53,900 research outputs found
Mechanisms of Auger-induced chemistry derived from wave packet dynamics
To understand how core ionization and subsequent Auger decay lead to bond breaking in large systems, we simulate the wave packet dynamics of electrons in the hydrogenated diamond nanoparticle C_(197)H_(112). We find that surface core ionizations cause emission of carbon fragments and protons through a direct Auger mechanism, whereas deeper core ionizations cause hydrides to be emitted from the surface via remote heating, consistent with results from photon-stimulated desorption experiments [Hoffman A, Laikhtman A, (2006) J Phys Condens Mater 18:S1517–S1546]. This demonstrates that it is feasible to study the chemistry of highly excited large-scale systems using simulation and analysis tools comparable in simplicity to those used for classical molecular dynamics
Quantum communication in the presence of a horizon
Based on homodyne detection, we discuss how the presence of an event horizon
affects quantum communication between an inertial partner, Alice, and a
uniformly accelerated partner, Rob. We show that there exists a low frequency
cutoff for Rob's homodyne detector that maximizes the signal to noise ratio and
it approximately corresponds to the Unruh frequency. In addition, the low
frequency cutoff which minimizes the conditional variance between Alice's input
state and Rob's output state is also approximately equal to the Unruh
frequency. Thus the Unruh frequency provides a natural low frequency cutoff in
order to optimize quantum communication of both classical and quantum
information between Alice and Rob.Comment: 7 pages, 6 figure
symmetry restoration in QCD with flavors
Recently, there have been reports that the chirally restored phase of QCD is
effectively symmetric under rather than . We supplement their argument by including the contributions from
topologically nontrivial gauge field configurations and discuss how the
conclusions are modified. General statements are made concerning the particle
spectrum of QCD with light flavors in the high temperature chirally
restored phase.Comment: 6 pages, no figures, revte
Reduced pattern training based on task decomposition using pattern distributor
Task Decomposition with Pattern Distributor (PD) is a new task decomposition method for multilayered feedforward neural networks. Pattern distributor network is proposed that implements this new task decomposition method. We propose a theoretical model to analyze the performance of pattern distributor network. A method named Reduced Pattern Training is also introduced, aiming to improve the performance of pattern distribution. Our analysis and the experimental results show that reduced pattern training improves the performance of pattern distributor network significantly. The distributor module’s classification accuracy dominates the whole network’s performance. Two combination methods, namely Cross-talk based combination and Genetic Algorithm based combination, are presented to find suitable grouping for the distributor module. Experimental results show that this new method can reduce training time and improve network generalization accuracy when compared to a conventional method such as constructive backpropagation or a task decomposition method such as Output Parallelism
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