20,302 research outputs found
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 GeSi nanocrystals from TDDFT and comparison with effective-medium theory
We present the optical spectra of GeSi 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 . 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
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 . The noise exponent is far away from a
Lorentzian, with . 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 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
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