Related papers: Conference summary: Workshop on Precision Astronom…
Charge-transfer loss on the Wide Field Planetary Camera 2 (WFPC2) onboard the Hubble Space Telescope is a primary source of uncertainty in stellar photometry obtained with this camera. This effect, discovered shortly after the camera was…
Deep learning has achieved significant breakthroughs in medical imaging, but these advancements are often dependent on large, well-annotated datasets. However, obtaining such datasets poses a significant challenge, as it requires…
Much of the science case for the next generation of deep, wide-field optical/infrared surveys has been driven by the further study of dark energy. This is a laudable goal (and the subject of a companion white paper by Zhan et al.). However,…
Radio maps provide metrics such as power spectral density for every location in a geographic area and find numerous applications such as UAV communications, interference control, spectrum management, resource allocation, and network…
The cosmological power spectrum of the coherent matter flow is measured exploiting an improved prescription for the apparent anisotropic clustering pattern in redshift space. New statistical analysis is presented to provide an optimal…
Astronomical observations typically provide three-dimensional maps, encoding the distribution of the observed flux in (1) the two angles of the celestial sphere and (2) energy/frequency. An important task regarding such maps is to…
Defect conformal field theories (dCFTs) have been attracting increased attention recently, mainly because they enable us to bridge the gap between idealistic, highly symmetric models of our world (such as the particle/string duality) and…
We present the photometric calibration of the HST Advanced Camera for Surveys (ACS). We give here an overview of the performance and calibration of the 2 CCD cameras, the Wide Field Channel (WFC) and the High Resolution Channel (HRC), and a…
This talk presents a pedagogical discussion of how precision distance-redshift observations can map out the recent expansion history of the universe, including the present acceleration and the transition to matter dominated deceleration.…
The complexity and accuracy of current and future precision cosmology observational campaigns has made it essential to develop an efficient technique for directly combining simulation and observational datasets to determine cosmological and…
This research aims to explore the application of deep learning in autonomous driving computer vision technology and its impact on improving system performance. By using advanced technologies such as convolutional neural networks (CNN),…
The potential of cosmic shear to probe cosmology is well recognized and future optical wide field surveys are currently being designed to optimize the return of cosmic shear science. High precision cosmic shear analysis requires high…
Deeper understanding of the properties of dark energy via SNIa surveys, and to a large extent other methods as well, will require unprecedented photometric precision. Laboratory and solar photometry and radiometry regularly achieve…
We have designed and built a new type of CCD that we call an orthogonal transfer CCD (OTCCD), which permits parallel clocking horizontally as well as vertically. The device has been used successfully to remove image motion caused by…
Aberration-corrected scanning transmission electron microscopes (STEM) provide sub-angstrom lateral resolution; however, the large convergence angle greatly reduces the depth of field. For microscopes with a small depth of field,…
Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagation and attenuation, perspective viewing geometry and…
Charge-coupled devices (CCDs) are widely used in astronomy to carry out a variety of measurements, such as for flux or shape of astrophysical objects. The data reduction procedures almost always assume that ther esponse of a given pixel to…
Semantic segmentation of raw 3D point clouds is an essential component in 3D scene analysis, but it poses several challenges, primarily due to the non-Euclidean nature of 3D point clouds. Although, several deep learning based approaches…
Complete depth information and efficient estimators have become vital ingredients in scene understanding for automated driving tasks. A major problem for LiDAR-based depth completion is the inefficient utilization of convolutions due to the…
This review aims at proposing to the field an overview of the Cusp-core problem, including a discussion of its advocated solutions, assessing how each can satisfactorily provide a description of central densities. Whether the Cusp-core…