Headline Speakers – Career Panelists – Workshops & Panels – Science Café – Student Talks – Student Posters

Andrea Liu – Keynote Speaker

Hepburn Professor of Physics, University of Pennsylvania

Andrea Liu is a theoretical soft and living matter physicist who received her A. B. and Ph.D. degrees in physics at the University of California, Berkeley, and Cornell University, respectively. She was a faculty member in the Department of Chemistry and Biochemistry at UCLA for ten years before joining the Department of Physics and Astronomy at the University of Pennsylvania in 2004. Liu is currently Speaker-Elect of the Council of the American Physical Society (APS) and Chair-Elect of the Physics Section of the American Association for the Advancement of Science (AAAS). She is a fellow of the APS, AAAS and the American Academy of Arts and Sciences, and a member of the National Academy of Sciences.

K. Renee Horton – Plenary Speaker

Space Launch System (SLS) Quality Engineer, NASA

Dr. K. Renee Horton is a native of Baton Rouge, Louisiana and lifelong lover of science and NASA. A graduate of Louisiana State University with a B.S. of Electrical Engineering with a minor in Math in 2002 and a Ph.D. in Material Science with a concentration in Physics, becoming the first African American to graduate from the University of Alabama in 2011 in this area. Dr. K. Renee Horton currently serves as the Space Launch System (SLS) Quality Engineer in the NASA Residential Management Office at Michoud Assembly Facility (MAF) in New Orleans. She worked for NASA, first as a student from 2009 to 2011, and then started her career as a mechanical test engineer in 2012. In 2014 she was promoted to her current position.

Njema Frazier – Plenary Speaker

Physicist, National Nuclear Security Administration, Department of Energy

Dr. Frazier is a physicist in the Department of Energy’s National Nuclear Security Administration (NNSA). Within NNSA, she manages scientific and technical projects established to ensure a safe, secure, and effective nuclear weapons stockpile without nuclear explosive testing. Dr. Frazier is a Leadership Ambassador for the OneDOE Campaign as well as a Champion for the Department’s Minorities in Energy (MIE) Initiative. She is also the co-founder of the POWER (Professional Opportunities for Women at Energy Realized) Employee Resource Group at DOE. Outside of DOE, Dr. Frazier’s passion for STEM inclusion is reflected in her positions as member of the National Advisory Board of the National Society of Black Engineers (NSBE); Chair of the Algebra by 7th Grade (Ab7G) Initiative for grades 3 through 7; and the Founder and Chief Executive Officer of Diversity Science, LLC, an expert-based network of scientists and engineers dedicated to broadening participation in STEM.

Ayana Ledford – Seminar Leader

Executive Director of PROGRESS & Director of Diversity Initiatives for Dietrich College, Carnegie Mellon University

Serving as the Executive Director of PROGRESS and Director for Diversity and Inclusion at Carnegie Mellon University, Ms. Ledford is a highly sought out national lecturer by nonprofits, corporations, government agencies, and academic institutions that aim to improve diversity and inclusion in all facets of their organization. She is an expert on multiple factors influencing women’s long-term career success and utilizes negotiation as an essential leadership skill within her program offerings. She developed an innovative capacity building curriculum, Speak Up!, whose goal is to minimize the wage and leadership gap between men and women.

Cynthia Correa – Career Panelist

Data Scientist, Resy

Cynthia Correa is currently a data scientist at Resy, a reservations management platform for restaurants. There, she is in charge of data modeling, data infrastructure, and business intelligence reporting. Before this, she was developing data research reports for CBS interactive and teaching a data science bootcamp at DSLA. Before her transition into data science, Cynthia did computational plasma physics at the University of Texas at Austin, modeling plasmas on MHD scales as fluids. She led the Women In Physics group at UT Austin, majored in Physics at Harvard, and was born in Mexico, not in this order.

Mary Soon Lee – Career Panelist

Author

Mary Soon Lee was born and raised in London, but now lives in Pittsburgh. She writes both fiction and poetry, and has won the Rhysling Award and the Elgin Award. Her book “Elemental Haiku,” containing haiku for each element of the periodic table, was published by Ten Speed Press in October 2019. Her work has appeared in places ranging from American Scholar, to the Magazine of Fantasy & Science Fiction, to Science. Before she took up writing, she had a more analytical background, with degrees in mathematics and computer science from Cambridge University, and an MSc. in astronautics and space engineering from Cranfield University. She tweets at @MarySoonLee and has a website at http://www.marysoonlee.com.

Jami Valentine Miller – Career Panelist

Primary Patent Examiner, U.S. Patent and Trademark Office

Jami earned a master’s at Brown University, then went to Johns Hopkins University, where she studied the spin properties of rare earth metals under Professor C.L. Chien. In 2006 Jami became the first African-American woman to earn a Ph.D. in physics from Johns Hopkins University. In 2006 she joined the U.S. Patent and Trademark Office. She examines patent applications for a wide variety of semiconductor devices. Dr. Jami founded a website dedicated to African-American women in physics, AAWiP.com. The goal of the website is to honor the women who paved the way, to inspire future physicists, and to connect with all people interested in promoting diversity in Physics and other STEM fields.

Diana Parno – Career Panelist

Assistant Professor of Physics, Carnegie Mellon University

Diana Parno, Assistant Professor of Physics at Carnegie Mellon University, is an experimental nuclear/particle physicist who studies neutrinos, strange ghostly particles that give unique insight into the Standard Model. Currently she’s working with the KATRIN experiment to explore how much neutrinos weigh (we’re not sure yet, but the neutrino mass is less than 1/460,000 of the mass of an electron!), the COHERENT experiment to study how neutrinos interact with matter, and the TRIMS experiment to gain deeper insight into the beta decay of tritium molecules. This work usually involves ultra-high vacuum, high voltage, strong magnetic fields, exquisitely sensitive detectors, intensive coding, and lots of collaboration. She also wrangles two young kids (ages 5 and 1) and works actively with the LGBT+ Physicists group to improve the climate in physics. A native of DC, physics has brought her to 14 states and 4 countries.

