Sulaiman Alvi

The question I aim to answer this summer is whether quantum machine learning can provide an advantage over classical machine learning techniques for certain high energy physics applications. Analyzing data from particle collider experiments involves distinguishing signal events, which correspond to the particle physics of interest, from background events. Currently, classical machine learning techniques are used to tackle many of these classification problems. However, these techniques often require large amounts of data to classify with a high degree of certainty. In the growing area of anomaly-detection searches, datasets may be small. This can lead to poor classification performance of classical machine learning models. Several recent results have shown that quantum machine learning can provide an advantage for data-limited classification problems. However, these works have applied quantum machine learning to situations where classical machine learning techniques are already sufficient. Over this summer, I plan to directly test the possibility for a […]

Gabriel Perko-Engel

Most iron, and much nickel-based superconductivity is found in the same region as a magnetically ordered state. The transition temperatures for these magnetic states have in turn been found to be strongly correlated with those of “nematic” phase transitions reducing the lattice symmetry from tetragonal to orthorhombic. Given the intersection between these nematically fluctuating regions and superconducting phases in so many unconventional superconductors, several questions naturally arise. This first of these is of course what connection exists between the nematic phase and superconductivity. But, beyond that, the origin of the nematic phase itself isn’t completely clear in and of itself. And the existence of the aforementioned magnetic phase creates a confounding variable, making it challenging to disentangle nematic from magnetic order in the effects on superconductivity. BaNi2As2 is a nematically ordered superconductor with no observed long-range magnetic order. Using resonant ultrasound spectroscopy (RUS), I hope to extract complete symmetry information […]

Justin Nelson

Fertility in women and across mammalian species requires a series of temporally coordinated neuroendocrine events by the circadian system in the brain. Disruptions to circadian timing across mammalian species from stress or environmental factors result in irregularities in the estrous/menstrual cycles, reduced fertility, and increased miscarriage rates. The proposed studies examine the role of neuroendocrine signaling events and circadian timekeeping in ovulation. Across mammalian species, ovulation requires timed neuroendocrine events organized by the master circadian pacemaker in the suprachiasmatic nucleus (SCN). Evidence points to E2-sensitive kisspeptin (Kp) neurons, potent stimulators of the reproductive axis that maintain their own circadian timekeeping, as the locus for estradiol (E2) and neuroendocrine signal integration. The preovulatory luteinizing hormone (LH) surge, the hormone signaling cascade required for ovulation, is triggered by timed neuroendocrine signals from the SCN to kisspeptin (Kp) neurons. Alterations in neuroendocrine signals to Kp neurons results in disrupted fertility. Findings from the […]

Julia Nicholson

Groundwater is essential to ecosystems in Sierra Nevada meadows. Flora and fauna depend on groundwater cycles for a reliable source of water. Climate change is expected to disrupt groundwater supply, so understanding precisely how groundwater responds to temperature change, and how groundwater affects surrounding flora is an integral part of protecting meadow ecosystems in the face of climate change. This summer, I will develop a mathematical model to analyze time series of meadow groundwater, in order to study the relationship between groundwater and the ecosystems it fuels. I will study what local factors influence how groundwater levels respond to temperature, and how vegetation responds to varying groundwater. I have the support of a graduate student, Jen Natalie, who collected this groundwater and greenness data, as well as Professor Albert Ruhi, who taught me all I know about time series analysis. As a mathematics major who is passionate about climate change, […]

Zaid Ahmad

I’m interested in developing computational methods to quantitatively describe the impact of natural selection on various traits and genes expressed in modern human populations. Detecting and inferring natural selection is central to understanding how populations of individuals have evolved over time. Advances in next-generation genomic sequencing technologies have made it possible to extract high-quality DNA data from ancient relics such as fossils. Specifically, I want to understand how this ancient DNA data can help us detect selection, and I’ll also be testing methods that I develop with real ancient DNA data from Europe. Combining both modern and ancient DNA samples into an analysis will allow me to paint a clear picture of how our genome has evolved in response to various environmental factors over the past ten thousand years. I’ll be developing scalable methods that can use both ancient and modern DNA data to accurately detect selection across hundreds of […]

