Research, teaching and outreach in Physics at UW–Madison
dark energy survey
Physics has three winners in the Cool Science Image contest!
The winners of the UW–Madison 13th annual Cool Science Image contest were announced, and Physics has three winners! Our winners include graduate student Jacob Scott, the graduate student-professor pairing of Jimena González and Keith Bechtol, and alum Aedan Gardill, PhD ’23. Their winning images are below.
A panel of experienced artists, scientists and science communicators chose 12 winning images based on the aesthetic, creative and scientific qualities that distinguished them from scores of entries. The winning entries showcase the research, innovation, scholarship and curiosity of the UW–Madison community through visual representations of socioeconomic strata, brain cells snuffed out in Parkinson’s disease, the tangle of technology required to equip a quantum computing lab and a bug-eyed frog that opened students’ eyes to the world.
The winning images go on display this week in an exhibit at the McPherson Eye Research Institute’s Mandelbaum and Albert Family Vision Gallery on the ninth floor of the Wisconsin Institutes for Medical Research, 111 Highland Ave. The exhibit, which runs through the end of 2023, opens with a public reception at the gallery Thursday, Sept. 28, from 4:30 to 6:30 p.m. The exhibit also includes historical images of UW science, in celebration of the 175th anniversary of the University of Wisconsin’s founding.
The Cool Science Image Contest recognizes the technical and creative skills required to capture and create images, videos and other media that reveal something about science or nature while also leaving an impression with their beauty or ability to induce wonder. The contest is sponsored by Madison’s Promega Corp., with additional support from UW–Madison’s Office of University Communications.
To better understand the nature of dark energy, she uses machine learning to search Dark Energy Survey cosmology data for evidence of strong gravitational lensing — where a heavy foreground galaxy bends the light of another galaxy, producing multiple images of it that can get so distorted that they appear as long arcs of light around the large galaxy in telescope images. She also focuses on finding very rare cases of strong gravitational lensing in which two galaxies are lensed by the same foreground galaxy, systems known as double-source-plane lenses.
First, she had to create simulations of the galaxy systems. Next, she used those simulations to train the machine learning model to identify the systems in the heaps and heaps of DES data. Lastly, she would apply the trained model to the real DES data. All told, she expected to find hundreds of “simple” strong gravitational lenses and only a few double-source-plane lenses out of 230 million images.
“But, for example, when I did the search the first time, I mostly only got spiral galaxies, so then I had to include spiral galaxies in my training,” says González, a physics graduate student in Keith Bechtol’s group.
The initial steps took around two weeks (hence the waiting) before she could even know what needed to be changed to better train the model. Once she had the model trained and would be ready to apply it to the entire dataset, she estimated it would take five to six years just to find the images of interest — and then she would finally be able to study the systems found.
Then, the email from the Open Science Grid (OSG) Consortium came. The OSG Consortium operates a fabric of distributed High Throughput Computing (dHTC) services, allowing users to take advantage of massive amounts of computing power. Researchers can apply to the OSG User School, an annual workshop for scientists who want to learn and use dHTC methods.
“[dHTC] is parallelizing things. It’s like if you had 500 exams to grade, you can distribute them among different people and it would take less time,” González says. “It sounded perfect for me.”
González applied and was accepted into the 2021 program, which was run virtually that year. At the OSG User School, she learned methods that would allow her to take advantage of dHTC and apply them to her work. Her multi-year processing time was cut down to mere days.
“Because it was so fast, there were many new things that I could implement in my research,” González says. “A lot of the methodology I implemented would not have been possible without OSG.”
David Swanson was a longtime champion of and contributor to OSG, who passed away in 2016. In his memory, the award is bestowed annually upon one or more former students of the OSG User School who have subsequently achieved significant dHTC-enabled research outcomes.
She accepted the award at the Throughput Computing 2023 conference, where she presented her research and discussed how she used her training from the OSG User School to successfully comb through the DES data and find the systems of interest.