Aria Soha – Career Panelist

Engineering Physicist, Fermi National Accelerator Laboratory

Aria graduated from Carnegie Mellon University with her BS in Physics in 2002. She then began her career at Fermilab as an Accelerator Operator, operating the Tevatron, and producing anti-protons. She was at the controls when the most anti-protons accumulated in one hour occurred. Aria is currently the Installation Coordinator for the Short Baseline Neutrino (SBN) Far Detector, and the Technician Manager for the Fermilab Neutrino Division. She is the founder and current president of the Fermilab Society of Hispanic Professional Engineers, the first professional chapter at a national lab. She is also the Program Manager of the Fermilab VetTech program, an initiative to employ military veterans and revitalize the retiring technician workforce. Her leadership in this area has been recognized by the US congress whom she has advised on legislation to enshrine the program into law as a model for all DOE labs. Her story was told by Representative Underwood on the House Floor.

Janet Waldeck – Career Panelist

Physics Teacher, Pittsburgh Allderdice High School

Janet Waldeck teaches high school physics and research classes. She received her A.B. and Ph.D. degrees in chemistry from the University of Chicago and Stanford University, respectively. She was a research scientist at the Weizmann Institute before moving into education. Janet serves on regional boards of the American Association of Physics Teachers and the Pennsylvania Junior Academy of Sciences. She is involved with reading the AP Physics exams, consults for the National Math and Science Initiative and the National Board for Professional Teaching Standards, and was a 2019 recipient of the prestigious Presidential Award for Excellence in Mathematics and Science Teaching.

Dean Rebecca Doerge – Welcoming Remarks

Glen de Vries Dean, Mellon College of Science, Carnegie Mellon Univeristy

Student Talks

Emma Brann (Michigan State)

Antihelium as a Signature of Dark Matter

The General Antiparticle Spectrometer (GAPS) experiment aims to detect antimatter as a signature of dark matter. At low energies, the predicted flux of antinuclei with baryon number A < -1 is orders of magnitude higher than the cosmic ray background, making these antinuclei, particularly antideuterons, a smoking gun signature of beyond the standard model physics. The Alpha Magnetic Spectrometer experiment has claimed several tentative antihelium-3 and antihelium-4 detections, which see even lower cosmic ray background than antideuterons. GAPS is uniquely suited to validate these claims. GEANT4 simulations reveal that GAPS is sensitive enough to detect antihelium, potentially providing insight into the nature of dark matter and probing new possibilities in physics.

Jessica Chellino (Rochester Institute of Technology)

Analysis of High Redshift Galaxies Through Image Stacking

I am examining the relationship between galaxies’ star formation rates and stellar masses, as well as the role that environment plays in galaxy evolution.  Data from the Herschel Space Observatory is used to investigate galaxies over a redshift range of 0.5 to 3.0.  Star formation rate tends to increase with stellar mass and among merging galaxies.  An increase in star formation density is expected for objects near a redshift of 2.0.  I am writing an image stacking code in order to determine the total signal from undetected galaxies at known positions in Herschel images.  I am also using point spread function photometry to find the average flux of the undetected sources within the stacked images.  Mean spectral energy distributions will be created for the sources to examine their star formation rates, masses and the environments that they are located in.

Grace Fiacco (Rochester Institute of Technology)

Generating Physically Realistic Neutron Star Initial Data
With the first direct detection of  gravitational waves followed by the first multimessenger observations of a binary neutron star (BNS) merger, the field of multimessenger astrophysics has been flourishing. Due to difficulties with various numerical techniques and simulations, equal mass binaries are more commonly analyzed than those with more unequal mass ratios, though the latter lead to substantially greater mass loss and potentially different observational signatures. Through modifications to the LORENE initial data code, we have been able to generate a wide range of physically realistic binary neutron star initial data for both equal and unequal mass ranges for a variety of equations of state, which has not been previously done before. The BNS initial data we have generated has allowed us to perform dynamical simulations of real-life BNS mergers using the Einstein Toolkit evolution code, and will allow us to analyze merger parameters in the near future.

Serena Flint (University of Rochester)

Using Deep Learning for Spectropolarimetric Inversions

The ability to perform spectropolarimetric inversions in heliophysics is invaluable to our understanding of the solar atmosphere. Although we cannot directly measure physical properties of the solar atmosphere, we can infer temperatures, velocities, and magnetic fields from the shapes of observed spectral lines. However, codes that perform these inversions remain computationally intensive and are orders of magnitude slower than the retrieval of the spectral scans. Our project explores the use of convolutional neural networks (CNNs) to perform such inversions in a fraction of the time, while still remaining reliable and accurate. We trained a CNN using an archive of atmospheres created by introducing random perturbations to the semi-empirical FAL-C model of the solar atmosphere. From this archive we calculated spectra of the Ca II 8542 line, frequently used for chromospheric diagnostics. We then trained the network to map an input spectrum to the appropriate atmosphere. Results from the validation set show that our network is able to very accurately infer temperatures and velocities from the spectra in 10^-4 seconds or less. We further tested the CNN using data from synoptic solar instrument SOLIS and spectro-polarimeter IBIS from the Dunn Solar Telescope. Interpretation of both datasets yielded atmospheres with temperatures in an expected range. Specifically, IBIS chromospheric temperature maps closely resemble the line core intensity maps. Moving forward, we are looking to extend this network to perform magnetic field diagnostics from full Stokes observations.

