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The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will detect an unprecedentedly large sample of actively accreting supermassive black holes with typical accretion disk (AD) sizes of a few light days. This brings us to face challenges in the reverberation mapping (RM) measurement of AD sizes in active galactic nuclei (AGNs) using interband continuum delays. We examine the effect of LSST cadence strategies on AD RM using our metric AGNTimeLagMetric. It accounts for redshift, cadence, the magnitude limit, and magnitude corrections for dust extinction. Running our metric on different LSST cadence strategies, we produce an atlas of the performance estimations for LSST photometric RM measurements. We provide an upper limit on the estimated number of quasars for which the AD time lag can be computed within 01000 sources in each Deep Drilling field (DDF, 10 sq. deg) in any filter, with the redshift distribution of these sources peaking at z~1. We find the LSST observation strategies with a good cadence (~ 5 days) and a long cumulative season (~9 yr), as proposed for LSST DDF, are favored for the AD size measurement. We create synthetic LSST light curves for the most suitable DDF cadences and determine RM time lags to demonstrate the impact of the best cadences based on the proposed metric., Comment: accepted for publication in the Astrophysical Journal Focus Issue on Rubin LSST cadence and survey strategy

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science., Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" workshop

The upcoming photometric surveys, such as the Rubin Observatory's Legacy Survey of Space and Time (LSST) will monitor unprecedented number of active galactic nuclei (AGN) in a decade long campaign. Motivated by the science goals of LSST, which includes the harnessing of broadband light curves of AGN for photometric reverberation mapping (PhotoRM), we implement the existing formalism to estimate the lagged response of the emission line flux to the continuum variability using only mutli-band photometric light curves. We test the PhotoRM method on a set of 19 artificial light curves simulated using a stochastic model based on the Damped Random Walk process. These light curves are sampled using different observing strategies, including the two proposed by the LSST, in order to compare the accuracy of time-lag retrieval based on different observing cadences. Additionally, we apply the same procedure for time-lag retrieval to the observed photometric light curves of NGC 4395, and compare our results to the existing literature., Comment: The manuscript was accepted for publication in the Astronomische Nachrichten Special Issue

The consequences of complex disturbed environments in the vicinity of a supermassive black hole are not well represented by standard statistical models of optical variability in active galactic nuclei (AGN). Thus, developing new methodologies for investigating and modeling AGN light curves is crucial. Conditional Neural Processes (CNPs) are nonlinear function models that forecast stochastic time-series based on a finite amount of known data without the use of any additional parameters or prior knowledge (kernels). We provide a CNP algorithm that is specifically designed for simulating AGN light curves. It was trained using data from the All-Sky Automated Survey for Supernovae, which included 153 AGN. We present CNP modeling performance for a subsample of five AGNs with distinctive difficult-to-model properties. The performance of CNP in predicting temporal flux fluctuation was assessed using a minimizing loss function, and the results demonstrated the algorithm's usefulness. Our preliminary parallelization experiments show that CNP can efficiently handle large amounts of data. These results imply that CNP can be more effective than standard tools in modeling large volumes of AGN data (as anticipated from time-domain surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time)., Comment: The manuscript was accepted for publication in the Astronomische Nachrichten Special Issue

Motivated by upcoming photometric and spectroscopic surveys (Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Manuakea Spectroscopic Explorer), we design the statistical proxies to measure the cadence effects on active galactic nuclei (AGN) variability-observables (time-lags, periodicity, and structure-function (SF)). We constructed a multiple-regression model to statistically identify the cadence-formal error pattern knowing AGN time-lags and periodicity from different surveys. We defined the simple metric for the SF's properties, accounting for the 'observed' SF's deviation relative to those obtained from the homogenously-sampled light curves. We tested the regression models on different observing strategies: the optical dataset of long light-curves of eight AGN with peculiarities and the artificial datasets based on several idealized and LSST-like cadences. The SFs metric is assessed on synthetic datasets. The regression models (for both data types) predict similar cadences for time-lags and oscillation detection, whereas for light curves with low variability ($\sim 10\%$), cadences for oscillation detection differ. For higher variability ($\sim20\%$), predicted cadences are larger than for $F_{var}\sim 10\%$. The predicted cadences are decreasing with redshift. SFs with dense and homogenous cadences are more likely to behave similarly. SFs with oscillatory signals are sensitive to the cadences, possibly impacting LSST-like operation strategy. The proposed proxies can help to select spectroscopic and photometric-surveys cadence strategies, and they will be tested further in larger samples of objects., Comment: accepted for publication in the MNRAS

