Quantum dynamics in canonical and micro-canonical ensembles. Part I. Anderson localization of electrons

The new numerical approach for consideration of quantum dynamics and calculations of the average values of quantum operators and time correlation functions in the Wigner representation of quantum statistical mechanics has been developed. The time correlation functions have been presented in the form of the integral of the Weyl's symbol of considered operators and the Fourier transform of the product of matrix elements of the dynamic propagators. For the last function the integral Wigner- Liouville's type equation has been derived. The numerical procedure for solving this equation combining both molecular dynamics and Monte Carlo methods has been developed. For electrons in disordered systems of scatterers the numerical results have been obtained for series of the average values of the quantum operators including position and momentum dispersions, average energy, energy distribution function as well as for the frequency dependencies of tensor of electron conductivity and permittivity according to quantum Kubo formula. Zero or very small value of static conductivity have been considered as the manifestation of Anderson localization of electrons in 1D case. Independent evidence of Anderson localization comes from the behaviour of the calculated time dependence of position dispersion.Comment: 8 pages, 10 figure

Hyperparameter Importance Across Datasets

With the advent of automated machine learning, automated hyperparameter optimization methods are by now routinely used in data mining. However, this progress is not yet matched by equal progress on automatic analyses that yield information beyond performance-optimizing hyperparameter settings. In this work, we aim to answer the following two questions: Given an algorithm, what are generally its most important hyperparameters, and what are typically good values for these? We present methodology and a framework to answer these questions based on meta-learning across many datasets. We apply this methodology using the experimental meta-data available on OpenML to determine the most important hyperparameters of support vector machines, random forests and Adaboost, and to infer priors for all their hyperparameters. The results, obtained fully automatically, provide a quantitative basis to focus efforts in both manual algorithm design and in automated hyperparameter optimization. The conducted experiments confirm that the hyperparameters selected by the proposed method are indeed the most important ones and that the obtained priors also lead to statistically significant improvements in hyperparameter optimization.Comment: \c{opyright} 2018. Copyright is held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use, not for redistribution. The definitive Version of Record was published in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Minin

Multidimensional Quasi-Monte Carlo Malliavin Greeks

We investigate the use of Malliavin calculus in order to calculate the Greeks of multidimensional complex path-dependent options by simulation. For this purpose, we extend the formulas employed by Montero and Kohatsu-Higa to the multidimensional case. The multidimensional setting shows the convenience of the Malliavin Calculus approach over different techniques that have been previously proposed. Indeed, these techniques may be computationally expensive and do not provide flexibility for variance reduction. In contrast, the Malliavin approach exhibits a higher flexibility by providing a class of functions that return the same expected value (the Greek) with different accuracies. This versatility for variance reduction is not possible without the use of the generalized integral by part formula of Malliavin Calculus. In the multidimensional context, we find convenient formulas that permit to improve the localization technique, introduced in Fourni\'e et al and reduce both the computational cost and the variance. Moreover, we show that the parameters employed for variance reduction can be obtained \textit{on the flight} in the simulation. We illustrate the efficiency of the proposed procedures, coupled with the enhanced version of Quasi-Monte Carlo simulations as discussed in Sabino, for the numerical estimation of the Deltas of call, digital Asian-style and Exotic basket options with a fixed and a floating strike price in a multidimensional Black-Scholes market.Comment: 22 pages, 6 figure

Parental bonding and identity style as correlates of self-esteem among adult adoptees and nonadoptees

Adult adoptees (n equals 100) and non-adoptees (n equals 100) were compared with regard to selfesteem, identity processing style, and parental bonding. While some differences were found with regard to self-esteem, maternal care, and maternal overprotection, these differences were qualified by reunion status such that only reunited adoptees differed significantly from nonadoptees. Moreover, hierarchical regression analyses indicated that parental bonding and identity processing style were more important than adoptive status per se in predicting self esteem. Implications for practitioners who work with adoptees are discussed

A low-memory algorithm for finding short product representations in finite groups

We describe a space-efficient algorithm for solving a generalization of the subset sum problem in a finite group G, using a Pollard-rho approach. Given an element z and a sequence of elements S, our algorithm attempts to find a subsequence of S whose product in G is equal to z. For a random sequence S of length d log_2 n, where n=#G and d >= 2 is a constant, we find that its expected running time is O(sqrt(n) log n) group operations (we give a rigorous proof for d > 4), and it only needs to store O(1) group elements. We consider applications to class groups of imaginary quadratic fields, and to finding isogenies between elliptic curves over a finite field.Comment: 12 page

The Base Excision Repair Pathway Is Required for Efficient Lentivirus Integration

An siRNA screen has identified several proteins throughout the base excision repair (BER) pathway of oxidative DNA damage as important for efficient HIV infection. The proteins identified included early repair factors such as the base damage recognition glycosylases OGG1 and MYH and the late repair factor POLß, implicating the entire BER pathway. Murine cells with deletions of the genes Ogg1, Myh, Neil1 and Polß recapitulate the defect of HIV infection in the absence of BER. Defective infection in the absence of BER proteins was also seen with the lentivirus FIV, but not the gammaretrovirus MMLV. BER proteins do not affect HIV infection through its accessory genes nor the central polypurine tract. HIV reverse transcription and nuclear entry appear unaffected by the absence of BER proteins. However, HIV integration to the host chromosome is reduced in the absence of BER proteins. Pre-integration complexes from BER deficient cell lines show reduced integration activity in vitro. Integration activity is restored by addition of recombinant BER protein POLß. Lentiviral infection and integration efficiency appears to depend on the presence of BER proteins

Synthesis, Molecular Editing, and Biological Assessment of the Potent Cytotoxin Leiodermatolide

It was by way of total synthesis that the issues concerning the stereostructure of leiodermatolide (1) have recently been solved; with the target now being unambiguously defined, the mission of synthesis changes as to secure a meaningful supply of this exceedingly scarce natural product derived from a deep-sea sponge. To this end, a scalable route of 19 steps (longest linear sequence) has been developed, which features a catalytic asymmetric propargylation of a highly enolizable β-keto-lactone, a ring closing alkyne metathesis and a modified Stille coupling as the key transformations. Deliberate digression from this robust blueprint brought a first set of analogues into reach, which allowed the lead qualities of 1 to be assessed. The acquired biodata show that 1 is a potent cytotoxin in human tumor cell proliferation assays, distinguished by GI50 values in the ≤3 nM range even for cell lines expressing the Pgp efflux transporter. Studies with human U2OS cells revealed that 1 causes mitotic arrest, micronucleus induction, centrosome amplification and tubulin disruption, even though no evidence for direct tubulin binding has been found in cell-free assays; moreover, the compound does not seem to act through kinase inhibition. Indirect evidence points at centrosome declustering as a possible mechanism of action, which provides a potentially rewarding outlook in that centrosome declustering agents hold promise of being inherently selective for malignant over healthy human tissue

Electron Cooling in the Presence of Undulator Fields

The design of the higher-energy cooler for Relativistic Heavy Ion Collider (RHIC) recently adopted a non-magnetized approach which requires a low temperature electron beam. However, to avoid significant loss of heavy ions due to recombination with electrons in the cooling section, the temperature of the electron beam should be high. These two contradictory requirements are satisfied in the design of the RWIC cooler with the help of the undulator fields. The model of the friction force in the presence of an undulator field was benchmarked vs. direct numerical simulations with an excellent agreement. Here, we discuss cooling dynamics simulations with a helical undulator, including recombination suppression and resulting luminosities