Nuclear Spin Relaxation Rate of Disordered px+ipyp_x+ip_y-wave Superconductors

Based on an effective Hamiltonian with the binary alloy disorder model defined in the triangular lattice, the impurity scattering effects on the density of states and especially on the spin-lattice relaxation rate $1/T_1$ of $p_x+ip_y$-wave superconductors are studied by solving numerically the Bogoliubov-de Gennes equations. In the clean limit, the coherence peak of $1/T_1$ is observed as expected. More intriguingly, for strong scattering potential, the temperature dependence of $1/T_1$ exhibits the two different power law behaviors near $T_{\text{c}}$ and at low temperatures, respectively, which is in good agreement with the nuclear quadrupolar resonance measurement.Comment: 4 pages, 3 figure

Stokes Parameters as a Minkowskian Four-vector

It is noted that the Jones-matrix formalism for polarization optics is a six-parameter two-by-two representation of the Lorentz group. It is shown that the four independent Stokes parameters form a Minkowskian four-vector, just like the energy-momentum four-vector in special relativity. The optical filters are represented by four-by-four Lorentz-transformation matrices. This four-by-four formalism can deal with partial coherence described by the Stokes parameters. A four-by-four matrix formulation is given for decoherence effects on the Stokes parameters, and a possible experiment is proposed. It is shown also that this Lorentz-group formalism leads to optical filters with a symmetry property corresponding to that of two-dimensional Euclidean transformations.Comment: RevTeX, 22 pages, no figures, submitted to Phys. Rev.

Coauthor prediction for junior researchers

Research collaboration can bring in different perspectives and generate more productive results. However, finding an appropriate collaborator can be difficult due to the lacking of sufficient information. Link prediction is a related technique for collaborator discovery; but its focus has been mostly on the core authors who have relatively more publications. We argue that junior researchers actually need more help in finding collaborators. Thus, in this paper, we focus on coauthor prediction for junior researchers. Most of the previous works on coauthor prediction considered global network feature and local network feature separately, or tried to combine local network feature and content feature. But we found a significant improvement by simply combing local network feature and global network feature. We further developed a regularization based approach to incorporate multiple features simultaneously. Experimental results demonstrated that this approach outperformed the simple linear combination of multiple features. We further showed that content features, which were proved to be useful in link prediction, can be easily integrated into our regularization approach. © 2013 Springer-Verlag

Using Monte Carlo Search With Data Aggregation to Improve Robot Soccer Policies

RoboCup soccer competitions are considered among the most challenging multi-robot adversarial environments, due to their high dynamism and the partial observability of the environment. In this paper we introduce a method based on a combination of Monte Carlo search and data aggregation (MCSDA) to adapt discrete-action soccer policies for a defender robot to the strategy of the opponent team. By exploiting a simple representation of the domain, a supervised learning algorithm is trained over an initial collection of data consisting of several simulations of human expert policies. Monte Carlo policy rollouts are then generated and aggregated to previous data to improve the learned policy over multiple epochs and games. The proposed approach has been extensively tested both on a soccer-dedicated simulator and on real robots. Using this method, our learning robot soccer team achieves an improvement in ball interceptions, as well as a reduction in the number of opponents' goals. Together with a better performance, an overall more efficient positioning of the whole team within the field is achieved

Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) PARM tape user's guide

The Scanning Multichannel Microwave Radiometer (SMMR) instrument, onboard the Nimbus-7 spacecraft, collected data from Oct. 1978 until Jun. 1986. The data were processed to physical parameter level products. Geophysical parameters retrieved include the following: sea-surface temperatures, sea-surface windspeed, total column water vapor, and sea-ice parameters. These products are stored on PARM-LO, PARM-SS, and PARM-30 tapes. The geophysical parameter retrieval algorithms and the quality of these products are described for the period between Nov. 1978 and Oct 1985. Additionally, data formats and data availability are included

Blending in Future Space-based Microlensing Surveys

We investigate the effect of blending in future gravitational microlensing surveys by carrying out simulation of Galactic bulge microlensing events to be detected from a proposed space-based lensing survey. From this simulation, we find that the contribution of the flux from background stars to the total blended flux will be equivalent to that from the lens itself despite the greatly improved resolution from space observations, implying that characterizing lenses from the analysis of the blended flux would not be easy. As a method to isolate events for which most of the blended flux is attributable to the lens, we propose to use astrometric information of source star image centroid motion. For the sample of events obtained by imposing a criterion that the centroid shift should be less than three times of the astrometric uncertainty among the events for which blending is noticed with blended light fractions $f_{\rm B}>0.2$, we estimate that the contamination of the blended flux by background stars will be less than 20% for most ($\sim 90$) of the sample events. The expected rate of these events is $\gtrsim 700$ events/yr, which is large enough for the statistical analysis of the lens populations.Comment: total 6 pages, including 5 figures, ApJ, in pres

Coordination motifs and large-scale structural organization in atomic clusters

The structure of nanoclusters is complex to describe due to their noncrystallinity, even though bonding and packing constraints limit the local atomic arrangements to only a few types. A computational scheme is presented to extract coordination motifs from sample atomic configurations. The method is based on a clustering analysis of multipole moments for atoms in the first coodination shell. Its power to capture large-scale structural properties is demonstrated by scanning through the ground state of the Lennard-Jones and C$_{60}$ clusters collected at the Cambridge Cluster Database.Comment: 6 pages, 7 figure

User's guide for the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) CELL-ALL tape

The SMMR instrument onboard the Nimbus-7 satellite has been in operation since October 1978. It provided global coverage of passive microwave observations at 6.6, 10.7, 18, 21, and 37 GHz. The oberved brightness temperature can be used to retrieve geophysical parameters, principally sea surface temperature, atmospheric water vapor and liquid water content over oceans, sea ice concentration, and snow cover over land. The SMME CELL-ALL Tape contains earth-located calibrated brightness temperature data which have been appropriately binned into cells of various grid sizes, allowing intercomparisons of observations made at different frequencies (with corresponding different footprint sizes). This user's guide describes the operation of the instrument, the flow of the data processing the calibration procedure, and the characteristics of the calibrated brightness temperatures and how they are binned. Detailed tape specifications and lists of available data are also provided