Structure of W3(OH) from Very High Spectral Resolution Observations of 5 Centimeter OH Masers

Recent studies of methanol and ground-state OH masers at very high spectral resolution have shed new light on small-scale maser processes. The nearby source W3(OH), which contains numerous bright masers in several different transitions, provides an excellent laboratory for high spectral resolution techniques. We present a model of W3(OH) based on EVN observations of the rotationally-excited 6030 and 6035 MHz OH masers taken at 0.024 km/s spectral resolution. The 6.0 GHz masers are becoming brighter with time and show evidence for tangential proper motions. We confirm the existence of a region of magnetic field oriented toward the observer to the southeast and find another such region to the northeast in W3(OH), near the champagne flow. The 6.0 GHz masers trace the inner edge of a counterclockwise rotating torus feature. Masers at 6030 MHz are usually a factor of a few weaker than at 6035 MHz but trace the same material. Velocity gradients of nearby Zeeman components are much more closely correlated than in the ground state, likely due to the smaller spatial separation between Zeeman components. Hydroxyl maser peaks at very long baseline interferometric resolution appear to have structure on scales both smaller than that resolvable as well as on larger scales.Comment: 21 pages using emulateapj.cls including 16 figures and 2 tables, accepted to Ap

Neural Network Kalman Filtering for 3-D Object Tracking From Linear Array Ultrasound Data

Many interventional surgical procedures rely on medical imaging to visualise and track instruments. Such imaging methods not only need to be real-time capable, but also provide accurate and robust positional information. In ultrasound applications, typically only two-dimensional data from a linear array are available, and as such obtaining accurate positional estimation in three dimensions is non-trivial. In this work, we first train a neural network, using realistic synthetic training data, to estimate the out-of-plane offset of an object with the associated axial aberration in the reconstructed ultrasound image. The obtained estimate is then combined with a Kalman filtering approach that utilises positioning estimates obtained in previous time-frames to improve localisation robustness and reduce the impact of measurement noise. The accuracy of the proposed method is evaluated using simulations, and its practical applicability is demonstrated on experimental data obtained using a novel optical ultrasound imaging setup. Accurate and robust positional information is provided in real-time. Axial and lateral coordinates for out-of-plane objects are estimated with a mean error of 0.1mm for simulated data and a mean error of 0.2mm for experimental data. Three-dimensional localisation is most accurate for elevational distances larger than 1mm, with a maximum distance of 6mm considered for a 25mm aperture

T-PHOT version 2.0: improved algorithms for background subtraction, local convolution, kernel registration, and new options

We present the new release v2.0 of T-PHOT, a publicly available software package developed to perform PSF-matched, prior-based, multiwavelength deconfusion photometry of extragalactic fields. New features included in the code are presented and discussed: background estimation, fitting using position dependent kernels, flux prioring, diagnostical statistics on the residual image, exclusion of selected sources from the model and residual images, individual registration of fitted objects. These new options improve on the performance of the code, allowing for more accurate results and providing useful aids for diagnostics.Comment: 7 pages, 8 figure

Dynamics of the solar magnetic bright points derived from their horizontal motions

The sub-arcsec bright points (BP) associated with the small scale magnetic fields in the lower solar atmosphere are advected by the evolution of the photospheric granules. We measure various quantities related to the horizontal motions of the BPs observed in two wavelengths, including the velocity auto-correlation function. A 1 hr time sequence of wideband H$\alpha$ observations conducted at the \textit{Swedish 1-m Solar Telescope} (\textit{SST}), and a 4 hr \textit{Hinode} \textit{G}-band time sequence observed with the Solar Optical telescope are used in this work. We follow 97 \textit{SST} and 212 \textit{Hinode} BPs with 3800 and 1950 individual velocity measurements respectively. For its high cadence of 5 s as compared to 30 s for \textit{Hinode} data, we emphasize more on the results from \textit{SST} data. The BP positional uncertainty achieved by \textit{SST} is as low as 3 km. The position errors contribute 0.75 km$^2$ s$^{-2}$ to the variance of the observed velocities. The \textit{raw} and \textit{corrected} velocity measurements in both directions, i.e., $(v_x,v_y)$, have Gaussian distributions with standard deviations of $(1.32,1.22)$ and $(1.00, 0.86)$ km s$^{-1}$ respectively. The BP motions have correlation times of about $22 - 30$ s. We construct the power spectrum of the horizontal motions as a function of frequency, a quantity that is useful and relevant to the studies of generation of Alfv\'en waves. Photospheric turbulent diffusion at time scales less than 200 s is found to satisfy a power law with an index of 1.59.Comment: Accepted for publication in The Astrophysical Journal. 24 pages, 9 figures, and 1 movie (not included

