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William O'Mullane

Publications and source records attributed to William O'Mullane.

At least 19 recordsLinked to original sources
arXiv2026

Modeling of the diffuse background produced by the Vera C. Rubin Observatory M2 baffle scattered light

The Vera C. Rubin Observatory, with its unprecedented field of view and fast focal ratio, will survey the entire sky every 3.5 nights. This unique capacity requires dealing with off axis light that can produce stray light artefacts on the images. The secondary mirror (M2) baffle restricts the light that reaches the LSSTCam detector and it contributes to shaping the inner edge of the telescope optical pupil. This work studies the contribution to the background from the light scattered by the M2 baffle itself. The evanescence of this feature, together with the challenge of isolating it from the sky background, led to the necessity of performing in dome tests using a Collimated Beam Projector (CBP), normally used for calibration purposes. To complete the analysis, in addition to the in dome tests, an on sky observational campaign was conducted. This campaign employed both stellar targets and the Moon as illumination sources in order to determine the actual energy associated with the feature. The test data have been retro fitted thanks to the combination of ray tracing simulation, CBP and on sky data to infer the intensity and spatial distribution of the background scattered light within the different LSSTCam filters. We quantified the on sky impact of scattered light from the M2 baffle, both for light coming from bright and red stars and from the Moon. We also developed an approximate relation to transform the in dome measurements into predictions of on sky behavior. This transformation was achieved by comparing the illumination footprint produced by an off axis star with that generated by the CBP and by mapping the stellar Spectral Energy Distribution (SED) onto the CBP's set of discrete wavelengths. Finally, we extrapolated the scattered light behavior of the Moon to stellar sources, in order to build a compplete description of the M2 baffle contribution over the full range of magnitudes.

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arXiv2026

An overview of stray light findings and interpretation during on-sky commissioning of LSSTCam

Wide-field telescopes are intrinsically difficult to shield from unwanted stray and scattered light, while the search to identify sources of contaminating light is frequently a challenging task. The Vera C.~Rubin Observatory, which achieved its first photon with the LSST Camera (LSSTCam) on April 15, 2025, will initiate a revolutionary era for the study of dark matter, dark energy, the transient sky, the Solar System, and the Milky Way. LSSTCam will provide near seeing-limited images of the sky in six bands ($u,g,r,i,z,y$) over a $3.^\circ 5$-diameter field of view, and over the course of a decade, it will execute the Legacy Survey of Space and Time (LSST). This work provides an overview of the dedicated stray and scattered light test campaign that has been undertaken since the start of Rubin commissioning. In particular, we highlight the processes used to characterize, model, and mitigate stray light present in LSSTCam images. The Rubin commissioning team created a series of testing and analysis tools to track stray light artifacts from their initial discovery through reproduction with timely observations, simulation using ray tracing to identify opto-mechanical origins, and finally devising corrective actions. The complex stray light features encountered by Rubin provide a wealth of experience for the future wide-field and extremely wide-field observatories. This work covers the many stages of a long journey that started with conceiving an innovative and challenging optical design, followed by the engineering and system engineering efforts to build it, to finally delivering an optimized and revolutionary cutting-edge facility.

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arXiv2023

The Future of Astronomical Data Infrastructure: Meeting Report

The astronomical community is grappling with the increasing volume and complexity of data produced by modern telescopes, due to difficulties in reducing, accessing, analyzing, and combining archives of data. To address this challenge, we propose the establishment of a coordinating body, an "entity," with the specific mission of enhancing the interoperability, archiving, distribution, and production of both astronomical data and software. This report is the culmination of a workshop held in February 2023 on the Future of Astronomical Data Infrastructure. Attended by 70 scientists and software professionals from ground-based and space-based missions and archives spanning the entire spectrum of astronomical research, the group deliberated on the prevailing state of software and data infrastructure in astronomy, identified pressing issues, and explored potential solutions. In this report, we describe the ecosystem of astronomical data, its existing flaws, and the many gaps, duplication, inconsistencies, barriers to access, drags on productivity, missed opportunities, and risks to the long-term integrity of essential data sets. We also highlight the successes and failures in a set of deep dives into several different illustrative components of the ecosystem, included as an appendix.

