The Discovery of a Field Methane Dwarf from Sloan Digital Sky Survey Commissioning Data

Strauss, Michael A.; Fan, Xiaohui; Gunn, James E.; Leggett, S. K.; Geballe, T. R.; Pier, Jeffrey R.; Lupton, Robert H.; Knapp, G. R.; Annis, J.; Brinkmann, J.; Crocker, James H.; Csabai, I.; Fukugita, M.; Golimowski, D. A.; Harris, Frederick H.; Hennessy, G. S.; Hindsley, Robert B.; Ivezić, Željko; Kent, Stephen M.; Lamb, D. Q.; Munn, Jeffrey A.; Newberg, Heidi Jo; Rechenmacher, R.; Schneider, Donald P.; Smith, J. Allyn; Stoughton, Chris; Tucker, D. L.; Waddell, Patrick; York, Donald G.

doi:10.1086/312218

Cited by 185 publications

(90 citation statements)

References 35 publications

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“…References. Albert et al (2011) [A11]; Artigau et al (2006) [A06]; Artigau et al (2010) [A10]; [B06]; Bouy et al (2003) [B03]; Burgasser et al (1999) [B99]; Burgasser et al (2000) [B00]; Burgasser et al (2003) [B02]; Burgasser et al (2003) [BK03]; Burgasser et al (2004) [B04]; Burgasser et al (2005) [B05]; Burgasser et al (2006) [BK06]; Burgasser et al (2008) [B08]; Burgasser et al (2010) [BC10]; Burningham et al (2010) [B10]; Chiu et al (2006) [C06]; Dahn et al (2002) [D02]; [D12]; Ellis et al (2005) [E05]; Faherty et al (2012) [F12]; Gelino et al (2002) [G02]; Hawley et al (2002) [H02]; Knapp et al (2004) [K04]; Leggett et al (2000) [L00]; Looper et al (2007) [L07]; Looper et al (2008) [L08]; Reid et al (2008) [R08]; Scholz et al (2003) [S03]; Scholz et al (2003) [S10]; Stumpf et al (2011) [S11]; Smart et al (2013) [S13]; Strauss et al (1999) [S99]; Tinney et al (2003) [T03]; Tinney et al (2005) [T05]; Vrba et al (2004) [V04]. …”

Section: Discussionmentioning

confidence: 99%

The brown dwarf atmosphere monitoring (BAM) project

Wilson

Rajan

Patience

2014

A&A

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Using the SofI instrument on the 3.5 m New Technology Telescope, we have conducted an extensive near-infrared monitoring survey of an unbiased sample of 69 brown dwarfs spanning the L0 to T8 spectral range, with at least one example of each spectral type. Each target was observed for a 2−4 h period in the J s -band, and the median photometric precision of the data is ∼0.7%. A total of 14 brown dwarfs were identified as variables with min-to-max amplitudes ranging from 1.7% to 10.8% over the observed duration. All variables satisfy a statistical significance threshold with a p-value ≤5% based on comparison with a median reference star light curve. Approximately half of the variables show pure sinusoidal amplitude variations similar to 2MASSJ2139+0220, and the remainder show multi-component variability in their light curves similar to SIMPJ0136+0933. It has been suggested that the L-T transition should be a region of a higher degree of variability if patchy clouds are present, and this survey was designed to test the patchy cloud model with photometric monitoring of both the L-T transition and non-transition brown dwarfs. The measured frequency of variables is 13 +10 −4 % across the L7−T4 spectral range, indistinguishable from the frequency of variables of the earlier spectral types (30 +11 −8 %), the later spectral types (13 +10 −4 %), or the combination of all non-transition region brown dwarfs (22 +7 −5 %). The variables are not concentrated in the transition, in a specific colour, or in binary systems. Of the brown dwarfs previously monitored for variability, only ∼60% maintained the state of variability (variable or constant), with the remaining switching states. The 14 variables include 9 newly identified variables that will provide important systems for follow-up multi-wavelength monitoring to further investigate brown dwarf atmosphere physics.

