On January 1, assistant professor Moritz Münchmeyer joined the UW–Madison physics department. He specializes in theoretical and computational cosmology. His research combines theoretical investigation, the analysis of data from different observatories, and the development of machine learning techniques to probe fundamental physics with cosmological data. He joins us from the Perimeter Institute for Theoretical Physics in Waterloo, where he was a Senior Postdoctoral Fellow. To welcome Münchmeyer to the department and to learn more about him and his research, we sat down for a (virtual) interview.
What are your research interests?
I work at the intersection of theory and observation in cosmology. On the one hand we have the mathematical theories of how the universe works, and then we have observations made by telescopes and detectors. The universe, of course, is incredibly complicated. There are many forces and particles and radiation that all interact with each other. And that makes it often hard to go from observational data to the theory that you’re interested in. We want to know, for example, what were the laws of physics in the very early universe? Or how does the universe evolve? And so, I develop new methods to use the data to probe the theories.
One thing that I’m very excited about now is using techniques from data science and machine learning for cosmology. As everybody knows, there’s a machine learning revolution going on which is having an impact on many fields, including cosmology. But the techniques in machine learning are often developed to do things like object recognition in images. They do not necessarily work well for the kind of data that we have, which has very different properties and is described by physical theories. So, I’m trying to adapt these machine learning techniques, or find new ones, that are specifically suited for the problems of cosmology.
I also work on new theoretical ideas to use observational data. There will be a huge influx of new cosmological data in the next decade: many experiments are being built and they are often much better than previous experiments. We’ll get amazing new data of the universe and I’m thinking about how to use this data to learn more about fundamental physics, for example by combining different data sources in new ways that have not been explored before.
What is the source of the data you use in your research?
When I started in cosmology, I became a member of the Planck satellite collaboration, which was a Cosmic Microwave Background (CMB) experiment. Many of the best measurements of cosmological parameters, such as the age of the universe, come from Planck. Of course, now we are building even better CMB experiments, such as the Simons Observatory which I am a member of. In about two years it will start to take precision measurements of the radiation from the early universe. I am also a member of the CHIME experiment, which is detecting Fast Radio Bursts, a new exciting source of data for cosmology and astrophysics. In Madison I am looking to also become involved with Vera Rubin Observatory, one the major upcoming galaxy surveys, which can be combined with CMB experiments. Prof. Keith Bechtol in the physics department is a leading contributor to this experiment. As a theorist, I am not involved much in the data taking process, but once the data is taken, my group will work on its analysis with the methods we have developed.
Once you settle into your new role here, what are the first research projects your group will start on?
The broad subject we’ll work on is to learn about the initial conditions of the universe from CMB and galaxy data. We will develop new statistical tools and machine learning methods towards this goal. We will also think about new ideas to use cosmological data, such as the Fast Radio Bursts I mentioned before.
What hobbies and interests do you have?
I have a family with two young children, so I like to go on adventures with them. I also play piano, especially to get my mind off physics. My current favorite sport is Brazilian Jiu-Jitsu. I’ve also always been interested in entrepreneurship. A few years ago, I co-founded a small company, Wolution, which uses machine learning — not in cosmology, but for image analyses in bio sciences, agriculture, and other fields.
What is your favorite element and/or elementary particle?
My favorite elementary particle is the photon, because it’s extremely versatile: the entire electromagnetic spectrum, like radio waves and x-rays and of course visible light. All the experiments I mentioned above fundamentally detect photons.
Dark Energy Survey makes public catalog of nearly 700 million astronomical objects
The second data release from the Dark Energy Survey, or DES, is the culmination of over a half-decade of astronomical data collection and analysis with the ultimate goal of understanding the accelerating expansion of the universe and the phenomenon of dark energy, which is thought to be responsible for this accelerated expansion. It is one of the largest astronomical catalogs released to date. Keith Bechtol, assistant professor of physics at UW–Madison, has served as the DES Science Release co-coordinator since 2017, guiding the effort to assemble, scientifically validate, and document data releases for both cosmology analysis by the DES Collaboration and exploration by the broad astronomical community.
Including a catalog of nearly 700 million astronomical objects, DR2 builds on the 400 million objects cataloged with the survey’s prior data release, or DR1, and also improves on it by refining calibration techniques, which, with the deeper combined images of DR2, lead to improved estimates of the amount and distribution of matter in the universe.
