No Arabic abstract
The study of the extragalactic background light (EBL) is undergoing a renaissance. New results from very high energy experiments and deep space missions have broken the deadlock between the contradictory measurements in the optical and near-IR arising from direct versus discrete source estimates. We are also seeing advances in our ability to model the EBL from gamma-ray to radio wavelengths with improved dust models and AGN handling. With the advent of deep and wide spectroscopic and photometric redshift surveys, we can now subdivide the EBL into redshift intervals. This allows for the recovery of the Cosmic Spectral Energy Distribution (CSED), or emissivity of a representative portion of the Universe, at any time. With new facilities coming online, and more unified studies underway from gamma-ray to radio wavelengths, it will soon be possible to measure the EBL to within 1 per cent accuracy. At this level correct modelling of reionisation, awareness of missing populations or light, radiation from the intra-cluster and halo gas, and any signal from decaying dark-matter all become important. In due course, the goal is to measure and explain the origin of all photons incident on the Earths surface from the extragalactic domain, and within which is encoded the entire history of energy production in our Universe.
In Hubble Space Telescope (HST) imaging taken on 10 November 2014, four images of supernova (SN) Refsdal (redshift z=1.49) appeared in an Einstein-cross--like configuration (images S1-S4) around an early-type galaxy in the cluster MACS J1149.5+2223 (z=0.54). Almost all lens models of the cluster have predicted that the SN should reappear within a year in a second host-galaxy image created by the clusters potential. In HST observations taken on 11 December 2015, we find a new source at the predicted position of the new image of SN Refsdal approximately 8 from the previous images S1-S4. This marks the first time the appearance of a SN at a particular time and location in the sky was successfully predicted in advance! We use these data and the light curve from the first four observed images of SN Refsdal to place constraints on the relative time delay and magnification of the new image (SX), compared to images S1-S4. This enables us, for the first time, to test blind lens model predictions of both magnifications and time delays for a lensed SN. We find that the timing and brightness of the new image are consistent with the blind predictions of a fraction of the models. The reappearance illustrates the discriminatory power of this blind test and its utility to uncover sources of systematic uncertainty. From planned HST photometry, we expect to reach a precision of 1-2% on the time delay between S1-S4 and SX.
We describe the construction of an all-sky galaxy catalogue, using SuperCOSMOS scans of Schmidt photographic plates from the UKST and POSS2 surveys. The photographic photometry is calibrated using SDSS data, with results that are linear to 2% or better. All-sky photometric uniformity is achieved by matching plate overlaps and also by requiring homogeneity in optical-to-2MASS colours, yielding zero points that are uniform to 0.03 mag. or better. The typical AB depths achieved are B_J<21, R_F<19.5 and I_N<18.5, with little difference between hemispheres. In practice, the I_N plates are shallower than the B_J & R_F plates, so for most purposes we advocate the use of a catalogue selected in these two latter bands. At high Galactic latitudes, this catalogue is approximately 90% complete with 5% stellar contamination; we quantify how the quality degrades towards the Galactic plane. At low latitudes, there are many spurious galaxy candidates resulting from stellar blends: these approximately match the surface density of true galaxies at |b|=30 deg. Above this latitude, the catalogue limited in B_J & R_F contains in total about 20 million galaxy candidates, of which 75% are real. This contamination can be removed, and the sky coverage extended, by matching with additional datasets. This SuperCOSMOS catalogue has been matched with 2MASS and with WISE, yielding quasi-allsky samples of respectively 1.5 million and 18.5 million galaxies, to median redshifts of 0.08 and 0.20. This legacy dataset thus continues to offer a valuable resource for large-angle cosmological investigations.
We present a point-source detection algorithm that employs the second order Spherical Mexican Hat wavelet filter (SMHW2), and use it on C-BASS northern intensity data to produce a catalogue of point-sources. This catalogue allows us to cross-check the C-BASS flux-density scale against existing source surveys, and provides the basis for a source mask which will be used in subsequent C-BASS and cosmic microwave background (CMB) analyses. The SMHW2 allows us to filter the entire sky at once, avoiding complications from edge effects arising when filtering small sky patches. The algorithm is validated against a set of Monte Carlo simulations, consisting of diffuse emission, instrumental noise, and various point-source populations. The simulated source populations are successfully recovered. The SMHW2 detection algorithm is used to produce a $4.76,mathrm{GHz}$ northern sky source catalogue in total intensity, containing 1784 sources and covering declinations $deltageq-10^{circ}$. The C-BASS catalogue is matched with the Green Bank 6,cm (GB6) and Parkes-MIT-NRAO (PMN) catalogues over their areas of common sky coverage. From this we estimate the $90$ per cent completeness level to be approximately $610,mathrm{mJy}$, with a corresponding reliability of $98$ per cent, when masking the brightest $30$ per cent of the diffuse emission in the C-BASS northern sky map. We find the C-BASS and GB6 flux-density scales to be consistent with one another to within approximately $4$ per cent.
The All-sky Medium Energy Gamma-ray Observatory (AMEGO) is a probe class mission concept that will provide essential contributions to multimessenger astrophysics in the late 2020s and beyond. AMEGO combines high sensitivity in the 200 keV to 10 GeV energy range with a wide field of view, good spectral resolution, and polarization sensitivity. Therefore, AMEGO is key in the study of multimessenger astrophysical objects that have unique signatures in the gamma-ray regime, such as neutron star mergers, supernovae, and flaring active galactic nuclei. The order-of-magnitude improvement compared to previous MeV missions also enables discoveries of a wide range of phenomena whose energy output peaks in the relatively unexplored medium-energy gamma-ray band.
Using the k-means cluster analysis algorithm, we carry out an unsupervised classification of all galaxy spectra in the seventh and final Sloan Digital Sky Survey data release (SDSS/DR7). Except for the shift to restframe wavelengths, and the normalization to the g-band flux, no manipulation is applied to the original spectra. The algorithm guarantees that galaxies with similar spectra belong to the same class. We find that 99 % of the galaxies can be assigned to only 17 major classes, with 11 additional minor classes including the remaining 1%. The classification is not unique since many galaxies appear in between classes, however, our rendering of the algorithm overcomes this weakness with a tool to identify borderline galaxies. Each class is characterized by a template spectrum, which is the average of all the spectra of the galaxies in the class. These low noise template spectra vary smoothly and continuously along a sequence labeled from 0 to 27, from the reddest class to the bluest class. Our Automatic Spectroscopic K-means-based (ASK) classification separates galaxies in colors, with classes characteristic of the red sequence, the blue cloud, as well as the green valley. When red sequence galaxies and green valley galaxies present emission lines, they are characteristic of AGN activity. Blue galaxy classes have emission lines corresponding to star formation regions. We find the expected correlation between spectroscopic class and Hubble type, but this relationship exhibits a high intrinsic scatter. Several potential uses of the ASK classification are identified and sketched, including fast determination of physical properties by interpolation, classes as templates in redshift determinations, and target selection in follow-up works (we find classes of Seyfert galaxies, green valley galaxies, as well as a significant number of outliers). The ASK classification is publicly accessible through various websites.