Nicolas Anderson

1.1 billion years ago, Laurentia, the Craton which makes up majority of modern North America’s landmass, was rifting apart in the Lake Superior region and growing in the American Southwest. Both of these processes produce magma. As magma cools, the magnetic minerals within align with Earth’s magnetic field and these alignments can be used to determine the age of a rock (paleomagnetism). Similarly, small crystals formed within the magma can also indicate a rocks age (geochronology). There is a likely connection between the locations due to similar timing of emplacement and geochemical signals. Recent, high-quality data collected for Lake Superior indicate a high volume, short duration magmatic event 1096 million years ago, which is inconsistent with a typical rift (long duration, low volume). It is hypothesized that an upwelling magma plume encountered topography at the base of the crust, bifurcating it, sending some magma into the rift, with the rest […]

Orion Ning

Quantum field theory (QFT) — a theory describing subatomic particles as excitations of fundamental ‘fields’ — has long been established as the de facto framework for modern particle physics, yet it remains a topic riddled with open problems. Interacting QFTs in higher dimensions, particularly 6D, is one such problem, motivated by string theory, a highly theoretical mathematical model attempting to describe all of nature. These interacting QFTs have Lagrangians (precursors to ‘equations of motion’) that can probe M5-branes, which are objects of fundamental interest in string theory. However, the Lagrangians for these theories are susceptible to quantum anomalies, which are red flags indicating that a symmetry of classical physics is incompatible with quantum mechanics. Analysis of the behavior of these anomalies, and the quantum interactions they induce in the corresponding theory, can be explored by looking at their consequences in lower dimensions. My research will investigate the lower-dimensional behavior of […]

Novia Kayfetz-Vuong

In Ecuador, the Epipedobates clade of poison frogs (Dendrobatidae) have speciated in different climate zones (Tarvin et al., 2017). Poison frogs are aposematic; they possess colorations and markings that serve to warn predators of their toxic defenses. Determining poison frog species can be difficult due to aposematism, as possessing different color and marking patterns does not necessarily indicate a separate species (Tarvin et al., 2017). Thus, genomic level studies are necessary to understand ongoing gene flow, i.e., the introduction of genetic material from one species to another through interbreeding. Advances in next-generation sequencing (NGS) has allowed increased research on how climate change affects biodiversity and gene flow between species. Gene flow studies are important in evolution as they help us to understand the speciation process. The goal of this project is to understand how climate differences affect gene flow among neighboring poison frog species using genomic information. To do this, […]

Druv Punjabi

Type Ia supernovae (SNe Ia) are a category of exploding stars, and serve as one of the most important tools for probing our universe today. Because of their extreme and consistent luminosity, they are widely used to measure distances to faraway galaxies. Determining these large-scale distances allows a better understanding of the universe’s expansion, and thus of dark energy itself, the driver behind the expansion’s acceleration. Several recent studies have suggested that the luminosities of these supernovae can be better standardized if we factor in the properties of their host galaxies, such as the galaxy’s mass or age. This project aims to statistically correlate these properties with models of SNe Ia luminosities. We also pursue a new method of standardizing these luminosities, which would ultimately improve the cosmological applications of distance measurements with SNe Ia, advancing our understanding of dark energy.

Karthik Vegesna

Clathrin-mediated endocytosis is a crucial cellular event during which vesicles at the cell surface containing nutrients, receptor molecules, and viral proteins are formed and brought into the cell interior. The process works via the formation of a clathrin-coated vesicle which is internalized against membrane tension with the assistance of a branched actin network. In mammalian cells, this process is incompletely understood, especially at later stages of internalization. Mathematical modeling efforts have successfully been able to evaluate the mechanism by which actin filaments can generate force to spur internalization, but so far, only minimal models have been created. In order to fully understand and model the behavior of branched actin networks during internalization, it is important to add in additional proteins such as actin filament crosslinkers and cofilin, which would more accurately capture the mechanism by which force generation and internalization occur. This research aims to determine the impact of these […]