En Masse relay selection algorithms for multi-source, multi-relay, decode-and-forward cooperative systems

Opportunistic relay selection in a multiple source-destination (MSD) cooperative system requires quickly allocating to each source-destination (SD) pair a suitable relay based on channel gains. Since the channel knowledge is available only locally at a relay and not globally, efficient relay selection algorithms are needed. For an MSD system, in which the SD pairs communicate in a time-orthogonal manner with the help of decode-and-forward relays, we propose three novel relay selection algorithms, namely, contention-free en masse assignment (CFEA), contention-based en masse assignment (CBEA), and a hybrid algorithm that combines the best features of CFEA and CBEA. En masse assignment exploits the fact that a relay can often aid not one but multiple SD pairs, and, therefore, can be assigned to multiple SD pairs. This drastically reduces the average time required to allocate an SD pair when compared to allocating the SD pairs one by one. We show that the algorithms are much faster than other selection schemes proposed in the literature and yield significantly higher net system throughputs. Interestingly, CFEA is as effective as CBEA over a wider range of system parameters than in single SD pair systems.

Entropy of quantum states: Ambiguities

The von Neumann entropy of a generic quantum state is not unique unless the state can be uniquely decomposed as a sum of extremal or pure states. As pointed out to us by Sorkin, this happens if the GNS representation (of the algebra of observables in some quantum state) is reducible, and some representations in the decomposition occur with non-trivial degeneracy. This non-unique entropy can occur at zero temperature. We will argue elsewhere in detail that the degeneracies in the GNS representation can be interpreted as an emergent broken gauge symmetry, and play an important role in the analysis of emergent entropy due to non-Abelian anomalies. Finally, we establish the analogue of an H-theorem for this entropy by showing that its evolution is Markovian, determined by a stochastic matrix.

Polynomial time and parameterized approximation algorithms for boxicity

The boxicity (cubicity) of a graph G, denoted by box(G) (respectively cub(G)), is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes (cubes) in ℝ k . The problem of computing boxicity (cubicity) is known to be inapproximable in polynomial time even for graph classes like bipartite, co-bipartite and split graphs, within an O(n 0.5 − ε ) factor for any ε > 0, unless NP = ZPP. We prove that if a graph G on n vertices has a clique on n − k vertices, then box(G) can be computed in time n22O(k2logk) . Using this fact, various FPT approximation algorithms for boxicity are derived. The parameter used is the vertex (or edge) edit distance of the input graph from certain graph families of bounded boxicity - like interval graphs and planar graphs. Using the same fact, we also derive an O(nloglogn√logn√) factor approximation algorithm for computing boxicity, which, to our knowledge, is the first o(n) factor approximation algorithm for the problem. We also present an FPT approximation algorithm for computing the cubicity of graphs, with vertex cover number as the parameter.

Near infrared detectors based on HgSe and HgCdSe quantum dots generated at the liquid-liquid interface

HgSe and Hg0.5Cd0.5Se quantum dos (QDs) are synthesized at room temperature by a novel liquid-liquid interface method and their photodetection properties in the near-IR region are investigated. The photodetection properties of our Te-free systems are found to be comparable to those of the previously reported high performance QD vis-IR detectors including HgTe. The present synthesis indicates the cost-effectiveness of selenium based IR detectors owing to the abundance and lower toxicity of selenium compared to tellurium.

Maximum likelihood algorithms for joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing system

Maximum likelihood (ML) algorithms, for the joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system, are investigated in this work. A system model that takes into account the effects of carrier frequency offset, sampling frequency offset, symbol timing error and channel impulse response is formulated. Cramer-Rao lower bounds for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation. The authors propose an ML algorithm for the estimation of synchronisation impairments and channel together, using the grid search method. To reduce the complexity of the joint grid search in the ML algorithm, a modified ML (MML) algorithm with multiple one-dimensional searches is also proposed. Further, a stage-wise ML (SML) algorithm using existing algorithms, which estimate less number of parameters, is also proposed. Performance of the estimation algorithms is studied through numerical simulations and it is found that the proposed ML and MML algorithms exhibit better performance than SML algorithm.

Highly photoactive heterostructures of PbO quantum dots on TiO2

We present a non-hydrolytic sol-gel combustion method for synthesizing nanocomposites of PbO quantum dots on anatase TiO2 with a high surface area. XRD, electron microscopy, DRS, cathodoluminescence and BET were employed for structural, microstructural and optical characterization of the composites. The photocatalytic activity of TiO2 and PbO/TiO2 was investigated and compared with Degussa P-25. The results indicate that the photocatalytic activity of quantum dot dispersed TiO2 is higher than that of bare TiO2 and much higher than that of commercial Degussa P-25. The origin of enhanced photoreactivity of the synthesized material can be assigned to a synergetic effect of high surface area, higher number of active sites and an engineered band structure in the heterostructure. The mechanisms for photocatalytic activity are discussed based on production of photogenerated reactive species. The knowledge gained through this report open up ideal synthesis routes for designing advanced functional heterostructures with engineered band structure and has important implications in solar energy based applications.

Tuning the parameters to establish Quenching and enhancement regimes in hybrid Gold nanoparticles and CdSe Quantum dots monolayer

The multi-component nanomaterials combine the individual properties and give rise to emergent phenomenon. Optical excitations in such hybrid nonmaterial's ( for example Exciton in semiconductor quantum dots and Plasmon in Metal nanomaterials) undergo strong weak electromagnetic coupling. Such exciton-plasmon interactions allow design of absorption and emission properties, control of nanoscale energy-transfer processes, and creation of new excitations in the strong coupling regime.This Exciton plasmon interaction in hybrid nanomaterial can lead to both enhancement in the emission as well as quenching. In this work we prepared close-packed hybrid monolayer of thiol capped CdSe and gold nanoparticles. They exhibit both the Quenching and enhancements the in PL emission.The systematic variance of PL from such hybrid nanomaterials monolayer is studied by tuning the Number ratio of Gold per Quantum dots, the surface density of QDs and the spectral overlap of emission spectrum of QD and absorption spectrum of Gold nanoparticles. Role of Localized surface Plasmon which not only leads to quenching but strong enhancements as well, is explored.

