One way to obtain plasma is by using a Direct Current (DC) discharge. Plasma is an ionized gas, meaning the separation of positive ions and electrons in a gas. There are three main variables when it comes to a DC discharge configuration. A gas forms into a plasma in an isolated space of low pressure between 2 electrodes, a cathode and an anode. Voltage must constantly be applied across the cathode and the anode to maintain the plasma. The initial voltage needed to initiate the separation of electrons and protons in a gas to produce a plasma is called the breakdown voltage. Our study investigates the configuration of a DC discharge plasma and the correlation between electrode separation, breakdown voltage, and pressures in a DC discharge environment. We constructed an environment consisting of long oval glass tube housing an anode and cathode on each side. A vacuum pump is attached to the glass container to extract air to reduce pressure in our glass tube. To maintain an ideal pressure, we established a concealed air tube connected to our glass tube with a fine adjust valve to let air into our glass tube at the same rate as our vacuum pump extraction resulting in a stable low pressure in our experimental configuration. We designed and conducted a series of tests to investigate the properties of a DC plasma formation. Moreover, we wanted to establish evidence of the Paschen Curve, which relates the breakdown voltage and the product of electrode distance and pressure in DC discharge. We experimentally determined the optimum pressure and electrode separation distance product for plasma breakdown in air and Argon gas. DC plasmas can be utilized as sputter sources to deposit thin films for solar panels; characterizing the breakdown voltage is significant at low pressures and short spacing to control the sputtering rate.

In the human immune system, there is a coevolutionary arms race occurring between pathogens and the host. Pathogens, especially viruses like HIV and SARS-CoV-2, evolve to escape the immune challenge presented by the human immune system. In return, the human immune system can re-organize and through processes that resemble Darwinian evolution, produce novel antibodies that target and neutralize the evolved pathogens. However, it is unclear who leads and who follows in this coevolutionary arms race. I introduce a bipartite, Markovian model to study a coevolving network of species and investigate causality in stochastically evolving systems. My results include novel analytical expressions for observables that discern causality, e.g., the rate of change of partial mutual information, and characterize how causal relationships change with the dimension and topology of the network. I compare the theory to simulations and describe statistical features of these processes. The tools I develop will be useful for distinguishing drivers of evolution in fitness seascapes and, more broadly, detecting causality in any type of dynamic network that undergoes nonequilibrium stochastic dynamics.

The trapping of individual ions has allowed physicists to control and observe otherwise inaccessible phenomena. Ion traps have enabled the most precise measurements of fundamental physical constants, mass spectrometry for chemical characterization, atomic clocks that would only lose a fraction of a second over the entire age of the universe, and the direct observation of many core concepts in quantum mechanics. Many crucial developments in ion traps occurred here at the University of Washington in the group of Hans Dehmelt, who shared the 1989 Nobel Prize in physics for that work. Today, techniques in ion trapping continue to be developed because trapped ions are one platform for creating qubits in quantum computers. With the growth of quantum information science in academia and industry, there is a need for inexpensive, scalable educational labs to introduce students to concepts in quantum computing. To fill this need, we developed a reproducible lab, which demonstrates key concepts in ion trapping. Our process utilized, first, a comparative approach with reference to literature and, second, iterative improvement on built components. The lab consists of two, independent quadrupole traps: a four-rod trap and a planar five-rail trap. To reduce cost and complexity, we trap charged particles with 25 µm and 50 µm diameter, rather than atomic ions. The particles are trapped in air, at atmospheric pressure. Due to the damping forces provided by this background gas, the trapped particles are easy to control. The result of our project is a lab capable of several experiments, including controlling the number of particles trapped through voltage modulation at a constant frequency, studying the phase transition between one- and two-dimensional Coulomb crystals, exploring micromotion compensation, observing two- and three-particle secular modes, and demonstrating particle shuttling along the trapping axis of the planar trap.

Trapped ions are one of the promising candidates for an operating quantum computer. Ions trapped in an electromagnetic trapp serve as a physical qubit, where the qubit states are manipulated by applying lasers to the system. As quantum computers use quantum gates with a given precise angle of rotation of the qubit state within the Bloch sphere, applying a laser with very narrow bandwidth is essential for minimizing errors, and thus stabilization of laser frequency is a required process for trapped ion qubit control. In our project, we stabilize the 1762 nm InfraRed fiber laser by using an optical cavity lock, where we obtain the resonant frequency of the cavity by measuring the intensity of the laser across the Fabry-Perot cavity, while varying the laser frequency. However, this model cannot distinguish between the laser intensity noise and the laser frequency noise. To address this, we eliminate the intensity noise by analyzing the signal reflected back from the cavity, where we observed a frequency dependent signal which reaches zero at resonance, allowing us to stabilize the laser to the desired frequency. A deeper understanding of the laser stabilization techniques may help us to minimize the trapped ion qubit control errors.

