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Title: Candidate human landing sites within 10 degrees of Mars’ equator
Description:
Humans are expected to begin journeying to Mars within the next decades. The need for humans to land in areas allowing access to H2O has been driving mission planners to favor mid to high latitude locations on Mars where ground ice is thermodynamically stable in the shallow subsurface. However, Mars' mid to high latitudes are significantly colder than lower latitudes, and they also present reduced solar illumination annually and fewer daylight hours in the winter, making Mars surface operations much more challenging than at lower latitudes. The student will work with Dr Lee to systematically search for, and characterize, potential human landing sites within 10° of Mars' equator where alternative sources of H2O, such as exceptionally insulated subsurface ice and polyhydrated sulfates, will be sought. In addition to their H2O potential, other site selection criteria such as science and exploration value, terrain elevation, slope, roughness, and trafficability, will be considered and weighed. Several Mars data visualization and mapping tools will be used, in particular Mars QuickMap, Mars Trek, and Google Mars. The study is expected to result in a better understanding of landing site options for future human missions to Mars, and help identify candidate targets for upcoming robotic scouting missions.
Title: Analyzing unexplained features in Saturn's F Ring
Description:
The origin and evolution of Saturn's rings is one of the great mysteries of the solar system. The narrow and dusty F ring changes on timescales from hours to years, constantly perturbed by the nearby moons Prometheus and Pandora. Between 2004 and 2017, the Cassini orbiter took more than 20,000 images of the F ring, and researchers have observed and analyzed structures such as "extended clumps", "kittens", "fans", "channel-streamers", and "kinematic spirals". However, plenty of mysteries remain. In this project, the student will use existing software tools and develop new tools to analyze features in these images, especially those related to unexpected changes in orbital parameters. The work will involve extensive programming for orbital simulations and data visualization as well as the use of a Linux-based high-performance data analysis workstation.
Qualifications:
Due to the dynamical nature of Saturn's rings and the emphasis on orbital analysis, this project is most suited for an astronomy, physics, or math major with experience in classical mechanics above the freshman level. Intermediate/advanced Python programming experience is required, and experience with Linux and the command line is highly desired.
Title: Searching for radio technosignatures with the Allen Telescope Array
Description:
Radio waves are low-energy, travel at the speed of light, and are not blocked by gas and dust. For these reasons (among many others), it is hypothesized that extraterrestrial intelligences (ETIs) might use radio transmitters to send signals across the galaxy. We might be able to detect these radio “technosignatures” using radio instruments such as the Allen Telescope Array (ATA). In this project, the REU student will select a set of technosignature targets and observe them with the ATA. The student will then use existing software such as bliss or SPANDAK to perform a novel, in-depth technosignature search of those targets, with the goal of setting novel upper limits ever for the chosen targets (or detecting ETI!).
The student will complete a discrete observing project over the course of the summer, including planning an observing campaign, executing observations at HCRO, and analyzing data. They will work primarily at the SETI Institute in Mountain View, but will also have the opportunity to travel to Hat Creek Radio Observatory to get hands-on experience with the ATA.
Title: Fluvial and hydrothermal studies of the surface of Mars
Description:
Dr. Ginny Gulick examines erosional features on Mars, looking for the tell-tale signs of running water in Mars’ geological history. Some of the meandering valley networks that lace the landscape may indicate that Mars was a warmer, wetter world billions of years ago. But other features, including gullies found around many impact craters and valley walls, may be evidence of water that flowed on the martian surface more recently.
Dr. Gulick uses stereo images and Digital Terrain Models (DTMs) from Mars-orbiting cameras including HiRISE, CTX, and HRSC to look for features caused by flowing water (“fluvial” features) or by heated groundwater (“hydrothermal” features). The current project is focused on understanding gully formation in Mars’ more recent geological history, by studying their 3D slope morphology, their spatially-associated landforms, and their topographic and environmental settings. However, we are also interested in understanding the formational environments of channels, valleys, and paleolakes throughout Mars’s geological history. We will use information from terrestrial analog sites, hydrologic models, and DTMs to estimate water discharges, volumes, and erosion rates to better understand the implications for paleoclimatic change.
