The fact that the universe is not locally real is one of the more disquieting discoveries of the last half-century.
Category: physics
An international research team led by the Max Planck Institute for Astronomy (MPIA) and involving the University of Bonn has mapped the cold, dense gas of future star nurseries in one of our neighboring galaxies with an unprecedented degree of detail. The data will enable the researchers for the first time to mount an in-depth study of the conditions that exist within the gas during the early stages of star formation outside the Milky Way at the scale of individual star-forming regions.
Their findings have now been published in Astronomy & Astrophysics.
Paradoxically, hot stars begin to form in some of the coldest regions of the universe, specifically in thick clouds of gas and dust that straddle entire galaxies. “To investigate the early phases of star formation, where gas gradually condenses to eventually produce stars, we must first identify these regions,” says Sophia Stuber, a doctoral student at the MPIA in Heidelberg and the first author of the research paper.
UCLA Department of Integrative Biology and PhysiologyLuskin Endowment forLeadership SymposiumPushing the Boundaries: Neuroscience, Cognition, and LifeKarl Fris…
In 2022, scientists from Northwestern University presented novel observational data indicating that long gamma-ray bursts (GRBs) might originate from the collision of a neutron star with another dense celestial body, such as another neutron star or a black hole — a finding that was previously believed to be impossible.
Now, another Northwestern team offers a potential explanation for what generated the unprecedented and incredibly luminous burst of light.
After developing the first numerical simulation that follows the jet evolution in a black hole — neutron star merger out to large distances, the astrophysicists discovered that the post-merger black hole can launch jets of material from the swallowed neutron star.
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An international team of astronomers has employed a set of space telescopes to observe a peculiar nuclear transient known as AT 2019avd. Results of the observational campaign, presented in a paper published December 21 on the pre-print server arXiv, deliver important insights into the properties and behavior of this transient.
Nuclear astrophysics is key to understanding supernova explosions, and in particular the synthesis of the chemical elements that evolved after the Big Bang. Therefore, detecting and investigating nuclear transient events could be essential in order to advance our knowledge in this field.
At a redshift of 0.028, AT 2019avd is a peculiar nuclear transient discovered by the Zwicky Transient Facility (ZTF) in 2009. The transient has been detected in various wavelengths, from radio to soft X-rays, and has recently exhibited two continuous flaring episodes with different profiles, spanning over two years.
Facing a power wall and the limit of physics, chip makers are in a constant battle to reengineer and re-evaluate ways to build a better CPU.
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It’s said that the clock is always ticking, but there’s a chance that it isn’t. The theory of “presentism” states that the current moment is the only thing that’s real, while “eternalism” is the belief that all existence in time is equally real. Find out if the future is really out there and predictable—just don’t tell us who wins the big game next year.
This video is episode two from the series “Mysteries of Modern Physics: Time”, Presented by Sean Carroll.
Published 12 August 2020 • © 2020 The Author(s). Published by IOP Publishing Ltd Journal of Physics: Photonics, Volume 2, Number 4 Focus on Photonics for Neural Information Processing Citation Matěj Hejda et al 2020 J. Phys. Photonics 2 044001 DOI 10.1088/2515–7647/aba670
The science of predicting chaotic systems lies at the intriguing intersection of physics and computer science. This field delves into understanding and forecasting the unpredictable nature of systems where small initial changes can lead to significantly divergent outcomes. It’s a realm where the butterfly effect reigns supreme, challenging the traditional notions of predictability and order.
Central to the challenge in this domain is the unpredictability inherent in chaotic systems. Forecasting these systems is complex due to their sensitive dependence on initial conditions, making long-term predictions highly challenging. Researchers strive to find methods that can accurately anticipate the future states of such systems despite the inherent unpredictability.
Prior approaches in chaotic system prediction have largely centered around domain-specific and physics-based models. These models, informed by an understanding of the underlying physical processes, have been the traditional tools for tackling the complexities of chaotic systems. However, their effectiveness is often limited by the intricate nature of the systems they attempt to predict.