Hexagonal boron nitride (hBN) is essential for nearly all nanoscale two-dimensional (2D) devices, as its flatness and wide bandgap make it an ideal dielectric for applying electrostatic gating. At high electric fields, hBN undergoes electrical breakdown where large currents flow to the sample, damaging the device. Gating fields are therefore limited by hBN’s dielectric strength. While the dielectric properties of hBN have been studied previously, the preparation of those samples differed from that used in practice. I conducted an experiment with the help of my advisors to understand how hBN’s dielectric breakdown characteristics depend on sample thickness and temperature. I began by fabricating three hBN devices, each containing multiple regions of different thicknesses. By measuring the current and varying the voltage on a given region, I was able to locally probe the hBN’s electric breakdown characteristics with thicknesses ranging from 5 to 24 nm. I tested each device multiple times using a cryostat at a range of temperatures from 4 to 300 K. During initial measurements, I observed an increase in the breakdown voltage with temperature in hBN between 15 and 24 nm thick, conflicting with previous reports. I repeated these measurements with a finer resolution which yielded the same result. The thinnest hBN regions showed no temperature dependence, confirming the absence of systematic temperature effects. I am currently fabricating more devices to reproduce this temperature dependence and working with my advisors to find a theoretical basis for this observation. Understanding how thickness and temperature effect hBN’s dielectric strength will allow researchers to construct more resilient devices, facilitating the study of 2D materials at higher electric fields. Moreover, the study of defects in hBN remains an active subject of research for quantum information applications, and a probe of the capacitive properties of hBN may shed light on this topic.

A large composition of our universe remains unidentified. Ordinary ‘visible’ matter comprises 5% of the known universe whereas dark matter comprises 27%. The Dark Matter in CCDs (DAMIC) research team hypothesizes that charge-coupled devices (CCDs) may be able to detect weakly interactive massive particles (WIMPs) as a possible candidate for dark matter. The silicon CCDs gather information by measuring the ionized charge from collisions between its silicon atoms and external particles, yet these measurements can become inaccurate in the presence of noise. The leading noise source is leakage current across the CCDs, which can be mitigated by operating the experiment at 100K. Furthermore, CCD performance is highly dependent on temperature so we must assure a constant temperature across the CCDs. Obtaining this temperature is essential in the successful implementation of the DAMIC-M experiment. We started with multiple thermal tests on a single mock CCD module housed in a copper box to ensure proper cooling. We aimed for minimal temperature differences of the box and across the silicon once they reached 110K temperatures. Our initial tests showed large temperature differences leading us to make modifications to the arrangement of the module in the box. Once these modifications were implemented, a consistent trend of minimal temperature differences between the box and silicon was present. Following this development, we began further testing with a new box which holds 13 mock CCD modules. This new arrangement mimics the final DAMIC-M experiment which allows for a more accurate representation for future thermal tests. 

Radon in high concentrations has been proven to be one of the world’s leading causes of lung cancer. Climate change is an ongoing problem that affects the environment and human beings; however, there is not yet a widely known relationship between radon exposure and climate change. Our research aims to find a correlation between climate change and risk of radon exposure. We are reviewing how radon exposure potentially increases through the lens of greenhouse gas emissions, melting ice caps, and human habits based on increased global warming effects. In our literary review, we are comparing how radon is measured, finding the limitations of each technique and which technique is best suited to measuring radon in air, soil, and water. We are also working with our collaborators overseas to understand the radon concentrations in soil in Hebron, Palestine. We will investigate our hypothesis that radon exposure will increase with climate change.

Climate change is a growing threat to communities worldwide, with extreme weather events like droughts and wildfires causing food insecurity and affecting the lives of millions of people. Despite the availability of research that describes the consequences of climate change, there is a lack of urgency in the response to this crisis. To understand the barriers that inhibit action on climate change, a study was conducted on 206 STEM students at the University of Washington. The study surveyed the students to identify factual and conceptual barriers to addressing climate change. We distributed questionnaires through social media and undergraduate classes. I analyzed survey responses to compare and contrast the concern levels for ecocentric and anthropocentric consequences of climate change. The findings of the study indicate that environmental education was not associated with more climate change knowledge, and students were more concerned with ecocentric impacts and anthropocentric consequences that directly impact basic human needs like water, food, and shelter. We aim to develop a teaching tool that addresses the conceptual barriers identified in their research. The results of the study emphasize the need to shift the focus towards addressing the immediate impacts of climate change that affect human well-being. The lack of urgency in the response to the climate crisis highlights the need for more education and action to mitigate the effects of climate change.

