Experience for Undergraduates Program |
UC Davis Physics and Astronomy Department
June 12 to August 20, 2022
Dr. Chiang's laboratory uses high-resolution microscopy to study the surfaces of metals deposited on both semiconductor and metal substrates. This work improves our understanding of two-dimensional materials growth and transformation, which are of technological importance in semiconductor devices, magnetic disks, and heterogeneous catalysis. Understanding how the surface orders during the processes of surface reconstruction, adsorption of atoms and molecules, and phase transformations allows better control of the surface structure and properties. Dr. Chiang's group has recently measured the unusually high rate of mass transport of Pb atoms during island formation at 220-283K on Ge(111). An REU student will work with a graduate student in growing thin films of metals on semiconductors and imaging their surface changes at the nanometer to micron scale. The student will learn to operate sophisticated ultrahigh vacuum surface equipment: either a low energy electron microscope for real-time measurements at 10 nm lateral resolution of surface dynamical processes as a function of both temperature and adsorbate coverage, or a variable temperature scanning tunneling microscope for atomic-scale imaging of nucleation and growth at steps and defects. The student will also use image processing software to analyze the measurements.
Dr. Curro's group studies the behavior of strongly correlated electron materials at low temperature using Nuclear Magnetic Resonance (NMR). There are numerous cases in the natural world where the collective behavior of a group differs dramatically from that of the individual particles. A prime example is the flocking of birds, which cannot be understood by investigating a single bird. These beautiful and unexpected phenomena are known as emergent behavior, and play a role in all realms of science, from the behavior of animals and people, to the quantum mechanical realm of the electron. In some cases electrons in condensed matter exhibit behavior typical of individual particles, but they can also do unexpected and surprising things. Superconductivity, for example, arises because of interactions between electrons that enables them to enter into a new quantum phase of matter. The group uses NMR to investigate these new types of quantum behavior of electrons, in materials such as heavy fermions, iron pnictides, and transition metal oxides. An REU student can participate in hands-on or computational aspects of the work.
Dr. Taufour's group designs, grows, and studies new materials with bizarre ground states. These are often strongly correlated electron materials in which the interactions of many electrons give rise to unusual phenomena, sometimes with the potential for practical applications. These physical properties can be explored and controlled with low temperatures, high magnetic fields, and high pressures. An REU student will take part in the Taufour group's ongoing research efforts and learn how to grow single crystals of novel intermetallic compounds. The student will collaborate with other research groups at UC Davis to further characterize and understand the physical properties of the new crystals.
The Vishik group uses angle-resolved photoemission spectroscopy (ARPES) and other photoemission techniques, as well as ultrafast optics to learn about electronic structure and dynamics in quantum materials. Quantum materials are characterized by emergence, whereby the properties of a many-electron system cannot be derived in a reductionist manner from the properties of one electron. As a result, these materials often yield experimental surprises, which can be discovered with precision tools sensitive to electrons such as the ones in this lab. The emergent phenomena studied include unconventional superconductivity, strong electronic correlations, topologically protected electronic states, and exciton condensation. An REU student would study one of the materials systems currently under investigation (including but not limited to: copper oxide superconductors, transition metal dichalcogenides, 3D topological insulators, magnetic Weyl semimetals), and simultaneously learn about optical systems, ultrahigh vacuum systems, instrumentation programming, data analysis, cryogenic systems, and data analysis.
Dr. Yu investigates charge transport in low-dimensional materials using spatially resolved optoelectronic techniques. Irradiating a spot on the sample with a laser creates charge carriers. They move depending on sample characteristics and applied fields, and are detected as currents reaching fixed electrodes on the sample. By successively focusing the laser on different spots, his group can determine the lifetime and distance traveled by the excited carriers, and much more. One possible project for an REU student is to study hybrid halide perovskites for solar energy harvesting and light emitting devices. The other one is on topological insulators for spintronics and quantum computing. The student will have the opportunity of synthesizing materials, fabricating nano-devices, as well as optoelectronic measurements.
Below 2 Kelvin, liquid helium becomes superfluid, with unusual properties from zero viscosity to high thermal conductivity to quantized vortices. While helium is the only superfluid on Earth, neutrons deep inside neutron stars also form a superfluid. The behavior of vortices in the neutron superfluid may explain the observed glitches in neutron stars' rotation, where the angular momentum abruptly increases. Dr. Zieve's group is setting up an experiment to monitor a vessel of rotating superfluid helium for similar glitch behavior. If observed, the conditions for glitches to occur can be tested far more easily in the lab than by observing distant stars. An REU student will work on one or more of the mechanical assembly, electronics, and programming required.
Dr. Scalettar's group uses Quantum Monte Carlo simulations to study magnetic, metal-insulator, superfluid and superconducting transitions in condensed matter and in atomic condensates. Projects generally involve studying a simple model to see if it can capture the qualitative physics of a particular experimental system. Typically an REU student begins by learning some of the fundamentals of the Monte Carlo method and statistical mechanics before learning about an open question in the field and writing a research code to address it. (An introductory college programming class provides sufficient background.) Dr. Scalettar's group includes postdoctoral researchers, graduate and undergraduate students with whom the REU student can work. Work of past REU students can be found here:
Dr. Singh's project involves series expansion methods, such as high-temperature series expansions or expansions in coupling constants, which provide controlled ways to study thermodynamic properties of macroscopic many-body systems. They are straightforward to calculate and analyze, and useful for understanding a variety of systems and experimental probes, including magnetic susceptibility and specific heat of spin models, spin-wave spectra of magnetically ordered phases, critical phenomena near quantum phase transitions, and quantum entanglement in many-body systems. A summer project will focus on one of these problems. The student will learn and apply certain expansion methods. To complete the project within the REU timeframe, the student should have some prior knowledge of quantum mechanics and computer programming.
