Measuring the 3D Clustering of Undetected Galaxies Through Cross Correlation of their Cumulative Flux Fluctuations from Multiple Spectral Lines

We discuss a method for detecting the emission from high redshift galaxies by cross correlating flux fluctuations from multiple spectral lines. If one can fit and subtract away the continuum emission with a smooth function of frequency, the remaining signal contains fluctuations of flux with frequency and angle from line emitting galaxies. Over a particular small range of observed frequencies, these fluctuations will originate from sources corresponding to a series of different redshifts, one for each emission line. It is possible to statistically isolate the fluctuations at a particular redshift by cross correlating emission originating from the same redshift, but in different emission lines. This technique will allow detection of clustering fluctuations from the faintest galaxies which individually cannot be detected, but which contribute substantially to the total signal due to their large numbers. We describe these fluctuations quantitatively through the line cross power spectrum. As an example of a particular application of this technique, we calculate the signal-to-noise ratio for a measurement of the cross power spectrum of the OI(63 micron) and OIII(52 micron) fine structure lines with the proposed Space Infrared Telescope for Cosmology and Astrophysics. We find that the cross power spectrum can be measured beyond a redshift of z=8. Such observations could constrain the evolution of the metallicity, bias, and duty cycle of faint galaxies at high redshifts and may also be sensitive to the reionization history through its effect on the minimum mass of galaxies. As another example, we consider the cross power spectrum of CO line emission measured with a large ground based telescope like CCAT and 21-cm radiation originating from hydrogen in galaxies after reionization with an interferometer similar in scale to MWA, but optimized for post-reionization redshifts.Comment: 21 pages, 6 figures; Replaced with version accepted by JCAP; Added an example of cross correlating CO line emission and 21cm line emission from galaxies after reionizatio

Engineering of Cyclodextrin Product Specificity and pH Optima of the Thermostable Cyclodextrin Glycosyltransferase from Thermoanaerobacterium thermosulfurigenes EM1

The product specificity and pH optimum of the thermostable cyclodextrin glycosyltransferase (CGTase) from Thermoanaerobacterium thermosulfurigenes EM1 was engineered using a combination of x-ray crystallography and site-directed mutagenesis. Previously, a crystal soaking experiment with the Bacillus circulans strain 251 β-CGTase had revealed a maltononaose inhibitor bound to the enzyme in an extended conformation. An identical experiment with the CGTase from T. thermosulfurigenes EM1 resulted in a 2.6-Å resolution x-ray structure of a complex with a maltohexaose inhibitor, bound in a different conformation. We hypothesize that the new maltohexaose conformation is related to the enhanced α-cyclodextrin production of the CGTase. The detailed structural information subsequently allowed engineering of the cyclodextrin product specificity of the CGTase from T. thermosulfurigenes EM1 by site-directed mutagenesis. Mutation D371R was aimed at hindering the maltohexaose conformation and resulted in enhanced production of larger size cyclodextrins (β- and γ-CD). Mutation D197H was aimed at stabilization of the new maltohexaose conformation and resulted in increased production of α-CD. Glu258 is involved in catalysis in CGTases as well as α-amylases, and is the proton donor in the first step of the cyclization reaction. Amino acids close to Glu258 in the CGTase from T. thermosulfurigenes EM1 were changed. Phe284 was replaced by Lys and Asn327 by Asp. The mutants showed changes in both the high and low pH slopes of the optimum curve for cyclization and hydrolysis when compared with the wild-type enzyme. This suggests that the pH optimum curve of CGTase is determined only by residue Glu258.

Demonstrating the Feasibility of Line Intensity Mapping Using Mock Data of Galaxy Clustering from Simulations

Visbal & Loeb (2010) have shown that it is possible to measure the clustering of galaxies by cross correlating the cumulative emission from two different spectral lines which originate at the same redshift. Through this cross correlation, one can study galaxies which are too faint to be individually resolved. This technique, known as intensity mapping, is a promising probe of the global properties of high redshift galaxies. Here, we test the feasibility of such measurements with synthetic data generated from cosmological dark matter simulations. We use a simple prescription for associating galaxies with dark matter halos and create a realization of emitted radiation as a function of angular position and wavelength over a patch of the sky. This is then used to create synthetic data for two different hypothetical instruments, one aboard the Space Infrared Telescope for Cosmology and Astrophysics (SPICA) and another consisting of a pair of ground based radio telescopes designed to measure the CO(1-0) and CO(2-1) emission lines. We find that the line cross power spectrum can be measured accurately from the synthetic data with errors consistent with the analytical prediction of Visbal & Loeb (2010). Removal of astronomical backgrounds and masking bright line emission from foreground contaminating galaxies do not prevent accurate cross power spectrum measurements.Comment: 12 pages, 6 figures, Submitted to JCA

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

A Universal Power-law Prescription for Variability from Synthetic Images of Black Hole Accretion Flows

We present a framework for characterizing the spatiotemporal power spectrum of the variability expected from the horizon-scale emission structure around supermassive black holes, and we apply this framework to a library of general relativistic magnetohydrodynamic (GRMHD) simulations and associated general relativistic ray-traced images relevant for Event Horizon Telescope (EHT) observations of Sgr A*. We find that the variability power spectrum is generically a red-noise process in both the temporal and spatial dimensions, with the peak in power occurring on the longest timescales and largest spatial scales. When both the time-averaged source structure and the spatially integrated light-curve variability are removed, the residual power spectrum exhibits a universal broken power-law behavior. On small spatial frequencies, the residual power spectrum rises as the square of the spatial frequency and is proportional to the variance in the centroid of emission. Beyond some peak in variability power, the residual power spectrum falls as that of the time-averaged source structure, which is similar across simulations; this behavior can be naturally explained if the variability arises from a multiplicative random field that has a steeper high-frequency power-law index than that of the time-averaged source structure. We briefly explore the ability of power spectral variability studies to constrain physical parameters relevant for the GRMHD simulations, which can be scaled to provide predictions for black holes in a range of systems in the optically thin regime. We present specific expectations for the behavior of the M87* and Sgr A* accretion flows as observed by the EHT