Two-dimensional van der Waals materials are a class of materials that can be exfoliated into thin layers. Exotic properties can emerge in these thin-layer materials, such as electric polarization. In this presentation, we report the observation of irregular piezoelectric domains in natural flakes of thin-layer tungsten disulfide, a transition metal dichalcogenide (TMD), detected with piezoresponse force microscopy (PFM). These domains also exhibit different surface potential when analyzed with kelvin probe force microscopy, which is consistent with our PFM observation. We attribute the emergence of these intriguing domains to the formation of opposite R-stacked regions with inversion symmetry breaking, as opposed to inversion-symmetric H-stacked layers. To investigate this further, we performed reflectance measurements in a dual gated device with strong position dependent hysteresis, indicating different built-in potentials of the domains. Our work provides a new avenue to engineer electric polarization in thin-layer materials, which will contribute to applications such as information storage.

The first direct observations of gravitational waves (GWs) by the LIGO and Virgo interferometers in 2016 confirmed the predictions of general relativity for the dynamics of black hole mergers, and has since advanced the field of GW astronomy. These interferometers focus on detecting GWs in the Hz-kHz frequency range. There are no known astrophysical objects that emit beyond the 10 kHz range, motivating an interest in detectors for frequencies above this range which could lead to the discovery of new physics beyond the Standard Model. Theoretical potential sources of these high frequency GWs include mergers of sub-solar mass objects such as primordial black holes (PBH) or boson clouds from PBH superradiance. Resonant microwave cavity detectors such as the detector used in ADMX are shown to be sensitive to GWs in the GHz range, and generate a coherent electromagnetic (EM) signal through the GW-EM coupling if the GW frequency matches the cavity resonance frequency. To detect these signals, I use a matched filtering technique on power measurements collected from the cavity during ADMX’s Run 1B data acquisition period in 2018. I generated templates for a range of frequencies based on an expected signal a PBH merger would emit and convolved it with the data to find similar signals. This analysis may confirm or further constrain the existence of PBH sources within the GHz frequency range. PBHs could comprise a significant fraction of cold dark matter, and its detection allows us to probe the density fluctuations and phase transitions of the early universe with implications in galaxy formation and supermassive black hole formation.

Blackbody radiation is the name given to the phenomenon that makes warm objects radiate—it explains why a hot stove glows red, or why the sun is so bright. This radiation is well-understood in physics, but some theories of new particles suggest that at low temperatures there will be small deviations to the equations that normally predict the amount of power radiated by these bodies. I am conducting an experiment designed to search for these deviations. This experiment will involve measuring the radiated microwave power from a resonant cavity and a resistor as they are cooled to liquid nitrogen temperatures; standard physics predicts these power values scale linearly with temperature, which is the expected result. However, some expanded standard model theories predict a deficit of power at low temperatures due mixing of photons with new light particles. This research will help refine our understanding of blackbody radiation at low temperatures, including our understanding of the results from the UW Axion Dark Matter eXperiment (ADMX).

Neutrinos are fundamental particles involved in many important universal processes; however, because they only interact via the weak force and gravity, reliably detecting neutrinos directly is notoriously difficult. A new strategy is to study neutrinos through interactions with enhanced cross-section, like coherent elastic neutrino-nucleus scattering (CEvNS), in which the neutrino interacts with the nucleus as a whole (coherent) while conserving kinetic energy (elastic). However, due to the low energy of nuclear recoil in CEvNS, not all nuclei can produce detectable recoil if the recoil energy is on the order of the noise fluctuations in other background radiative processes, as recoil energies become indiscernible. Sodium iodide (NaI) is a candidate for detectable recoil, and I am characterizing the background spectrum of NaI crystals to see if NaI has low enough rates of background processes to be used in CEvNS studies. I analyzed previously collected NaI background spectra to calibrate the event energies and to perform a waveform analysis to distinguish physics pulses from electronics noise. The resulting spectra are used to determine the background rates in the crystals. These routines were converted into scripts to automate the same analysis for future data. Measuring the energy of CEvNS nuclear recoil can help characterize neutrino-quark interactions, which the coherent nature of CEvNS amplifies, providing unprecedented sensitivity to searches for non-standard interactions between neutrinos and matter. Improved characterization of CEvNS also allows for novel checks of predictions made by the Standard Model of particle physics, and has broader applications in understanding supernovae (which produce large quantities of neutrinos) and searches of dark matter candidates that may interact with neutrinos.

