We investigate two different systematic arrangements of ultrasonic (28,000 Hz) acoustic waves and Styrofoam particles in combination with schlieren imaging. For both arrangements, schlieren imaging is used to visualize the particle's motion within the acoustic wave. The first arrangement is a standing acoustic wave in which Styrofoam balls are levitated. Using a camera to image the system, the positions of the levitated Styrofoam balls are recorded and compared to theoretical predictions of the positions due to the acoustic radiation force. We find that the acoustic radiation force can be used to map the spatial pattern where the Styrofoam balls are levitated in the acoustic waves. The second arrangement is a double-slit acoustic system with Styrofoam particles launched into the system. Trajectories of the Styrofoam balls will be recorded using computer software, and then compared to an experimental simulation of Bohmian trajectories that are predicted for a double-slit electron diffraction system. The simulated trajectories are created by using the quantum potential and Schrodinger equation to map the evolution of all possible particle positions that are under consideration. We look to find if a double-slit acoustic wave diffraction pattern with particles being launched into the system may be a systematic visual analog to an electron undergoing diffraction in a double slit. We finish by discussing the possible future applications of this experiment as an instructional tool. We gratefully acknowledge support from the U.S. National Science Foundation under Grant No. PHY-2207697.

Although galaxies appear to be defined by their starlight, almost all galaxies like the Milky Way have flattened disks, the very outermost parts of which are filled with hydrogen gas, and not stars. HII regions are clouds of ionized hydrogen gas commonly found in the outer arms of a spiral galaxy where bluer massive stars form. These very hot stars also ionize the hydrogen, and the recombining electrons give rise to Hydrogen-alpha emission. We are using deep imaging of nearby galaxies to explore Hydrogen-alpha and far-ultraviolet emission as indicators for the rate of star formation in the edges of nearby galaxies. The Halos and Environments of Nearby Galaxies (HERON) project images 30 nearby large galaxies in Hydrogen-alpha and will be compared to far-ultraviolet data from the Galaxy Evolution Explorer satellite. Under the supervision of Professor Rich, I planned and executed observations using the CCD cameras mounted on the Centurion 28-inch and Centurion 18-inch telescopes. The CCD images were captured using automation software, Sequence Generator Pro and Maxim DL. We have conducted observations for over 100 nights, and have obtained nearly 1000 hours of data on 30 nearby galaxies. The results will improve our understanding of star formation, the accretion of hydrogen from the intergalactic medium, and the process of photoionization caused by hot ultraviolet stars and active galactic nuclei.

Type IIn supernovae (SNe IIn) are characterized by their spectral features, notably the presence of a blue-shifted hydrogen alpha (H-alpha) line in their spectrographs. This phenomenon has puzzled astronomers for years, prompting investigations into its cause. We shall present novel research aimed at elucidating the mechanism responsible for the blue-shifted H-alpha line and propose a compelling explanation involving the role of dust formed within the supernova. Our research findings indicate that dust, generated during post-Supernova, plays a crucial role in masking any redshifted Hα line in the spectrograph. By analyzing observational data from a sample of Type IIn supernovae, we have identified a consistent pattern where the H-alpha line exhibits a blue-shifted profile. This blue-shift can’t always be the case when viewing all Supernovae. We propose that the presence of newly formed dust within the supernova scatters and absorbs the redshifted photons, effectively masking their detection in the spectrograph. The scattering and absorption processes by the dust produce a net blue-shifted effect on the observed H-alpha line. This explanation not only accounts for the observed spectral characteristics but also provides insights into the formation of dust within Type IIn supernovae. Our research advances the understanding of the complex interplay between dust and the spectroscopic properties of Type IIn supernovae. By demonstrating how dust causes the blue-shifted Hα line, our study challenges previous hypotheses and provides a compelling explanation for this mystery. The findings here have implications for future observations and efforts aimed at unraveling the mechanisms underlying Type IIn supernovae.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a fatal pulmonary artery disease characterized by mean pulmonary arterial pressure (mPAP) greater than 20 mmHg, presence of lesions, blood clots, and other obstructions. Surgical intervention is required to treat CTEPH, either through the removal of clotting factors by pulmonary endarterectomy or increase blood flow past embolisms by balloon pulmonary angioplasty (BPA). Mathematical models of pulmonary hemodynamics can alleviate the requirements of these procedures by providing hemodynamical insight in silico. Prior to hemodynamic simulation, data on the patient’s pulmonary arteries must be obtained through images. CT images from 1 control and 7 CTEPH patients were obtained from Duke University Hospital. From these images and manual segmentation, volumetric models of the pulmonary arteries were obtained using 3D Slicer. Centerlines, which contain data on radius, length, and position through every artery, were extracted using the Vascular Modeling Toolkit. From these, changepoints––points within a vessel expressing significant statistical difference––were identified. Changepoint locations in each vessel were then used to create a radius-correction algorithm. Likewise, an asymmetric binary tree was used to extend arterial networks past their centerlines. Simulations were then used to generate blood pressure and flow of a patient’s arterial network. Due to segmentation uncertainty, multiple network configurations were used and parameter changes were observed. Comparing these quantities between subjects will assist in the standardization of critical values, such as mPAP and blood flow, in CTEPH diagnoses. Further, in silico optimization of mPAP values through lesion removal will decrease potential patient risk and hasten CTEPH intervention.