The influence of spin on jet power in neutron star X-ray binaries

We investigate the role of the compact object in the production of jets from neutron star X-ray binaries. The goal is to quantify the effect of the neutron star spin, if any, in powering the jet. We compile all the available measures or estimates of the neutron star spin frequency in jet-detected neutron star X-ray binaries. We use as an estimate of the ranking jet power for each source, the normalisation of the power law which fits the X-ray/radio and X-ray/infrared luminosity correlations L_(radio/IR) proportional to L_(X)^(Gamma) (using infrared data for which there is evidence for jet emission). We find a possible relation between spin frequency and jet power (Spearman rank 97%), when fitting the X-ray/radio luminosity correlation using a power law with slope 1.4; Gamma=1.4 is observed in 4U 1728-34 and is predicted for a radiatively efficient disc and a total jet power proportional to the mass accretion rate. If we use a slope of 0.6, as observed in Aql X-1, no significant relation is found. An indication for a similar positive correlation is also found for accreting millisecond X-ray pulsars (Spearman rank 92%), if we fit the X-ray/infrared luminosity correlation using a power law with slope 1.4. While our use of the normalisation of the luminosity correlations as a measure of the ranking jet power is subject to large uncertainties, no better proxy for the jet power is available. However, we urge caution in over-interpreting the spin-jet power correlations, particularly given the strong dependence of our result on the (highly uncertain) assumed power law index of the luminosity correlations. We discuss the results in the framework of current models for jet formation in black holes and young stellar objects and speculate on possible different jet production mechanisms for neutron stars depending on the accretion mode.Comment: Accepted for publication in MNRA

Similarity-Aware Spectral Sparsification by Edge Filtering

In recent years, spectral graph sparsification techniques that can compute ultra-sparse graph proxies have been extensively studied for accelerating various numerical and graph-related applications. Prior nearly-linear-time spectral sparsification methods first extract low-stretch spanning tree from the original graph to form the backbone of the sparsifier, and then recover small portions of spectrally-critical off-tree edges to the spanning tree to significantly improve the approximation quality. However, it is not clear how many off-tree edges should be recovered for achieving a desired spectral similarity level within the sparsifier. Motivated by recent graph signal processing techniques, this paper proposes a similarity-aware spectral graph sparsification framework that leverages efficient spectral off-tree edge embedding and filtering schemes to construct spectral sparsifiers with guaranteed spectral similarity (relative condition number) level. An iterative graph densification scheme is introduced to facilitate efficient and effective filtering of off-tree edges for highly ill-conditioned problems. The proposed method has been validated using various kinds of graphs obtained from public domain sparse matrix collections relevant to VLSI CAD, finite element analysis, as well as social and data networks frequently studied in many machine learning and data mining applications

Photothermal characterization of encapsulant materials for photovoltaic modules

A photothermal test matrix and a low cost testing apparatus for encapsulant materials of photovoltaic modules were defined. Photothermal studies were conducted to screen and rank existing as well as future encapsulant candidate materials and/or material formulations in terms of their long term physiochemical stability under accelerated photothermal aging conditions. Photothermal characterization of six candidate pottant materials and six candidate outer cover materials were carried out. Principal products of photothermal degradation are identified. Certain critical properties are also monitored as a function of photothermal aging