We discuss the system requirements for obtaining millimagnitude photometric precision over a wide field using small‐aperture, short focal length telescope systems such as those being developed by a number of research groups to search for transiting extrasolar planets. We describe a Hungarian Automated Telescope (HAT) system, which attempts to meet these requirements. The attainable precision of HAT has been significantly improved by a technique in which the telescope is made to execute small pointing steps during each exposure so as to broaden the effective point‐spread function (PSF) of the system to a value more compatible with the pixel size of our CCD detector. Experiments during a preliminary survey (spring 2003) of two star fields with the HAT‐5 instrument allowed us to optimize the HAT photometric precision using this method of PSF broadening; in this way we have been able to achieve a precision as good as 2 mmag on brighter stars. We briefly describe development of a network of longitudin...

https://iopscience.iop.org/article/10.1086/382735/pdf

Wide‐Field Millimagnitude Photometry with the HAT: A Tool for Extrasolar Planet Detection

1. The formulation of conservation policy relies heavily on demographic, biological and ecological knowledge that is often elusive for threatened species. Essential estimates of abundance, survival and life-history parameters are accessible through mark and recapture studies given a sufficiently large sample. Photographic identification of individuals is an established mark and recapture technique, but its full potential has rarely been exploited because of the unmanageable task of making visual identifications in large data sets. 2. We describe a novel technique for identifying individual whale sharks Rhincodon typus through numerical pattern matching of their natural surface 'spot' colourations. Together with scarring and other markers, spot patterns captured in photographs of whale shark flanks have been used, in the past, to make identifications by eye. We have automated this process by adapting a computer algorithm originally developed in astronomy for the comparison of star patterns in images of the night sky. 3. In tests using a set of previously identified shark images, our method correctly matched pairs exhibiting the same pattern in more than 90% of cases. From a larger library of previously unidentified images, it has to date produced more than 100 new matches. Our technique is robust in that the incidence of false positives is low, while failure to match images of the same shark is predominantly attributable to foreshortening in photographs obtained at oblique angles of more than 30°. 4. We describe our implementation of the pattern-matching algorithm, estimates of its efficacy, its incorporation into the new ECOCEAN Whale Shark Photo-identification Library, and prospects for its further refinement. We also comment on the biological and conservation implications of the capability of identifying individual sharks across wide geographical and temporal spans. 5. Synthesis and applications. An automated photo-identification technique has been developed that allows for efficient 'virtual tagging' of spotted animals. The pattern-matching software has been implemented within a Web-based library created for the management of generic encounter photographs and derived data. The combined capabilities have demonstrated the reliability of whale shark spot patterns for long-term identifications, and promise new ecological insights. Extension of the technique to other species is anticipated, with attendant benefits to management and conservation through improved understanding of life histories, population trends and migration routes, as well as ecological factors such as exploitation impact and the effectiveness of wildlife reserves.

An astronomical pattern-matching algorithm for computer-aided identification of whale sharks Rhincodon typus

An autonomous star identification algorithm is described that is simple and requires less computer resources than other such algorithms. In simulations using an 8/spl times/8 degree field of view (FOV), the algorithm identifies the correct section of sky on 99.7% of the sensor orientations where spatial accuracy of the imaged star is 1 pixel (56.25 arc seconds) in standard deviation and the apparent brightness deviates by 0.4 units stellar magnitude. This compares very favorably with other algorithms in the literature.

A grid algorithm for autonomous star identification

https://groups.physics.ox.ac.uk/genemachines/group/SH_TIRF_BiophyJ.pdf

Defining the Limits of Single-Molecule FRET Resolution in TIRF Microscopy

The eXtreme Deep Field (XDF) combines data from ten years of observations with the HST Advanced Camera for Surveys (ACS) and the Wide-Field Camera 3 Infra-Red (WFC3/IR) into the deepest image of the sky ever in the optical/near-IR. Since the initial observations on the Hubble Ultra-Deep Field (HUDF) in 2003, numerous surveys and programs, including supernova followup, HUDF09, CANDELS, and HUDF12 have contributed additional imaging data across the HUDF region. Yet these have never been combined and made available as one complete ultra-deep optical and near-infrared image dataset. We do so now for the eXtreme Deep Field (XDF) program. Our new and improved processing techniques provide higher quality reductions of the total dataset. All WFC3 near-IR and optical ACS data sets have been fully combined and accurately matched, resulting in the deepest imaging ever taken at these wavelengths ranging from 29.1 to 30.3 AB mag (5sigma in a 0.35" diameter aperture) in 9 filters. The gains in the optical for the four filters done in the original ACS HUDF correspond to a typical improvement of 0.15 mag, with gains of 0.25 mag in the deepest areas. Such gains are equivalent to adding ~130 to ~240 orbits of ACS data to the HUDF. Improved processing alone results in a typical gain of ~0.1 mag. Our 5sigma (optical+near-IR) SExtractor catalogs reveal about 14140 sources in the full field and about 7121 galaxies in the deepest part of the XDF (the HUDF09 region). The XDF is the deepest image of the universe ever taken, reaching, in the combined image for a flat f_nu source, to 31.2 AB mag 5sigma (32.9 at 1sigma) in a 0.35" diameter aperture.

E. J. Groth

Papers

A pattern-matching algorithm for two-dimensional coordinate lists. [for stellar positions