Qualifications:
Students with a geology, geography, or hydrology background with an emphasis in geomorphology and experience with computer software ArcGIS and/or ENVI are strongly desired. Experience with Python and/or MatLab preferred.
TOPIC #1
Title: Extremophiles: How do they do it?
Description:
Over the past 4 decades, our knowledge about life that can flourish under extreme conditions has dramatically expanded. Psychrophiles can metabolize down to -25°C, while hyperthermophiles grow at up to 122°C. In the deep ocean, piezophiles have been found living under pressures of >110 MPa. Life under other marginal conditions such as high salinity, extremes of pH, desiccation, and radiation, as well as combinations of stressors, has now been found.
Information about extremophiles is relevant for biotechnological applications, bioremediation, and in our search for life elsewhere in the universe. Some scientists argue that proteins adapted for high temperature or pressure will be stiffer than those that operate under freezing conditions. Others argue it is not so simple.
To address this issue, we are studying a set of small proteins called rubredoxins by multiple techniques to compare their dynamics at different temperatures. Rubredoxins (Rds) are the smallest of all Fe-S proteins – with only about 55 amino acids, their simplicity makes them an ideal system for testing theories about protein structure.
This project will involve growing crystals of rubredoxins and collecting x-ray diffraction data on these proteins as a function of temperature. The crystal structures will be compared with results from spectroscopy experiments (circular dichroism and fluorescence) to see if the predicted differences in flexibility do in fact exist. For the student with a computational bent, normal mode and molecular dynamics calculations will assist in interpretation of the data.
Qualifications:
The ideal candidate would have at least one year each of chemistry, physics, and some knowledge of biochemistry. Familiarity with Mathematica and/or bioinformatics software would be a plus but is not essential. This project is suitable for a student interested in proteins and life under extreme conditions.
TOPIC #2
Title: Enzymes that capture hydrogen: What is the first step?
Description:
The production or consumption of molecular H2 by hydrogenase can be as fast as by the best artificial fuel cells, but using earth-abundant Fe or Ni instead of rare and expensive Pt. Along with their metabolic significance, hydrogenases are important targets for novel antiparasitic drugs. They also generate intense technological interest for a future H2 economy. In [NiFe] hydrogenases, catalysis occurs at a Ni-Fe site, while in [FeFe] hydrogenases the active site is an ‘H-cluster’. We plan to study both of these enzymes.
Most mechanisms for hydrogenases assume an enzyme-H2 complex as a key intermediate, although some proposals skirt the existence of a bound H2 species, with splitting to hydride and proton directly through a transition state. To settle this debate, we are planning to examine hydrogenases in cryosolvents at low temperatures, down to perhaps -100 °C. We will use photochemistry to generate H2 in low temperature samples, and we will look for intermediates using IR spectroscopy. This project will provide experience with nanoparticles, Nd:YAG lasers, quantum cascade lasers, and FT-IR spectrometers.
Qualifications:
The ideal candidate would have at least one year each of chemistry, physics, and some knowledge of biochemistry. Some knowledge of basic spectroscopy would be helpful. Familiarity with Mathematica and/or molecular graphics software would be a plus but is not essential. This project is suitable for a student interested in enzymes, catalysis, and spectroscopy.
Title: Modeling outflows from young planet-forming disks
Description:
Young stars are surrounded by flat disk-like structures that eventually go on to form planetary systems. These disks are observed to continuously funnel material toward the central star, but for this to happen the material must lose angular momentum. How angular momentum loss and mass transport occurs has been a long-standing puzzle. Magnetically driven outflows are the leading theoretical mechanism, where mass is removed from the disk especially in the planet forming regions. The James Webb Space Telescope is now unraveling this mystery by capturing spectacular images of outflows from the disk. The project will involve using computational models to simulate emission, compare with JWST images and data, and infer the mass loss rates and conditions in the wind emitting regions.
Qualifications:
Physics majors are preferred. Computational experience with Python or another high-level programming language is required.
