Near-infrared luminosity function and colours of dwarf galaxies in the Coma Cluster

We present K-band observations of the low-luminosity galaxies in the Coma cluster, which are responsible for the steep upturn in the optical luminosity function at M_R ~ -16, discovered recently. The main results of this study are (i) The optical$-$near-infrared colours of these galaxies imply that they are dwarf spheroidals. The median M-K colour for galaxies with -19.3 < M_K < -16.3 is 3.6 mag. (ii) The K-band luminosity function in the Coma cluster at the faint-end is not wee constrained, because of the uncertainties due to the field-to-field variance of the background. However, within the estimate large errors, it is consistent with the R-band luminosity function, shifted by $\sim3$ magnitudes. (iii) Many of the cluster dwarfs lie in a region of the B-K vs. B-R colour-colour diagram where background galaxies are rare Local dwarf spheroidal galaxies lie in this region too. This suggests that a better measurement of the K-band cluster luminosity function can be made if the field-to-field variance of the background can be measured as a function of colour. (iv) If we assume that none of the galaxies in the region of the B-K vs. B-R plane given in (iii) in our cluster fields are background, and that all the cluster galaxies with $15.5 < K < 18.5$ lie in this region of the plane, then we measure alpha = -1.41 +/- 0.35 for -19.3 < M_K < -16.3, where alpha is the logarithmic slope of the luminosity function.Comment: 6 pages, 8 figs, 2 tabs, MNRAS in press; email: [email protected], [email protected]

The stellar content of brightest cluster galaxies

We present near-infrared K-band spectroscopy of 21 elliptical or cD Brightest Cluster Galaxies (BCGs), for which we have measured the strength of the 2.293 micron CO stellar absorption feature. We find that the strength of this feature is remarkably uniform among these galaxies, with a smaller scatter in equivalent width than for the normal elliptical population in the field or clusters. The scatter for BCGs is 0.156 nm, compared with 0.240 nm for Coma cluster ellipticals, 0.337 nm for ellipticals from a variety of other clusters, and 0.422 nm for field ellipticals. We interpret this homogeneity as being due to a greater age, or more uniform history, of star formation in BCGs than in other ellipticals; only a small fraction of the scatter can be due to metallicity variations, even in the BCGs. Notwithstanding the small scatter, correlations are found between CO strength and various galaxy properties, including R-band absolute magnitude, which could improve the precision of these galaxies as distance indicators in measurements of cosmological parameters and velocity flows.Comment: 7 pages, 8 figures, accepted for publication by MNRA

Hot-Dust (690K) Luminosity Density and its Evolution in the last 7.5Gyr

[Abridged] We study the contribution of hot-dust to the luminosity density of galaxies and its evolution with cosmic time. Using the Spitzer-IRAC data in the COSMOS field, we estimate the contribution from hot-dust at rest-frame 4.2um (from ~0 < z < ~0.2 up to ~0.5 < z < ~0.9). This wavelength corresponds to black-body temperature of ~690K. The contribution due to stellar emission is estimated from the rest-frame 1.6um luminosity (assumed to result from stellar emission alone) and subtracted from the mid-infrared luminosity of galaxies to measure hot-dust emission. In order to attempt the study of the 3.3um-PAH feature, we use the rest-frame 4.2um to infer the hot-dust flux at 3.3um. This study is performed for different spectral types of galaxies: early-type, late-type, starburst, and IR-selected AGN. We find that: (a) the decrease of the hot-dust luminosity density since ~0.5 < z < ~1 is steeper (by at least ~0.5dex) compared to that of the cold-dust, giving support to the scenario where galaxy obscuration increases with redshift, as already proposed in the literature; (b) hot-dust and PAH emission evolution seems to be correlated with stellar mass, where rest-frame 1.6um luminous non-AGN galaxies (i.e., massive systems) show a stronger decrement (with decreasing redshift) in hot-dust and PAH emission than the less luminous (less massive) non-AGN galaxies; (c) despite comprising < ~3% of the total sample, AGN contribute as much as a third to the hot-dust luminosity density at z < 1 and clearly dominate the bright-end of the total hot-dust Luminosity Density Function at ~0.5 < z < ~0.9; (d) the average dust-to-total luminosity ratio increases with redshift, while PAH-to-total luminosity ratio remains fairly constant; (e) at M_1.6 > -25, the dust-to-total and PAH-to-total luminosity ratios increase with decreasing luminosity, but deeper data is required to confirm this result.Comment: Accepted on The Astrophysical Journal on August 20th 2013, emulateapj, 14 pages, 16 figure

Communication Over MIMO Broadcast Channels Using Lattice-Basis Reduction

A simple scheme for communication over MIMO broadcast channels is introduced which adopts the lattice reduction technique to improve the naive channel inversion method. Lattice basis reduction helps us to reduce the average transmitted energy by modifying the region which includes the constellation points. Simulation results show that the proposed scheme performs well, and as compared to the more complex methods (such as the perturbation method) has a negligible loss. Moreover, the proposed method is extended to the case of different rates for different users. The asymptotic behavior of the symbol error rate of the proposed method and the perturbation technique, and also the outage probability for the case of fixed-rate users is analyzed. It is shown that the proposed method, based on LLL lattice reduction, achieves the optimum asymptotic slope of symbol-error-rate (called the precoding diversity). Also, the outage probability for the case of fixed sum-rate is analyzed.Comment: Submitted to IEEE Trans. on Info. Theory (Jan. 15, 2006), Revised (Jun. 12, 2007

Comparison of Observed Galaxy Properties with Semianalytic Model Predictions using Machine Learning

With current and upcoming experiments such as WFIRST, Euclid and LSST, we can observe up to billions of galaxies. While such surveys cannot obtain spectra for all observed galaxies, they produce galaxy magnitudes in color filters. This data set behaves like a high-dimensional nonlinear surface, an excellent target for machine learning. In this work, we use a lightcone of semianalytic galaxies tuned to match CANDELS observations from Lu et al. (2014) to train a set of neural networks on a set of galaxy physical properties. We add realistic photometric noise and use trained neural networks to predict stellar masses and average star formation rates on real CANDELS galaxies, comparing our predictions to SED fitting results. On semianalytic galaxies, we are nearly competitive with template-fitting methods, with biases of $0.01$ dex for stellar mass, $0.09$ dex for star formation rate, and $0.04$ dex for metallicity. For the observed CANDELS data, our results are consistent with template fits on the same data at $0.15$ dex bias in $M_{\rm star}$ and $0.61$ dex bias in star formation rate. Some of the bias is driven by SED-fitting limitations, rather than limitations on the training set, and some is intrinsic to the neural network method. Further errors are likely caused by differences in noise properties between the semianalytic catalogs and data. Our results show that galaxy physical properties can in principle be measured with neural networks at a competitive degree of accuracy and precision to template-fitting methods.Comment: 19 pages, 10 figures, 6 tables. Accepted for publication in Ap