Robust ab initio calculation of condensed matter: transparent convergence through semicardinal multiresolution analysis

We present the first wavelet-based all-electron density-functional calculations to include gradient corrections and the first in a solid. Direct comparison shows this approach to be unique in providing systematic ``transparent'' convergence, convergence with a priori prediction of errors, to beyond chemical (millihartree) accuracy. The method is ideal for exploration of materials under novel conditions where there is little experience with how traditional methods perform and for the development and use of chemically accurate density functionals, which demand reliable access to such precision.Comment: 4 pages, 3 figures, 4 tables. Submitted to Phys. Rev. Lett. (updated to include GGA

Cross-Dimensional relaxation in Bose-Fermi mixtures

We consider the equilibration rate for fermions in Bose-Fermi mixtures undergoing cross-dimensional rethermalization. Classical Monte Carlo simulations of the relaxation process are performed over a wide range of parameters, focusing on the effects of the mass difference between species and the degree of initial departure from equilibrium. A simple analysis based on Enskog's equation is developed and shown to be accurate over a variety of different parameter regimes. This allows predictions for mixtures of commonly used alkali atoms.Comment: 7 pages, 4 figures, uses Revtex 4. This is a companion paper to [PRA 70, 021601(R) (2004)] (cond-mat/0405419

Elastic effects of vacancies in strontium titanate: Short- and long-range strain fields, elastic dipole tensors, and chemical strain

We present a study of the local strain effects associated with vacancy defects in strontium titanate and report the first calculations of elastic dipole tensors and chemical strains for point defects in perovskites. The combination of local and long-range results will enable determination of x-ray scattering signatures that can be compared with experiments. We find that the oxygen vacancy possesses a special property -- a highly anisotropic elastic dipole tensor which almost vanishes upon averaging over all possible defect orientations. Moreover, through direct comparison with experimental measurements of chemical strain, we place constraints on the possible defects present in oxygen-poor strontium titanate and introduce a conjecture regarding the nature of the predominant defect in strontium-poor stoichiometries in samples grown via pulsed laser deposition. Finally, during the review process, we learned of recent experimental data, from strontium titanate films deposited via molecular-beam epitaxy, that show good agreement with our calculated value of the chemical strain associated with strontium vacancies.Comment: 14 pages, 11 figures, 4 table

Dynamics of Quintessence Models of Dark Energy with Exponential Coupling to the Dark Matter

We explore quintessence models of dark energy which exhibit non-minimal coupling between the dark matter and the dark energy components of the cosmic fluid. The kind of coupling chosen is inspired in scalar-tensor theories of gravity. We impose a suitable dynamics of the expansion allowing to derive exact Friedmann-Robertson-Walker solutions once the coupling function is given as input. Self-interaction potentials of single and double exponential types emerge as result of our choice of the coupling function. The stability and existence of the solutions is discussed in some detail. Although, in general, models with appropriated interaction between the components of the cosmic mixture are useful to handle the coincidence problem, in the present study the coincidence can not be evaded due to the choice of the solution generating ansatz.Comment: 10 pages, 7 figure

Isolation and characterisation of the first microsatellite markers for \u3ci\u3eCyperus rotundus\u3c/i\u3e

This is the first report of microsatellite markers for Cyperus rotundus. A total of 191 sequence-specific microsatellite markers were isolated and used to screen12 accessions of C. rotundus and one accession of Cyperus esculentus collected from 10 different countries. Polymorphisms were observed in 49% of the markers tested, 22% of the markers were monomorphic and 29% had weak or no amplification. The best 57 markers are reported, and cluster analysis was used to analyse their resolving power. BLASTx screening of the contig sequences was also performed. Multiallelic loci over all samples ranged from 24% to 60%. The maximum number of alleles detected by the markers suggests a polyploidy nature of all C. rotundus accessions tested, except for the sample N25-Brazil. Chromosome number was determined for N12-Taiwan and used as an internal flow cytometry standard to estimate the amount of DNA within haploid nuclei of the remaining material. Chromosome numbers estimated for C. rotundus were 16 and 24. The markers identified in this study can be used for the identification of biotypes and detection of potential crosses of C. rotundus, to implement management practices for the effective control of this weed