Title: Studying TESS exoplanet candidate detections
Description:
Dr Douglas Caldwell is an astronomer who studies the detection and characterization of exoplanets. NASA’s Kepler mission showed us that planets, including small potentially habitable ones, are common. The Transiting Exoplanet Survey Satellite (TESS), operating since 2018, has been finding more planets, including many in our Solar neighborhood. As TESS data continue to pour in, the number of detections of potential planets is outpacing the ability of scientists to manually keep up.
The TESS Science Processing Operations Center is currently searching the light curves of 160,000 stars per month from the TESS full-frame image data and detecting thousands of potential planets, known as Threshold Crossing Events (TCE). Currently, the TCEs are recorded in the TESS archive, but are not systematically vetted to determine which of them might be promising exoplanet candidates.
The student will work to refine and develop tools to help classify and vet the TESS full-frame image detections. They will start by using a set of existing vetting tools, tuning them to work on the full-frame image results. The student will work with a group that is using a deep neural network to classify the TESS TCEs by helping to incorporate these full-frame image results into the machine learning model. The work will involve reviewing scientific literature; running, modifying, and writing code to analyze data; and writing-up results. The ideal outcome of this project will be a set of new planet candidates from TESS data and a scientific publication describing the work.
Qualifications:
This project is ideal for someone who is interested in exoplanets and has a solid programming background. A familiarity with either the Python or MATLAB programming languages is beneficial, as is interest in, or experience with machine learning techniques. The student should have a background in science or engineering and an interest in learning about detection statistics.
Title: Details in the devils: Environmental controls of dust devil physical characteristics
Description:
Dr. Lori Fenton’s research involves studying evidence for recent climate change on Mars, with a focus on aeolian (wind-blown) processes. This includes atmospheric modeling of near-surface wind conditions, morphologic studies of windblown landscapes (e.g., ripples, dunes, yardangs) and phenomena (e.g., dust devils), and analog field studies to better understand how similar features and processes occur on Mars.
Dust devils are swirls of air that loft dust and other small debris off the ground in dry regions on Earth. Unlike tornadoes that form from shear generated during thunderstorms, dust devils seem to appear out of nowhere on warm, cloudless days – however they are actually part of a turbulent and convective atmosphere that only becomes visible when convectively-driven vortices skim the surface and grow strong enough to loft sediment. Dust devils are also common on Mars, where dust is plentiful and the weather is most often clear and convectively buoyant.
What can we learn about environmental controls on Mars dust devils (that is, how tall and wide they grow, how densely packed they are, etc.) by studying those that form on Earth? Can we then use observations of dust devils on Mars to infer local weather conditions? Field campaigns to a Nevada site in 2019 and 2021 produced a vast data set full of dust devil images and the meteorological conditions in which they form. The student will help discover the physical characteristics of these dust devils, answering a subset of a nearly endless list of interesting questions: Where do dust devils preferentially form – on bare playa or alluvial plain? How fast do they move relative to the background wind? Does dust devil width change with location or wind speed? Does the width change with increasing solar energy as the sun rises in the morning? If a dust devil loses its dust and becomes invisible, can it once again pick up energy and reappear downwind?
Qualifications:
Some background in geology or meteorology, as well as Python (or any programming language), is preferred. However, the project can be scaled to the experience level of the student.
Title: Radiative transfer modeling of trans-neptunian objects: A Machine Learning approach
Description:
The project will be part of a larger effort aimed at understanding the importance of methanol in the chemical evolution of Trans Neptunian Objects (TNOs) in the Solar System.
Methanol is an interesting molecule as it can be present on a surface as the product of irradiation of volatile ices or from metanogenesis and as such can help trace the history and evolution of the TNO. When the object is part of a class and the study is performed on a statistical basis the result can provide further evidence on the evolution of the outer Solar System.
The student will participate in creating the training set that will be adopted to detect trends and discern subtle variations in the different TNOs’ chemical properties, key to understand the overall picture. The task is mostly programming, including running the radiative transfer code and potentially setting up (formatting) datasets for a ML analysis.
Qualifications:
Python programming experience is required. Intermediate machine learning (ML) experience is preferred. No need for experience in radiative transfer modeling.