Isabella Ginnett (Michigan State)

Particle Identification Away from the Bragg Peak Using dE/dx

MicroBooNE is a liquid argon time projection chamber (LArTPC) experiment that aims to further probe the low energy excess discovered by MiniBooNE. To do this, MicroBooNE needs an array of particle identification (PID) techniques that are able to accurately classify the types of particles created in the LArTPC. The standard method of PID relies on analyzing dE/dx patterns in a particle’s track around its Bragg Peak. This is the point where the separation in different particle’s average dE/dx values is at its greatest. However, there are problems with this method because it cannot be applied in all situations. This creates the motivation to investigate if it is still possible to use dE/dx data away from the Bragg Peak to identify particles. I investigated if this modification to the Bragg Peak identification method would still be a viable method of particle identification and what the limits to its applicability would be.

Mairead Heiger (University of Pittsburgh)

Investigating the Evolution of Variable Stars with the Delay-time Distribution

In this era of large stellar population surveys, one tool available to probe and constrain stellar evolution is the delay-time distribution (DTD). The DTD is the hypothetical rate of occurrence for an object versus time since a brief burst of star formation—it determines how many objects appear per year in a stellar population of a given age. As a model-independent test, it can provide important constraints on the formation, progenitors, and lifetimes of any number of stellar objects and clarify highly uncertain stages of stellar evolution. We have calculated the DTD for three types of variable stars: RR Lyrae, Cepheids, and δ Scuti. Variable stars are critical for measuring astronomical distances, tracing stellar populations, and studying stellar interiors; their wide-ranging utility and ubiquity makes them important targets for further study. We present the methodology and results of the DTD calculation for these variable stars, as well as discuss future applications and implications for upcoming LSST-era surveys.

Alexis Osmond (University of Michigan – Dearborn)

Space-based Characterization of a Quarter-billion-star Photometric Catalog

The formation and history of the Bulge of the Milky Way galaxy remains a mystery, with debate still raging about the epoch and duration of star formation episodes over its history. These studies are undergoing something of a renaissance, with very large datasets at all wavebands leading to new discoveries impossible just a few years ago. The Blanco DECam Bulge Survey (BDBS, P. I. R. Michael Rich) is currently the largest ground-based imaging survey of the inner Milky Way bulge at visible wavelengths, with 6-filter {ugrizY} images covering about 400 square degrees of the Southern Bulge over a three-year interval. With about ten billion individual measurements covering 250 million stars towards the inner Milky Way, BDBS is an excellent pathfinder for future large-scale surveys such as the upcoming Large Synoptic Survey Telescope, and will be useful for a wide range of Galactic studies. I will present my work using the second Gaia Data Release (Gaia DR2) to perform the crucial photometric and astrometric characterization of our massive photometric dataset. Gaia DR2 provides a space-based astrometric reference catalog, but to less great depth than our dataset. It thus allows us to both characterize and calibrate residual astrometric systematics in our own data, while allowing us to demonstrate the degree to which our seeing-limited ground-based data extend and complement the sample probed by Gaia DR2.

Helena Richie (University of Pittsburgh)

The Survey of Tranisiting Extrasolar Planets at the University of Pittsburgh

STEPUP is an undergraduate research group lead by Helena Richie with the goal of discovering new exoplanets using transit photometry. By conducting observations using the 16” Keeler telescope based out of the Allegheny Observatory in Pittsburgh, PA, STEPUP is able to collect and analyze photometric data on planet candidate targets to draw conclusions about the existence of the planet. To process our data, we use STEPUP Image Analysis (SIA), an image analysis routine developed by Helena Richie that is responsible for calibrating, plate-solving, and performing absolute differential photometry on the datasets.In the past, we have done work to contribute to data platforms such as the Exoplanet Transit Database, the American Association of Variable Star Observers, and publish unknown planetary parameters by collaborating observation. Currently, STEPUP is focusing its efforts on contributing data to the Transiting Extrasolar Survey Satellite (TESS) collaboration as members of the TESS Follow-up Observing Program Sub-Group 1 (TFOP SG1), which consists of seeing-limited photometric observers that do follow-up observations on TESS planet candidates (PCs) to weed out false positives.

Kalista Schauer (US Military Academy)

Particle creation and energy conditions for a quantized scalar field in the presence of an external, time-dependent Mamaev-Trunov potential.

In 2011, Solomon proposed a model of a quantized scalar field interacting with a time-dependent Mamaev-Trunov potential in two-dimensional Minkowski spacetime1. This model is governed by the Klein-Gordon equation with a time-dependent potential.He claims that this model violates both the classical energy conditions of special relativity and the quantum energy conditions of quantum field theory in curved spacetime. Unfortunately, Solomon neglects the contribution to the energy density due to particle creation when the potential is turned off at time t=0. In this project, we calculate the contribution to the energy density due to particle creation. We show that the classical energy conditions are still violated, but that the quantum energy inequalities hold, contrary to Solomon’s statements.

Zhiquan Sun (University of Michigan – Ann Arbor)

Indirect Detection for Axion Dark Matter with Neutron Stars

Axions are one of the best-motivated dark matter candidates and are able to solve the solve the strong CP problem. In the presence of magnetic fields, axions can resonantly convert to photons, making the strong magnetic fields around neutron stars a natural channel for axion indirect detection. By solving the axion-photon equations of motion, we calculate the expected radio signal flux due to the conversion from several astrophysical targets. Focusing on the Milky Way, the Andromeda Galaxy M31, and the globular cluster M54, we show that narrow-band radio observation will be able to probe the axion parameter space over two orders of magnitude. We also show preliminary data analysis results from the observational data taken by the Green Bank Telescope.