Machine Learning Models that Remember Too Much

Machine learning (ML) is becoming a commodity. Numerous ML frameworks and services are available to data holders who are not ML experts but want to train predictive models on their data. It is important that ML models trained on sensitive inputs (e.g., personal images or documents) not leak too much information about the training data. We consider a malicious ML provider who supplies model-training code to the data holder, does not observe the training, but then obtains white- or black-box access to the resulting model. In this setting, we design and implement practical algorithms, some of them very similar to standard ML techniques such as regularization and data augmentation, that "memorize" information about the training dataset in the model yet the model is as accurate and predictive as a conventionally trained model. We then explain how the adversary can extract memorized information from the model. We evaluate our techniques on standard ML tasks for image classification (CIFAR10), face recognition (LFW and FaceScrub), and text analysis (20 Newsgroups and IMDB). In all cases, we show how our algorithms create models that have high predictive power yet allow accurate extraction of subsets of their training data

Calculations of giant magnetoresistance in Fe/Cr trilayers using layer potentials determined from {\it ab-initio} methods

The ab initio full-potential linearized augmented plane-wave method explicitly designed for the slab geometry was employed to elucidate the physical origin of the layer potentials for the trilayers nFe/3Cr/nFe(001), where n is the number of Fe monolayers. The thickness of the transition-metal ferromagnet has been ranged from $n=1$ up to n=8 while the spacer thickness was fixed to 3 monolayers. The calculated potentials were inserted in the Fuchs-Sondheimer formalism in order to calculate the giant magnetoresistance (GMR) ratio. The predicted GMR ratio was compared with the experiment and the oscillatory behavior of the GMR as a function of the ferromagnetic layer thickness was discussed in the context of the layer potentials. The reported results confirm that the interface monolayers play a dominant role in the intrinsic GMR.Comment: 17 pages, 7 figures, 3 tables. accepted in J. Phys.: Cond. Matte

The Abelian Topological Mass Mechanism From Dimensional Reduction

We show that the abelian topological mass mechanism in four dimensions, described by the Cremmer-Sherk action, can be obtained from dimensional reduction in five dimensions. Starting from a gauge invariant action in five dimensions, where the dual equivalence between a massless vector field and a massless second-rank antisymmetric field in five dimensions is established, the dimensional reduction is performed keeping only one massive mode. Furthermore, the Kalb-Ramond action and the Stuckelberger formulation for massive spin-1 are recovered.Comment: Three references added, 6 pages, late

Two interacting particles in a random potential

We study the scaling of the localization length of two interacting particles in a one-dimensional random lattice with the single particle localization length. We obtain several regimes, among them one interesting weak Fock space disorder regime. In this regime we derive a weak logarithmic scaling law. Numerical data support the absence of any strong enhancement of the two particle localization length

Noise-correlation spectrum for a pair of spin qubits in silicon

Semiconductor qubits are appealing for building quantum processors as they may be densely integrated due to small footprint. However, a high density raises the issue of noise correlated across different qubits, which is of practical concern for scalability and fault tolerance. Here, we analyse and quantify in detail the degree of noise correlation in a pair of neighbouring silicon spin qubits ~100 nm apart. We evaluate all a-priori independent auto- and cross- power spectral densities of noise as a function of frequency. We reveal strong inter-qubit noise correlation with a correlation strength as large as ~0.7 at ~1 Hz (70% of the maximum in-phase correlation), even in the regime where the spin-spin exchange interaction contributes negligibly. We furthermore find that fluctuations of single-spin precession rates are strongly correlated with exchange noise, giving away their electrical origin. Noise cross-correlations have thus enabled us to pinpoint the most influential noise in the present device among compelling mechanisms including nuclear spins. Our work presents a powerful tool set to assess and identify the noise acting on multiple qubits and highlights the importance of long-range electric noise in densely packed silicon spin qubits