Esta web estará fuera de servicio por mantenimiento el lunes 6 de mayo de 7:30 a 8:00.

Near-IR and Optical Observations of the Ongoing Outburst of SAX J1808.4-3658

Bibcode
2008ATel.1733....1M
Maitra, D.; Buxton, M.; Tourtellotte, S.; Altamirano, D.; Patruno, A.; Casella, P.; Linares, M.; Tudose, V.; Russell, D.; Wijnands, R.; Bailyn, C.
Referencia bibliográfica

The Astronomer's Telegram, #1733

Fecha de publicación:
9
2008
Número de autores
11
Número de autores del IAC
0
Número de citas
1
Número de citas referidas
0
Descripción
Following the report of a new outburst of the accreting millisecond pulsar SAX J1808.4-3658 by Markwardt and Swank (ATel #1728), the source was observed using the CTIO/SMARTS 1.3m telescope on MJD 54732.0998, in I- and H- bands. We clearly detected the source at magnitudes significantly higher than its quiescent level, confirming that the source is indeed in outburst.
Tipo
Sin árbitro
Estrellas de neutrones
Púlsares

Te puede interesar

  • Sin árbitro
    CONCERTO: Instrument and status
    CONCERTO (CarbON CII line in post-rEionization and ReionizaTiOn) is a low-resolution Fourier transform spectrometer dedicated to the study of star-forming galaxies and clusters of galaxies in the transparent millimeter windows from the ground. It is characterized by a wide instantaneous 18.6 arcmin field of view, operates at 130-310 GHz, and was
    Fasano, Alessandro et al.

    Fecha de publicación:

    6
    2024
    Bibcode
    2024EPJWC.29300018F
    Número de citas
    0
  • Sin árbitro
    Generating galaxy clusters mass density maps from mock multiview images via deep learning
    Galaxy clusters are composed of dark matter, gas and stars. Their dark matter component, which amounts to around 80% of the total mass, cannot be directly observed but traced by the distribution of diffused gas and galaxy members. In this work, we aim to infer the cluster's projected total mass distribution from mock observational data, i.e. stars
    de Andres, Daniel et al.

    Fecha de publicación:

    6
    2024
    Bibcode
    2024EPJWC.29300013D
    Número de citas
    0
  • Sin árbitro
    A machine learning method to infer clusters of galaxies mass radial profiles from mock Sunyaev-Zel'dovich maps with The Three Hundred clusters
    Our study introduces a new machine learning algorithm for estimating 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich (SZ) effect maps. We generate mock images from 2522 simulated clusters, employing an autoencoder and random forest in our approach. Notably, our model makes no prior assumptions
    Ferragamo, A. et al.

    Fecha de publicación:

    6
    2024
    Bibcode
    2024EPJWC.29300019F
    Número de citas
    0