Browse research papers in Astronomy and Astrophysics - Physics and Astronomy Discover 5 academic papers with AI-powered analysis

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Astronomy and Astrophysics

The study of celestial objects and cosmic phenomena, including stellar evolution, galaxies, cosmology, exoplanets, gravitational waves, and observational astronomy techniques

5 papers in this specialization

Papers

Gravitational Bounce from the Quantum Exclusion Principle

This paper proposes a model within standard general relativity where the universe originates from the collapse and bounce of a finite, closed region of matter. The bounce arises from a "ground state" characterized by constant energy density and negative degeneracy pressure, leading to an inflationary expansion phase and potentially explaining dark energy as a boundary effect of the finite universe.

The role of the Lorentz force in sunspot equilibrium

This paper investigates the role of the Lorentz force in maintaining the equilibrium of sunspots, specifically focusing on the often-neglected azimuthal direction. Combining observations and 3D MHD simulations, the study finds that despite the complex magnetic field structure, both the umbra and penumbra of sunspots are very close to azimuthal magnetohydrostatic equilibrium, helping explain their longevity.

Geometrization of light bending and its application to SdSw spacetime

This paper proposes a new method to measure the effects of dark energy on the bending of light using a "Gaussian deflection angle." They suggest this method could amplify dark energy's impact by 14 orders of magnitude, potentially making it detectable within our solar system using existing technology like GRAVITY.

The SunPy Project: Open Source Development and Status of the Version 1.0 Core Package

This paper describes the first stable release (version 1.0) of the SunPy core package, a community-developed, open-source Python library for solar physics data analysis. SunPy provides tools for data search and retrieval, visualization, coordinate transformations, and analysis, leveraging the broader scientific Python ecosystem to facilitate advanced solar research.

Lunar impact crater identification and age estimation with Chang'E data by deep and transfer learning

This study used deep and transfer learning with Chang'E data to identify lunar impact craters, resulting in a database of 117,240 craters (more than 10x previous counts) and estimated ages for nearly 19,000 large craters. This method offers a robust and automated approach for lunar crater studies, surpassing previous methods in quantity and potentially accuracy, paving the way for improved lunar chronology and geologic understanding.

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Jul 14, 06:47 AM