Results 151 to 160 of about 2,155,828 (298)

Effects of Fine Spectral Structure of Chorus Emissions on Nonlinear Scattering and Acceleration of Radiation Belt Electrons

Journal of Geophysical Research: Space Physics, Volume 130, Issue 4, April 2025.
Abstract Whistler‐mode chorus waves play a crucial role in accelerating electrons in Earth's outer radiation belt to relativistic and ultrarelativistic energies. While this electron evolution is typically modeled using a diffusion approximation for scattering, high‐amplitude chorus waves induce nonlinear resonant effects that challenge this approach on
Miroslav Hanzelka, Yuri Shprits, Dedong Wang, Bernhard Haas, Ondřej Santolík, Longzhi Gan   +5 more
wiley   +1 more source

The K2 Mission: Characterization and Early results

, 2014
The K2 mission will make use of the Kepler spacecraft and its assets to expand upon Kepler's groundbreaking discoveries in the fields of exoplanets and astrophysics through new and exciting observations.
Aigrain, Suzanne, Barclay, Thomas, Bryson, Stephen T., Caldwell, Doug, Chaplin, William J., Cochran, William D., Fortney, Jonathan J., Haas, Michael, Howell, Steve B., Huber, Daniel, Marcy, Geoffrey W., Miglio, Andrea, Mullally, Fergal, Najita, Joan R., Smith, Marcie, Sobeck, Charlie, Still, Martin, Troeltzsch, John, Twicken, J. D.   +18 more
core   +1 more source

Pointing LISA-like gravitational wave detectors [PDF]

arXiv, 2013
Space-based gravitational wave detectors based on the Laser Interferometer Space Antenna (LISA) design operate by synthesizing one or more interferometers from fringe velocity measurements generated by changes in the light travel time between three spacecraft in a special set of drag-free heliocentric orbits.
arxiv  

Limits on the Efficacy of Wave‐Particle Interaction on the Energization and Transport of Atomic and Molecular Heavy Ionospheric Ions

Journal of Geophysical Research: Space Physics, Volume 130, Issue 4, April 2025.
Abstract Ionospheric molecular ions, such as N2+ ${\mathrm{N}}_{2}^{+}$, NO+, and O2+ ${\mathrm{O}}_{2}^{+}$, have been observed in Earth's high‐altitude ionosphere and the magnetosphere by several spacecraft missions. Their presence not only indicates that they obtain sufficient energy through effective energization mechanisms, predominantly during ...
Mei‐Yun Lin, Raluca Ilie, Alex Glocer
wiley   +1 more source

Evaluating the Accuracy of Magnetospheric Magnetic Field Models Using Cluster Spacecraft Magnetic Field Measurements [PDF]

, 2021
F. Němec, Marie Kotková
openalex   +1 more source

Systems Engineering of a Nuclear-Electric Spacecraft [PDF]

, 1961
Studies have shown that nuclear-electric propulsion systems will provide superior payload capability and unique advantages over chemical systems for high-energy deep-space missions.
Beale, Robert J.
core   +1 more source

Particle‐To‐Field Energy Conversion Inside a Magnetotail Flux Rope

Geophysical Research Letters, Volume 52, Issue 6, 28 March 2025.
Abstract Magnetic flux ropes (FRs) are commonly observed in the universal plasmas, in which various dynamic processes can be embedded and thus become important places for energy conversion. Previous observations generally suggested that the energy conversion inside FRs is from the field to particles.
C. X. Du, H. S. Fu, J. B. Cao, E. Grigorenko, Z. Z. Chen, Z. Wang, Z. Z. Guo, Z. Y. Xu, W. D. Fu   +8 more
wiley   +1 more source

A Review of Cluster Wideband Data Multi‐Spacecraft Observations of Auroral Kilometric Radiation [PDF]

, 2022
K. H. Yearby, J. S. Pickett
openalex   +1 more source

Auroral Cluster: A Space Physics Mission for Multiple, Electronically Tethered Small Satellites [PDF]

, 1991
Auroral Cluster is a space physics mission that has been identified by the NASA Space Physics Strategic Implementation Study as a candidate for flight in the next decade.
Andrews, J.P., Burch, J.L., Scherrer, J.R., Waite, J.H.   +3 more
core   +1 more source

Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain Features [PDF]

arXiv, 2018
Unsupervised learning of time series data, also known as temporal clustering, is a challenging problem in machine learning. Here we propose a novel algorithm, Deep Temporal Clustering (DTC), to naturally integrate dimensionality reduction and temporal clustering into a single end-to-end learning framework, fully unsupervised.
arxiv