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Jung Research Group Part of the High Energy Physics Group

High Energy Physics

Research

The Jung group focuses on research related to the analysis of vast data sample using cutting-edge analysis techniques and Instrumentation R&D to develop future detector for high energy physics. We are also engaged in quantum algorithm development at the intersection of quantum physics and advanced data analysis techniques, including machine learning on quantum computers for high energy physics and business applications. We offer UG research opportunities in all areas at all times, just get in contact with the Jung group.

Data Analysis

The focus of our research is to shed light on the question of what stabilizes the electroweak scale or more precisely the Higgs mass. A future more complete theory would allow to calculate the Higgs mass and in our current best understanding (known as standard model of particle physics) the Higgs mass would receive quantum loop corrections. The loops are in fact dominated by top quarks since these are the most heavy known elementary particles.


Figure 1: Loop corrections to the Higgs mass
are dominated by top quark loops.


The loop corrections shift the Higgs mass effectively to the enormous Planck scale. However, the experimentally observed Higgs boson has a mass of about 125 GeV, much lower than the Planck mass either potentially indicating beyond the standard model effects to cancel these corrections or an incredible fine-tuning in that future theory.

We search for beyond the standard model effects by employing the top quark sector which is closely tied to the Higgs boson sector. An elegant way of avoiding the loop corrections in a future theory is by the exact cancellation of these loop corrections due to a partner of the top quark. Members of the group carried out direct searches for vector-like top quark partners up to highest achievable mass scales (see a Preliminary result here: CMS-B2G-16-002). In the absence of clear indications in the early 13 TeV data the Jung group has shifted the research focus more and more to search indirectly for any signs of deviations from the standard model via precision measurements in the top quark sector.

 


Figure 2: The unfolded distribution of the azimuthal
opening angle between two leptons in top quark events.

An example being the analysis of top quark spin correlations via a multi-differential cross section measurement, which allows to pinpoint any non-SM contributions provided the systematic uncertainties are well understood and under control. An example being the distribution of the opening angle of the decay leptons steming from the decay of the top quarks, refered to as |Δφ(ll)| in Figure 2. This and other highly precise differential distributions measured by CMS are sensitive to the spin correlation and polarization: PRD 100 (2019) 072002. Results are used to challenge the modeling of how top quarks are produced as predicted by the Standard Model theory.


Please take a look at the Open Positions/Contact page for Ph.D. and undergraduate research opportunities related to CMS data analysis in the group. Undergraduate researchers are an integral and critical part of the research effort.

Applied Physics: AI/ML & Quantum Algorithm Development

Automation methods for gamma ray spectroscopy and data analysis

This applied physics research aims to enhance gamma-ray spectroscopy analysis using machine learning. Traditional methods struggle with complex data interpretation due to limited or missing theoretical predictions. By integrating machine learning into "Radware", a widely used spectroscopy analysis program, we aim to accelerate the identification of isotope level schemes and uncover transitions that may have been previously overlooked. The project involves training algorithms with synthetic toy spectral data generated through Monte Carlo techniques, ultimately improving the efficiency and accuracy of nuclear spectroscopy analysis.

Supply Chain and Inventory Management

The Jung group is leading activities to solve real-world problems such as optimization, data science, and optimizations by employing quantum computing resources. These resources are either quantum annealing system (DWave) or also the Ion-Q & IBM-Q gate-based systems.

Purdue Quantum Computing Landscape

The Purdue Quantum Science & Engineering Institute (PQSEI) provides a stimulating environment to foster the development and ideas of practical and impactful aspects of quantum science. The Jung group is engaged in research and development of quantum algorithms that solve computational challenges arising in times of the High-Luminosity LHC phase. We currently work with a quantum annealing system (D-Wave) and also use Ion-Q, IBM-Q gate-based quantum computer hardware platforms as well.
An overview of quantum computing activities can also be found here: Quantum Informatics. We are members of the Midwest Quantum Collaboratory in the research area of Quantum Algorithms, Quantum machine learning, Data Analytics, and also Quantum sensor development.
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