Navya Uberoi (University of Rochester)

Studying Core-Collapse Supernovae with the IceCube Neutrino Observatory

Estimates of star formation rates in the Milky Way predict about three supernovae per century in the galaxy, of which two are expected to be core-collapse supernovae. However, we have not observed a supernova in our galaxy since the invention of the telescope 400 years ago – a potential discrepancy that calls for novel methods of supernova observation. Neutrino signals from core-collapse supernovae could not only provide up to 24 hours advance warning of the explosion for optical astronomers, but also help us study unique characteristics of neutrinos. The IceCube Neutrino Observatory, located at the South Pole, is currently the world’s largest neutrino detector and is a part of the Supernova Early Warning System (SNEWS). In the event of a supernova, data from IceCube would be instrumental in alerting the world of an imminent supernova in our galaxy and the Magellanic Clouds. Using existing models of neutrino luminosities for various stellar progenitors, the detector response can be simulated assuming different neutrino oscillation scenarios, at different stages of the supernova explosion. This response can be analyzed to test the sensitivity of IceCube to parameters such as progenitor distance and mass, as well as fundamental properties of neutrinos such as flavor oscillations and the mass hierarchy problem.

Yue Wang (University of Rochester)

Uncover Charge Density Waves

X-ray scattering provides crucial information about charge density waves (CDW) in quantum materials including high-temperature superconductors. CDW are ubiquitous in such superconductors. In this project, we consider 2D x-ray scattering maps from an experiment conducted at Linac Coherent Light Source (LCLS) in 2017. The images were collected with a newly built 2D fiber-coupled Multi-Channel Plate (MCP). This experiment produced a massive amount of data on the scale of 20TB. Therefore, methods to filter and to propagate the data efficiently are required. Furthermore, a nonstandard background elevated the difficulty of the data analysis. Here we present the algorithms used to uncover CDW information.

Amanda Wasserman (University of Rochester)

Liquid Xenon Purification Modeling for XENONnT

Dark matter detectors use liquid scintillators to produce photons when a dark matter particle passes through. XENON’s newest phase, XENONnT, will feature their largest volume of liquid xenon yet. This increased quantity of xenon allows for a higher likelihood of detection, but also increases contamination and background noise. XENONnT will be the first dark matter detector to use a liquid purification system to filter its scintillator. The goal of this project is to find the flow rate of the liquid xenon through the purification system and the heat transfer as the xenon passes through the system.

Student Posters

Charlotte Albunio (University of Michigan – Ann Arbor)

The Optical Properties of RFMO

My goal is to interpret the optical properties of the multiferroic superconductor RbFe(MoO4)2 using ultraviolet spectroscopy. Studying these allows us to develop white and ultraviolet light emitting diodes called UV LEDs. These would create inexpensive lighting solutions and be applicable to numerous global issues such as replacing power consuming UV lamps and other existing water purification methods with highly efficient UV LEDs and improving crop health and yield. So far, we have used linear optic techniques such as absorption and photoluminescence to gain a better understanding of the material.

Kylie Anderson (Thomas More College)

Continuing Investigation of Eclipsing Binaries at The BB&T Observatory of Thomas More University

Danielle Bovie (University of Rochester)

Charge Sharing Between Pixels in NEOCam Detectors

Infrared detectors for the NEOCam mission are being designed and tested by the University of Rochester. These detectors have many image distortions that need to be identified and studied in order to be corrected. I specifically looked into the Brighter Fatter Effect, similar to Blooming seen in CCD cameras, and worked to identify and measure this effect as well as help develop theories for its cause. It is believed that the effect is caused by charge sharing between pixels.

Anna Campbell-Sowden (Allegheny College)

Parasitic Capacitance in Floating Gate-Electrolyte Gated Transistors (FG-EGTs)

Biosensing has come far with new techniques and technological advances. Floating gate, electrolyte-gated transistors (FG-EGTs), show promise for advancements in the field due to their portability and ease of fabrication. FG-EGT sensors are devices where one side of the floating gate is functionalized with bioreceptors, acting as the sensing pad, and is capacitively coupled to the EGT. Upon a binding event, the FG-EGT elicits a response based on a potentiometric change at the sensing pad. The transistor’s response is transduced into an electrical signal and then processed to provide an electronic readout, detailing the binding of the analyte of interest at the sensing pad. This project will focus partly on altering the sensing pad size to see how device response is affected, and partly to investigate ways to reduce parasitic capacitance between the floating gate and substrate. Parasitic capacitance causes less polarization of the electrolyte due to trapped charges at the gold/silicon interface, necessitating a larger gate voltage to turn on the transistor. By changing the substrate to glass, an insulating material, parasitic capacitance can be eliminated.

Veronica Cisneros (University of Rochester)

Determining the relative concentration and efficiency of incorporated centers in Europium doped Gallium Nitride with different structures

Determining the most efficient light-emitting diode structure poses as an intriguing issue in the field of optics. Doping the layers with europium through organometallic vapor-phase epitaxy serves as a potential method of obtaining optimal red luminescence. These in situ doped samples were studied through combined excitation emission spectroscopy showcasing sites and their relative concentration. Comparing this to the UV spectrum obtained at low power levels reveals the different excitation efficiency of the centers. Comparing samples, we found that the multi-layered (MLS) sample with optimal growth parameters and growth conditions demonstrated centers with strong energy emission that serve as a promising candidate for the application of the europium ion within LED structures.

Serena Cronin (Ohio State University – Columbus)

Where Do Stars Explode in Galaxies?