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arXiv2022

Software Architecture and System Design of Rubin Observatory

Starting from a description of the Rubin Observatory Data Management System Architecture, and drawing on our experience with and involvement in a range of other projects including Gaia, SDSS, UKIRT, and JCMT, we derive a series of generic design patterns and lessons learned.

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arXiv2022

From Data to Software to Science with the Rubin Observatory LSST

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.

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arXiv2021

Rubin Science Platform on Google: the story so far

We describe Rubin Observatory's experience with offering a data access facility (and associated services including our Science Platform) deployed on Google Cloud infrastructure as part of our pre-Operations Data Preview program.

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arXiv2020

Cost Management on Commercial Cloud Platforms

Commercial cloud platforms are a powerful technology for astronomical research. Despite the benefits of cloud computing -- such as on-demand scalability and reduction of systems management overhead -- confusion over how to manage costs remains, for many, one of the biggest barriers to entry. This confusion is exacerbated by the rapid growth in services offered by commercial providers, by the growth in the number of these providers, and by storage, compute, and I/O metered at separate rates -- all of which can change without notice. As a rule, processing is very cheap, storage is more expensive, and downloading is very expensive. Thus, an application that produces large image data sets for download will be far more expensive than an application that performs extensive processing on a small data set. This Birds of a Feather (BoF) session aimed to quantify the above statement by presenting case studies of the costing of astronomy applications on commercial clouds that covered a range of processing scenarios; these presentations were the basis for discussion by the attendees.

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arXiv2019

The demise of the filesystem and multi level service architecture

Many astronomy data centres still work on filesystems. Industry has moved on; current practice in computing infrastructure is to achieve Big Data scalability using object stores rather than POSIX file systems. This presents us with opportunities for portability and reuse of software underlying processing and archive systems but it also causes problems for legacy implementations in current data centers.

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arXiv2019

Future Uses of the LSST Facility: Input from the LSST Project Science Team

In this white paper, we discuss future uses of the LSST facility after the planned 10-year survey is complete. We expect the LSST survey to profoundly affect the scientific landscape over the next ten years, and it is likely that unexpected discoveries may drive its future scientific program. We discuss various operations and instrument options that could be considered for an extended LSST mission beyond ten years.

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arXiv2019

Astro2020 APC White Paper: Astronomy should be in the clouds

Commodity cloud computing, as provided by commercial vendors such as Amazon, Google, and Microsoft, has revolutionized computing in many sectors. With the advent of a new class of big data, public access astronomical facility such as LSST, DKIST, and WFIRST, there exists a real opportunity to combine these missions with cloud computing platforms and fundamentally change the way astronomical data is collected, processed, archived, and curated. Making these changes in a cross-mission, coordinated way can provide unprecedented economies of scale in personnel, data collection and management, archiving, algorithm and software development and, most importantly, science.

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arXiv2018

An Overview of the LSST Image Processing Pipelines

The Large Synoptic Survey Telescope (LSST) is an ambitious astronomical survey with a similarly ambitious Data Management component. Data Management for LSST includes processing on both nightly and yearly cadences to generate transient alerts, deep catalogs of the static sky, and forced photometry light-curves for billions of objects at hundreds of epochs, spanning at least a decade. The algorithms running in these pipelines are individually sophisticated and interact in subtle ways. This paper provides an overview of those pipelines, focusing more on those interactions than the details of any individual algorithm.

