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Difference imaging is a technique for obtaining precise relative photometry of variable sources in crowded stellar fields and, as such, constitutes a crucial part of the data reduction pipeline in surveys for microlensing events or transiting extrasolar planets. The Optimal Image Subtraction (OIS) algorithm permits the accurate differencing of images by determining convolution kernels which, when applied to reference images of particularly good quality, provide excellent matches to the point-spread functions (PSF) in other images of the time series to be analysed. The convolution kernels are built as linear combinations of a set of basis functions, conventionally bivariate Gaussians modulated by polynomials. The kernel parameters must be supplied by the user and should ideally be matched to the PSF, pixel-sampling, and S/N of the data to be analysed. We have studied the outcome of the reduction as a function of the kernel parameters using our implementation of OIS within the TRIPP package. From the analysis of noise-free PSF simulations as well as test images from the ISIS OIS package, we derive qualitative and quantitative relations between the kernel parameters and the success of the subtraction as a function of the PSF sizes and sampling in reference and data images and compare the results to those of implementations in the literature. On this basis, we provide recommended parameters for data sets with different S/N and sampling.
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We look into the minimisation of the connection time between non-equilibrium steady states. As a prototypical example of an intrinsically non-equilibrium system, a driven granular gas is considered. For time-independent driving, its natural time scale for relaxation is characterised from an empirical -- the relaxation function -- and a theoretical -- the recently derived classical speed limits -- point of view. Using control theory, we find that bang-bang protocols -- comprising two steps, heating with the largest possible value of the driving and cooling with zero driving -- minimise the connecting time. The bang-bang time is shorter than both the empirical relaxation time and the classical speed limit: in this sense, the natural time scale for relaxation is beaten. Information theory quantities stemming from the Fisher information are also analysed over these optimal protocols. The implementation of the bang-bang processes in numerical simulations of the dynamics of the granular gas show an excellent agreement with the theoretical predictions. Moreover, general implications of our results are discussed for a wide class of driven non-equilibrium systems. Specifically, we show that analogous bang-bang protocols, with a number of bangs equal to the number of relevant physical variables, give the minimum connecting time under quite general conditions.
Visual Relationship Detection is defined as, given an image composed of a subject and an object, the correct relation is predicted. To improve the visual part of this difficult problem, ten preprocessing methods were tested to determine whether the widely used Union method yields the optimal results. Therefore, focusing solely on predicate prediction, no object detection and linguistic knowledge were used to prevent them from affecting the comparison results. Once fine-tuned, the Visual Geometry Group models were evaluated using Recall@1, per-predicate recall, activation maximisations, class activation maps, and error analysis. From this research it was found that using preprocessing methods such as the Union-Without-Background-and-with-Binary-mask (Union-WB-and-B) method yields significantly better results than the widely used Union method since, as designed, it enables the Convolutional Neural Network to also identify the subject and object in the convolutional layers instead of solely in the fully-connected layers.
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.
SN2010jl was a luminous Type IIn supernova (SN), detected in radio, optical, X-ray and hard X-rays. Here we report on its six year R- and g-band light curves obtained using the Palomar Transient Factory. The light curve was generated using a pipeline based on the proper image subtraction method and we discuss the algorithm performances. As noted before, the R-band light curve, up to about 300 days after maximum light is well described by a power-law decline with a power-law index of about -0.5. Between day 300 and day 2300 after maximum light, it is consistent with a power-law decline, with a power-law index of about -3.4. The longevity of the light curve suggests that the massive circum-stellar material around the progenitor was ejected on time scales of at least tens of years prior to the progenitor explosion.
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