The Local Environments of Supernovae Supernovae are the explosive deaths of stars. They enrich the universe with heavy elements and are vital to the formation of new stars in galaxies. Core-collapse supernovae are the deaths of high-mass stars. Type Ia supernovae are the explosions of white dwarfs, which are the leftover cores of dead, low-mass stars. Beyond these two main classifications, the nature of the stellar populations that produce supernovae and their impact on host galaxies are still debated. In this work, we characterize the gas, dust, and stellar properties at supernova sites in order to constrain these stellar populations and this impact on the surrounding gas and dust. This is the largest such study to date, with a sample size of ~1,000 supernovae drawn from the Open Supernova Catalog. We then locate each supernova in ultraviolet and infrared images of galaxies. These images highlight the locations of old stars, young stars, and dust in these galaxies. We search for the correlation between this infrared and ultraviolet emission and different types of supernovae. Following previous works, we use pixel statistics in order to generate cumulative distribution functions (CDFs) of supernova types in relation to the ultraviolet and infrared emission of their host galaxies. The resulting CDFs support the idea that there is a correlation between environment and supernova type. Specifically, type Ia supernovae track the total distribution of stars in a galaxy while core-collapse supernovae occur in areas of star formation, which is in line with current theoretical expectations.

Amelia Doetsch (Wayne State University)

Baryon Correlations in the STAR Experiment at RHIC

Heavy-ion collisions at the Relativistic Heavy Ion Collider (RHIC) produce a state of nuclear matter called the Quark Gluon Plasma (QGP), which is hot and consists of deconfined quarks and gluons. As the system quickly cools, hadrons are formed. The Solenoidal Tracker at RHIC (STAR) measures these hadrons. Of particular interest is the measurement of correlations between the particles, which indicate the importance of different reaction mechanisms. One mechanism could be a true critical point in the phase diagram of nuclear matter. Correlations can indicate clustering, where multiple particles are produced in close proximity to each other. This study is an exploratory analysis of baryon clustering in the STAR experiment, specifically focusing on protons and deuterons. The status and outlook for future results will be presented.

Abigail Ferris (Duquesne University)

Design and test of a low-cost turbidity meter using an LED and a photodiode

We designed a device to establish a more cost efficient way of testing the turbidity(cloudiness) of a water sample. Using an Adafruit Metro Mini board, a color sensor, an LCD screen, a red LED and a photodiode, we built a device which measured the cloudiness of a sample by measuring the amount of light emitted perpendicular to a monochromatic light source by the process of Mie Scattering. Once the device was properly built, we used milk as a test sample, as the turbidity of milk has been well studied and is less toxic than the standard, formalin. The amount of light scattered by the sample was measured by the color sensor, allowing for turbidity to be measured. Cloudier samples, with higher concentrations of milk, have a higher turbidity, measured in NTU (Nephelometric Turbidity Units). Our device has a much lower cost (about $50) than comparable commercial units (about $1000).

Serena Flint (University of Rochester)

Using Deep Learning for Spectropolarimetric Inversions

The ability to perform spectropolarimetric inversions in heliophysics is invaluable to our understanding of the solar atmosphere. Although we cannot directly measure physical properties of the solar atmosphere, we can infer temperatures, velocities, and magnetic fields from the shapes of observed spectral lines. However, codes that perform these inversions remain computationally intensive and are orders of magnitude slower than the retrieval of the spectral scans. Our project explores the use of convolutional neural networks (CNNs) to perform such inversions in a fraction of the time, while still remaining reliable and accurate. We trained a CNN using an archive of atmospheres created by introducing random perturbations to the semi-empirical FAL-C model of the solar atmosphere. From this archive we calculated spectra of the Ca II 8542 line, frequently used for chromospheric diagnostics. We then trained the network to map an input spectrum to the appropriate atmosphere. Results from the validation set show that our network is able to very accurately infer temperatures and velocities from the spectra in 10^-4 seconds or less. We further tested the CNN using data from synoptic solar instrument SOLIS and spectro-polarimeter IBIS from the Dunn Solar Telescope. Interpretation of both datasets yielded atmospheres with temperatures in an expected range. Specifically, IBIS chromospheric temperature maps closely resemble the line core intensity maps. Moving forward, we are looking to extend this network to perform magnetic field diagnostics from full Stokes observations.

Gracy Frost (Washington & Jefferson College)

A Multiwavelength Study of Messier 100

We present an HI, CO (J=1-0), and optical analysis of Messier 100 using unpublished archival data taken with the VLA, ALMA, and CFHT. Messier 100 is a grand design intermediate spiral galaxy of similar structure to the Milky Way and is one of the largest and brightest galaxies in the Virgo cluster. Our moment 0 maps show the HI has ring morphology, with a central H2 region implying central star-forming activity. We also produce rotation curves from the HI and H2 moment 1 maps.

Alyssa Gadsby (Duquesne University)
Probing for high momentum protons in 4He via the 4 He(e,e′p)X reaction.
Helium-4 is the lightest nucleus that has the characteristics of heavier nuclei and also allows us to study the proton momentum distributions . The E08009 experiment in hall A at Jefferson lab aims to study proton momentum distributions inside this nucleus. This is possible through the extraction of the cross section and the study of the missing energy spectrum versus missing momentum of the 4He(e,e’p)X reaction. My work was on data analysis and the extraction of the missing energy spectra after background subtraction. The cleaning of the spectra was done by the study the Physics acceptance that takes into account the geometrical phase-pace and target length reconstruction as well as spectrometer momentum resolution. In addition, coincidence events were validated by selecting a time window of 20 ns for the difference of the arrival time of electrons and protons. Cross section results were then compared to relativistic calculations and showed that some of the strength in the cross section is not accounted for.

