5,723 research outputs found
The IBMAP approach for Markov networks structure learning
In this work we consider the problem of learning the structure of Markov
networks from data. We present an approach for tackling this problem called
IBMAP, together with an efficient instantiation of the approach: the IBMAP-HC
algorithm, designed for avoiding important limitations of existing
independence-based algorithms. These algorithms proceed by performing
statistical independence tests on data, trusting completely the outcome of each
test. In practice tests may be incorrect, resulting in potential cascading
errors and the consequent reduction in the quality of the structures learned.
IBMAP contemplates this uncertainty in the outcome of the tests through a
probabilistic maximum-a-posteriori approach. The approach is instantiated in
the IBMAP-HC algorithm, a structure selection strategy that performs a
polynomial heuristic local search in the space of possible structures. We
present an extensive empirical evaluation on synthetic and real data, showing
that our algorithm outperforms significantly the current independence-based
algorithms, in terms of data efficiency and quality of learned structures, with
equivalent computational complexities. We also show the performance of IBMAP-HC
in a real-world application of knowledge discovery: EDAs, which are
evolutionary algorithms that use structure learning on each generation for
modeling the distribution of populations. The experiments show that when
IBMAP-HC is used to learn the structure, EDAs improve the convergence to the
optimum
Thermal collapse of a granular gas under gravity
Free cooling of a gas of inelastically colliding hard spheres represents a
central paradigm of kinetic theory of granular gases. At zero gravity the
temperature of a freely cooling homogeneous granular gas follows a power law in
time. How does gravity, which brings inhomogeneity, affect the cooling? We
combine molecular dynamics simulations, a numerical solution of hydrodynamic
equations and an analytic theory to show that a granular gas cooling under
gravity undergoes thermal collapse: it cools down to zero temperature and
condenses on the bottom of the container in a finite time.Comment: 4 pages, 12 eps figures, to appear in PR
Coolant topology options for high temperature superconducting transmission and distribution systems
This paper investigates coolant topologies for High Temperature Superconducting (HTS) transmission and distribution cable systems. We explore options that allow for flexibility of operation, low temperature rise in the superconductor and low refrigerator power consumption. Topologies for cooling the cryostat and HTS in long-distance electric power transmission systems are explored. For transmission, the goal is to achieve long spans between cooling stations along the transmission line, and low power consumption. For HTS distribution systems, the issue is cooling the superconductor and the current leads and the goals are to minimize the power consumption and to prevent excessive heating of the superconductor. Means are explored to cool distribution systems where cryogenic loads are dominated by current lead loss. Use of multiple fluids or multiple coolant circuits of the same fluid to decrease the energy ingress in the low temperature environment is described. Potential alternative coolants are proposed. We show that it is possible to reduce electrical consumption by about a factor of 2, while also decreasing the temperature rise of the superconductor
Response of discrete nonlinear systems with many degrees of freedom
We study the response of a large array of coupled nonlinear oscillators to
parametric excitation, motivated by the growing interest in the nonlinear
dynamics of microelectromechanical and nanoelectromechanical systems (MEMS and
NEMS). Using a multiscale analysis, we derive an amplitude equation that
captures the slow dynamics of the coupled oscillators just above the onset of
parametric oscillations. The amplitude equation that we derive here from first
principles exhibits a wavenumber dependent bifurcation similar in character to
the behavior known to exist in fluids undergoing the Faraday wave instability.
We confirm this behavior numerically and make suggestions for testing it
experimentally with MEMS and NEMS resonators.Comment: Version 2 is an expanded version of the article, containing detailed
steps of the derivation that were left out in version 1, but no additional
result
Quantum walks of correlated particles
Quantum walks of correlated particles offer the possibility to study
large-scale quantum interference, simulate biological, chemical and physical
systems, and a route to universal quantum computation. Here we demonstrate
quantum walks of two identical photons in an array of 21 continuously
evanescently-coupled waveguides in a SiOxNy chip. We observe quantum
correlations, violating a classical limit by 76 standard deviations, and find
that they depend critically on the input state of the quantum walk. These
results open the way to a powerful approach to quantum walks using correlated
particles to encode information in an exponentially larger state space
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