Monday - May 6, 2024
Physics Tipoffs from TNS Newsletter for Sunday April 07, 2024 ( 4 items )  

Max Planck Society: Mysterious Object in the Gap
MUNICH, Germany, April 6 (TNSres) -- The Max Planck Society issued the following news: * * * When a black hole and a neutron star merge * * * On May 29, 2023, the LIGO Livingston detector observed a mysterious signal, called GW230529. It originated from the merger of a neutron star with an unknown compact object, most likely an unusually light-weight black hole. With a mass of only a few times that of our Sun, the object falls into the "lower mass gap" between the heaviest neutron stars and   more

Northwestern: First Gravitational-Wave Detection of a Mass-Gap Object Merging With a Neutron Star
EVANSTON, Illinois, April 6 -- Northwestern University issued the following news release: * * * * LIGO-Virgo-KAGRA Collaboration detected an unexpected signal at start of fourth observing run * Merger includes a mystery object that is heavier than a neutron star but lighter than black holes observed in the Milky Way * Scientists infer that the mystery object is most likely a low-mass black hole * * * An international research collaboration, including Northwestern University astrophysicists  more

Pacific Northwest National Laboratory: Substantially Positive Contributions of New Particle Formation to Cloud Condensation Nuclei Under Low Supersaturation in China Based on Numerical Model Improvements
WASHINGTON, April 6 (TNSres) -- The U.S. Department of Energy Pacific Northwest National Laboratory issued the following abstract of a journal article: * * * Abstract New particle formation (NPF) and its subsequent growth are important sources of condensation nuclei (CN) and cloud condensation nuclei (CCN). A number of observed evidence has shown the positive contributions of NPF on CCN under low supersaturation (SS), nevertheless, traditional numerical studies reveal opposite findings with d  more

Physics-Informed Gaussian Process Regression for States Estimation and Forecasting in Power Grids
WASHINGTON, April 6 (TNSres) -- The U.S. Department of Energy Pacific Northwest National Laboratory issued the following abstract of a journal article: * * * Abstract Real-time state estimation and forecasting is critical for efficient operation of power grids. In this paper, a physics-informed Gaussian process regression (PhI-GPR) method is presented and used for forecasting and estimating the phase angle, angular speed, and wind mechanical power of a three-generator power grid system using   more