What causes the universe to expand? How many galaxies are out there that we don’t even know exist?

Given the vastness of our universe, studying astrophysics and cosmology often brings more questions than answers. But those questions, and finding some answers, are what drive physics major Evan Jones, ’18.

Jones’ curiosity about physics was piqued by Carl Sagan’s seminal book Cosmos, and nurtured by UR faculty, particularly astrophysicists Ted Bunn and Jack Singal. “The professors are highly educated, and they’re passionate about what they do, and that passion is contagious,” Jones said. 

With Singal as his mentor, Jones set out to answer one of the larger questions currently facing astrophysicists: how do we measure the distance of galaxies from Earth, when there are hundreds of billions of objects out there in the universe?

“I’ve developed a computer system, SPIDERz, for estimating photometric redshift, which is the distance of galaxies from Earth, measured from a small number of measured brightness values in different wave bands of light,” Jones said. A lot of theoretical cosmology relies on the distance measurement of redshift in galaxies to Earth, but knowing the exact accurate redshift for every object in the universe is impossible to measure; it would take too much time to attempt to analyze the billions of objects out there. “My research is aimed at estimating the distances with easily obtained observations, using the power of machine learning to obtain these estimates at a fast rate,” he said.

Jones spent his first summer teaching himself Interactive Data Language, a computer programming language regularly used for data analysis in the astrophysics community. Once he had a handle on the language he would need to write the program, he spent the next two years working alongside Singal to code and test SPIDERz against existing redshift data to hone its accuracy in estimations. “I’m working with up to eight computers, each running different computations simultaneously because the data sets are so large,” he said.

Having good estimates of galaxy redshift, which SPIDERz provides, will be incredibly important to astrophysics in the near future. “In the next decade, there’s going to be rapid release of data for millions of objects for the first time ever, with new large extragalactic surveys,” Jones said. “Now is the time to prepare for how to analyze that data that will be coming, so that theories about how the universe is formed, can progress as fast as we can enable them to.”

Jones and Singal had their work on SPIDERz published in to the journal Astronomy and Astrophysics and Jones was also recognized with the A&S Student Symposium Paper Competition award in April. He has spent this summer refining the program in advance of submitting a second article. “SPIDERz now performs better in estimating, and the methods that I’ve implemented into the program to make it perform better can potentially be used in other machine learning programs,” he said. “What we’ve done has the potential for others to take our information and apply it to what they’re doing.”

What makes Jones happiest, though, is knowing that his work on SPIDERz has the potential to answer some of the large questions that people have about our universe. “The project can be used by theorists to help answer some of the most interesting questions anyone can come up with,” he said. “I think about that stuff all the time, so spending my time working on something related to that, I was really motivated to do it.”