya’s classical result on random walks on the square grids (\({\mathbf {Z}}^d\)), we consider a random walk where the steps, while still have unit length, point to different directions. We show that in dimensions at least 4, the returning probability after n steps is at most \(n^{-d/2 - d/(d-2) +o(1) }\), which is sharp. The real surprise is in dimensions 2 and 3. In dimension 2, where the traditional grid walk is recurrent, our upper bound is \(n^{-\omega (1) }\), which is much worse than in higher dimensions. In dimension 3, we prove an upper bound of order \(n^{-4 +o(1) }\). We find a new conjecture concerning incidences between spheres and points in \({\mathbf {R}}^3\), which, if holds, would improve the bound to \(n^{-9/2 +o(1) }\), which is consistent to the \(d \ge 4\) case. This conjecture resembles Szemerédi-Trotter type results and is of independent interest.     

Alternative Entropy Measures and Generalized Khinchin–Shannon Inequalities

The Khinchin–Shannon generalized inequalities for entropy measures in Information Theory, are a paradigm which can be used to test the Synergy of the distributions of probabilities of occurrence in physical systems. The rich algebraic structure associated with the introduction of escort probabilities seems to be essential for deriving these inequalities for the two-parameter Sharma–Mittal set of entropy measures. We also emphasize the derivation of these inequalities for the special cases of one-parameter Havrda–Charvat’s, Rényi’s and Landsberg–Vedral’s entropy measures.     

Optimally Conditions for Pareto Nonsmooth Nonconvex Programming in Banach Spaces

In this paper, we consider a vector optimization problem where all functions involved are defined on Banach spaces. We obtain necessary and sufficient criteria for optimality in the form of Karush–Kuhn–Tucker conditions. We also introduce a nonsmooth dual problem and provide duality theorems.