Rachel Guest (Mercyhurst University)

Epitaxial growth and characterization of β-Ga2O3/µ-Fe2O3 superlattices on (010) β-Ga2O3 substrates

This poster demonstrates the growth study of β-Ga2O3 and µ-Fe2O3 superlattices on (010) β-Ga2O3 substrates. The successful synthesis of µ-Fe2O3 has a strong potential to replace SiC and GaN in high power electronics and integrate magnetism into this industry. This superlattice was grown using Plasma-Assisted Molecular Beam Epitaxy (PAMBE) and analyzed with Atomic Force Microscopy (AFM) for surface roughness measurements, X-ray Diffraction (XRD) to confirm the lattice matching, and Superconducting Quantum Interference Device (SQUID) for magnetic properties. One of the project’s goals is to find the optimal flux and temperature parameters that produce a smooth surface. So far, the smoothest surface achieved had an RMS roughness of 0.474 nm and was grown at a beam flux equivalent of 5.94×10^(-8) Torr for gallium and 3.64×10^(-8) Torr for iron sources while the substrate temperature during growth was 700°C. In the future, samples will be grown at a higher flux and substrate temperature.

Mairead Heiger (University of Pittsburgh)

The Delay-Time Distribution of δ Scuti Variable Stars

δ Scuti variables are a class of intrinsically variable stars used to measure intra- and extra-galactic distances. They are also a valuable tool for asteroseismology and studying stellar interiors. In this era of large stellar population surveys, one tool available to study δ Scuti and other stellar objects is the delay-time distribution (DTD). The DTD is the hypothetical rate of occurrence for an object versus time since a brief burst of star formation—it determines how many objects appear per year in a stellar population of a given age. We have calculated the DTD of δ Scuti variables in the Large Magellanic Cloud, and, coupled with comparisons to stellar models, the DTD can help us to constrain the progenitors of δ Scuti and measure their formation timescale. We will also use the DTD to calculate the lifetimes of δ Scuti variables, which can provide insight into their instability strip-crossing timescale.

Sophie Hourihane (University of Michigan – Ann Arbor)

Applying the Viterbi Algorithm to Continuous Gravitational Wave Searches

Neha Joshi (Carnegie Mellon University)

Validation Tests for DESC Image Simulation

The Large Synoptic Survey Telescope (LSST), which does not have data yet, has simulations catalogs to prepare to analyze LSST data. The Dark Energy Science Collaboration (DESC) data simulations must be tested to verify that they are valid models of the sky, so that these simulations can be used to develop and test analysis software. To do this, properties of the galaxies in the input (before simulation) and output (after simulation and detection) catalogs should be realistic. We present results for some validation tests designed to identify issues in the simulation software so that problems can be found and improved simulations can be generated.

Elizabeth Kowalczyk (Michigan State)

Reconstruction Low Energy Neutrinos in IceCube using a 3D Convolutional Neural Net

IceCube is a neutrino observatory in Antarctica which detects neutrinos by recording the light produced by the byproducts of interactions of neutrinos with nuclei in the ice. These interactions create charged particles that travel faster than the speed of light in ice, which then produce photons that are detected by a 3D array of 5,160 Digital Optical Modules (DOMs). The main goal of IceCube is to identify the astrophysical accelerators that create neutrinos, but it has also been used to better our understanding of the fundamental physics of neutrinos, such as oscillations at low energy (~50 GeV). This is accomplished by using the arrival times and directions of observed photons to reconstruct the energy of the incoming neutrino. One method uses neural nets, which is a set of adjustable weights that has been utilized for image recognition, and can be repurposed to accurately reconstruct neutrino events. My 3D Convolutional Neural Net uses nearby DOMs to discover patterns in photon detection over time in order to predict the energy of the incoming neutrino, which will contribute to our understanding of neutrino oscillations.

Abigail Lupi (Rochester Institute of Technology)
Spectral Image Quality Comparisons for Multi- and Hyperspectral Cultural Heritage Imaging Systems.
There has been recent growth in the use of spectral imaging in the field of cultural heritage studies. Spectral imaging systems can be used for simple digitization, but in many cases are used to discover new information about the artifacts, materials, and tools themselves. Spectral imaging can be used to enhance faded or erased text, and given enough spectral coverage and sampling, assess material properties of inks, pigments, and substrates. However, the question remains as to which imaging technology is most appropriate in addressing a given imaging-related problem. This research investigates distinctions between hyperspectral and multispectral data in the context of cultural heritage artifact imaging. Comparisons are based on signal to noise ratio, and spectral and spatial fidelity, with the goal of providing high quality imagery for use by scholars. Utility comparisons after processing will also be presented. Assessments reveal quantitative distinctions between the image quality of hyperspectral vs multispectral data with respect to these metrics. The image quality (IQ) measurement itself is based on a simple metric involving those three measurements. A palimpsest from the RIT Cary Collection and a medieval manuscript from the University of Rochester were both imaged with multiple imaging systems and serve as our objects of interest, though the processes documented here can be applied to any object with substantial hyperspectral and multispectral datasets.

Heidi Mach (Allegheny College)

Celestial Body Collisions: Stars and Black Holes

Using the SPH model, I have collided two stars with each other. Then I took one of the stars out of the collision and replaced it with a black hole that is equal in mass. In my poster presentation, I will identify the process of making the simulations using the SPH model, the relaxation of the stars, the collisions, and how/if the collisions are different.

Jahnavee Mittal (Duquesne University)

Generating Forbidden 5-Fold Symmetry Quasicrystals using an Optical System

Quasicrystals are non-periodic arrangements of atoms, first discovered in the 1980s, that possess no translational symmetry but still maintain long-range order. The empirical mechanical, thermal, and electronic properties of quasicrystals match neither those of true crystals non amorphous materials, making these properties difficult to predict theoretically. We will study the quantum mechanical properties of quasicrystals by building analogs to them using atoms at nanokelvin temperatures in an optical potential equal to that of a quasicrystal. We numerically simulated a quasicrystal with 10-fold symmetry built by the interference of five nearly co-propagating laser beams using Fresnel propagation software written in Python and constructed a simple optical setup to demonstrate the potential. The quasicrystal structure of the laser interference pattern is experimentally verified using the Fourier transform of a photograph of the pattern, which clearly shows “forbidden” 10-fold rotational symmetry.

