Daniel Grün stands near the University Observatory in Munich. The picture was taken just half an hour after submitting his thesis. Photo courtesy of Daniel Grün
As a child from a small village in southern Germany, Daniel Grün looked toward the clear, night sky to track and document shooting stars.
“Nothing gives you the feeling of being a small part of this huge universe as much as going outside at night and seeing all the stars around you,” he said.
But by the time Grün entered college, he decided to pursue physics with no plan to study astrophysics. In a series of coincidences, he stumbled upon opportunities to work on small astronomy-based projects.
His interest in space was reinvigorated, and when he entered grad school, he received another opportunity – to work on the Dark Energy Survey. Today, he focuses on weak gravitational lensing by galaxy clusters. His research and participation on DES, presented in his Ph.D. thesis, won him the 2016 URA Thesis Award.
“URA is very pleased to confer its Thesis Award on Daniel Grun,” said URA Executive Director Marta Cehelsky. “It recognizes both the excellence of his work, and the role that Fermilab plays in the training of young scientists.”
The Universities Research Association, or URA, and Fermilab annually present the URA outstanding doctoral thesis award for work conducted at Fermilab or in collaboration with Fermilab scientists.
“Daniel is an outstanding scientist and a young leader of this project,” said Josh Frieman, the DES director and a Fermilab scientist in the Theoretical Astrophysics Group. “As a student he made multiple, important contributions to DES and to research on the cosmic frontier.”
Grün earned his Ph.D. in 2015 at the Ludwig Maximilian University in Munich under Stella Seitz and Ralf Bender, and he is currently a postdoctoral fellow at SLAC National Accelerator Laboratory. Since 2010, he has collaborated with Fermilab and other scientists on DES.
While working on DES, one of Grün’s roles was implementing better image correction methods for precision data analysis.
One technical challenge Grün tackled was removing image artifacts, such as satellite and plane tracks, reflections from bright stars, and imperfections on the camera sensor itself. Artifacts can litter the data and misrepresent the swath of sky under investigation. Grün helped fix this issue by developing an algorithm to “mask,” or clean up, the image to show only the stars and galaxies.
Another technical issue scientists face is the blurring of images by Earth’s atmosphere and the telescope camera. The Dark Energy Camera (DECam), atop the Blanco Telescope in Chile, is a powerful digital camera with charge-coupled device chips (CCDs), a 570-megapixel-sensor array used to photograph the sky in great detail.
Turbulence in the atmosphere causes both stars and galaxies to appear blurry in images, and scientists use the blurriness of stars in the Milky Way to calibrate how blurry a galaxy on the same image should appear and correct for this effect in their analysis.
In a digital camera, such as DECam, there is an additional blurring effect caused by the CCDs, where starlight creates charges on the camera sensor and causes electrons on the chips to repel each other, thus creating a more diffused glow. To fix this, Grün developed a method to shift the charges on the CCDs back to the pixels they belong to, which is now used in the image-processing pipeline for all of the DECam data in the survey.
“One aspect I enjoyed about my work is the broad range of topics,” Grün said. “You need to do all of this, and do it well, in order to get results you can trust.”
With improved visuals and clear data, Grün was able to focus on his main interest – weak gravitational lensing. Weak lensing is an important tool in the quest to determine the nature of dark energy, the force driving the universe’s accelerated expansion, and for understanding dark matter, the invisible material constituting 85 percent of all matter in the observable universe.
Gravitational lensing occurs when a massive foreground object bends light coming from background galaxies. Scientists believe dark matter dominates the mass content of galaxy clusters, and they use weak lensing to determine how much mass is in the observed galaxy clusters by measuring how much light bends around the massive foreground object. However, the weak lensing effect is tiny, and we cannot pick it up with the unaided eye. Grün used the weak lensing technique and made statistical measurements so he could “see” the effects of dark energy and dark matter in the galaxy clusters and measure clusters’ overall masses.
Frieman said Grün’s thesis does an excellent job of connecting both the technical and physics objectives, and his new methods paved the way to better understanding the dark universe.
Grün will present his research and accept the URA Thesis Award June 15, during the two-day Users Meeting at Fermilab.
“The committee was impressed by the breadth of contributions to dark energy studies detailed in this thesis,” said Leonard Spiegel, URA Thesis Award Committee chair. “Grün’s work in his thesis will help improve the accuracy of cosmological measurements in DES and future imaging surveys.”