Likelihood smoothing using gravitational wave surrogate models

Likelihood surfaces in the parameter space of gravitational wave signals can contain many secondary maxima, which can prevent search algorithms from finding the global peak and correctly mapping the distribution. Traditional schemes to mitigate this problem maintain the number of secondary maxima and thus retain the possibility that the global maximum will remain undiscovered. By contrast, the recently proposed technique of likelihood transform can modify the structure of the likelihood surface to reduce its complexity. We present a practical method to carry out a likelihood transform using a Gaussian smoothing kernel, utilising gravitational wave surrogate models to perform the smoothing operation analytically. We demonstrate the approach with Newtonian and post-Newtonian waveform models for an inspiralling circular compact binary.RHC is supported by STFC. JG is supported by the Royal Society.This is the accepted manuscript. The final version is available from APS at http://journals.aps.org/prd/abstract/10.1103/PhysRevD.90.124043

Definition of Naturally Processed Peptides Reveals Convergent Presentation of Autoantigenic Topoisomerase I Epitopes in Scleroderma.

ObjectiveAutoimmune responses to DNA topoisomerase I (topo I) are found in a subset of scleroderma patients who are at high risk for interstitial lung disease (ILD) and mortality. Anti-topo I antibodies (ATAs) are associated with specific HLA-DRB1 alleles, and the frequency of HLA-DR-restricted topo I-specific CD4+ T cells is associated with the presence, severity, and progression of ILD. Although this strongly implicates the presentation of topo I peptides by HLA-DR in scleroderma pathogenesis, the processing and presentation of topo I has not been studied.MethodsWe developed a natural antigen processing assay (NAPA) to identify putative CD4+ T cell epitopes of topo I presented by monocyte-derived dendritic cells (mo-DCs) from 6 ATA-positive patients with scleroderma. Mo-DCs were pulsed with topo I protein, HLA-DR-peptide complexes were isolated, and eluted peptides were analyzed by mass spectrometry. We then examined the ability of these naturally presented peptides to induce CD4+ T cell activation in 11 ATA-positive and 11 ATA-negative scleroderma patients.ResultsWe found that a common set of 10 topo I epitopes was presented by Mo-DCs from scleroderma patients with diverse HLA-DR variants. Sequence analysis revealed shared peptide-binding motifs within the HLA-DRβ chains of ATA-positive patients and a subset of topo I epitopes with distinct sets of anchor residues capable of binding to multiple different HLA-DR variants. The NAPA-derived epitopes elicited robust CD4+ T cell responses in 73% of ATA-positive patients (8 of 11), and the number of epitopes recognized correlated with ILD severity (P = 0.025).ConclusionThese findings mechanistically implicate the presentation of a convergent set of topo I epitopes in the development of scleroderma

Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior

The human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in “conjunction hubs”—brain regions that selectively integrate sensory, cognitive, and motor activations. We used recent advances in using functional connectivity to map the flow of activity between brain regions to construct a task-performing neural network model from fMRI data during a cognitive control task. We verified the importance of conjunction hubs in cognitive computations by simulating neural activity flow over this empirically-estimated functional connectivity model. These empiricallyspecified simulations produced above-chance task performance (motor responses) by integrating sensory and task rule activations in conjunction hubs. These findings reveal the role of conjunction hubs in supporting flexible cognitive computations, while demonstrating the feasibility of using empirically-estimated neural network models to gain insight into cognitive computations in the human brain

Nondestructive SEM for surface and subsurface wafer imaging

The scanning electron microscope (SEM) is considered as a tool for both failure analysis as well as device characterization. A survey is made of various operational SEM modes and their applicability to image processing methods on semiconductor devices

The Periodic Standing-Wave Approximation: Overview and Three Dimensional Scalar Models

The periodic standing-wave method for binary inspiral computes the exact numerical solution for periodic binary motion with standing gravitational waves, and uses it as an approximation to slow binary inspiral with outgoing waves. Important features of this method presented here are: (i) the mathematical nature of the ``mixed'' partial differential equations to be solved, (ii) the meaning of standing waves in the method, (iii) computational difficulties, and (iv) the ``effective linearity'' that ultimately justifies the approximation. The method is applied to three dimensional nonlinear scalar model problems, and the numerical results are used to demonstrate extraction of the outgoing solution from the standing-wave solution, and the role of effective linearity.Comment: 13 pages RevTeX, 5 figures. New version. A revised form of the nonlinearity produces better result

Binary Quasars in the Sloan Digital Sky Survey: Evidence for Excess Clustering on Small Scales

We present a sample of 218 new quasar pairs with proper transverse separations R_prop < 1 Mpc/h over the redshift range 0.5 < z < 3.0, discovered from an extensive follow up campaign to find companions around the Sloan Digital Sky Survey and 2dF Quasar Redshift Survey quasars. This sample includes 26 new binary quasars with separations R_prop < 50 kpc/h (theta < 10 arcseconds), more than doubling the number of such systems known. We define a statistical sample of binaries selected with homogeneous criteria and compute its selection function, taking into account sources of incompleteness. The first measurement of the quasar correlation function on scales 10 kpc/h < R_prop < 400 kpc/h is presented. For R_prop < 40 kpc/h, we detect an order of magnitude excess clustering over the expectation from the large scale R_prop > 3 Mpc/h quasar correlation function, extrapolated down as a power law to the separations probed by our binaries. The excess grows to ~ 30 at R_prop ~ 10 kpc/h, and provides compelling evidence that the quasar autocorrelation function gets progressively steeper on sub-Mpc scales. This small scale excess can likely be attributed to dissipative interaction events which trigger quasar activity in rich environments. Recent small scale measurements of galaxy clustering and quasar-galaxy clustering are reviewed and discussed in relation to our measurement of small scale quasar clustering.Comment: 25 pages, 12 figures, 9 tables. Submitted to the Astronomical Journa