We have developed two metrics related to AGN variability observables (time-lags, periodicity, and Structure Function (SF)) to evaluate LSST OpSim FBS 1.5, 1.6, 1.7 performance in AGN time-domain analysis. For this purpose, we generate an ensemble of AGN light curves based on AGN empirical relations and LSST OpSim cadences. Although our metrics show that denser LSST cadences produce more reliable time-lag, periodicity, and SF measurements, the discrepancies in the performance between different LSST OpSim cadences are not drastic based on Kullback-Leibler divergence. This is complementary to Yu and Richards results on DCR and SF metrics, extending them to include the point of view of AGN variability., Comment: Cadence Notes AGN and TVS SC

The Karma asteroid family is a group of primitive asteroids in the middle part of the main belt, just at the outer edge of the 3J:1A mean-motion resonance. We obtained the list of the family members with 317 asteroids and estimated that it was formed by the catastrophic disruption of a parent body that was between 34 and 41 km in diameter. Based on the V-shape method, age of the Karma family is estimated to be about 137 Myr. A detailed dynamical map of the region combined with numerical simulations allowed us to reconstruct the long-term dynamical evolution of the family, and to identify the mechanisms responsible for this evolution. The numerical simulations successfully reproduced the main features in the orbital distribution of the family members but also showed that some regions of the Karma family could be missing. A more detailed analysis revealed that these regions likely consist of very dark objects, fainter than absolute magnitude H = 17, that have not yet been detected. Based on the obtained results, we concluded that magnitude-frequency distribution of family members up to H = 16 mag is neither affected by dynamical erosion nor observational incompleteness and therefore represents the result of collisional grinding of the original family population. Finally, we found that the Karma family have been supplying some asteroids to the near-Earth region via the 3J:1A resonance. Currently, there should about 10 family members larger than 1 km in diameter, orbiting in the near-Earth space., Comment: 12 pages, 13 Postscript figures, accepted for publication in MNRAS

A specially interesting subgroup of asteroid families are young ones, i.e. those formed less than 10 Myrs ago. They have attracted a lot of attention since the first such family has been discovered in 2002. About 20 young families have been discovered so far, but new discoveries are still very important. Here we report discovery of four new young asteroid families. Three of them are located in the inner asteroid belt, namely the (525) Adelaide, (6142) Tantawi and (18429) 1994AO1, while the family of (2258) Viipuri is located in the middle part of the asteroid belt.

We applied the theory of regularly varying functions to the analysis of the cosmological parameters for the $\Lambda$CDM model with the matter dominated evolution. Carroll et al. proved in 1992 that for this type of universe with the curvature $k=0, -1$, the expression $H(t)t$\, ($H(t)$ is the Hubble parameter) depends solely on the density parameter $\Omega(t)$. Using this result and the theory of regular variation we infer for such universe the complete asymptotics of all main cosmological parameters. More specifically, the following is derived. If the limit $\omega= \lim_{t\to\infty} \Omega(t)$ does exist and $\omega \not= 0$ then the cosmological constant $\Lambda$ is equal to $0$. If $\omega=0$ then for the expansion scale factor $a(t)$ we have $a(t)\sim e^{\sqrt{\Lambda/3}}$. On the other hand, if the limit $\lim_{t\to\infty} \Omega(t)$ does not exist then $a(t)$ bounces between two power functions and therefore has infinitely many flexion points. Hence, the deceleration parameter in this case changes the sign infinitely many times., Comment: 20 pages, 4 figures. In revised version: Added new coauthor Viktor Radovi\'c ; Added several new references; Corrected typos; Completely revised section 3.1 and a new result added: if \Omega\ converges to a non-zero value then the Cosmological constant \Lambda\ must be equal 0