Astronomical researchers around the world can access these unprecedented data and mine them to make new discoveries about the universe, complementary to the studies being carried out by the Dark Energy Survey collaboration. The full data release is online and available to the public to explore and gain their own insights as well.
“Most of the nearly 700 million objects visible in DES DR2 images had never been seen by humans before the past few years,” Bechtol says. “If you take a moment to look at even a small patch of sky in the DES images, you can see asteroids of our Solar System, stars out to the edge of the Milky Way, and distant galaxies as they were billions of years ago. We look forward to see how our colleagues use this enormous new dataset for research and education.”
DES was designed to map hundreds of millions of galaxies and to discover thousands of supernovae in order to measure the history of cosmic expansion and the growth of large-scale structure in the universe, both of which reflect the nature and amount of dark energy in the universe. DES has produced the largest and most accurate dark matter map from galaxy weak lensing to date, as well as a new map, three times larger, that will be released in the near future.
One early result relates to the construction of a catalog of a type of pulsating star known as “RR Lyrae,” which tells scientists about the region of outer space beyond the edge of our Milky Way. In this area nearly devoid of stars, the motion of the RR Lyrae hints at the presence of an enormous “halo” of invisible dark matter, which may provide clues on how our galaxy was assembled over the last 12 billion years. In another result, DES scientists used the extensive DR2 galaxy catalog, along with data from the LIGO experiment, to estimate the location of a black hole merger and, independent of other techniques, infer the value of the Hubble constant, a key cosmological parameter. Combining their data with other surveys, DES scientists have also been able to generate a complete map of the Milky Way’s dwarf satellites, giving researchers insight into how our own galaxy was assembled and how it compares with cosmologists’ predictions.
Covering 5,000 square degrees of the southern sky (one-eighth of the entire sky) and spanning billions of light-years, the survey data enables many other investigations in addition to those targeting dark energy, covering a vast range of cosmic distances — from discovering new nearby solar system objects to investigating the nature of the first star-forming galaxies in the early universe.
“This is a momentous milestone. For six years, the Dark Energy Survey collaboration took pictures of distant celestial objects in the night sky. Now, after carefully checking the quality and calibration of the images captured by the Dark Energy Camera, we are releasing this second batch of data to the public,” said DES Director Rich Kron of Fermilab and the University of Chicago. “We invite professional and amateur scientists alike to dig into what we consider a rich mine of gems waiting to be discovered.”
Once captured, these images (and the large amount of data surrounding them) are transferred to the National Center for Supercomputing Applications for processing via the DES Data Management project. Using the Blue Waters supercomputer at NCSA, the Illinois Campus Cluster and computing systems at Fermilab, NCSA prepares calibrated data products for public and research consumption. It takes approximately four months to process one year’s worth of data into a searchable, usable catalog.
The detailed precision cosmology constraints based on the full six-year DES data set will come out over the next two years.
NCSA, NOIRLab and the LIneA Science Server collectively provide the tools and interfaces that enable access to DR2.
“Because astronomical data sets today are so vast, the cost to handle them is prohibitive for individual researchers or most organizations. CSDC provides open access to big astronomical data sets like DES DR2 and the necessary tools to explore and exploit them — then all it takes is someone from the community with a clever idea to discover new and exciting science,” said Robert Nikutta, project scientist for Astro Data Lab at CSDC.
“With information on the positions, shapes, sizes, colors and brightnesses of over 690 million stars, galaxies and quasars, the release promises to be a valuable source for astronomers and scientists worldwide to continue their explorations of the universe, including studies of matter (light and dark) surrounding our home Milky Way galaxy, as well as pushing further to examine groups and clusters of distant galaxies, which hold precise evidence about how the size of the expanding universe changes over time,” said Dark Energy Survey Data Management Project Scientist Brian Yanny of Fermilab.
This work is supported in part by the U.S. Department of Energy Office of Science.
The Dark Energy Survey is a collaboration of more than 400 scientists from 26 institutions in seven countries. Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, Funding Authority for Studies and Projects in Brazil, Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro, Brazilian National Council for Scientific and Technological Development and the Ministry of Science, Technology and Innovation, the German Research Foundation and the collaborating institutions in the Dark Energy Survey, the list of which can be found at www.darkenergysurvey.org/collaboration.
