News and Events

Wed, Apr 1, 4:00 PM (C215 ESC, and online)
Cosmology and Unification

 I will describe the mechanism of “cosmological collider physics” in which precision cosmological measurements can allow us to probe particle physics and cosmic inflation at energies which are orders of magnitude above those of terrestrial particles colliders such as the CERN Large Hadron Collider. I will show how this may give us unprecedented access to some of the highest ambitions of fundamental physics such as the Grand Unification of the forces of Nature.

What is the sound of two black holes merging in deep space? Sound waves don't propagate in vacuum, but gravitational waves do. In 2015 we were able to "hear" them for the first time and confirm one of Albert Einstein's theoretical predictions. Each square on the grid of the featured image represents one of the gravitational wave detections announced so far by the LIGO-VIRGO-KAGRA Collaboration. These plots show how the binary pair accelerates in their orbit around each other towards merger: the rising frequency effect is called a "chirp". Although there are significantly more neutron stars than black holes, most of the detections are binary black hole mergers. That happens because black holes are heavier and their signals are louder and can be seen farther away, resulting in more detections. These events are rare, and we don't expect to see one close by in our Galaxy any time soon. But they are happening continuously throughout the cosmos.
Temp:  64 °FN2 Boiling:75.9 K
Humidity: 35%H2O Boiling:   368.5 K
Pressure:86 kPaSunrise:7:20 AM
Wind:4 m/s   Sunset:7:44 PM
Precip:0 mm   Sunlight:600 W/m²  
Nobel Laureate Kip Thorne Inspires BYU Students with the Future of Gravitational-Wave Science
Four Decades Under the Stars: Honoring Dr. Mike Joner and the Legacy of West Mountain Observatory.
Connecting Experience to Opportunity: External Advisory Council Supports Career Pathways and Job Success for BYU Physics and Astronomy Students.

Selected Publications

J. Nicholas Porter, David J. Anderson, Julio Escobedo, David D. Allred, Nathan D. Powers, and Richard L. Sandberg

We present an undergraduate optics instructional laboratory designed to teach skills relevant to a broad range of modern scientific and technical careers. In this laboratory project, students image a custom aperture using coherent diffraction imaging, while learning principles and skills related to digital image processing and computational imaging, including multidimensional Fourier analysis, iterative phase retrieval, noise reduction, finite dynamic range, and sampling considerations. After briefly reviewing these imaging principles, we describe the required experimental materials and setup for this project. Our experimental apparatus is both inexpensive and portable, and a software application we developed for interactive data analysis is freely available.

Hunter J. Pratt, Logan T. Mathews, Tyce W. Olaveson, and Kent L. Gee

A sound power spectrum analysis has been conducted on a T-7A-installed F404 engine, for operating conditions spanning intermediate thrust to afterburner. From free-field pressure spectra at microphone arc arrays with radii of 38 and 76 m, sound power level spectra are calculated from surface integrals and assumed axisymmetric radiation. The spectral peak-frequency region, from ∼100–500 Hz, broadens with increasing engine conditions. When the power level spectra are plotted with Strouhal number, the spectral peak decreases with engine condition. Comparing this decrease with rocket data suggests that military jet noise radiation is becoming more rocket-like, especially at afterburner conditions.

Jason Meziere, Brayden Bekker, Hayden Oliver, Luke Cvetko, and Gus L.W. Hart (et al.)

Understanding the atomic structure of precipitate phases in shape memory alloys is critical to determining their structure–property relationships and developing high-performance shape memory alloys. However, experimental methods are limited in determining atomic configurations in cases where the number of atoms per unit cell is very high, or the phase is small (few nms). While density functional theory (DFT) can aid in the accurate determination of a phase’s crystallography, this is challenged by the number of candidate structures. Recently, a cubic phase was discovered during the heat treatment of a Hf-Ni-Ti alloy developed with improved tribological applications and rolling contact fatigue. We use DFT, machine learned interatomic potentials (MLIPs), and a genetic algorithm to identify likely configurations for the cubic phase. Likely candidate structures consistent with experimentally determined structural information were identified. Limitations of experimental microscopy methods, crystal simulation, and DFT-MLIP techniques are discussed.

We analyze three nearby spiral galaxies—NGC 1097, NGC 1566, and NGC 3627—using images from the DustPedia database in seven infrared bands (3.6, 8, 24, 70, 100, 160, and 250 μm). For each image, we perform photometric decomposition and construct a multi-component model, including a detailed representation of the spiral arms. Our results show that the light distribution is well described by an exponential disk and a Sérsic bulge when non-axisymmetric components are properly taken into account. We test the predictions of the stationary density wave theory using the derived models in bands, tracing both old stars and recent star formation. Our findings suggest that the spiral arms in all three galaxies are unlikely to originate from stationary density waves. Additionally, we perform spectral energy distribution (SED) modeling using the hierarchical Bayesian code HerBIE, fitting individual components to derive dust properties. We find that spiral arms contain a significant (>10%) fraction of cold dust, with an average temperature of approximately 18–20 K. The estimated fraction of polycyclic aromatic hydrocarbons (PAHs) declines significantly toward the galactic center but remains similar between the arm and interarm regions.

Joshua Ebbert, Bryce Hedelius, Jyothish Joy, Daniel H. Ess, and Dennis Della Corte

TrIP2 is an advanced version of the transformer interatomic potential (TrIP) trained on the expanded ANI-2x data set, including more diverse molecular configurations with sulfur, fluorine, and chlorine. It leverages the equivariant SE(3)-transformer architecture, incorporating physical biases and continuous atomic representations. TrIP was introduced as a highly promising transferable interatomic potential, which we show here to generalize to new atom types with no alterations to the underlying model design. Benchmarking on COMP6 energy and force calculations, structure minimization tasks, torsion drives, and applications to molecules with unexpected conformational energy minima demonstrates TrIP2’s high accuracy and transferability. Direct architectural comparisons demonstrate superior performance against ANI-2x, while holistic model evaluations─including training data and level-of-theory considerations─show comparative performance with state-of-the-art models like AIMNet2 and MACE-OFF23. Notably, TrIP2 achieves state-of-the-art force prediction performance on the COMP6 benchmarks and closely approaches DFT-optimized structures in torsion drives and geometry optimization tasks. Without requiring any architectural modifications, TrIP2 successfully capitalizes on additional training data to deliver enhanced generalizability and precision, establishing itself as a robust and scalable framework capable of accommodating future expansions or applications to new domains with minimal reengineering.

Sharisse Poff, Benjamin Boyack, Robert C. Davis, and Shiuh-hua Wood Chiang (et al.)

Pulsatile bioimpedance measurements require filters with very narrow bandwidths to preserve heartbeat-rate modulation while suppressing excess noise. At the signal's carrier frequency, this demands an impractically-high-Q filter. Multirate signal processing is an attractive solution to this problem, as it provides an avenue to extract the signals of interest practically. This paper presents a multirate filtering solution and shows step-by-step how the bioimpedance data of interest are extracted from noise and excitation frequency in in-phase and quadrature signals acquired from an analog measurement circuit. The tested impedance values resemble realistic human tissue impedance, demonstrating the method's ability to measure a human pulse within an approximately 50−Hz bandwidth at a 1−MHz carrier. This method is useful for high-Q bioimpedance measurements where interest lies in the details of signals pulsing at the rate of a beating human heart.