Probing multipartite entanglement in a coupled Jaynes-Cummings system

We show how to probe multipartite entanglement in $N$ coupled Jaynes-Cummings cells where the degrees of freedom are the electronic energies of each of the $N$ atoms in separate single-mode cavities plus the $N$ single-mode fields themselves. Specifically we propose probing the combined system as though it is a dielectric medium. The spectral properties and transition rates directly reveal multipartite entanglement signatures. It is found that the Hilbert space of the $N$ cell system can be confined to the totally symmetric subspace of two states only that are maximally-entangled W states with 2N degrees of freedom

Continuous Multipartite Entangled State in Wigner Representation and the Violation of Zukowski-Brukner Inequality

We construct an explicit Wigner function for N-mode squeezed state. Based on a previous observation that the Wigner function describes correlations in the joint measurement of the phase-space displaced parity operator, we investigate the non-locality of multipartite entangled state by the violation of Zukowski-Brukner N-qubit Bell inequality. We find that quantum predictions for such squeezed state violate these inequalities by an amount that grows with the number N.Comment: 5 pages, rewritten version, accepted by Phys. Rev.

Mathematics from China to Virginia by Way of Singapore

Our article follows from an interesting concurrence of mathematical and educational lines. At least the concurrence seems so to us and we hope that those who read on will agree. The lines or streams are a joint minimester program at St. Catherine’s and St. Christopher‘s Schools, an interest in problem solving, and a Singapore connection. We shall describe the lines first and then describe the mathematics that we found at their intersection

Microscopic theory of single-electron tunneling through molecular-assembled metallic nanoparticles

We present a microscopic theory of single-electron tunneling through metallic nanoparticles connected to the electrodes through molecular bridges. It combines the theory of electron transport through molecular junctions with the description of the charging dynamics on the nanoparticles. We apply the theory to study single-electron tunneling through a gold nanoparticle connected to the gold electrodes through two representative benzene-based molecules. We calculate the background charge on the nanoparticle induced by the charge transfer between the nanoparticle and linker molecules, the capacitance and resistance of molecular junction using a first-principles based Non-Equilibrium Green's Function theory. We demonstrate the variety of transport characteristics that can be achieved through ``engineering'' of the metal-molecule interaction.Comment: To appear in Phys. Rev.

Orientation and strain modulated electronic structures in puckered arsenene nanoribbons

Orthorhombic arsenene was recently predicted as an indirect bandgap semiconductor. Here, we demonstrate that nanostructuring arsenene into nanoribbons can successfully transform the bandgap to be direct. It is found that direct bandgaps hold for narrow armchair but wide zigzag nanoribbons, which is dominated by the competition between the in-plane and out-of-plane bondings. Moreover, straining the nanoribbons also induces a direct bandgap and simultaneously modulates effectively the transport property. The gap energy is largely enhanced by applying tensile strains to the armchair structures. In the zigzag ones, a tensile strain makes the effective mass of holes much higher while a compressive strain cause it much lower than that of electrons. Our results are crutial to understand and engineer the electronic properties of two dimensional materials beyond the planar ones like graphene

Solving the global atmospheric equations through heterogeneous reconfigurable platforms

One of the most essential and challenging components in climate modeling is the atmospheric model. To solve multiphysical atmospheric equations, developers have to face extremely complex stencil kernels that are costly in terms of both computing and memory resources. This article aims to accelerate the solution of global shallow water equations (SWEs), which is one of the most essential equation sets describing atmospheric dynamics. We first design a hybrid methodology that employs both the host CPU cores and the field-programmable gate array (FPGA) accelerators to work in parallel. Through a careful adjustment of the computational domains, we achieve a balanced resource utilization and a further improvement of the overall performance. By decomposing the resource-demanding SWE kernel, we manage to map the double-precision algorithm into three FPGAs. Moreover, by using fixed-point and reduced-precision floating point arithmetic, we manage to build a fully pipelined mixed-precision design on a single FPGA, which can perform 428 floating-point and 235 fixed-point operations per cycle. The mixed-precision design with four FPGAs running together can achieve a speedup of 20 over a fully optimized design on a CPU rack with two eight-core processorsand is 8 times faster than the fully optimized Kepler GPU design. As for power efficiency, the mixed-precision design with four FPGAs is 10 times more power efficient than a Tianhe-1A supercomputer node.</jats:p

Numerical simulation of Quasi-Normal Modes in time-dependent background

We study the massless scalar wave propagation in the time-dependent Schwarzschild black hole background. We find that the Kruskal coordinate is an appropriate framework to investigate the time-dependent spacetime. A time-dependent scattering potential is derived by considering dynamical black hole with parameters changing with time. It is shown that in the quasinormal ringing both the decay time-scale and oscillation are modified in the time-dependent background.Comment: 10 pages, 8 figures; reference adde

A path-aware approach to mutant reduction in mutation testing

Context: Mutation testing, which systematically generates a set of mutants by seeding various faults into the base program under test, is a popular technique for evaluating the effectiveness of a testing method. However, it normally requires the execution of a large amount of mutants and thus incurs a high cost. Objective: A common way to decrease the cost of mutation testing is mutant reduction, which selects a subset of representative mutants. In this paper, we propose a new mutant reduction approach from the perspective of program structure. Method: Our approach attempts to explore path information of the program under test, and select mutants that are as diverse as possible with respect to the paths they cover. We define two path-aware heuristic rules, namely module-depth and loop-depth rules, and combine them with statement- and operator-based mutation selection to develop four mutant reduction strategies. Results: We evaluated the cost-effectiveness of our mutant reduction strategies against random mutant selection on 11 real-life C programs with varying sizes and sampling ratios. Our empirical studies show that two of our mutant reduction strategies, which primarily rely on the path-aware heuristic rules, are more effective and systematic than pure random mutant selection strategy in terms of selecting more representative mutants. In addition, among all four strategies, the one giving loop-depth the highest priority has the highest effectiveness. Conclusion: In general, our path-aware approach can reduce the number of mutants without jeopardizing its effectiveness, and thus significantly enhance the overall cost-effectiveness of mutation testing. Our approach is particularly useful for the mutation testing on large-scale complex programs that normally involve a huge amount of mutants with diverse fault characteristics