How do astronomers test-drive a telescope?
Graduate student Leslie Taylor helped fine-tune a high-energy gamma-ray telescope this summer. Detecting the Crab Nebula was the “gold standard” for success.
Massive halo finally explains stream of gas swirling around the Milky Way
The Large and Small Magellanic Clouds are satellite galaxies of the Milky Way. They are surrounded by a high-velocity gaseous structure called the Magellanic Stream, which consists of gas stripped from both clouds. So far, simulations have been unable to reconcile observations with a complete picture of how the stream was formed. In this Nature week’s issue, numerical simulations carried out at by Scott Lucchini, graduate student at the Physics Department working with Elena D’Onghia, present a model that potentially resolves this conundrum. By embedding the Large Magellanic Cloud in a corona of ionized gas, the researchers were able to simulate the Magellanic Stream accurately and explain its structure. Ellen Zweibel and Chad Bustard are also co-authors of the article.
In particular, the new results constrain the minimum mass of the dark matter particles, as well as the strength of interactions between dark matter and normal matter.
According to these new results, a dark matter particle must be heavier than a zeptoelectronvolt, which is 10-21 electronvolts. That’s one trillionth of a trillionth of the mass of an electron. This study also shows that dark matter’s interactions with normal matter must be roughly 1,000 times weaker than the weak nuclear force. Of the known forces, only gravity is weaker.
These novel measurements used data from the Dark Energy Survey, a cosmological survey designed to study dark energy, the mysterious force driving the accelerated expansion of the universe. In contrast, dark matter is gravitationally attractive, resisting the expansion of the universe and gravitationally binding astronomical systems such as galaxies. The smallest “dwarf” galaxies can have hundreds to thousands of times more dark matter than normal matter. Over the past five years, the Dark Energy Survey has combined with other surveys to more than double the known population of these tiny galaxies. The current total is now over 50.
“The large number of dwarf galaxies that we found orbiting the Milky Way is consistent with expectations from the simplest picture of dark matter — that is, comprising slow-moving particles that interact only through gravity,” Bechtol explained. “In this new paper, we rule out several alternative possibilities for the nature of dark matter.”
Dark matter makes up 85% of the matter in the universe, but we have yet to detect it directly in the laboratory. The gravitational effects of dark matter are clearly visible in the motions of stars in galaxies, the clumpy distribution of galaxies in the universe, and even in the amount of lightweight elements. The robust astronomical evidence for the existence of dark matter has motivated many experimental searches here on Earth, using instruments ranging from cryogenic detectors buried deep underground to energetic particle colliders.
“The faintest galaxies are among the most valuable tools we have to learn about dark matter because they are sensitive to several of its fundamental properties all at once,” said Ethan Nadler, the study’s lead author and graduate student at Stanford University and SLAC.
In these multi-year, multi-telescope sky surveys, the raw data comes in the form of tens of thousands high-resolution digital images. But identifying these ultrafaint galaxies, as their description implies, is not as simple as looking at an image and seeing a faint smudge of light. Bechtol and his group, including physics grad student Mitch McNanna, designed the search algorithms needed to identify, with some statistical assurance, which individual stars are part of a dwarf galaxy.
“We worked closely with experts in galaxy formation and particle physics theory to compare the Dark Energy Survey observations with predictions,” Bechtol said. “Part of our job was to determine the sensitivity of our search — how far away from the Earth could we spot a galaxy with only a few hundred stars?”
By combining the observed census of dwarf galaxies with advanced cosmological simulations of the distribution of dark matter around the Milky Way, scientists were able to predict how the physical properties of dark matter would affect the number of small galaxies. Small galaxies form in regions where the dark matter density in the early universe is very slightly above average. Physical processes that smooth out these regions of higher density (if dark matter moves too quickly or gains energy due to interactions with normal matter) or prevent density variations from collapsing to form galaxies (thanks to quantum interference effects) would reduce the number of galaxies observed by the Dark Energy Survey.
“Astrophysical observations provide unique information about the fundamental nature of dark matter, and are complementary to searches for dark matter particles in terrestrial experiments.” Bechtol said. “With the Dark Energy Survey, we continue to learn about the deep connection between particle physics and the growth of cosmic structure, ranging from the vast network of galaxies in the cosmic web, down to smallest individual galaxies.”