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arXiv2017

Gaia TGAS search for Large Magellanic Cloud runaway supergiant stars:Candidate hypervelocity star discovery, and the nature of R71

We search for runaway stars in the Large Magellanic Cloud (LMC) by computing the space velocities of the visually brightest stars in the LMC that are included in the Gaia TGAS proper motion catalog. We compare with predictions from stellar dynamical models to obtain (peculiar) velocities relative to their local stellar environment. Two of the 31 stars have unusually high proper motions. Of the remaining 29 stars we find that most objects in this sample have velocities in very good agreement with model predictions of a circularly rotating disk model. Indeed the excellent fit to the model implies that the TGAS uncertainty estimates are likely overestimated. The fastest outliers in this subsample contain the LBV R71 and a few other well known emission line objects though in no case do we derive velocities consistent with fast (~100 km/s) runaways. Our results imply that R 71 in particular has a moderate deviation from the local stellar velocity field (40 km/s) lending support to the proposition that this object cannot have evolved as a normal single star since it lies too far from massive star forming complexes to have arrived at its current position during its lifetime. Our findings therefore strengthen the case for this LBV being the result of binary evolution. Of the two stars with unusually high proper motions we find that one, the isolated B1.5 Ia+ supergiant Sk-67 2 (HIP 22237), is a candidate hypervelocity star, the TGAS proper motion implying a very large peculiar transverse velocity (~360 km/s) directed radially away from the LMC centre. If confirmed, for example by Gaia Data Release 2, it would imply that this massive supergiant, on the periphery of the LMC, is leaving the galaxy where it will explode as a supernova.

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arXiv2016

COTS software in science operations, is it worth it?

Often, perhaps not often enough, we choose Common Off the Shelf (COTS) software for integration in our systems. These range from repositories to databases and tools we use on a daily basis. It is very hard to assess the effectiveness of these choices. While none of us would consider a project specific word processing solution when LaTeX (or even Word) many will consider writing their own data management systems. We will look at some of the COTS we have used and attempt to explain how we came to the decision and if it was worth it.

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arXiv2016

GAVIP: A Platform for Gaia Data Analysis

Gaia is a major European Space Agency (ESA) astrophysics mission designed to map and analyse 10$^9$ stars, ultimately generating more than 1 PetaByte of data products. As Gaia data becomes publicly available and reaches a wider audience, there is an increasing need to facilitate the further use of Gaia products without needing to download large datasets. The Gaia Added Value Interface Platform (GAVIP) is designed to address this challenge by providing an innovative platform within which scientists can submit and deploy code, packaged as "Added Value Interfaces" (AVIs), which will be executed close to the data. Deployed AVIs and associated outputs may also be made available to other GAVIP platform users, thus providing a mechanism for scientific experiment reproducibility. This paper describes the capabilities and features of GAVIP.

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arXiv2015

ESA Sky: a new Astronomy Multi-Mission Interface

We present a science-driven discovery portal for all the ESA Astronomy Missions called ESA Sky that allow users to explore the multi-wavelength sky and to seamlessly retrieve science-ready data in all ESA Astronomy mission archives from a web application without prior-knowledge of any of the missions. The first public beta of the service has been released, currently featuring an interface for exploration of the multi-wavelength sky and for single and/or multiple target searches of science-ready imaging data and catalogues. Future releases will enable retrieval of spectra and will have special time-domain exploration features. From a technical point of view, the system offers progressive multi-resolution all-sky projections of full mission datasets using a new generation of HEALPix projections called HiPS, developed at the CDS; detailed geometrical footprints to connect the all-sky mosaics to individual observations; and direct access to science-ready data at the underlying mission-specific science archives.

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arXiv2014

The Past, Present and Future of Astronomical Data Formats

The future of astronomy is inextricably entwined with the care and feeding of astronomical data products. Community standards such as FITS and NDF have been instrumental in the success of numerous astronomy projects. Their very success challenges us to entertain pragmatic strategies to adapt and evolve the standards to meet the aggressive data-handling requirements of facilities now being designed and built. We discuss characteristics that have made standards successful in the past, as well as desirable features for the future, and an open discussion follows.

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arXiv2012

Astronomy and Computing: a New Journal for the Astronomical Computing Community

We introduce \emph{Astronomy and Computing}, a new journal for the growing population of people working in the domain where astronomy overlaps with computer science and information technology. The journal aims to provide a new communication channel within that community, which is not well served by current journals, and to help secure recognition of its true importance within modern astronomy. In this inaugural editorial, we describe the rationale for creating the journal, outline its scope and ambitions, and seek input from the community in defining in detail how the journal should work towards its high-level goals.

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