Identification of fullerene-like CdSe nanoparticles from optical spectroscopy calculations

Semiconducting nanoparticles are the building blocks of optical nanodevices as their electronic states, and therefore light absorption and emission, can be controlled by modifying their size and shape. CdSe is perhaps the most studied of these nanoparticles, due to the efficiency of its synthesis, the high quality of the resulting samples, and the fact that the optical gap is in the visible range. In this article, we study light absorption of CdSe nanostructures with sizes up to 1.5 nm within density functional theory. We study both bulk fragments with wurtzite symmetry and novel fullerene-like core-cage structures. The comparison with recent experimental optical spectra allows us to confirm the synthesis of these fullerene-like CdSe clusters

A complete criterion for separability detection

Using new results on the separability properties of bosonic systems, we provide a new complete criterion for separability. This criterion aims at characterizing the set of separable states from the inside by means of a sequence of efficiently solvable semidefinite programs. We apply this method to derive arbitrarily good approximations to the optimal measure-and-prepare strategy in generic state estimation problems. Finally, we report its performance in combination with the criterion developed by Doherty et al. [1] for the calculation of the entanglement robustness of a relevant family of quantum states whose separability properties were unknown

Alloying effects on the optical properties of Ge1−x_{1-x}Six_x nanocrystals from TDDFT and comparison with effective-medium theory

We present the optical spectra of Ge$_{1-x}$Si$_x$ alloy nanocrystals calculated with time-dependent density-functional theory in the adiabatic local-density ap proximation (TDLDA). The spectra change smoothly as a function of the compositio n $x$. On the Ge side of the composition range, the lowest excitations at the ab sorption edge are almost pure Kohn-Sham independent-particle HOMO-LUMO transitio ns, while for higher Si contents strong mixing of transitions is found. Within T DLDA the first peak is slightly higher in energy than in earlier independent-par ticle calculations. However, the absorption onset and in particular its composit ion dependence is similar to independent-particle results. Moreover, classical depolarization effects are responsible for a very strong suppression of the abs orption intensity. We show that they can be taken into account in a simpler way using Maxwell-Garnett classical effective-medium theory. Emission spectra are in vestigated by calculating the absorption of excited nanocrystals at their relaxe d geometry. The structural contribution to the Stokes shift is about 0.5 eV. Th e decomposition of the emission spectra in terms of independent-particle transit ions is similar to what is found for absorption. For the emission, very weak tra nsitions are found in Ge-rich clusters well below the strong absorption onset.Comment: submitted to Phys. Rev.

Enhancing the superconducting transition temperature of BaSi2 by structural tuning

We present a joint experimental and theoretical study of the superconducting phase of the layered binary silicide BaSi2. Compared with the layered AlB2 structure of graphite or diboride-like superconductors, in the hexagonal structure of binary silicides the sp3 arrangement of silicon atoms leads to corrugated sheets. Through a high-pressure synthesis procedure we are able to modify the buckling of these sheets, obtaining the enhancement of the superconducting transition temperature from 4 K to 8.7 K when the silicon planes flatten out. By performing ab-initio calculations based on density functional theory we explain how the electronic and phononic properties of the system are strongly affected by changes in the buckling. This mechanism is likely present in other intercalated layered superconductors, opening the way to the tuning of superconductivity through the control of internal structural parameters.Comment: Submitte

1/f1/f noise and avalanche scaling in plastic deformation

We study the intermittency and noise of dislocation systems undergoing shear deformation. Simulations of a simple two-dimensional discrete dislocation dynamics model indicate that the deformation rate exhibits a power spectrum scaling of the type $1/f^{\alpha}$. The noise exponent is far away from a Lorentzian, with $\alpha \approx 1.5$. This result is directly related to the way the durations of avalanches of plastic deformation activity scale with their size.Comment: 6 pages, 5 figures, submitted to Phys. Rev.

Chern-Simons theory, exactly solvable models and free fermions at finite temperature

We show that matrix models in Chern-Simons theory admit an interpretation as 1D exactly solvable models, paralleling the relationship between the Gaussian matrix model and the Calogero model. We compute the corresponding Hamiltonians, ground-state wavefunctions and ground-state energies and point out that the models can be interpreted as quasi-1D Coulomb plasmas. We also study the relationship between Chern-Simons theory on $S^3$ and a system of N one-dimensional fermions at finite temperature with harmonic confinement. In particular we show that the Chern-Simons partition function can be described by the density matrix of the free fermions in a very particular, crystalline, configuration. For this, we both use the Brownian motion and the matrix model description of Chern-Simons theory and find several common features with c=1 theory at finite temperature. Finally, using the exactly solvable model result, we show that the finite temperature effect can be described with a specific two-body interaction term in the Hamiltonian, with 1D Coulombic behavior at large separations.Comment: 19 pages, v2: references adde

Does Big Data Require Complex Systems? A Performance Comparison Between Spark and Unicage Shell Scripts

The paradigm of big data is characterized by the need to collect and process data sets of great volume, arriving at the systems with great velocity, in a variety of formats. Spark is a widely used big data processing system that can be integrated with Hadoop to provide powerful abstractions to developers, such as distributed storage through HDFS and resource management through YARN. When all the required configurations are made, Spark can also provide quality attributes, such as scalability, fault tolerance, and security. However, all of these benefits come at the cost of complexity, with high memory requirements, and additional latency in processing. An alternative approach is to use a lean software stack, like Unicage, that delegates most control back to the developer. In this work we evaluated the performance of big data processing with Spark versus Unicage, in a cluster environment hosted in the IBM Cloud. Two sets of experiments were performed: batch processing of unstructured data sets, and query processing of structured data sets. The input data sets were of significant size, ranging from 64 GB to 8192 GB in volume. The results show that the performance of Unicage scripts is superior to Spark for search workloads like grep and select, but that the abstractions of distributed storage and resource management from the Hadoop stack enable Spark to execute workloads with inter-record dependencies, such as sort and join, with correct outputs.Comment: 10 pages, 14 figure