Stars and brown dwarfs in the σ Orionis cluster (Research Note) III. OSIRIS/GTC low-resolution spectroscopy of variable sources

Context. Although many studies have been performed so far, there are still dozens of low-mass stars and brown dwarfs in the young σ Orionis open cluster without detailed spectroscopic characterisation. Aims. We look for unknown strong accretors and disc hosts that were undetected in previous surveys. Methods. We collected low-resolution spectroscopy (R ~ 700) of ten low-mass stars and brown dwarfs in σ Orionis with OSIRIS at the Gran Telescopio Canarias under very poor weather conditions. These objects display variability in the optical, infrared, Hα, and/or X-rays on time scales of hours to years. We complemented our spectra with optical and near-/mid-infrared photometry. Results. For seven targets, we detected lithium in absorption, identified Hα, the calcium doublet, and forbidden lines in emission, and/or determined spectral types for the first time. We characterise in detail a faint, T Tauri-like brown dwarf with an 18 h-period variability in the optical and a large Hα equivalent width of –125  ±  15 Å, as well as two M1-type, X-ray-flaring, low-mass stars, one with a warm disc and forbidden emission lines, the other with a previously unknown cold disc with a large inner hole. Conclusions. New unrevealed strong accretors and disc hosts, even below the substellar limit, await discovery among the list of known σ Orionis stars and brown dwarfs that are variable in the optical and have no detailed spectroscopic characterisation yet.

Fixed vs. variable noise in 2AFC contrast discrimination: lessons from psychometric functions.

Recent discussion regarding whether the noise that limits 2AFC discrimination performance is fixed or variable has focused either on describing experimental methods that presumably dissociate the effects of response mean and variance or on reanalyzing a published data set with the aim of determining how to solve the question through goodness-of-fit statistics. This paper illustrates that the question cannot be solved by fitting models to data and assessing goodness-of-fit because data on detection and discrimination performance can be indistinguishably fitted by models that assume either type of noise when each is coupled with a convenient form for the transducer function. Thus, success or failure at fitting a transducer model merely illustrates the capability (or lack thereof) of some particular combination of transducer function and variance function to account for the data, but it cannot disclose the nature of the noise. We also comment on some of the issues that have been raised in recent exchange on the topic, namely, the existence of additional constraints for the models, the presence of asymmetric asymptotes, the likelihood of history-dependent noise, and the potential of certain experimental methods to dissociate the effects of response mean and variance.