The Dark Energy Survey is a collaboration of more than 300 scientists from 25 institutions in six countries. For more information about the survey, please visit the experiment’s website.
Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of ChicagoFunding Authority for Funding and Projects in Brazil, Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro, Brazilian National Council for Scientific and Technological Development and the Ministry of Science and Technology, the German Research Foundation and the collaborating institutions in the Dark Energy Survey.
Vandenbroucke group plays instrumental role in proving viability of innovative gamma-ray telescope
Scientists in the Cherenkov Telescope Array (CTA) consortium have detected gamma rays from the Crab Nebula using the prototype Schwarzschild-Couder Telescope (pSCT), proving the viability of the novel telescope design for use in gamma-ray astrophysics. The announcement was made today by Justin Vandenbroucke, associate professor at the University of Wisconsin–Madison, on behalf of the CTA Consortium at the virtual 236th meeting of the American Astronomical Society (AAS).
“The Crab Nebula is the brightest steady source of TeV, or very high-energy, gamma rays in the sky, so detecting it is an excellent way of proving the pSCT technology,” says Vandenbroucke, who is also affiliated with the Wisconsin IceCube Particle Astrophysics Center (WIPAC) at UW–Madison. “Very high-energy gamma rays are the highest energy photons in the universe and can unveil the physics of extreme objects, including black holes and possibly dark matter.”
Vandenbroucke is coleader of a team made up of WIPAC scientists and other collaborators that developed and operate a critical part of the telescope: its high-speed camera. Vandenbroucke has worked on the design, construction, and integration of the camera since 2009.
Keith Bechtol, Rob Morgan win UW’s Cool Science Image contest
Congrats to Prof. Keith Bechtol and graduate student Rob Morgan for their winning entry in the UW–Madison Cool Science Images contest! Their winning entry — one of 12 selected out of 101 entries — earns them a large-format print which initially will be displayed in a gallery at the McPherson Eye Research Institute’s gallery in the WIMR building.
This snapshot of the sky contains thousands of distant galaxies, each containing billions of stars. Bechtol and Morgan were looking for the flash of the explosion of a single star, the potential source of a sub-atomic particle called a neutrino, spotted zipping through the Earth by the IceCube Neutrino Observatory at the South Pole. The distant galaxies, swirling billions of light years away, are all the harder to see because of nearby objects, like the pictured Helix Nebula. The image was captured with a Dark Energy Camera and Victor M. Blanco telescope.
Just as the sun has planets and the planets have moons, our galaxy has satellite galaxies, and some of those might have smaller satellite galaxies of their own. To wit, the Large Magellanic Cloud (LMC), a relatively large satellite galaxy visible from the southern hemisphere, is thought to have brought at least six of its own satellite galaxies with it when it first approached the Milky Way, based on recent measurements from the European Space Agency’s Gaia mission.
Astrophysicists believe that dark matter is responsible for much of that structure, and now researchers with the Dark Energy Survey — including University of Wisconsin–Madison assistant professor of physics Keith Bechtol and his research group — have drawn on observations of faint galaxies around the Milky Way to place tighter constraints on the connection between the size and structure of galaxies and the dark matter halos that surround them. At the same time, they have found more evidence for the existence of LMC satellite galaxies and made a new prediction: If the scientists’ models are correct, the Milky Way should have an additional 150 or more very faint satellite galaxies awaiting discovery by next-generation projects such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.
Two new studies, forthcoming in the Astrophysical Journal and available as preprints (pre-print 1; pre-print 2), are part of a larger effort to understand how dark matter works on scales smaller than our galaxy.
“The ultra-faint galaxies that orbit the Milky Way are small clouds of dark matter with just enough stars to see that they exist. They are nearly invisible, but if spotted, they make excellent natural laboratories to study dark matter,” Bechtol says. “We hope to learn what dark matter is made of, how it was produced in the early Universe, and what relationship it has to the known particle species.”
Shining galaxies’ light on dark matter
Astronomers have long known the Milky Way has satellite galaxies, including the Large Magellanic Cloud, which can be seen by the naked eye from the southern hemisphere, but the number was thought to be around just a dozen or so until around the year 2000. Since then, the number of observed satellite galaxies has risen dramatically. Thanks to the Sloan Digital Sky Survey and more recent discoveries by projects including the Dark Energy Survey (DES), the number of known satellite galaxies has climbed to about 60.