Gabrielle Nowak (Central Michigan University)

Automating the Detection of Stellar Disk Dissipation and Growth Trends in Massive Stars

Circumstellar disks found around hot and massive stars, specifically around active B-type stars, are known to grow and dissipate on timescales as short as a few years. The physical mechanisms responsible for B-emission (Be) star disk changes between dissipation and growth phases are not fully understood, and this study focuses on the development of numerical methods that can detect and quantify how disks change over an extended period of time. Because the prominent H𝛼 emission line present in the spectra of Be stars is directly attributable to the rotating circumstellar material, we utilize the strength of the H𝛼 emission as a proxy for disk variability. Automating the detection of disk variability also allows to assess changes in disk dissipation and growth rates. We also discuss the connection between the observed growth and dissipation rates to physical changes in the average temperature and density characteristics of the disks. Using results from a sample of 12 targets, we demonstrate how automated methods can detect changes in disk growth or dissipation phases and constrain the rates of change associated with these systems. Support for this work was provided by NSF grant AST-1614983.

Asia Parker (Duquesne University)
The study of strange sea quarks’ contribution to the nucleon spin.
The “Proton Spin Puzzle” was evoked by the European Muon Collaboration (EMC), which strived to determine the spin configuration of the proton. Formerly physicists theorized valence quarks to contribute 100% of the proton spin; however, this was proven false. Valence quarks only contribute about 30%. Physicists then theorized that virtual sea quarks contribute to the overall spin to protons. In order to prove this theory, Semi-Inclusive Deep Inelastic Scattering (SIDIS) was employed to probe the inside of deuterons using electrons, to study particle jets such as kaons. At Thomas Jefferson National Accelerator Facility (JLAB) a Ring Imaging Cherenkov (RICH) detector was built in to measure the strange sea in Hall B, which works by measuring emissions of Cherenkov radiation to identify particles based on the mass and charge collected. In this work, I will present the method used to extract the strange sea and the predicted statistics

Madison Parry (Mercyhurst University)
Chaos is defined as the “aperiodic bounded dynamics in a deterministic system with sensitive dependence on initial conditions.” A chaotic system’s aperiodic property means that the same state is never repeated twice, or that any evidence of periodic behavior is shown in extremely long cycles. A system that is bounded stays in a finite range and will not approach positive or negative infinity. The deterministic property is shown by a definite rule and a lack of any random terms; an initial value of a function can be used to determine all future values of that same function. The last property defining chaos is the dependence on initial condition, and is the property that will be observed in this experiment. This property states that two points that are initially close will drift apart as time increases, meaning we cannot make predictions over long periods of time. Two different initial conditions may, however, lead to similar cycles for a finite differential equation with a fixed cycle. In this work, the dependence on initial condition of a chaotic system will be examined through the observation of a double pendulum.

Helena Richie (University of Pittsburgh)

The Survey of Tranisiting Extrasolar Planets at the University of Pittsburgh

STEPUP is an undergraduate research group lead by Helena Richie with the goal of discovering new exoplanets using transit photometry. By conducting observations using the 16” Keeler telescope based out of the Allegheny Observatory in Pittsburgh, PA, STEPUP is able to collect and analyze photometric data on planet candidate targets to draw conclusions about the existence of the planet. To process our data, we use STEPUP Image Analysis (SIA), an image analysis routine developed by Helena Richie that is responsible for calibrating, plate-solving, and performing absolute differential photometry on the datasets. In the past, we have done work to contribute to data platforms such as the Exoplanet Transit Database, the American Association of Variable Star Observers, and publish unknown planetary parameters by collaborating observation. Currently, STEPUP is focusing its efforts on contributing data to the Transiting Extrasolar Survey Satellite (TESS) collaboration as members of the TESS Follow-up Observing Program Sub-Group 1 (TFOP SG1), which consists of seeing-limited photometric observers that do follow-up observations on TESS planet candidates (PCs) to weed out false positives.”

Jennifer Rodriguez (Michigan State)

New X-ray and Radio Observations of the Dimmest Known Black Hole

Black holes are primarily detected when they enter bright phases of activity. Those with significantly lower luminosities are more difficult to observe and therefore, not as well studied. However, because they occupy a unique parameter space, studying low-luminosity black holes is necessary in order to form a complete picture of how black holes take in matter and turn it into energy. GS 2000+25 is a black hole binary, which is a system where the black hole feeds from a nearby star. More importantly, it is one of these low-luminosity sources. Here we present its new X-ray and radio observations.

Aria Salyapongse (Carnegie Mellon University)

Use of Scattering Density Profile Computer Program to Analyze Changes in Thickness and Area/Lipid upon Addition of eCAPS WLBU2 and D8 to Lipid Model Membranes
Increased multi-drug resistance to traditional antibiotics presents an enormous threat to global health and medical safety. To aid in the constant battle between bacteria and their treatment we have analyzed engineered cationic antimicrobial peptides (eCAPs): WLBU2 and D8. These eCAPs have the sequence RRWVRRVRRWVRRVVRVVRRWVRR, except that in D8 all of the valines are the D-enantiomer. Past work in the Deslouches lab has shown that WLBU2 and D8 affect the membranes of red blood cells differently (RBCs): while WLBU2 is quite toxic to RBCs, D8 is not, although they both successfully kill gram-negative (G(-)) and –positive (G(+)) bacteria. The Tristram-Nagle lab has used a lipid model membrane mimicking the lipid composition of the RBC membrane. They found that WLBU2 and D8 affect the chain order and bending modulus of different bacterial mimics differently: while D8 increases stiffness and chain order, WLBU2 causes a membrane softening and disordering of lipid chains. This suggested that membrane elastic properties are correlated with eCAP functionTo obtain structural information the Scattering Density Profile (SDP) computer program was used to examine the LAXS data taken at CHESS for G(-), G(+), LPS, KDO2, Euk30, and Euk 50 membrane mimics in order to study the change in thickness and area of the lipid bilayer with eCAPs in the membrane. Together with the location of the peptide provided by NR from Dr. Heinrich’s lab, we are able predict a the mechanism of action of these eCAPs in line with the domain formation theory. Further examination of the mechanism of action was done by comparing the x-ray form factor data with all-atom simulations performed by the Gumbart lab and visualized via Visual Molecular Dynamics (VMD). We suggest that the location of the peptide in bacterial membrane mimics forms domains consistent with the bactericidal theory presented by the Epand lab.