Title: Finding patterns of lights in the sky!
Description:
This is literally a SETI Institute project to find patterns of lights in the sky! The Geostationary Lightning Mapper (GLM) instruments onboard the GOES 16, 17, 18 and 19 weather satellites are designed to detect lightning, but they can also detect other bright flashes in Earth's atmosphere. We have developed a machine learning based exploding meteor (i.e. bolide) detection pipeline as part of the Asteroid Threat Assessment Project (ATAP) funded by NASA's Planetary Defense Coordination Office (PDCO). With the pipeline running for numerous years now, we have assembled a vast and unique catalog of bright meteors using a consistent and wide field of view. This project will involve studying the statistical distribution of bolides in our data set. Can we find patterns in these bolides? Can we find clusters of bolides, possibly multiple events from a single fragmented object? Are all the bolides evenly distributed across the globe?
Qualifications:
The ideal student should already be familiar with Python and have experience processing large data sets. A basic understanding or a desire to learn more about machine learning, cluster analysis and population statistics is highly desirable.
Title: Characterizing Martian North Polar processes using HiRISE morphology and CRISM mineralogy
Description:
Dr. Janice Bishop’s research involves characterizing the surface of Mars using hyperspectral visible/near-infrared (VNIR) images of Mars collected by the CRISM spectrometer on MRO (http://crism.jhuapl.edu/). My group is interested in studying the geochemical environment of Mars through detection of phyllosilicates, sulfates, and other aqueous minerals.
Dr. Lori Fenton’s research involves studying evidence for recent climate change on Mars, with a focus on aeolian (wind-blown) processes. This includes atmospheric modeling of near-surface wind conditions, morphologic studies of windblown landscapes (e.g., ripples, dunes, yardangs) and phenomena (e.g., dust devils), and analog field studies to better understand how similar features and processes occur on Mars.
Dr. Bishop and Dr. Fenton are seeking a summer intern to study the North Polar region of Mars, which has been influenced by several geologic processes and contains basalt, sulfates, salts, and ice. We will be working together to investigate a few sites using data from two instruments on board the Mars Reconnaisance Orbiter – spectra from CRISM and images from HiRISE – to document the formation of the dunes and the types of mineralogy.
The student will learn how to evaluate HiRISE images of Mars to document and characterize geologic processes. The student will also learn how to collect spectra from CRISM images and compare these with lab spectra of minerals. Additionally, in our laboratory we will measure spectra of Mars-analog rocks and relate these to CRISM spectra of Mars. The student will master how to measure reflectance spectra of geologic samples, how to use several image processing techniques, and how to identify different materials based on spectral features (e.g. clays, sulfates, chlorides, basalt).
Qualifications:
The ideal candidate would have at least one year each of chemistry, physics, geology, and some knowledge of mineralogy. Experience measuring the spectral properties of rocks and/or using CRISM spectra of Mars is a plus, but not required. Familiarity with KaleidaGraph, IDL or ENVI software would also be helpful because we’ll be using those over the summer, but is not required. This project is suitable for a student interested in mineralogy, remote sensing, or planetary geology.
Title: From case studies to a galactic population: A unified survey of Giant HII regions
Description:
Giant HII regions (GHII) are the most luminous hubs of clustered star formation in the Milky Way, containing the majority of the Galaxy’s massive stars (i.e., stars greater than 8 times the mass of our Sun). GHII regions shape everything from galactic chemical enrichment to the environments in which planetary systems evolve. Yet despite their fundamental role, we lack a complete, distance-accurate census of these star factories within our own Galaxy. Current catalogs are fragmented, incomplete, and biased by various observational limitations.
The purpose of this research program is to compile the first flux-limited, data-complete survey of GHII regions in the Milky Way, integrating cutting-edge radio and infrared archives with the newest and most accurate distance estimates from astrometric studies and databases. This high-impact project will allow for the construction of a Milky Way GHII luminosity function—a benchmark for our understanding of clustered star formation, galactic spiral structure, and massive-star feedback.
