Extremely Large Telescope

Abstract:

We present the first degree-scale tomography map of the dusty magnetized interstellar medium (ISM) from stellar polarimetry and distance measurements. We used the RoboPol polarimeter at Skinakas Observatory to conduct a survey of the polarization of starlight in a region of the sky of about four square degrees. We propose a Bayesian method to decompose the stellar-polarization source field along the distance to invert the three-dimensional (3D) volume occupied by the observed stars. We used this method to obtain the first 3D map of the dusty magnetized ISM. Specifically, we produced a tomography map of the orientation of the plane-of-sky component of the magnetic field threading the diffuse, dusty regions responsible for the stellar polarization. For the targeted region centered on Galactic coordinates (l, b) (103.3, 22.3), we identified several ISM clouds. Most of the lines of sight intersect more than one cloud. A very nearby component was detected in the foreground of a dominant component from which most of the polarization signal comes and which we identified as being an intersection of the wall of the Local Bubble and the Cepheus Flare. Farther clouds, with a distance of up to 2 kpc, were similarly detected. Some of them likely correspond to intermediate-velocity clouds seen in H I spectra in this region of the sky. We found that the orientation of the plane-of-sky component of the magnetic field changes along distance for most of the lines of sight. Our study demonstrates that starlight polarization data coupled to distance measures have the power to reveal the great complexity of the dusty magnetized ISM in 3D and, in particular, to provide local measurements of the plane-of-sky component of the magnetic field in dusty regions. This demonstrates that the inversion of large data volumes, as expected from the PASIPHAE survey, will provide the necessary means to move forward in the modeling of the Galactic magnetic field and of the dusty magnetized ISM as a contaminant in observations of the cosmic microwave background polarization.

Abstract:

Context. The calibration of optical polarimeters relies on the use of stars with negligible polarization (i.e., unpolarized standard stars) for determining the instrumental polarization zero point. For wide-field polarimeters, calibration is often done by imaging the same star over multiple positions in the field of view (FoV), which is a time-consuming process. A more effective technique is to target fields containing multiple standard stars. While this method has been used for fields with highly polarized stars, there are no such sky regions with well measured unpolarized standard stars. Aims. We aim to identify sky regions with tens of stars exhibiting negligible polarization that are suitable for a zero-point calibration of wide-field polarimeters. Methods. We selected stars in regions with extremely low reddening, located at high Galactic latitudes. We targeted four ∼40′ × 40′ fields in the northern and eight in the southern equatorial hemispheres. Observations were carried out at the Skinakas Observatory and the South African Astronomical Observatory. Results. We found two fields in the north and seven in the south characterized by a mean polarization lower than p < 0.1%. Conclusions. At least 9 out of the 12 fields can be used for a zero-point calibration of wide-field polarimeters.

Abstract:

The arrival of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), Euclid-Wide and Roman wide-area sensitive surveys will herald a new era in strong lens science in which the number of strong lenses known is expected to rise from to. However, current lens-finding methods still require time-consuming follow-up visual inspection by strong lens experts to remove false positives which is only set to increase with these surveys. In this work, we demonstrate a range of methods to produce calibrated probabilities to help determine the veracity of any given lens candidate. To do this we use the classifications from citizen science and multiple neural networks for galaxies selected from the Hyper Suprime-Cam survey. Our methodology is not restricted to particular classifier types and could be applied to any strong lens classifier which produces quantitative scores. Using these calibrated probabilities, we generate an ensemble classifier, combining citizen science, and neural network lens finders. We find such an ensemble can provide improved classification over the individual classifiers. We find a false-positive rate of 10-3 can be achieved with a completeness of 46 per cent, compared to 34 per cent for the best individual classifier. Given the large number of galaxy-galaxy strong lenses anticipated in LSST, such improvement would still produce significant numbers of false positives, in which case using calibrated probabilities will be essential for population analysis of large populations of lenses and to help prioritize candidates for follow-up.