The Nab experiment at the Spallation Neutron Source aims to measure non-polarized beta decay correlation parameters, which will be used for precision tests of the Standard Model. The apparatus is installed on the Fundamental Neutron Physics Beamline and will be taking data over the summer. One of the vital systematic tests is to make sure no contribution from polarization observable exists. To this end, a dedicated series of measurements where the beam will be actively polarized with novel techniques will be performed. The successful student will assist in planning and preparing for the measurement, carrying it out, and participating in the data analysis.
Advisor: Professor Nadia Fomin
Topological insulators (TIs) are exotic quantum matters that become metallic
only on the boundary. The surface/edge
conductive channels of TIs are believed to be a necessary outcome of the
topological properties of bulk electronic wavefunctions. However,
recent studies have revealed violations of this 1-to-1 relation between boundary
metallicity and bulk topology in out-of-equilibrium quantum systems.
In this project, we will explore such
unconventional topological physics in nonequilibrium systems subject to a
time-periodic drive. A major goal is to reveal
whether and how spacetime symmetries can protect fractionalized quasiparticles
in these systems. The students will have hands-on
experience in model design of quantum systems, numerical simulation, and
symmetry & topological analysis.
Advisor: Professor Ruixing Zhang
The CMS experiment at CERN will start colliding protons again this year, opening up new opportunities to search for physics beyond the Standard Model. Students will have an opportunity to help design these searches, studying triggers that make sure our detectors capture the particles we’re most interested in. We also have projects related to the design of future LHC detectors, focusing on an upgrade to the CMS tracker. In addition, there are opportunities in the group to influence where our field may head next by doing studies for a future muon collider. Projects will involve programming, so students are encouraged to build familiarity with python and a unix terminal in advance of the summer.
Advisor: Professor Tova Holmes
The UTK group is involved in the development of neutron detectors for the future FRIB Decay Station and its present incarnation, FRIB Decay Station Initiator https://fds.ornl.gov/initiator/. The FDSi is currently the primary detector to study decays of exotic nuclei at the Facility for Rare Isotope (FRIB) https://frib.msu.edu/. Our focus is on developing a new generation system that uses neutron interaction tracking to improve the energy resolution of the neutrons. Neutron-time-of-flight measurements also require the implementation of fast-response pixelated implant detectors. The summer projects will include characterizing pixelated detectors constructed using GAGG inorganic scintillators and implementing new scintillator materials for neutron detection.
Advisor: Professor Robert Grzywacz
High-energy quarks and gluons lose energy as they traverse the hot, dense matter created in high energy nuclear collisions. We study what happens to this energy, investigating measurement techniques and making comparisons between data and models. This project will involve using a high performance computing cluster to run model studies and may involve using machine learning techniques to understand methods better. Students will learn how to use tools such as Rivet for conducting analysis and will make presentations to working groups in the JETSCAPE, PHENIX, or sPHENIX collaboration, as appropriate.
Advisor: Professor Christine Nattrass
We use a scanning tunneling microscope (STM) to probe various kinds of quantum materials in the atomic scale. By analyzing the atomic and electronic structure acquired by STM, it is possible to reveal the novel quantum states in these materials. In this project, students will be involved in three tasks: (1) use STMs to acquire atomic structure of materials; (2) modify materials properties by manipulating individual atoms; and (3) analyze STM data with advanced statistic tools to extract hidden orders.
Advisor: Professor Wonhee Ko
In preparation of a new experiment at the HFIR reactor at Oak Ridge searching for mirror dark matter neutrons, two solenoidal magnets are being constructed at UT. Experiment are expected to start in Fall 2024. The magnet commissioning and calibration work are planned for the summer. This work will be performed at UT and at ORNL. Participation of an undergraduate student in this commissioning work is highly desirable. After completion of the commissioning, the student will have a chance to participate in the physics experiment at the HFIR in the Fall and in the subsequent data analysis, and be the author of the published paper with the results of the measurement.
Advisor: Professor Yuri Kamyshkov
A basic building block of life is a cell. It hosts DNA and myriad other complex molecules such as proteins, lipids, and RNA species. How these molecules arrange in space and time in a coordinated manner to make a cell a living entity is yet unclear. Equilibrium statistical physics can explain some of their organization, but non-equilibrium processes also play a significant role and is a hallmark of life. This summer project will combine state-of-the-art microscopic measurements and image analysis, including AI-based methods, to understand how DNA is organized in a bacterial cell. This knowledge is important in designing next-generation antibacterial drugs and synthetic cells.
Advisor: Prof. J. Mannik
The CMS Experiment at CERN is upgrading its silicon tracking detector for the High-Luminosity LHC era. This project will involve participation in the assembly, control, calibration, and QA/QC for tracker modules at Fermilab. The project will require training in programming in C++ and python, analog and digital electronics, and the physics of particle detection. This work will involve working closely with the team at the Silicon Detector Facility at Fermilab, in Batavia, IL.r.
Advisor: Professor Larry Lee
Protons and Neutrons are constituents of most observable matter in the universe. Understanding the origin of nucleon spin has been an overarching challenge for nuclear physics since the 1980s. To probe this experimentally with a polarized electron beam, spin-polarized nuclear targets are required. We have a program if such experiment approved at the Thomas Jefferson National Accelerator Facility. This summer, the successful student fellow will assist in setting up a lab at UT to polarized 3He gas using Metastability exchange optical pumping method. The work will include characterizing the cell, mapping the magnetic field, laser testing, writing code to control equipment and optic alignment.
