News and Events

The beautiful Trifid Nebula, also known as Messier 20, is easy to find with a small telescope in the nebula rich constellation Sagittarius. About 5,000 light-years away, the colorful study in cosmic contrasts shares this well-composed, nearly 1 degree wide field with open star cluster Messier 21 (right). Trisected by dust lanes the Trifid itself is about 40 light-years across and a mere 300,000 years old. That makes it one of the youngest star forming regions in our sky, with newborn and embryonic stars embedded in its natal dust and gas clouds. Estimates of the distance to open star cluster M21 are similar to M20's, but though they share this gorgeous telescopic skyscape there is no apparent connection between the two. In fact, M21's stars are much older, about 8 million years old.
Check current conditions and historical weather data at the ESC.
The BYU Department of Physics and Astronomy invites applications for two faculty positions to begin August 2021. The application deadline is October 15, 2020.
Notice of Intent to File a Labor Condition Application to Employ an Alien H-1B Temporary Worker at Brigham Young University
New telescope installed in the campus dome on February 22, 2020
A new study from researchers at Brigham Young University and Pennsylvania State University provides the most accurate estimate of the number of Earth-like planets in the universe. The team looked at the frequency of planets that are similar to Earth in size and in distance from their host star, stars similar to our Sun. Knowing the rate that these potentially habitable planets occur will be important for designing future astronomical missions to characterize nearby rocky planets around Sun-like stars that could support life.

Selected Publications

BYU Authors: Benjamin A. Frandsen, published in Phys. Rev. B

We present a coordinated study of the paramagnetic-to-antiferromagnetic, rhombohedral-to-monoclinic, and metal-to-insulator transitions in thin-film specimens of the classic Mott insulator using low-energy muon spin relaxation, x-ray diffraction, and nanoscale-resolved near-field infrared spectroscopic techniques. The measurements provide a detailed characterization of the thermal evolution of the magnetic, structural, and electronic phase transitions occurring in a wide temperature range, including quantitative measurements of the high- and low-temperature phase fractions for each transition. The results reveal a stable coexistence of the high- and low-temperature phases over a broad temperature range throughout the transition. Careful comparison of temperature dependence of the different measurements, calibrated by the resistance of the sample, demonstrates that the electronic, magnetic, and structural degrees of freedom remain tightly coupled to each other during the transition process. We also find evidence for antiferromagnetic fluctuations in the vicinity of the phase transition, highlighting the important role of the magnetic degree of freedom in the metal-insulator transition.

BYU Authors: Benjamin A. Frandsen, published in Phys. Rev. B
The majority of the iron-based superconductors (FeSCs) exhibit a two-dimensional square lattice structure. Recent reports of pressure-induced superconductivity in the spin-ladder system, BaFe2X3 (X=S, Se), introduce a quasi-one-dimensional prototype and an insulating parent compound to the FeSCs. Here we report x-ray, neutron diffraction, and muon spin relaxation experiments on BaFe2Se3 under hydrostatic pressure to investigate its magnetic and structural properties across the pressure-temperature phase diagram. A structural phase transition was found at a pressure of 3.7(3) GPa. Neutron diffraction measurements at 6.8(3) GPa and 120 K show that the block magnetism persists even at these high pressures. A steady increase and then fast drop of the magnetic transition temperature TN and greatly reduced moment above the pressure Ps indicate potentially rich and competing phases close to the superconducting phase in this ladder system.
BYU Authors: David Van Komen and Tracianne B. Neilsen, published in Proc. Meet. Acoust.

Neural networks learn features that are useful for classification directly from a source, such as a recorded signal, which removes the need for feature extraction or domain transformations necessary in other machine learning algorithms. To take advantage of these benefits and have a finer temporal resolution, a one-dimensional convolutional neural network is applied to pressure time-series to find source range and ocean environment class from a received signal. The neural network was trained on simulated signals generated in different environments (sandy, muddy, or mixed-layer sediment layers) for several ranges (0.5 to 15 km). We found significant potential in a neural network of this type, given a large amount of varied training samples for the network, to learn important features suitable for range and environment predictions. This type of network provides an alternative for frequency-domain learning and is potentially useful for impulsive sources. Success in the time domain also reduces the computational requirements of conversion to frequency domain and increases the temporal resolution, which might be beneficial for real-time applications.