343 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Universidad Nacional de ColombiaCO5 papers
- Universidad de Los AndesCO4 papers
- University of ChileCL4 papers
- National Radio Astronomy ObservatoryUS3 papers
- Universidad Católica de la Santísima ConcepciónCL3 papers
- University of California, BerkeleyUS3 papers
- Arizona State UniversityUS2 papers
- Centro de Investigación Docencia y Consultoria AdministrativaCO2 papers
- Commonwealth Scientific and Industrial Research OrganisationAU2 papers
- McGill UniversityCA2 papers
- Swinburne University of TechnologyAU2 papers
- The University of Texas at DallasUS2 papers
5 papers · 1 filter
Optimization of Antenna Performance for Global 21-cm Observations and Verification Using Scaled Copies
O. A. Restrepo, F. I. Lucero, G. Chaparro +5
The sky-averaged cosmological 21 cm signal can improve our understanding of the evolution of the early Universe from the Dark Age to the end of the Epoch of Reionization. Although…
Simulating the Detection of the Global 21 cm Signal with MIST for Different Models of the Soil and Beam Directivity
Raul A. Monsalve, Christian H. Bye, Jonathan L. Sievers +10
The Mapper of the IGM Spin Temperature (MIST) is a new ground-based, single-antenna, radio experiment attempting to detect the global 21 cm signal from the Dark Ages and Cosmic Daw…
Mapper of the IGM spin temperature: instrument overview
R. A. Monsalve, C. Altamirano, V. Bidula +17
The observation of the global 21 cm signal produced by neutral hydrogen gas in the intergalactic medium (IGM) during the Dark Ages, Cosmic Dawn, and Epoch of Reionization requires…
The Early Data Release of the Dark Energy Spectroscopic Instrument
DESI Collaboration, A. G. Adame, J. Aguilar +266
The Dark Energy Spectroscopic Instrument (DESI) completed its five-month Survey Validation in May 2021. Spectra of stellar and extragalactic targets from Survey Validation constitu…
Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks
Héctor J. Hortúa, Luz Ángela García, Leonardo Castañeda C
Methods based on Deep Learning have recently been applied on astrophysical parameter recovery thanks to their ability to capture information from complex data. One of these methods…