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Section: Discussionmentioning

confidence: 99%

The brown dwarf atmosphere monitoring (BAM) project

Wilson

Rajan

Patience

2014

A&A

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“…These total errors include the internal validation errors described in the previous section, and errors due to the imperfect representation of real spectra by synthetic models. The ground-based spectra used for validating the regression models are the compilations by Reid 2 (Burgasser et al 2000;Delfosse et al 1997;Gizis et al 2000b,a;Kirkpatrick et al 1999Kirkpatrick et al , 2000Reid et al 1999Reid et al , 2000Strauss et al 1999;Tsvetanov et al 2000), Leggett 3 (Chiu et al 2006;Golimowski et al 2004;Knapp et al 2004), the NIRSPEC Brown Dwarf Spectroscopic Survey 4 (McLean et al 2003), and the IRTF spectral library 5 (Cushing et al 2005;Rayner et al 2009). None of the observed spectra covers the full Gaia wavelength range,which is especially due to the lack of optical observations at the coolest end.…”

Section: Validation With Real Spectramentioning

confidence: 99%

Properties of ultra-cool dwarfs withGaia

Sarro¹,

Carrion²,

Barrado³

et al. 2013

A&A

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Context. The Gaia catalogue will contain observations and physical parameters of a vast number of objects, including ultra-cool dwarf stars, which we define here as stars with a temperature below 2500 K. Aims. We aimed to assess the accuracy of the Gaia T eff and log (g) estimates as derived with current models and observations. Methods. We assessed the validity of several inference techniques for deriving the physical parameters of ultra-cool dwarf stars: Gaussian processes, support vector machines, k-nearest neighbours, kernel partial least squares and Bayesian estimation. In addition, we tested the potential benefits of data compression for improving robustness and speed. We used synthetic spectra derived from ultracool dwarf models to construct (train) the regression models. We derived the intrinsic uncertainties of the best inference models and assessed their validity by comparing the estimated parameters with the values derived in the bibliography for a sample of ultra-cool dwarf stars observed from the ground. Results. We estimated the total number of ultra-cool dwarfs per spectral subtype, and obtained values that can be summarised (in orders of magnitude) as 400 000 objects in the M5−L0 range, 600 objects between L0 and L5, 30 objects between L5 and T0, and 10 objects between T0 and T8. A bright ultra-cool dwarf (with T eff = 2500 K and log (g) = 3.5) will be detected by Gaia out to approximately 220 pc, while for T eff = 1500 K (spectral type L5) and the same surface gravity, this maximum distance reduces to 10−20 pc. We found the cross-validation RMSE prediction error to be 10 K for regression models based on the k-nearest neighbours and 62 K for Gaussian process models in the faintest limit (Gaia magnitude G = 20). However, these values correspond to the evaluation of the regression models with independent test sets of synthetic spectra of the same model families as used in the training phase (internal errors). For the k-nearest neighbours model, this seems an overly optimistic error estimate due to the use of a dense grid of examples in the training set, together with a relatively high signal-to-noise ratio for the end-of-mission data. The RMSE of the prediction deduced from ground-based spectra of ultra-cool dwarfs simulated at the Gaia spectral range and resolution, and for a Gaia magnitude G = 20 is 213 K and 266 K for the models based on k-nearest neighbours and Gaussian process regression, respectively. These are total errors in the sense that they include the internal and external errors, with the latter caused by the inability of the synthetic spectral models (used for the construction of the regression models) to exactly reproduce the observed spectra, and by the large uncertainties in the current calibrations of spectral types and effective temperatures. We found maximum-likelihood methods (minimum χ 2 , k-nearest neighbours, and Bayesian estimation with flat priors) to be biased in the L0-T0 range in that they systematically assign a temperature around 1700 K. Finally, the likeliho...

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“…The selection of the L-dwarf sample was described in T01. The T-dwarfs were selected from the samples of Burgasser et al (2000Burgasser et al ( , 2002a, Leggett et al (2000), and Strauss et al (1999). The final sample consists of 54 cool field dwarfs, 17 M type, 26 L type, and 11 T type.…”

Section: The Samplementioning

confidence: 99%

A low-resolution near-infrared spectral library of M-, L-, and T-dwarfs

Testi

2009

A&A

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We present complete near-infrared (0.85-2.45 μm), low-resolution (R ∼ 100) spectra of a sample of 54 disk M-, L-, and T-dwarfs with reliable optical or near infrared spectral-type classification from the literature. The observations were obtained with a prism-based optical element, the Amici device, which provides a complete spectrum of the source on the detector. Our observations indicate that low-resolution near-infrared spectroscopy can be used to determine the spectral classification of late-type field dwarfs in a fast but accurate way. We derive a set of near-infrared spectral indices that are useful to the classification of field dwarfs not seriously affected by reddening. Finally, we show that the comparison of Amici spectra with model atmospheres allows us to obtain a reliable estimate of the dwarf effective temperatures.

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The Discovery of a Field Methane Dwarf from Sloan Digital Sky Survey Commissioning Data

Cited by 185 publications

References 35 publications

The brown dwarf atmosphere monitoring (BAM) project

The brown dwarf atmosphere monitoring (BAM) project

Properties of ultra-cool dwarfs withGaia

A low-resolution near-infrared spectral library of M-, L-, and T-dwarfs

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