Kalista Schauer (US Military Academy)

Particle creation and energy conditions for a quantized scalar field in the presence of an external, time-dependent Mamaev-Trunov potential.

In 2011, Solomon proposed a model of a quantized scalar field interacting with a time-dependent Mamaev-Trunov potential in two-dimensional Minkowski spacetime1. This model is governed by the Klein-Gordon equation with a time-dependent potential.He claims that this model violates both the classical energy conditions of special relativity and the quantum energy conditions of quantum field theory in curved spacetime. Unfortunately, Solomon neglects the contribution to the energy density due to particle creation when the potential is turned off at time t=0. In this project, we calculate the contribution to the energy density due to particle creation. We show that the classical energy conditions are still violated, but that the quantum energy inequalities hold, contrary to Solomon’s statements.

Urvashi Thongam (Wayne State University)

Development of new pancreatic cancer screening tools

Most human cancers display a dysregulated expression of one or more receptor tyrosine kinases (RTKs). There is strong evidence in the association between altering the RTK’s functions and the rate of cancer progression which has led to novel therapeutic strategies in the treatment of cancer. Although the entire oncogenic process is not completely understood, it has been proved that a unique RTK is known as the Discoidin Domain Receptors (DDRs) specifically binds to and is activated by collagen which in turn plays a role in cancer progression and metastasis by regulating the interactions between the cancer cells and their surrounding environment, specifically collagen. DDRs seem to play a key role in the contribution of tumor growth and metastasis in pancreatic cancer by sensing the collagen. Hence, disrupting the DDR-collagen interaction may impact the ability of PC cells to survive. This project is will be investigating the use of advanced technology to measure the interactions within the environment and behavior of DDR on live PC cells. These measurements will be done using a novel nano-mechanical method. An atomic force microscopy (AFM) will be used to investigate protein-protein interactions, in our case, to selectively measure individual surface receptors on live cells interactions to the collagen at a single molecule level. These measurements will be translated to binding kinetics of the ligands to receptors as well as capture the DDR density across cells. Matrices with varying mechanical properties will be created using hyaluronic acid and collagen to mimic PC environment. With these matrices in hand, we will explore how the matrix stiffness and presence or lack of collagen influence the expression of DDR on the PC cells. Two pancreatic cell lines will be used: Panc1b DDR and Panc EV. The Panc1b DDR cell line has been engineered to express wild type human DDR and the EV cells which were transfected with an expression vector without an insert. The EV cells will be used as control as their binding to collagen has been inhibited or low. The PC cells will then be cultured and seeded on the matrices. Finally, the atomic force microscope will be used to image and measure mechanical stiffness and adhesion of the cells to the matrix, and detect, quantify and measure single DDR receptors on the live PC cell surfaces. In addition, the morphology and proliferation of both cell lines will be documented on matrices of various stiffnesses with collagen and fibronectin coating. Fibronectin will be used as a control as other transmembrane integrin protein will allow for the adhesion of the cells. Immunostaining and western blotting will be performed to investigate the presence/absence and quantify the expression of DDR in both cell lines. The mechanics of the hyaluronic acid gel matrixes and pancreatic cancer cell lines were collected. DDR-collagen interactions were isolated, and the association/dissociation rates were quantified. The total DDR protein expression was performed using Western Blot and AFM analysis. The complete results will be presented in the poster session.

Nkeiru Ubadike (Schenectady County Community College)

Tracking Sagittarius A* with Cosmic Ray Tracking Detector

There are galactic cosmic rays (GCR) that reach high energies of 1PeV and some scientists propose that they originate from the black hole in the center of our galaxy: Sagittarius A*. In light of these proposals, the cosmic ray tracking detector is being configured to track Sagittarius A*. Automatic tracking was set up with use of computer software. Approximate tracking of certain celestial objects has been verified but issues remain with detector performance.

Melita Wiles (College of Wooster)

Energy Stability of Gravitationally Interacting Rods and Dumbbells

We extend classic dynamical results for two or three gravitationally interacting point masses to ideal rods and dumbbells. We derive equilibrium configurations by demanding that the vector of first derivatives of energy at constant angular momentum vanish. We investigate their stability by checking if the spectrum of the Hessian matrix of second derivatives is positive. The additional degrees of freedom allow the objects to store and exchange angular momentum and enable us to elucidate the behavior of non-spherical celestial bodies like asteroids and comet nuclei..

Laura Zaidenberg (University of Michigan – Ann Arbor)

The KOTO Experiment

KOTO is a high energy physics experiment aimed at observing a rare decay of a neutral kaon: KL0 → 𝜋0𝜈𝜈̄. The experiment focuses on the flavor changing neutral current (s quark to d quark). The decay is CP violating and has a Standard Model predicted branching ratio of (2.43±0.39±0.06)x10-11. To conduct this research, a high-intensity neutral beam was built at J-PARC, a particle accelerator facility in Japan. Through data analysis, KOTO has established more precise limits for the Standard Model and may even find new physics beyond it.