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Andy Connolly

Publications and source records attributed to Andy Connolly.

5 recordsLinked to original sources

The Cross-Survey Decade: A Call to Action

By 2027, three flagship wide-field surveys will be operating simultaneously from ground and space, observing overlapping sky and representing more than $6 billion in US and European public investment. Together they will produce overlapping petabyte-scale datasets across thousands of square degrees. This is a different class of challenge: the observations are no longer the bottleneck; realizing their joint scientific return now depends on shared computational infrastructure and coordination. Decades of community studies show that combining these datasets does more than improve precision. For science ranging from weak lensing to transient discovery and Galactic-plane astronomy, joint processing and analysis can unlock capabilities no single survey provides alone. Yet the required infrastructure -- joint pixel-level processing, cross-calibration and validation, interoperable data access, and the people to build and sustain it -- falls outside any single mission or institution's mandate. We issue a call to action for cross-survey science infrastructure, built around four pillars: (1) joint pixel-level processing and validation; (2) an AI-ready data substrate for scientific foundation models; (3) standardized, interoperable data access across surveys, democratizing participation in astrophysical discovery; and (4) dedicated personnel and career pathways. We outline concrete steps for policymakers, agencies, observatories, universities, the research community, and philanthropy, and argue that the moment to act is now, while foundational technical choices can still be aligned at a fraction of the cost of reconciling them later.

astro-ph.IM

Science-Driven Optimization of the LSST Observing Strategy

The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation. However, exactly how the LSST observations will be taken (the observing strategy or "cadence") is not yet finalized. In this dynamically-evolving community white paper, we explore how the detailed performance of the anticipated science investigations is expected to depend on small changes to the LSST observing strategy. Using realistic simulations of the LSST schedule and observation properties, we design and compute diagnostic metrics and Figures of Merit that provide quantitative evaluations of different observing strategies, analyzing their impact on a wide range of proposed science projects. This is work in progress: we are using this white paper to communicate to each other the relative merits of the observing strategy choices that could be made, in an effort to maximize the scientific value of the survey. The investigation of some science cases leads to suggestions for new strategies that could be simulated and potentially adopted. Notably, we find motivation for exploring departures from a spatially uniform annual tiling of the sky: focusing instead on different parts of the survey area in different years in a "rolling cadence" is likely to have significant benefits for a number of time domain and moving object astronomy projects. The communal assembly of a suite of quantified and homogeneously coded metrics is the vital first step towards an automated, systematic, science-based assessment of any given cadence simulation, that will enable the scheduling of the LSST to be as well-informed as possible.

astro-ph.IM

Image Coaddition with Temporally Varying Kernels

Large, multi-frequency imaging surveys, such as the Large Synaptic Survey Telescope (LSST), need to do near-real time analysis of very large datasets. This raises a host of statistical and computational problems where standard methods do not work. In this paper, we study a proposed method for combining stacks of images into a single summary image, sometimes referred to as a template. This task is commonly referred to as image coaddition. In part, we focus on a method proposed in previous work, which outlines a procedure for combining stacks of images in an online fashion in the Fourier domain. We evaluate this method by comparing it to two straightforward methods through the use of various criteria and simulations. Note that the goal is not to propose these comparison methods for use in their own right, but to ensure that additional complexity also provides substantially improved performance.

astro-ph.IM

Analysis of Systematic Effects and Statistical Uncertainties in Angular Clustering of Galaxies from Early SDSS Data

The angular distribution of galaxies encodes a wealth of information about large scale structure. Ultimately, the Sloan Digital Sky Survey (SDSS) will record the angular positions of order 10^8 galaxies in five bands, adding significantly to the cosmological constraints. This is the first in a series of papers analyzing a rectangular stripe 2.5x90 degrees from early SDSS data. We present the angular correlation function for galaxies in four separate magnitude bins on angular scales ranging from 0.003 degrees to 15 degrees. Much of the focus of this paper is on potential systematic effects. We show that the final galaxy catalog -- with the mask accounting for regions of poor seeing, reddening, bright stars, etc. -- is free from external and internal systematic effects for galaxies brighter than r* = 22. Our estimator of the angular correlation function includes the effects of the integral constraint and the mask. The full covariance matrix of errors in these estimates is derived using mock catalogs with further estimates using a number of other methods.

astro-ph

Fast Algorithms and Efficient Statistics: N-point Correlation Functions

We present here a new algorithm for the fast computation of N-point correlation functions in large astronomical data sets. The algorithm is based on kdtrees which are decorated with cached sufficient statistics thus allowing for orders of magnitude speed-ups over the naive non-tree-based implementation of correlation functions. We further discuss the use of controlled approximations within the computation which allows for further acceleration. In summary, our algorithm now makes it possible to compute exact, all-pairs, measurements of the 2, 3 and 4-point correlation functions for cosmological data sets like the Sloan Digital Sky Survey (SDSS; York et al. 2000) and the next generation of Cosmic Microwave Background experiments (see Szapudi et al. 2000).

astro-ph