“When I got the award, I didn’t know anything about [Swanson],” González says. “But once I attended this event, I heard so many people talking about him, and I understood why it was created. It is such an honor to receive this award in his name.”
Dark Energy Survey releases most precise look at the universe’s evolution
The Dark Energy Survey collaboration has created the largest ever maps of the distribution and shapes of galaxies, tracing both ordinary and dark matter in the universe out to a distance of more than 7 billion light years. The analysis, which includes the first three years of data from the survey, is consistent with predictions from the current best model of the universe, the standard cosmological model. Nevertheless, there remain hints from DES and other experiments that matter in the current universe is a few percent less clumpy than predicted.
New results from the Dark Energy Survey — a large international team that includes researchers from the University of Wisconsin–Madison — use the largest ever sample of galaxies over an enormous piece of the sky to produce the most precise measurements of the universe’s composition and growth to date. Scientists measured that the way matter is distributed throughout the universe is consistent with predictions in the standard cosmological model, the best current model of the universe.
Over the course of six years, DES surveyed 5,000 square degrees — almost one-eighth of the entire sky — in 758 nights of observation, cataloguing hundreds of millions of objects. The results, announced May 27, draw on data from the first three years — 226 million galaxies observed over 345 nights — to create the largest and most precise maps yet of the distribution of galaxies in the universe at relatively recent epochs.
Since DES studied nearby galaxies as well as those billions of light-years away, its maps provide both a snapshot of the current large-scale structure of the universe and a movie of how that structure has evolved over the course of the past 7 billion years.
“This a stringent test of the current standard cosmological paradigm, a model proposing that 95% of the universe is dark matter and dark energy that we do not yet understand,” explains UW–Madison physics professor Keith Bechtol. “By measuring the apparent positions and shapes of hundreds of millions of galaxies in our survey, we test whether the cosmic structures that have formed in the universe today match the predictions based on structures observed in the early universe.”
To test cosmologists’ current model of the universe, DES scientists compared their results with measurements from the European Space Agency’s orbiting Planck observatory. Planck used light signals known as the cosmic microwave background to peer back to the early universe, just 400,000 years after the Big Bang. The Planck data give a precise view of the universe 13 billion years ago, and the standard cosmological model predicts how the dark matter should evolve to the present. If DES’s observations don’t match this prediction, there is possibly an undiscovered aspect to the universe. While there have been persistent hints from DES and several previous galaxy surveys that the current universe is a few percent less clumpy than predicted—an intriguing find worthy of further investigation—the recently released results are consistent with the prediction.
“In the area of constraining what we know about the distribution and structure of matter on large scales as driven by dark matter and dark energy, DES has obtained limits that rival and complement those from the cosmic microwave background,” said Brian Yanny, a Fermilab scientist who coordinated DES data processing and management. “It’s exciting to have precise measurements of what’s out there and a better understanding of how the universe has changed from its infancy through to today.”
Ordinary matter makes up only about 5% of the universe. Dark energy, which cosmologists hypothesize drives the accelerating expansion of the universe by counteracting the force of gravity, accounts for about 70%. The last 25% is dark matter, whose gravitational influence binds galaxies together. Both dark matter and dark energy remain invisible and mysterious, but DES seeks to illuminate their natures by studying how the competition between them shapes the large-scale structure of the universe over cosmic time.
DES photographed the night sky using the 570-megapixel Dark Energy Camera on the Victor M. Blanco 4-meter Telescope at the Cerro Tololo Inter-American Observatory in Chile, a Program of the National Science Foundation’s NOIRLab. One of the most powerful digital cameras in the world, the Dark Energy Camera was designed specifically for DES and built and tested at Fermilab. The DES data were processed at the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign.
“These analyses are truly state-of-the-art, requiring artificial intelligence and high-performance computing super-charged by the smartest young scientists around,” said Scott Dodelson, a physicist at Carnegie Mellon University who co-leads the DES Science Committee with Elisabeth Krause of the University of Arizona. “What an honor to be part of this team.”
