169 citations
- University of California, Los AngelesUS4 papers
- University of Colorado BoulderUS4 papers
- West Virginia UniversityUS4 papers
- California Institute of TechnologyUS3 papers
- Laboratory for Atmospheric and Space PhysicsUS3 papers
- Chalmers University of TechnologySE2 papers
- Goddard Space Flight CenterUS2 papers
- KU LeuvenBE2 papers
- Max Planck Institute for AstronomyDE2 papers
- Nicolaus Copernicus Astronomical CenterPL2 papers
- Space Research InstituteRU2 papers
- Universidad Católica del NorteCL2 papers
15 papers
Electron Heat Flux and Whistler Instability in the Earth's Magnetosheath
Ida Svenningsson, Emiliya Yordanova, Yuri V. Khotyaintsev +4
Despite heat flux's role in regulating energy conversion in collisionless plasmas, its properties and evolution in the magnetosheath downstream of the Earth's bow shock are scarcel…
The large-scale kinematics of young stars in the Milky Way disc: first results from SDSS-V
Eleonora Zari, Jaime Villaseñor, Marina Kounkel +17
We present a first large-scale kinematic map of 50,000 young OB stars ( K), based on BOSS spectroscopy from the Milky Way Mapper OB program in the on…
The RoboPol sample of optical polarimetric standards
D. Blinov, S. Maharana, F. Bouzelou +34
Optical polarimeters are typically calibrated using measurements of stars with known and stable polarization parameters. However, there is a lack of such stars available across the…
The ESO's Extremely Large Telescope Working Groups
Paolo Padovani, Michele Cirasuolo, Remco van der Burg +82
Since 2005 ESO has been working with its community and industry to develop an extremely large optical/infrared telescope. ESO's Extremely Large Telescope, or ELT for short, is a re…
Calibrated and Enhanced NRLMSIS 2.0 Model with Uncertainty Quantification
Richard J. Licata, Piyush M. Mehta, Daniel R. Weimer +2
The Mass Spectrometer and Incoherent Scatter radar (MSIS) model family has been developed and improved since the early 1970's. The most recent version of MSIS is the Naval Research…
Science through Machine Learning: Quantification of Poststorm Thermospheric Cooling
Richard J. Licata, Piyush M. Mehta, Daniel R. Weimer +3
Machine learning (ML) is often viewed as a black-box regression technique that is unable to provide considerable scientific insight. ML models are universal function approximators…