A method for optimal image subtraction

We present a new method designed for optimal subtraction of two images with different seeing. Using image subtraction appears to be essential for the full analysis of the microlensing survey images, however a perfect subtraction of two images is not easy as it requires the derivation of an extremely accurate convolution kernel. Some empirical attempts to find the kernel have used the Fourier transform of bright stars, but solving the statistical problem of finding the best kernel solution has never really been tackled. We demonstrate that it is possible to derive an optimal kernel solution from a simple least square analysis using all the pixels of both images, and also show that it is possible to fit the differential background variation at the same time. We also show that PSF variations can also be easily handled by the method. To demonstrate the practical efficiency of the method, we analyzed some images from a Galactic Bulge field monitored by the OGLE II project. We find that the residuals in the subtracted images are very close to the photon noise expectations. We also present some light curves of variable stars, and show that, despite high crowding levels, we get an error distribution close to that expected from photon noise alone. We thus demonstrate that nearly optimal differential photometry can be achieved even in very crowded fields. We suggest that this algorithm might be particularly important for microlensing surveys, where the photometric accuracy and completeness levels could be very significantly improved by using this method.Comment: 8,pages, 4 Postscript figures, emulateapj.sty include

Digital computer processing of X-ray photographs

Enhanced digital computer processing of X-ray photographs by image subtraction or filterin

Real time image subtraction and "exclusive or" operation using a self-pumped phase conjugate mirror

Real time "exclusive or" operation with an interferometer using a self-pumped phase conjugate mirror is reported. Also, results of image subtraction and intensity inversion are shown

Photometry of SN 2002bo with template image subtraction

VRI photometry of the type Ia supernova 2002bo is presented. This SN exploded in a dusty region of the host galaxy NGC 3190, thus, subtraction of a template frame was necessary to obtain reliable photometry. We used a template frame of NGC 3190 taken during the course of our galaxy imaging project, fortunately, just a few days before SN 2002bo was discovered. The aim of this project is to collect template frames of nearby galaxies that are potential hosts of bright SNe. Subtraction of pre-SN images helped us to exclude the background light contamination of the host galaxy. The maximum occurred at JD 2452346, with maximal V brightness of 13.58. MLCS analysis led to T0(B)=JD 2452346.1 pm 0.8 (fiducial B-maximum), E(B-V)=0.24 pm 0.02, mu0=32.46 pm 0.06, Delta=-0.14 pm 0.04. E(B-V)=0.24(2) indicates a significant extinction in the host galaxy as the galactic reddening is negligible toward NGC 3190. The accepted value of Delta indicates that SN 2002bo was a slightly overluminous SN by about 0.14 relative to fiducial SN Type Ia. The distance turned out to be 31.0 pm 3 Mpc. In addition, the heavily obscured SN 2002cv was also detected on the I frame taken on JD 2452434 (June 8, 2002), and a variable star is found in the field, very close to the host galaxy.Comment: accepted by Astronomy and Astrophysic

Intermediate Palomar Transient Factory: Realtime Image Subtraction Pipeline

A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting follow-up observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using high-performance computing, efficient database, and machine learning algorithms, this pipeline manages to reliably deliver transient candidates within ten minutes of images being taken. Our experience in using high performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in near future.Comment: 18 pages, 6 figures, accepted for publication in PAS

Digital computer processing of X-ray photos

Digital computers correct various distortions in medical and biological photographs. One of the principal methods of computer enhancement involves the use of a two-dimensional digital filter to modify the frequency spectrum of the picture. Another computer processing method is image subtraction