The student will help with the development of data-driven analysis tools designed to mine astronomical databases, enabling the classification of star-forming regions in the Milky Way and the discovery of GHII region candidates. The work will involve using, writing, and running code to perform such analyses, ideally incorporating the help of AI/machine learning to assist in the classification schema. There will be considerable work reviewing scientific literature to distill critical physical quantities of the survey sources. The anticipated result of this project will be a catalog of newly identified GHII candidates with a database of their physical attributes, culminating in a peer-reviewed publication.
Qualifications:
Computational experience with Python, IDL, or another high-level programming language is preferred. Experience with machine learning techniques is highly desirable but not required. The student should have a background in science, engineering, or scientific programming and an interest in learning about high-mass star formation.
Title: Study of small-scale eruptive events on the Sun using Solar Orbiter, DKIST, and SDO data
Description:
Recent observations with advanced solar telescopes suggest that small-scale solar activities, such as spicules, narrow jets, and transient brightenings, may play a significant role in coronal heating and solar-wind propagation. Building on our previous investigations of such small-scale eruptions, the student will study events within quiet-Sun network regions using observations from the Solar Orbiter, the Solar Dynamics Observatory (SDO), and the Daniel K. Inouye Solar Telescope (DKIST). The project will involve co-aligning data from Solar Orbiter’s Extreme Ultraviolet Imager (174 Å) with corresponding observations from the DKIST / Visible Broadband Imager and the SDO / Atmospheric Imaging Assembly. Photospheric magnetic fields will be analyzed using the SDO / Helioseismic and Magnetic Imager and DKIST / Visible Spectro-Polarimeter. The student will identify and characterize small-scale events, quantifying their physical properties and evolution. These measurements will help constrain their formation mechanisms and assess their potential contribution to coronal heating and solar-wind generation.
Qualifications:
The applicant should have a background in Physics, Astronomy, or a closely related field, with experience in scientific programming using Python and/or IDL. Familiarity with basic data analysis techniques, image processing, and an interest in solar or space plasma physics is a plus, but not required.
Title: How Iron-Sulfur Clusters may have catalyzed the formation of the First Proteins
Description:
One of the central mysteries in origin-of-life research is how the first functional proteins arose before biology existed to make them. This project explores a key question: could Fe-S clusters have guided the earliest steps of protein evolution by acting as templates for polypeptides to assemble and fold? Fe-S clusters are nanoparticles of iron and sulfide which biology uses as protein-bound redox and catalytic centers. They readily “self-assemble”, and free clusters were almost certainly commonplace on the early Earth. They exhibit relevant Lewis-acid based catalytic chemistry and are known to provide structural templates for protein folding. The simplest Fe-S proteins, the ferredoxins, are considered to be amongst the most ancient proteins. In modern biology, many small Fe-S proteins rely on the cluster not just for reactivity, but for their three-dimensional structure. If similar interactions occurred on the early Earth, simple polypeptides may have been selected, stabilized and shaped by their ability to bind to Fe-S clusters.
The student will experimentally investigate these ideas by studying how short peptides, unfolded ferredoxins, and free Fe-S clusters interact and reorganize. Using time-resolved infrared spectroscopy with the MIRCat quantum-cascade laser spectrometer at SETI together with other instrumentation, the student will follow binding and folding events in real time, capturing how structure develops around a metal-sulfide core. Additional measurements will involve UV-visible spectroscopy, chromatography, as well as X-ray spectroscopy at Stanford Synchrotron Lightsource (SSRL) to characterize intermediates and products.
If time allows, a parallel set of experiments may examine Fe-S cluster chemistry with amino acids and small peptides under simulated alkaline hydrothermal vent conditions, thus examining how these interactions might have arisen on the prebiotic Earth.
This project will integrate modern spectroscopic tools with models of early biochemistry. The student will gain broad exposure to bioinorganic chemistry, protein folding, spectroscopic tools, experimental astrobiology, and the chemical logic behind the origin of life.
Qualifications:
The ideal candidate will have completed at least one year of chemistry or biochemistry. Prior experience with spectroscopy or wet-lab techniques is welcome but not required. A curiosity about how life and biology might have begun on Earth or elsewhere is essential.