Quantum Phase Diagram of One-Dimensional Spin and Hubbard Models with Transitions to Bond Order Wave Phases

Similar quantum phase diagrams and transitions are found for three classes of one-dimensional models with equally spaced sites, singlet ground states (GS), inversion symmetry at sites and a bond order wave (BOW) phase in some sectors. The models are frustrated spin-1/2 chains with variable range exchange, half-filled Hubbard models with spin-independent interactions and modified Hubbard models with site energies for describing organic charge transfer salts. In some range of parameters, the models have a first order quantum transition at which the GS expectation value of the sublattice spin < S-A(2)> of odd or even-numbered sites is discontinuous. There is an intermediate BOW phase for other model parameters that lead to two continuous quantum transitions with continuous < S-A(2)>. Exact diagonalization of finite systems and symmetry arguments provide a unified picture of familiar 1D models that have appeared separately in widely different contexts.

EFFICIENT QUANTUM RANDOM NUMBER GENERATION USING QUANTUM INDISTINGUISHABILITY

In this paper, we propose a quantum method for generation of random numbers based on bosonic stimulation. Randomness arises through the path-dependent indeterministic amplification of two competing bosonic modes. We show that the process provides an efficient method for macroscopic extraction of microscopic randomness.

Quantum Phase Diagram of One-Dimensional Spin and Hubbard Models with Transitions to Bond Order Wave Phases

Similar quantum phase diagrams and transitions are found for three classes of one-dimensional models with equally spaced sites, singlet ground states (GS), inversion symmetry at sites and a bond order wave (BOW) phase in some sectors. The models are frustrated spin-1/2 chains with variable range exchange, half-filled Hubbard models with spin-independent interactions and modified Hubbard models with site energies for describing organic charge transfer salts. In some range of parameters, the models have a first order quantum transition at which the GS expectation value of the sublattice spin < S-A(2)> of odd or even-numbered sites is discontinuous. There is an intermediate BOW phase for other model parameters that lead to two continuous quantum transitions with continuous < S-A(2)>. Exact diagonalization of finite systems and symmetry arguments provide a unified picture of familiar 1D models that have appeared separately in widely different contexts.

FUSION OF ALGORITHMS FOR COMPRESSED SENSING

Numerous algorithms have been proposed recently for sparse signal recovery in Compressed Sensing (CS). In practice, the number of measurements can be very limited due to the nature of the problem and/or the underlying statistical distribution of the non-zero elements of the sparse signal may not be known a priori. It has been observed that the performance of any sparse signal recovery algorithm depends on these factors, which makes the selection of a suitable sparse recovery algorithm difficult. To take advantage in such situations, we propose to use a fusion framework using which we employ multiple sparse signal recovery algorithms and fuse their estimates to get a better estimate. Theoretical results justifying the performance improvement are shown. The efficacy of the proposed scheme is demonstrated by Monte Carlo simulations using synthetic sparse signals and ECG signals selected from MIT-BIH database.

Atomic Structure of Quantum Gold Nanowires: Quantification of the Lattice Strain

Theoretical studies exist to compute the atomic arrangement in gold nanowires and the influence on their electronic behavior with decreasing diameter. Experimental studies, e.g., by transmission electron microscopy, on chemically synthesized ultrafine wires are however lacking owing to the unavailability of suitable protocols for sample preparation and the stability of the wires under electron beam irradiation. In this work, we present an atomic scale structural investigation on quantum single crystalline gold nanowires of 2 nm diameter, chemically prepared on a carbon film grid. Using low dose aberration-corrected high resolution (S)TEM, we observe an inhomogeneous strain distribution in the crystal, largely concentrated at the twin boundaries and the surface along with the presence of facets and surface steps leading to a noncircular cross section of the wires. These structural aspects are critical inputs needed to determine their unique electronic character and their potential as a suitable catalyst material. Furthermore, electron-beam-induced structural changes at the atomic scale, having implications on their mechanical behavior and their suitability as interconnects, are discussed.

Improved photovoltaic performance of CdSe/CdS/PbS quantum dot sensitized ZnO nanorod array solar cell

Single crystalline zinc oxide (ZnO) nanorod array has been used for the fabrication of CdSe/CdS/PbS/ZnO quantum dot sensitized solar cell (QDSSC). The ZnO nanorod array photoanodes are sensitized with consecutive layer of PbS, CdS and CdSe quantum dots by employing simple successive ion layer adsorption and reaction (SILAR) and chemical bath deposition (CBD) techniques. The performances of the QDSSCs are examined in detail using polysulfide electrolyte with copper sulfide (CuS) counter electrode. The combination of two successive layers of PbS with CdSe/CdS/ZnO shows an improved short circuit current density (12.223 mA cm(-2)) with a maximum power to conversion efficiency of 2.352% under 1 sun illumination. This enhancement is mainly attributed due to the better light harvesting ability of the PbS quantum dots and make large accumulation of photo-injected electrons in the conduction band of ZnO, and CdSe/CdS layers lower the recombination of photo-injected electrons with the electrolyte, these are well evidenced with the photovoltaic studies and electrochemical impedance spectroscopy. (C) 2013 Elsevier B.V. All rights reserved.

Progressive fusion of reconstruction algorithms for low latency applications in compressed sensing

Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data. (C) 2013 Elsevier B.V. All rights reserved.