Improved photometric redshifts with colour-constrained galaxy templates for future wide-area surveys

Cosmology and galaxy evolution studies with LSST, Euclid, and Roman, will require accurate redshifts for the detected galaxies. In this study, we present improved photometric redshift estimates for galaxies using a template library that populates three-colour space and is constrained by HST/CANDELS photometry. For the training sample, we use a sample of galaxies having photometric redshifts that allows us to train on a large, unbiased galaxy sample having deep, unconfused photometry at optical-to-mid infrared wavelengths. Galaxies in the training sample are assigned to cubes in 3D colour space, V − H, I − J, and z − H. We then derive the best-fitting spectral energy distributions of the training sample at the fixed CANDELS median photometric redshifts to construct the new template library for each individual colour cube (i.e. colour-cube-based template library). We derive photometric redshifts (photo-z) of our target galaxies using our new colour-cube-based template library and with photometry in only a limited set of bands, as expected for the aforementioned surveys. As a result, our method yields σ_(NMAD) of 0.026 and an outlier fraction of 6 per cent using only photometry in the LSST and Euclid/Roman bands. This is an improvement of ∼10 per cent on σ_(NMAD) and a reduction in outlier fraction of ∼13 per cent compared to other techniques. In particular, we improve the photo-z precision by about 30 per cent at 2 < z < 3. We also assess photo-z improvements by including K or mid-infrared bands to the ugrizYJH photometry. Our colour-cube-based template library is a powerful tool to constrain photometric redshifts for future large surveys

Insights into physical conditions and magnetic fields from high redshift quasars

We use archival WISE and Spitzer photometry to derive optical line fluxes for a sample of distant quasars at z ~6. We find evidence for exceptionally high equivalent width [OIII] emission (rest-frame EW ~400 {\AA}) similar to that inferred for star-forming galaxies at similar redshifts. The median Halpha and Hbeta equivalent widths are derived to be ~400{\AA} and 100~{\AA}, respectively, and are consistent with values seen among quasars in the local Universe, and at z ~2. After accounting for the contribution of photoionization in the broad line regions of quasars, we suggest that the OIII emission corresponds to strong, narrow line emission likely arising from feedback due to massive star-formation in the quasar host. The high [OIII]/Hbeta line ratios can uniquely be interpreted with radiative shock models, and translate to magnetic field strengths of ~8 microGauss with shock velocities of ~400km/s. Our measurement implies that strong, coherent magnetic fields were present in the interstellar medium at a time when the universe was < 1 billion years old. Comparing our estimated magnetic field strengths with models for the evolution of galaxy-scale fields, favors high seed field strengths exceeding 0.1 microGauss, the first observational constraint on such fields. This high value favors scenarios where seed magnetic fields were produced by turbulence in the early stages of galaxy formation. Forthcoming mid-infrared spectroscopy with the James Webb Space Telescope will help constrain the physical conditions in quasar hosts further.Comment: 11 pages, 6 figures, submitted to MNRA

Improved photometric redshifts with colour-constrained galaxy templates for future wide-area surveys

Cosmology and galaxy evolution studies with LSST, Euclid, and Roman, will require accurate redshifts for the detected galaxies. In this study, we present improved photometric redshift estimates for galaxies using a template library that populates three-colour space and is constrained by HST/CANDELS photometry. For the training sample, we use a sample of galaxies having photometric redshifts that allows us to train on a large, unbiased galaxy sample having deep, unconfused photometry at optical-to-mid infrared wavelengths. Galaxies in the training sample are assigned to cubes in 3D colour space, V − H, I − J, and z − H. We then derive the best-fitting spectral energy distributions of the training sample at the fixed CANDELS median photometric redshifts to construct the new template library for each individual colour cube (i.e. colour-cube-based template library). We derive photometric redshifts (photo-z) of our target galaxies using our new colour-cube-based template library and with photometry in only a limited set of bands, as expected for the aforementioned surveys. As a result, our method yields σ_(NMAD) of 0.026 and an outlier fraction of 6 per cent using only photometry in the LSST and Euclid/Roman bands. This is an improvement of ∼10 per cent on σ_(NMAD) and a reduction in outlier fraction of ∼13 per cent compared to other techniques. In particular, we improve the photo-z precision by about 30 per cent at 2 < z < 3. We also assess photo-z improvements by including K or mid-infrared bands to the ugrizYJH photometry. Our colour-cube-based template library is a powerful tool to constrain photometric redshifts for future large surveys

Galaxy Ellipticity Measurements in the Near-Infrared for Weak Lensing

We investigate the value of the near-infrared imaging from upcoming surveys for constraining the ellipticities of galaxies. We select galaxies between 0.5 < z < 3 that are brighter than expected Euclid sensitivity limits from the GOODS-S and N fields in CANDELS. The co-added CANDELS/HST V+I and J+H images are degraded in resolution and sensitivity to simulate Euclid-quality optical and near-infrared (NIR) images. We then run GALFIT on these simulated images and find that optical and NIR provide similar performance in measuring galaxy ellipticities at redshifts 0.5 1.0, the NIR-selected source density is higher by a factor of 1.4 and therefore the standard error in NIR-derived ellipticities is about 30% smaller, implying a more precise ellipticity measurement. The good performance of the NIR is mainly because galaxies have an intrinsically smoother light distribution in the NIR bands than in the optical, the latter tracing the clumpy star-forming regions. In addition, the NIR bands have a higher surface brightness per pixel than the optical images, while being less affected by dust attenuation. Despite the worse spatial sampling and resolution of Euclid NIR compared to optical, the NIR approach yields equivalent or more precise galaxy ellipticity measurements. If systematics that affect shape such as dithering strategy and point spread function undersampling can be mitigated, inclusion of the NIR can improve galaxy ellipticity measurements over all redshifts. This is particularly important for upcoming weak lensing surveys, such as with Euclid and WFIRST.Comment: 11 pages, 6 figures, and 1 table; Accepted for publication in the Ap

How to Find Variable Active Galactic Nuclei with Machine Learning

Machine-learning (ML) algorithms will play a crucial role in studying the large data sets delivered by new facilities over the next decade and beyond. Here, we investigate the capabilities and limits of such methods in finding galaxies with brightness-variable active galactic nuclei (AGNs). Specifically, we focus on an unsupervised method based on self-organizing maps (SOM) that we apply to a set of nonparametric variability estimators. This technique allows us to maintain domain knowledge and systematics control while using all the advantages of ML. Using simulated light curves that match the noise properties of observations, we verify the potential of this algorithm in identifying variable light curves. We then apply our method to a sample of ~8300 WISE color-selected AGN candidates in Stripe 82, in which we have identified variable light curves by visual inspection. We find that with ML we can identify these variable classified AGN with a purity of 86% and a completeness of 66%, a performance that is comparable to that of more commonly used supervised deep-learning neural networks. The advantage of the SOM framework is that it enables not only a robust identification of variable light curves in a given data set, but it is also a tool to investigate correlations between physical parameters in multidimensional space—such as the link between AGN variability and the properties of their host galaxies. Finally, we note that our method can be applied to any time-sampled light curve (e.g., supernovae, exoplanets, pulsars, and other transient events)