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Register a new userA 3D extinction map of the Northern Galactic Plane based on IPHAS photometry
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We present a three dimensional map of extinction in the Northern Galactic Plane derived using photometry from the IPHAS survey. The map has fine angular ($sim 10$ arcmin) and distance (100 pc) sampling allied to a significant depth ($gtrsim 5$ kpc). We construct the map using a method based on a hierarchical Bayesian model as previously described by Sale (2012). In addition to mean extinction, we also measure differential extinction, which arises from the fractal nature of the ISM, and show that it will be the dominant source of uncertainty in estimates of extinction to some arbitrary position. The method applied also furnishes us with photometric estimates of the distance, extinction, effective temperature, surface gravity, and mass for $sim 38$ million stars. Both the extinction map and the catalogue of stellar parameters are made publicly available via http://www.iphas.org/extinction .
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We report H$alpha$ filter photometry for 197 northern hemisphere planetary nebulae (PNe) obtained using imaging data from the IPHAS survey. H$alpha$+[N II] fluxes were measured for 46 confirmed or possible PNe discovered by the IPHAS survey and for 151 previously catalogued PNe that fell within the area of the northern Galactic Plane surveyed by IPHAS. After correcting for [N II] emission admitted by the IPHAS H$alpha$ filter, the resulting H$alpha$ fluxes were combined with published radio free-free fluxes and H$beta$ fluxes, in order to estimate mean optical extinctions to 143 PNe using ratios involving their integrated Balmer line fluxes and their extinction-free radio fluxes. Distances to the PNe were then estimated using three different 3D interstellar dust extinction mapping methods, including the IPHAS-based H-MEAD algorithm of Sale (2014). These methods were used to plot dust extinction versus distance relationships for the lines of sight to the PNe; the intercepts with the derived dust optical extinctions allowed distances to the PNe to be inferred. For 17 of the PNe in our sample reliable Gaia DR2 distances were available and these have been compared with the distances derived using three different extinction mapping algorithms as well as with distances from the nebular radius vs. H$alpha$ surface brightness relation of Frew et al. (2016). That relation and the H-MEAD extinction mapping algorithm yielded the closest agreement with the Gaia DR2 distances.
We present a method to simultaneously infer the interstellar extinction parameters $A_0$ and $R_0$, stellar effective temperature $T_{rm eff}$, and distance modulus $mu$ in a Bayesian framework. Using multi-band photometry from SDSS and UKIDSS, we train a forward model to emulate the colour-change due to physical properties of stars and the interstellar medium for temperatures from 4000 to 9000 K and extinctions from 0 to 5 mag. We introduce a Hertzsprung-Russel diagram prior to account for physical constraints on the distribution of stars in the temperature-absolute magnitude plane. This allows us to infer distances probabilistically. Influences of colour information, priors and model parameters are explored. Residual mean absolute errors (MAEs) on a set of objects for extinction and temperature are 0.2 mag and 300 K, respectively, for $R_0$ fixed to 3.1. For variable $R_0$, we obtain MAEs of 0.37 mag, 412.9 K and 0.74 for $A_0$, $T_{rm eff}$ and $R_0$, respectively. Distance moduli are accurate to approximately 2 mag. Quantifying the precisions of individual parameter estimates with $68%$ confidence interval of the posterior distribution, we obtain 0.05 mag, 66 K, 2 mag and 0.07 for $A_0$, $T_{rm eff}$, $mu$ and $R_0$, respectively, although we find that these underestimate the accuracy of the model. We produce two-dimensional maps in extinction and $R_0$ that are compared to previous work. Furthermore we incorporate the inferred distance information to compute fully probabilistic distance profiles for individual lines of sight. The individual stellar AP estimates, combined with inferred 3D information will make possible many Galactic science and modelling applications. Adapting our method to work with other surveys, such as Pan-STARRS and Gaia, will allow us to probe other regions of the Galaxy.
The INT Photometric Halpha Survey of the Northern Galactic Plane (IPHAS) is a 1800 square degrees CCD survey of the northern Milky Way spanning the latitude range -5 < b < +5 (degrees) and reaching down to r ~ 20 (10-sigma). It may increase the number of known northern emission line sources by an order of magnitude. Representative observations and an assessment of point-source data from IPHAS, now underway, are presented. The data obtained are Wide Field Camera images in Halpha narrow-band, and Sloan r and i broad-band, filters. We simulate IPHAS (r - Halpha, r - i) point-source colours using a spectrophotometric library of stellar spectra and available filter transmission profiles: this gives expected colours for (i) solar-metallicity stars, without Halpha emission, and (ii) emission line stars. Comparisons with Aquila field observations show that simulated normal star colours reproduce the data well for spectral types earlier than M. Spectroscopic follow-up of a Cepheus field confirms that sources lying above the main stellar locus in the (r - Halpha, r - i) plane are emission line objects, with very few failures. Examples of Halpha deficit objects -- a white dwarf and a carbon star -- are shown to be readily distinguished by their IPHAS colours. The role IPHAS can play in studies of nebulae is discussed briefly, and illustrated by a continuum-subtracted mosaic image of the SNR, Shajn 147. The final catalogue of IPHAS point sources will contain photometry on ~80 million objects. (abridged)
We present three 14400 square degree relative extinction maps of the Galactic Plane (|b|<20degrees) obtained from 2MASS using accumulative star counts (Wolf diagrams). This method is independent of the colour of the stars and the variation of extinction with wavelength. Stars were counted in 3.5x3.5 boxes, every 20. 1x1degree surrounding fields were chosen for reference, hence the maps represent local extinction enhancements and ignore any contribution from the ISM or very large clouds. Data reduction was performed on a Beowulf-type cluster (in approximately 120 hours). Such a cluster is ideal for this type of work as areas of the sky can be independently processed in parallel. We studied how extinction depends on wavelength in all of the high extinction regions detected and within selected dark clouds. On average a power law opacity index (beta) of 1.0 to 1.8 in the NIR was deduced. The index however differed significantly from region to region and even within individual dark clouds. That said, generally it was found to be constant, or to increase, with wavelength within a particular region.
We present an algorithm ({scshape mead}, for `Mapping Extinction Against Distance) which will determine intrinsic ($r - i$) colour, extinction, and distance for early-A to K4 stars extracted from the IPHAS $r/i/Halpha$ photometric database. These data can be binned up to map extinction in three dimensions across the northern Galactic Plane. The large size of the IPHAS database ($sim 200$ million unique objects), the accuracy of the digital photometry it contains and its faint limiting magnitude ($r sim 20$) allow extinction to be mapped with fine angular ($ sim 10 $ arcmin) and distance ($sim 0.1$ ~kpc) resolution to distances of up to 10 kpc, outside the Solar Circle. High reddening within the Solar Circle on occasion brings this range down to $sim 2$ kpc. The resolution achieved, both in angle and depth, greatly exceeds that of previous empirical 3D extinction maps, enabling the structure of the Galactic Plane to be studied in increased detail. {scshape mead} accounts for the effect of the survey magnitude limits, photometric errors, unresolved ISM substructure, and binarity. The impact of metallicity variations, within the range typical of the Galactic disc is small. The accuracy and reliability of {scshape mead} are tested through the use of simulated photometry created with Monte-Carlo sampling techniques. The success of this algorithm is demonstrated on a selection of fields and the results are compared to the literature.
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