Self-consistent redshift estimation using correlation functions without a spectroscopic reference sample

We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation redshift methods, this approach does not require a reference sample with known redshifts. By measuring the projected cross- and auto- correlations of different galaxy sub-samples, e.g., as chosen by simple cells in color-magnitude space, we are able to estimate the galaxy-dark matter bias model parameters, and the shape of the redshift distributions of each sub-sample. This method fully marginalises over a flexible parameterisation of the redshift distribution and galaxy-dark matter bias parameters of sub-samples of galaxies, and thus provides a general Bayesian framework to incorporate redshift uncertainty into the cosmological analysis in a data-driven, consistent, and reproducible manner. This result is improved by an order of magnitude by including cross-correlations with the CMB and with galaxy-galaxy lensing. We showcase how this method could be applied to real galaxies. By using idealised data vectors, in which all galaxy-dark matter model parameters and redshift distributions are known, this method is demonstrated to recover unbiased estimates on important quantities, such as the offset $\Delta_z$ between the mean of the true and estimated redshift distribution and the 68\% and 95\% and 99.5\% widths of the redshift distribution to an accuracy required by current and future surveys.Comment: 20pages, 11 figures, text revised for clarification, version accepted by journal, conclusions unchange

The Bolocam 1.1 mm Lockman Hole Galaxy Survey: SHARC II 350 micron Photometry and Implications for Spectral Models, Dust Temperatures, and Redshift Estimation

We present 350 micron photometry of all 17 galaxy candidates in the Lockman Hole detected in a 1.1 mm Bolocam survey. Several of the galaxies were previously detected at 850 microns, at 1.2 mm, in the infrared by Spitzer, and in the radio. Nine of the Bolocam galaxy candidates were detected at 350 microns and two new candidates were serendipitously detected at 350 microns (bringing the total in the literature detected in this way to three). Five of the galaxies have published spectroscopic redshifts, enabling investigation of the implied temperature ranges and a comparison of photometric redshift techniques. Lambda = 350 microns lies near the spectral energy distribution peak for z = 2.5 thermally emitting galaxies. Thus, luminosities can be measured without extrapolating to the peak from detection wavelengths of lambda > 850 microns. Characteristically, the galaxy luminosities lie in the range 1.0 - 1.2 x 10^13 L_solar, with dust temperatures in the range of 40 K to 70 K, depending on the choice of spectral index and wavelength of unit optical depth. The implied dust masses are 3 - 5 x 10^8 M_solar. We find that the far-infrared to radio relation for star-forming ULIRGs systematically overpredicts the radio luminosities and overestimates redshifts on the order of Delta z ~ 1, whereas redshifts based on either on submillimeter data alone or the 1.6 micron stellar bump and PAH features are more accurate.Comment: In Press (to appear in Astrophysical Journal, ApJ 20 May 2006 v643 1) 47 pages, 10 figures, 4 table

The Effect of Registration Errors on Tracking in a Networked Radar System

To successfully combine information from distributed radar sensors, it is essential that each sensor be correctly referenced in a global coordinate system. If there are biases in the reported position of these sensors, the reported target position will also be biased and the ensuing global estimate of the target position will be degraded. Furthermore, any biases in range or azimuth measurements of these sensors will likewise be reflected in the degradation of global estimate of target position. Registration is the process of ensuring that these errors do not result in the creation of an additional redundant target when only a single target exists. The objective of this thesis is to create a model for analyzing the impact of these biases quantitatively. The model consists of modules which perform the required coordinate conversion, tracking, and data correlation. The target tracks are provided by a standard Kalman filter assuming a constant velocity model. The measurements, state estimates, and covariance matrices obtained from the Kalman filter are combined to form a Chi-squared correlation gate. With this model, the bounds on position, range, and azimuth biases are determined individually and cumulatively. The simulated results compare favorably with the theoretically determined bounds. An additional benefit of this model is that the spatial dependence of the biases may be obtained