The axion is a hypothetical elementary particle beyond the Standard Model which serves as a candidate for dark matter, a mysterious form of matter that accounts for about 85 percent of total matter in the universe and is difficult to detect by conventional means due to its noninteracting nature with electromagnetic radiation. The ADMX (Axion Dark Matter eXperiment) is an axion haloscope which uses a strong magnetic field to convert axions inside a microwave resonant cavity into microwave photons that could be registered by the detector when the photon signal frequency is the same as the cavity’s resonant frequency. However, within a dataset, the axion signal can be hard to estimate and pinpoint due to the presence of RFI(radio frequency interference).In our research, we developed a new two-parameter statistical model that accounts for RFI appearance and estimates both the axion signal and RFI from a dataset. We show that contrary to the old one-parameter statistical model, which is currently utilized for processing datasets and does not account for RFI appearance, the new two-parameter model yields more accurate and consistent axion signal results regardless of RFI magnitude while the old one-parameter model fails to provide reasonable results at large RFI frequencies. The new two-parameter model would benefit ADMX by providing greater overall accuracy and precision for the search of axion dark matter signals and faster scan speeds.

The ForwArd Search ExpeRiment (FASER), located 480 m downstream from the ATLAS beam interaction point, is designed to study light weakly-interacting long-lived particles (LLPs) and neutrino interactions. One of the main components of FASER, used to detect the decay products of LLPs, is the four tracking stations, each with three layers and 24 semiconductor tracker (SCT) modules. Particles leave electronic hit signals on SCT modules, and particle tracks reconstructed from hits are used for analysis. To exploit the excellent intrinsic resolution of the silicon microstrip detectors, high-accuracy alignment is required. A local χ2 alignment algorithm is designed and tested on both Monte-Carlo and collision data to perform software alignment on the tracking stations. By aligning the FASER tracking stations, the performance of track reconstruction from detector hits is substantially improved, indicating reconstructed tracks are more likely created from their corresponding hits. Furthermore, the alignment allows researchers to match particle track information with other detectors. For the showcase for my research, the software alignment shows promising results when compared to survey data.

Nature uses only four nucleobases to store genetic information in DNA. However, additional synthetic bases which use Watson-Crick pairing have been developed and are known as non-standard bases (NSBs). NSBs P, Z, B and S incorporated alongside standard bases A, G, C and T compose DNA strands using a new genetic alphabet. Nanopores offer the potential capability for direct single-molecule sequencing of DNA containing non-standard bases (NSBs). Using a voltage gradient, DNA strands were directed through a nanopore, the biological membrane protein MspA, while we measured the ion current through the pore over time. In studying the effect of NSBs on the ion current through the pore, we observe current measurements corresponding to the Z base have a different noise profile compared to other bases. We hypothesize this noise may be associated with pH-dependent protonation of the base. To test this hypothesis, we conducted experiments with identical sequences in buffers of pH 8 and pH 7, as Z is known to have a pKa of 7.8. I analyzed the noise from the ion current signals to look for signs of protonation. I found increased current noise values associated with the Z NSB in pH 7 compared to pH 8, while the canonical A base had no change in noise values from pH 7 and pH 8, supporting the hypothesis that the increased current noise is due to protonation of the Z base. In addition to indicating potential sensing abilities of nanopores for probing protonation kinetics of DNA, this research contributes to a better understanding of the fundamental mechanisms that control the currents in nanopore sequencing of DNA.

One of the most cutting-edge instruments to probe the origins of our universe is the Murchison Widefield Array (MWA), a low-frequency telescope array located in Western Australia. Arrays like the MWA are best equipped to detect light from the Epoch of Reionization (EoR), which started about 400 million years after the big bang. Throughout this epoch many of the universe’s first stars and galaxies began to form, reionizing the surrounding neutral hydrogen gas. Understanding this period of cosmic history is essential because it reveals the properties of the first stars and galaxies and also impacts modern-day astronomy, for example by providing constraints on dark matter and information about present-day star formation. New ultra-wide angle images are being processed, hopefully giving us snapshots of the early universe. For this project, I searched and corrected for near-horizon contamination from astrophysical and anthropogenic radio emissions not caught by our flagging algorithm SSINS. I read processed Healpix data cubes into a jupyter notebook and Fourier transformed the data in two directions (the XX and YY polarizations) so that I am able to pick out radio frequency interference. After doing this for multiple images, I analyzed whether the consistent appearance of interference is significant enough to reevaluate the flagging software we use. By finding and correcting contamination that wasn’t flagged by SSINS, I was able to support the effort to create the world’s deepest reionization power spectrum measurement, the most powerful tool we have to probe the Epoch of Reionization. I hope to find and correct enough images of radio frequency interference so that we can improve the SSINS pipeline.