Galaxy blending effects in deep imaging cosmic shear probes of cosmology

Upcoming deep imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will be confronted with challenges that come with increased depth. One of the leading systematic errors in deep surveys is the blending of objects due to higher surface density in the more crowded images; a considerable fraction of the galaxies which we hope to use for cosmology analyses will overlap each other on the observed sky. In order to investigate these challenges, we emulate blending in a mock catalogue consisting of galaxies at a depth equivalent to 1.3 years of the full 10-year Rubin Observatory that includes effects due to weak lensing, ground-based seeing, and the uncertainties due to extraction of catalogues from imaging data. The emulated catalogue indicates that approximately 12% of the observed galaxies are "unrecognized" blends that contain two or more objects but are detected as one. Using the positions and shears of half a billion distant galaxies, we compute shear-shear correlation functions after selecting tomographic samples in terms of both spectroscopic and photometric redshift bins. We examine the sensitivity of the cosmological parameter estimation to unrecognized blending employing both jackknife and analytical Gaussian covariance estimators. A $\sim0.02$ decrease in the derived structure growth parameter $S_8 = \sigma_8 (\Omega_{\rm m}/0.3)^{0.5}$ is seen due to unrecognized blending in both tomographies with a slight additional bias for the photo-$z$-based tomography. This bias is about 2$\sigma$ statistical error in measuring $S_8$.Comment: 22 pages, 23 figures. This paper has undergone internal review in the LSST DESC. Submitted to MNRA

Observational Challenges in Deep Imaging Probes of Cosmology

Upcoming deep imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will be confronted with challenges that come with increased depth. One of the leading systematic errors in deep surveys is the blending of objects due to higher surface density in the more crowded images; a considerable fraction of the galaxies which we hope to use for cosmology analyses will overlap each other on the observed sky. In order to investigate these challenges, we emulate blending in a mock catalog consisting of galaxies at a depth equivalent to 1.3 years of the full 10-year Rubin Observatory, a limitation imposed by the available mock data. This catalog includes effects due to weak lensing, ground-based seeing, and the uncertainties due to extraction of catalogs from imaging data. The emulated catalog indicates that approximately 12 percent of the observed galaxies are ``unrecognized'' blends that contain two or more objects but are detected as one. Using observable quantities from over half a billion galaxies, we compute shear--shear, position--position, and position--shear correlation functions after selecting tomographic samples in terms of both spectroscopic and photometric redshift bins. We examine the sensitivity of the cosmological parameter estimation to unrecognized blending employing both jackknife and analytical Gaussian covariance estimators. In both cosmic shear-only and combined clustering and weak lensing analyses, a $\sim0.025$ decrease in the derived structure growth parameter $S_8 = \sigma_8 (\Omega_{\rm m}/0.3)^{0.5}$ is seen due to unrecognized blending in both tomographies with a slight additional bias for the photo-$z$-based tomography. This decrease of $0.025$ is greater than the $2\sigma$ statistical error in measuring $S_8$. The systematic error is therefore on the same order as the statistical error. As the statistical error is expected to decrease in the future with a full 10-year dataset, the impact of the systematic error will get comparatively worse, necessitating corrections

A collection of the novel coronavirus (COVID-19) detection assays, issues, and challenges

The global pandemic of COVID-19 has rapidly increased the number of infected cases as well as asymptomatic individuals in many, if not all the societies around the world. This issue increases the demand for accurate and rapid detection of SARS-CoV-2. While accurate and rapid detection is critical for diagnosing SARS-CoV-2, the appropriate course of treatment must be chosen to help patients and prevent its further spread. Testing platform accuracy with high sensitivity and specificity for SARS-CoV-2 is equally important for clinical, regional, and global arenas to mitigate secondary transmission rounds. The objective of this article is to compare the current detection technology and introduce the most accurate and rapid ones that are suitable for pandemic circumstances. Hence, the importance of rapid detection in societies is discussed initially. Following this, the current technology for rapid detection of SARS-CoV-2 is explained and classified into three different categories: nucleic acid-based, protein-based, and point of care (PoC) detection testing. Then, the current issues for diagnostic procedures in laboratories are discussed. Finally, the role of new technologies in countering COVID-19 is also introduced to assist researchers in the development of accurate and timely detection of coronaviruses. As coronavirus continues to affect human lives in a detrimental manner, the development of rapid and accurate virus detection methods could promote COVID-19 diagnosis accessible to both individuals and the mass population at patient care. In this regard, rRT-PCR and multiplex RT-PCR detection techniques hold promise

Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/

Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope

94 pages, 22 figures, 1 tableAstrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/

Dark Matter Science in the Era of LSST

Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental efforts, while simultaneously probing unique regions of dark matter parameter space. This white paper summarizes astrophysical observations that can constrain the fundamental physics of dark matter in the era of LSST. We describe how astrophysical observations will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational interactions with the Standard Model, and compact object abundances. Additionally, we highlight theoretical work and experimental/observational facilities that will complement LSST to strengthen our understanding of the fundamental characteristics of dark matter