Ankush Kanuganti
PhD Candidate Physics
We recently spoke with Ankush Kanuganti, a 6th-year Ph.D. Candidate in Physics, about his research and work in experimental particle physics at Baylor. He chose Baylor not only because his research interests are valued here, but because Baylor has faculty recognized and respected in the field of particle physics. Kanuganti notes his opportunities to travel to Geneva Switzerland to perform real particle experiments at CERN. Read more about Ankush's time here at Baylor.
Why did you choose to attend Baylor for Graduate School?
Baylor has research activity in experimental particle physics in which I am interested. Secondly, Baylor has the best faculty who are well recognized in my field and also are motivating and looking to explore new ideas in particle physics. We are well supported by the physics department and grants to travel to CERN for few months to carry out real life experimental physics at the CMS detector in Geneva, Switzerland.
What are your research interests?
Searching for new physics beyond the standard model has been a hot topic in the particle physics community since the discovery of the Higgs boson. With the new machine learning techniques and more data from the Large Hadron Collider (LHC), we are starting to become sensitive to large class of physics models which were still unexplored. I am very much interested to squeeze in every bit of phase-space with different machine learning techniques to search for supersymmetric particles.
What opportunities or implications stem from your research?
Our research mostly involves huge computational tasks on big data using clusters. Most of my skills revolve around processing large data, exploratory data analysis, optimization of the search regions, application of statistical modeling, and machine learning algorithms. It's very important to understand the universe in terms of the fundamental particle interactions and the existence of supersymmetry. My research aids the particle physics scientific community in this direction and also contributes to technology in terms of the new algorithms stemmed as a part of the particle hunt.
What research excites you right now?
With the recent start of LHC Run 3, there will be more data than ever before. It can be really exciting with the recent improvement in physics reconstruction. We could discover super symmetry or dark matter or rule out other theoretical predictions. Either direction will demand for other physics models which were never thought about. More exciting still is the news of the upgrade project for HL-LHC, implementing the latest tools in electronics and computing to build state-of-the-art detectors.
How does Baylor help you achieve your research?
Baylor provides me with resources like High-Performance Computing (HPC) which helps to run my computing jobs faster than any cluster at Fermilab or CERN with dedicated GPU resources. This significantly reduces the wait time and positively impacts the production of my research. I was supported for my travel to CERN to have hands-on experience with the detector installation and upgrade activities, which is the most exciting part of research. Last, but not least, I was supported as graduate research assistant, allowing me to concentrate on research and not having to work outside of my teaching and research duties. This has helped me stay focused on research.
If you are working on a thesis or dissertation, briefly describe your topic.
I started working on my thesis topic "Search for electroweak supersymmetry in all hadronic final states with large missing transverse momentum". My work involves data analysis from the Run2 (2016-2018) data from the CMS experiment at CERN. I was searching for the production of charginos and neutralinos (which are supersymmetric particles) which decay into bosons (we can reconstruct them in the detector). There is large missing momentum from the LSP's. Using various data analysis techniques, I identify regions to boost the presence of the signals and estimate the backgrounds in that region. Finally, statistical interpretation is done to evaluate any excess in data in the search region.
What grants/awards (if any) have you received for your research while at Baylor?
This research is supported by the Department of Energy grant DE-SC0007861.
List any publications you might like to feature.
https://arxiv.org/abs/2205.09597
*This paper is accepted to be published in the Physics Letters B journal soon.