How to Read (LSS)Tea Leaves to Better Understand Dark Energy

Title: Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey

Authors: M. Lochner, D. Scolnic, H. Awan, N. Regnault, P. Gris, et al.

First Author Institution: African Institute for Mathematical Sciences/South African Radio Astronomy Observatory

Status: The LSST DESC response (WFD) to the Call for White Papers on LSST Cadence Optimization, open access on arXiv

Figure 1. An artist’s rendition of the Large Synoptic Survey Telescope, approximately to scale (the LSST will have an 8.4 meter primary mirror) [Todd Mason, Mason Productions Inc. / LSST Corporation].

 

The Large Synoptic Survey Telescope (LSST) will spend ten years observing the Universe from its site in Chile. It can take large images (over forty full moons worth of the sky at once), while also detecting faint objects, enabling it to create rich visions of the entire sky every few nights. The LSST has enormous science potential, and one of its goals is to aid our understanding of dark energy and dark matter.

The LSST survey strategy will impact subfields in astronomy to different degrees. Individual observations will be taken as visits—a pair of 15-second exposures of the same 10 degrees of sky taken in succession. How and when these visits will occur over the decade of operation is still being discussed. The paper in this Astrobite comes out of the LSST Dark Energy Science Collaboration (DESC) and outlines their recommendations to maximize the LSST’s benefit to cosmology (this paper accompanies it).

 

Two Sources of Help

Observations of time-varying (supernovae, strong lensing) and static (large scale structure, weak lensing) sources will constrain values associated with dark energy. However, observing these two very different types of sources will require a balancing act between frequent observations and deep ones.

With regard to static source science, the LSST will produce the largest sample of galaxies to date, a goldmine for weak lensing studies. Weak lensing differs from its more popular counterpart, strong lensing, in that its effect cannot be detected with a single background source. To establish weak lensing, an ensemble of galaxies must examined for subtle distortions in their shapes and positions. The result is a map of mass density that can be split up by distance or redshift. The densities plotted in maps like these rely heavily on the nature of dark energy. Large scale structure can also be studied with a large sample of galaxies, telling us about the primordial fluctuations that caused matter to collapse into today’s cosmological structures.

Type Ia supernovae at large distances are well within the reach of the LSST. They require frequent observations to be properly characterized, making supernova science highly susceptible to the choice of observing pattern. The same can be said for studies of strongly lensed variable objects, such as quasars and supernovae. These transient objects offer a way to precisely measure large distances, allowing us to better understand the expansion of the Universe.

 

Some Survey Strategies

Figure 2. The proposed footprint of the DESC recommended WFD survey along with the footprint of other surveys—4MOST/TiDES (4-metre Multi-Object Spectroscopic Telescope/Time-Domain Extragalactic Survey) and DESI (Dark Energy Spectroscopic Instrument)—and the footprint of the WFD survey as per the kraken_2026 simulation [Figure 3 from the paper].

 

The LSST’s main survey will be a Wide-Fast-Deep (WFD) survey — 18,000 square degrees of sky that will be visited frequently (the total sky area is roughly 40,000 square degrees). Amongst their recommendations, the authors of this paper suggest moving the survey footprint away from the Galactic plane to avoid extinction. The footprint of the suggested survey is practically all of the southern sky, excluding the Galactic plane (see Figure 2).

To catch transient objects, the ideal gap between observations of the same field would be 5-10 days depending on the filter. This cadence is higher than the kraken_2026 observing strategy but it enables supernovae to be caught more quickly on their rise to peak brightness (see Figure 3). The authors place a heavy emphasis on the value of regular sampling.

Some of the metrics used to evaluate the suggested observing strategy are the occurrence of rare transients (like kilonovae), and the number and redshifts of Type Ia supernovae detected. The authors conclude with adaptations of the strategy to be tested by the application Operations Simulator. Suggested tweaks include prioritizing observations in some filters over others, changing exposure times, and contingency plans for bad weather.

Figure 3. The lightcurve of a supernova in different filters as observed with the kraken_2026 cadence (left) and the proposed DESC WFD cadence (right). The proposed observation cadence would catch supernovae more quickly as they brighten, as indicated by the number of data points in the lightcurve on the right [Figure 2 from the paper].

 

The LSST will be a powerful tool for astronomy in the next decade, but with great power comes great responsibility. This paper (along with others that have come out in response to the call for observing strategies) shows the groundwork that goes into large scale projects such as the LSST, and seeing this process unfold in real time is absolutely fascinating.

 

Featured image comes from the LSST Gallery.

 

About Tarini Konchady

I'm a second year graduate student at Texas A&M University. Currently I'm looking for Mira variables to better calibrate the distance ladder. I'm also looking for somewhere to hide my excess yarn (I'm told I may have a problem).

Leave a Reply