Pattern Recognition and Machine Learning
Citations
124 citations
Cites background or methods from "Pattern Recognition and Machine Lea..."
...(2011), and the R and I filters given in the tables of Claret (2004) using stellar parameters from the discovery paper, although we do not attempt a detailed calculation for the effective passband or the spectroscopic light curves....
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...5 arcmin squared, and consists of three 2048×4608 pixel CCDs arranged side by side with small gaps in-between. We observed the target (V = 11.3, R = 11.2) and two brighter comparison stars (V = 9.8 and V = 11.0) simultaneously in multi-object mode for 5.4 and 5.8 hours each night, allowing several hours either side of transit given the 3.1 hour transit duration. Conditions were not photometric for the duration of either night, and the observations were degraded due to variable cloud cover. This was considerably worse for the first transit, and we discuss the implications of this later. Observations used the R400 grism + OG515 filter with a central wavelength of 725 nm in 2×2 binning. The dispersion is 0.14 nm per (binned) pixel, giving wavelength coverage from about 510–930 nm. Similarly to Gibson et al. (2013), we read out only three regions of interest including the target and the two comparison stars to reduce the readout time to 11.5 seconds. For the first transit, exposure times started at 30 seconds and were reduced to 24 seconds towards the end of the observations to account for varying conditions, allowing for 482 exposures. For the second transit, owing to more stable conditions, the exposure times were kept at 25 seconds (except the first few exposures), resulting in 552 exposures. To minimise slit losses we created a mask with slits of 30′′ length and 15′′ width for the three stars designed using a pre-image taken with GMOS, giving seeing limited (therefore variable) resolution ranging from R≈650–1300 at 725 nm. Fig. 1 shows the pre-image of the field with the approximate positions of the slits marked. Immediately before and after the observations, standard calibrations were taken consisting of flat fields and arc lamp exposures. A calibration mask was also constructed using narrower 1′′ slits at the same positions. Arcs were taken with the calibration mask, and flat fields were obtained with both the science and calibration mask. Data were reduced using the same procedure as Gibson et al. (2013), with the standard GMOS pipeline contained...
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...(2013) and Crossfield et al. (2013) to measure the transmission spectra of WASP-29b, WASP-12b and GJ 3470b, respectively, and demonstrated that a precision of ∼ 1 × 10−4 in transit depth is achievable....
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...5 arcmin squared, and consists of three 2048×4608 pixel CCDs arranged side by side with small gaps in-between. We observed the target (V = 11.3, R = 11.2) and two brighter comparison stars (V = 9.8 and V = 11.0) simultaneously in multi-object mode for 5.4 and 5.8 hours each night, allowing several hours either side of transit given the 3.1 hour transit duration. Conditions were not photometric for the duration of either night, and the observations were degraded due to variable cloud cover. This was considerably worse for the first transit, and we discuss the implications of this later. Observations used the R400 grism + OG515 filter with a central wavelength of 725 nm in 2×2 binning. The dispersion is 0.14 nm per (binned) pixel, giving wavelength coverage from about 510–930 nm. Similarly to Gibson et al. (2013), we read out only three regions of interest including the target and the two comparison stars to reduce the readout time to 11....
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...(2011), and the R and I filters given in the tables of Claret (2004) using stellar parameters from the discovery paper, although we do not attempt a detailed calculation for the effective passband or the spectroscopic light curves. We note that the transit depth (and therefore planet radius) reported in Hartman et al. (2011) is perhaps diluted by the contaminant star. This will dilute the transit depth by a factor of (1 + q), where q is the ratio of the flux from the target and contaminant star in a particular passband. The transit parameters were inferred from i, z and g bands, and we caution that the HAT-P-32b’s radius could be marginally larger than that reported in Hartman et al. (2011), depending on the apertures used for the photometry and the relative contribution to the final parameters of each of the light curves. Using the distributions from the MCMC chains, we calculate further system parameters for HAT-P-32, also reported in Tab. 1. Where the distributions were not available, we generated draws from normal distributions from the values reported in the literature and combined them with those inferred from the MCMC chains. This included the stellar mass and radius (M? and R?) and the planetary mass (Mp). We calculated values for the transit duration (T14), inclination (i), planet radius (Rp), planet density (ρp), log surface gravity (log gp), and the equilibrium temperature (Tp). Again, these distributions are consistent with the results of Hartman et al. (2011)....
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124 citations
Cites background from "Pattern Recognition and Machine Lea..."
...For details, we refer the reader to [14], [34]....
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123 citations
Cites background from "Pattern Recognition and Machine Lea..."
...The denominator ) | ( H D P is called the marginal likelihood, or the evidence [51,77,80,82,91,92] of the model where the parameters have been marginalized out....
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...This change factor is equal to the fraction of the posterior parameter space to the prior parameter space [51,77,90] and effectively measures how much information the model has extracted from the data....
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...Bayesian inference [26,51,77,81,82] allows one to quantify uncertainties in quantities of interest in a formal way....
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...The next two sections describe the typical implementation of PBIL in the area of pattern recognition (PR) [51,52,53] and our adaptation to the FEM context....
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...9 is effectively the SSE and is commonly referred to as the data-fit term [51,77,78,79] and the second term is known as the model complexity penalty term....
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123 citations
123 citations
Cites methods from "Pattern Recognition and Machine Lea..."
...MLR can also be used for classification by defining an appropriate class label matrix [44]–[46]....
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