With the nuclear group's experiments running at Brookhaven's Relativistic Heavy Ion Collider (RHIC) and at the Large Hadron Collider (LHC) at CERN, an REU student will mainly do calculations and data analysis. As one example, the production of hadrons in heavy ion collisions at RHIC has been parameterized as a function of the number of participating nucleons and the number of binary collisions. These numbers are useful when comparing measured quantities as a function of the centrality of the collision to calculations done for the same centralities. Unfortunately, neither of the numbers can be measured directly in the experiment. Instead their values are obtained by comparing the measured distribution of charge multiplicity to the corresponding distributions obtained from phenomenological Glauber calculations. Applied to nucleus-nucleus collisions, Glauber theory calculates cross-sections from quantitative considerations of the geometrical configuration of the nuclei. An REU student will write, compile and validate code for a Glauber calculation. Ultimately, from a probability distribution for nucleons within the nucleus (based on the measurements of nuclear matter density) and a fundamental cross-section for nucleon-nucleon collisions, the code will calculate the numbers of participating nucleons and binary collisions as a function of impact parameter. Time permitting, the student can apply phenomenological models to obtain the charge multiplicity and compare the results to measured distributions.
The Crocker Nuclear Laboratory, supervised by Dr. Prebys, is adjacent to the Physics Building. It houses a cyclotron with proton beams tunable from 4 MeV to 67.5 MeV. This is a rare energy range for today's machines, and the machine has several specialized uses, from simulating radiation effects of outer space to medical treatment via proton therapy. This leads to numerous unique opportunities for hands-on experience for undergraduates, who can participate in all aspects of planning, simulation, data taking, and analysis. One possible project for a student working with Dr. Prebys is to measure the energy-dependent production cross section for protons on various nuclear targets, which surprisingly is unknown for many materials. The student will insert thin foils of the target material in a stack of aluminum plates, which lower the beam energy to the desired value. After irradiation the student will remove the foils, assay them with a sensitive photon detector, and identify the characteristic spectra of the daughter particles of interest.
Hamiltonian truncation is an approximation in quantum mechanics that involves truncating the space of states to a finite-dimensional vector space and numerically diagonalizing the Hamiltonian, which becomes a finite-dimensional matrix. This approximation scheme goes back to the early days of quantum mechanics, where it is known as the Rayleigh-Ritz variational method. In recent years, this approximation has been applied to study quantum field theories where weak coupling expansions fail. In this project, the student will begin by using Hamiltonian truncation to numerically analyze simple quantum mechanical models defined using constraints. These are relevant for the application of Hamiltonian truncation to gauge theories. Depending on the background knowledge of the student and progress made, the project can move on to analyzing simple quantum field theories in 2 spacetime dimensions. Students should have a solid background in quantum mechanics and some experience in scientific computation, preferably using Python. Some exposure to quantum field theory is useful, but is not an absolute requirement.
Dr. Jones studies how galaxies form in the early universe and evolve over time, using the world's most sensitive telescopes. His group studies gravitationally lensed galaxies which appear larger and brighter on the sky thanks to strong magnification, allowing resolution of their spatial structure even at great distances. From spectroscopic observations they address several topics including the formation of the first galaxy disks, the cycle of gas into and out of galaxies, and the distribution of heavy elements. An REU student will work on one of these aspects using data collected from Keck Observatory. Familiarity with computer programming and some knowledge of statistics, including curve fitting, is strongly preferred.
Understanding the constraints on cosmological models from cosmological data, such as temperature and polarization power spectra of the cosmic microwave background, often requires computations that require tens to hundreds of cpus working for hours to tens of hours. The bulk of this time is spent solving the coupled Einstein-Boltzmann equations to produce model spectra at tens of thousands of locations in the parameter space. A student will use convolutional neural nets to train an emulator to produce such spectra and then apply it to estimating constraints on cosmological model parameters from data from sky surveys made with the South Pole Telescope equipped with its third-generation camera (SPT-3G), as well as other publicly available data. The expected great reduction in computer resources required will allow for rapid testing of impacts of various sources of systematic error on our constraints on cosmological parameters and model spaces.
Dr. Richter uses high-resolution, infrared spectroscopy to study molecules, particularly in star and planet forming regions. The molecules can be diagnostics of temperature, gas motions, and chemical processes. His work involves analyzing observations from current instruments at observatories such as SOFIA and the Gemini-North 8m, and developing future instruments for the 30m telescope and a possible space mission using an immersion grating. Generally, an REU student might reduce existing data, develop analysis tools, or investigate potential future observations, such as simulating observations of an extrasolar planet atmosphere. A student interested in building instruments could work on preliminary designs. Familiarity with computers and programming languages is a must.
Dr. Wetzel's group uses the nation's most powerful supercomputers to simulate the formation of galaxies, including the physics of dark matter, gas hydrodynamics, star formation, and stellar evolution. They use these simulations to model the formation of our own Milky Way galaxy and its low-mass satellite galaxies. An REU student will work on a project to model the orbital and star-formation histories of these satellite galaxies, to explore how they can help us understand the early Universe during the epoch of reionization. Familiarity with Python, including data visualization with Matplotlib and array manipulation with NumPy and SciPy, is strongly preferred.