Advisor: Professor Dien Nguyen
The gravitational wave emission for two stars of nearly identical mass but different stellar structure and, therefore, different explosion history. Gravitational waves may allow us to disentangle the two scenarios when stellar mass becomes a degenerate parameter and where, in this regard, electromagnetic observations are inconclusive.
Advisor: Professor Tony Mezzacappa
The gravitational wave emission associated with anisotropic neutrino emission in a series of models initiated from the same progenitor mass but using different nuclear equations of state. The gravitational wave “memory” in each of these models may provide a signature of the underlying equation of state and, consequently, the underlying high-density, neutron-rich nuclear physics.
Advisor: Professor Tony Mezzacappa
The combination of an abundance of computational power and intense research and industry efforts has brought enormous advances in machine learning (ML) in the last decade. ML techniques have achieved best-in-class performance on a broad variety of problems, especially in computer vision and natural language processing. The application, adaptation, and development of ML techniques for the natural sciences, especially for material science and photonics, is an extremely exciting prospect that is now being pursued widely. The recent ML work of our group has shown that the topology of the bulk crystal is well-captured by machine-learned chemical rules called topogivity.
In this project, we will apply ML techniques to collect and classify experimental results (for example superconducting Tc) in published journal papers via natural language processing, and explore new physical and chemical rules in computationally challenging problems across superconductivity and magnetism. We will exploit techniques from self-supervised and transfer learning. learning. High-performance GPU workstations will be provided, with access to large-scale GPU clusters if needed.
Advisor: Prof Yang Zhang
The CMS experiment and the Large Hadron Collider will be upgraded to be able to search for particle reactions that violate of the current theory which is called the standard model. This program requires the development of new types of silicon pixel detectors. We characterize prototypes of these detectors with several measurements in the laboratory here at UT, and with particle beams at the Fermi National laboratory in Chicago. To obtain a comprehensive understanding of their performance, a machine learning algorithm needs to be developed. The candidate for summer research might also be able to participate in additional measurements with particle beams.
Advisor: Professor Stefan Spanier
Emergent phenomena in solid-state materials manifest low-energy excitations that mimic the behaviors of particles, serving the interest in both fundamental physics and functional materials. One example in this spirit is spin-ice in pyrochlore lattice, which has been identified as a Coulomb phase that hosts low-energy excitations behaving like monopolar magnetic charges. Recently, we have developed a new experimental method, namely time-dependent neutron diffuse scattering, to probe the slow dynamics of magnetic monopoles in spin ice. A completed dataset has been collected on the spin-ice compound Ho2Ti2O7, containing information on scattering intensity in three-dimensional momentum space with an added dimension of a pump-probe time stamp. We are looking for an undergraduate student to perform data analysis using the python-based software package (Mantid). The student will receive training for and exposure to the state-of-art methods to handle large-scale data, the research frontier of quantum magnetism, and the highly collaborative environment of modern experiments.
Tin (Sn) has two distinct phases: α-Sn with topological electronic structures and β-Sn with s-wave superconductivity. Low-temperature electrical transport is one of the promising methods to evidence the distinct electrical properties of the two phases, and Shubnikov-de Haas (SdH) oscillations (resistivity oscillations due to Landau level quantization) and superconducting features have been observed in α-Sn and β-Sn films, respectively. In this summer research, a series of thin films of pure -Sn, pure -Sn, and mixture of the two phases will be prepared, and structural, morphological, and electrical characterizations as well as transport studies will be carried out. Students will mainly participate in the low-temperature transport measurement and analysis of the SdH oscillations and superconducting features. Students will also gain hands-on experience in molecular beam epitaxy, ultrahigh vacuum systems, and various materials characterizations.
Advisor: Professor Joon Sue Lee
Strongly correlated bosons deposited on an atomic mono-layer substrate are an exciting playground to engineer two-dimensional quantum phases not possible in the bulk. It is known that the first layer of 4He adsorbed on graphene is a strongly correlated insulator, with subsequent layers displaying superfluid, and even possibly supersolid-like order. Recent experimental measurements have hinted at the possibility of an exotic hexatic phase in the second layer possessing intertwined superfluid and density wave order. In this project, large scale simulations will be employed to study the effects of corrugation in the graphene potential on the realization and stabilization of this exciting new state of matter. Students will learn about state-of-the art simulation techniques, high performance computing, and data analysis while working with an interdisciplinary team.
Professor Adrian Del Maestro
We model the deaths of massive stars in core-collapse supernovae with two and three dimensional simulations. Many of the most important observations, which can tell us if our models are correct, depend on the new atomic nuclei that are produced in the explosion. The student will assist in running our nucleosynthesis calculations and visualizing the results so that we may better understand the nuclear contributions from these exploding stars.
Advisor: Professor Raph Hix
Core-collapse supernovae (CCSNe), the explosions of massive stars, are
inherently 3D events, but simulations that contain the necessary physical detail
and resolution in 3D are computationally expensive and therefore rare.
Less costly 2D simulations suffer from artifacts generated in the
polar regions, around their axis of symmetry, that lessen their realism and
usefulness. Some prior 2D runs without the polar
regions (a wedge geometry) showed closer resemblance to 3D simulations.
The student will run several wedge models with CHIMERA and examine
the differences between 2D simulations of CCSNe with and without (wedge) the
polar regions with 3D counterparts to help determine if the 2D "wedge" models
are a viable alternative for computing large numbers of 2D models for extended
examination of CCSN physics and variation.
Advisor: Dr. Eric Lentz