Such discoveries are always exciting, but what’s perhaps most exciting is what the data could tell us about the cosmos. “For the first time, we can look for these satellite galaxies across about three-quarters of the sky, and that’s really important to several different ways of learning about dark matter and galaxy formation,” said Risa Wechsler, director of the Kavli Institute for Particle Astrophysics and Cosmology (KIPAC). Last year, for example, the DES team used data on satellite galaxies in conjunction with computer simulations to place much tighter limits on dark matter’s interactions with ordinary matter.
Now, the team is using data from a comprehensive search over most of the sky to ask different questions, including how much dark matter it takes to form a galaxy, how many satellite galaxies we should expect to find around the Milky Way and whether galaxies can bring their own satellites into orbit around our own – a key prediction of the most popular model of dark matter.
Hints of galactic hierarchy
The answer to that last question appears to be a resounding “yes.”
The possibility of detecting a hierarchy of satellite galaxies first arose some years back when DES detected more satellite galaxies in the vicinity of the Large Magellanic Cloud than they would have expected if those satellites were randomly distributed throughout the sky. More data was needed to conclusively attribute this excess to galaxies that arrived at the Milky Way with the Large Magellanic Cloud.
In the first published study, the DES group combined observations from DES with those from the Pan-STARRS survey, together covering 75% of the sky, to test this hypothesis. The DES data represents nearly 40,000 images from a 500-million-pixel camera collected over three years from a telescope in Chile.
The raw DES data was run through a series of data compressions, including a final step led by Bechtol’s group, to identify and catalog individual stars, including their color, which infers temperature, and how far away they are.
“We throw the star catalog into our search algorithms, which are responsible for identifying small groups of stars that are clustered in space and have similar colors and brightness. There’s a particular distribution for what we expect the stars to look like in ultrafaint galaxies,” says UW-Madison physics graduate student Mitch McNanna. “Even then we’re not 100 percent sure that we’ve found a real galaxy, so we also collect spectroscopic observations to measure the doppler motion of the stars. Hopefully we see the group of stars is moving in a way that’s different from the rest of the stars in the Milky Way halo.”
The team, including Alex Drlica-Wagner at Fermilab, produced a model of which satellite galaxies are most likely to be seen by current surveys, given where they are in the sky as well as their brightness, size and distance.
In the second study, led by others in the DES team including Ethan Nadler at Stanford University and collaborators, the team took the findings of the latest satellite census and analyzed computer simulations of millions of possible universes. Those simulations model the formation of dark matter structure that permeates the Milky Way, including details such as smaller dark matter clumps within the Milky Way that are expected to host satellite galaxies. To connect dark matter to galaxy formation, the researchers used a flexible model that allows them to account for uncertainties in the current understanding of galaxy formation, including the relationship between galaxies’ brightness and the mass of dark matter clumps within which they form.
Those components in hand, the team ran their model with a wide range of parameters and searched for simulations in which LMC-like objects fell into the gravitational pull of a Milky Way-like galaxy. By comparing those cases with galactic observations, they could infer a range of astrophysical parameters, including how many satellite galaxies should have tagged along with the LMC. The results were consistent with Gaia observations: Six satellite galaxies should currently be detected in the vicinity of the LMC, moving with roughly the right velocities and in roughly the same places as astronomers had previously observed. The simulations also suggested that the LMC first approached the Milky Way about 2.2 billion years ago, consistent with high-precision measurements of the motion of the LMC from the Hubble Space Telescope.
Galaxies yet unseen
In addition to the LMC findings, the team also put limits on the connection between dark matter halos and galaxy structure. For example, in simulations that most closely matched the history of the Milky Way and the LMC, the smallest galaxies astronomers could currently observe should have stars with a combined mass of around a hundred suns, and about a million times as much dark matter. According to an extrapolation of the model, the faintest galaxies that could ever be observed could form in halos up to a hundred times less massive than that.
And there could be more discoveries to come: If the simulations are correct, there are around 150 more satellite galaxies – more than double the number already discovered – hovering around the Milky Way. The discovery of those galaxies would help confirm the researchers’ model of the links between dark matter and galaxy formation, and likely place tighter constraints on the nature of dark matter itself.