To quantify the distribution of dark matter and the effect of dark energy, DES relied on two main phenomena. First, on large scales, galaxies are not distributed randomly throughout space but rather form a weblike structure due to the gravity of dark matter. DES measured how this cosmic web has evolved over the history of the universe. The galaxy clustering that forms the cosmic web, in turn, revealed regions with a higher density of dark matter.
Second, DES detected the signature of dark matter through weak gravitational lensing. As light from a distant galaxy travels through space, the gravity of both ordinary and dark matter can bend it, resulting in a distorted image of the galaxy as seen from Earth. By studying how the apparent shapes of distant galaxies are aligned with each other and with the positions of nearby galaxies along the line of sight, DES scientists inferred the spatial distribution (or clumpiness) of the dark matter in the universe.
Analyzing the massive amounts of data collected by DES was a formidable undertaking. The team began by analyzing just the first year of data, which was released in 2017. That process prepared the researchers to use more sophisticated techniques for analyzing the larger data set, which includes the largest sample of galaxies ever used to study weak gravitational lensing.
For example, calculating the redshift of a galaxy — the change in light’s wavelength due to the expansion of the universe — is a key step toward measuring how both galaxy clustering and weak gravitational lensing change over cosmic history. The redshift of a galaxy is related to its distance, which allows the clustering to be characterized in both space and time.
“Redshift calibration is one topic where we significantly improved upon our year-1 data analysis,” said Ross Cawthon, a UW-Madison physics postdoc who led the redshift calibration efforts for two of the main galaxy samples. “We developed new methods and refined old ones. It has been a huge effort by DES members from all over the world.”
Ten regions of the sky were chosen as “deep fields” that the Dark Energy Camera imaged repeatedly throughout the survey. Stacking those images together allowed the scientists to glimpse more distant galaxies. The team then used the redshift information from the deep fields to calibrate measurements of redshift in the rest of the survey region. This and other advancements in measurements and modeling, coupled with a threefold increase in data compared to the first year, enabled the team to pin down the density and clumpiness of the universe with unprecedented precision.
Along with the analysis of the weak-lensing signals, DES also precisely measures other probes that constrain the cosmological model in independent ways: galaxy clustering on larger scales (baryon acoustic oscillations), the frequency of massive clusters of galaxies, and high-precision measurements of the brightnesses and redshifts of Type Ia supernovae. These additional measurements will be combined with the current weak-lensing analysis to yield even more stringent constraints on the standard model.
“DES has delivered cost-effective, leading-edge science results directly related to Fermilab’s mission of pursuing the fundamental nature of matter, energy, space and time,” said Fermilab Director Nigel Lockyer. “A dedicated team of scientists, engineers and technicians from institutions around the world brought DES to fruition.”
The DES collaboration consists of over 400 scientists from 25 institutions in seven countries.
“The collaboration is remarkably young. It’s tilted strongly in the direction of postdocs and graduate students who are doing a huge amount of this work,” said DES Director and spokesperson Rich Kron, who is a Fermilab and University of Chicago scientist. “That’s really gratifying. A new generation of cosmologists are being trained using the Dark Energy Survey.”
UW–Madison physics graduate student Megan Tabbutt was one of the many significant contributors to this work, developing new methods that contributed to an independent validation of the galaxy clustering analysis.
DES concluded observations of the night sky in 2019. With the experience of analyzing the first half of the data, the team is now prepared to handle the complete data set. The final DES analysis is expected to paint an even more precise picture of the dark matter and dark energy in the universe. And the methods developed by the team have paved the way for future sky surveys to probe the mysteries of the cosmos.
“This work represents a ‘big statement’ from the Dark Energy Survey. DES data combined with other observations provide world-leading constraints on the nature of dark energy,” Bechtol says. “At the same time, we are training a new generation of cosmologists, and pioneering advanced methodologies that will be essential to realize the full potential of upcoming galaxy surveys, including the Vera C. Rubin Observatory Legacy Survey of Space and Time.”
The recent DES results were presented in a scientific seminar on May 27. Twenty-nine papers are available on the arXiv online repository.