Determining the HI content of galaxies via intensity mapping cross-correlations

We propose an innovative method for measuring the neutral hydrogen (HI) content of an optically-selected spectroscopic sample of galaxies through cross-correlation with HI intensity mapping measurements. We show that the HI-galaxy cross-power spectrum contains an additive shot noise term which scales with the average HI brightness temperature of the optically-selected galaxies, allowing constraints to be placed on the average HI mass per galaxy. This approach can estimate the HI content of populations too faint to directly observe through their 21cm emission over a wide range of redshifts. This cross-correlation, as a function of optical luminosity or colour, can be used to derive HI-scaling relations. We demonstrate that this signal will be detectable by cross-correlating upcoming Australian SKA Pathfinder (ASKAP) observations with existing optically-selected samples. We also use semi-analytic simulations to verify that the HI mass can be successfully recovered by our technique in the range M_HI > 10^8 M_solar, in a manner independent of the underlying power spectrum shape. We conclude that this method is a powerful tool to study galaxy evolution, which only requires a single intensity mapping dataset to infer complementary HI gas information from existing optical and infra-red observations.Comment: 8 pages, 4 figures, submitted to MNRA

Intensity mapping cross-correlations II: HI halo models including shot noise

HI intensity mapping data traces the large-scale structure matter distribution using the integrated emission of neutral hydrogen gas (HI). The cross-correlation of the intensity maps with optical galaxy surveys can mitigate foreground and systematic effects, but has been shown to significantly depend on galaxy evolution parameters of the HI and the optical sample. Previously, we have shown that the shot noise of the cross-correlation scales with the HI content of the optical samples, such that the shot noise estimation infers the average HI masses of these samples. In this article, we present an adaptive framework for the cross-correlation of HI intensity maps with galaxy samples using our implementation of the halo model formalism (Murray et al 2018, in prep) which utilises the halo occupation distribution of galaxies to predict their power spectra. We compare two HI population models, tracing the spatial halo and the galaxy distribution respectively, and present their auto- and cross-power spectra with an associated galaxy sample. We find that the choice of the HI model and the distribution of the HI within the galaxy sample have minor significance for the shape of the auto- and cross-correlations, but highly impact the measured shot noise amplitude of the estimators, a finding we confirm with simulations. We demonstrate parameter estimation of the HI halo occupation models and advocate this framework for the interpretation of future experimental data, with the prospect of determining the HI masses of optical galaxy samples via the cross-correlation shot noise.Comment: 15 pages, 8 figures, 3 tables. Comments welcom

Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease prediction tasks requires models capable of representing, at the same time, individual features as well as data associations between subjects from potentially large populations. Graphs provide a natural framework for such tasks, yet previous graph-based approaches focus on pairwise similarities without modelling the subjects' individual characteristics and features. On the other hand, relying solely on subject-specific imaging feature vectors fails to model the interaction and similarity between subjects, which can reduce performance. In this paper, we introduce the novel concept of Graph Convolutional Networks (GCN) for brain analysis in populations, combining imaging and non-imaging data. We represent populations as a sparse graph where its vertices are associated with image-based feature vectors and the edges encode phenotypic information. This structure was used to train a GCN model on partially labelled graphs, aiming to infer the classes of unlabelled nodes from the node features and pairwise associations between subjects. We demonstrate the potential of the method on the challenging ADNI and ABIDE databases, as a proof of concept of the benefit from integrating contextual information in classification tasks. This has a clear impact on the quality of the predictions, leading to 69.5% accuracy for ABIDE (outperforming the current state of the art of 66.8%) and 77% for ADNI for prediction of MCI conversion, significantly outperforming standard linear classifiers where only individual features are considered.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

Lack of clustering in low-redshift 21-cm intensity maps cross-correlated with 2dF galaxy densities

We report results from 21-cm intensity maps acquired from the Parkes radio telescope and cross-correlated with galaxy maps from the 2dF galaxy survey. The data span the redshift range $0.057<z<0.098$ and cover approximately 1,300 square degrees over two long fields. Cross correlation is detected at a significance of $5.18\sigma$. The amplitude of the cross-power spectrum is low relative to the expected dark matter power spectrum, assuming a neutral hydrogen (HI) bias and mass density equal to measurements from the ALFALFA survey. The decrement is pronounced and statistically significant at small scales. At $k\sim1.5$ $h \mathrm{Mpc^{-1}}$, the cross power spectrum is more than a factor of 6 lower than expected, with a significance of $14.8\,\sigma$. This decrement indicates either a lack of clustering of neutral hydrogen (HI), a small correlation coefficient between optical galaxies and HI, or some combination of the two. Separating 2dF into red and blue galaxies, we find that red galaxies are much more weakly correlated with HI on $k\sim1.5$ $h \mathrm{Mpc^{-1}}$ scales, suggesting that HI is more associated with blue star-forming galaxies and tends to avoid red galaxies.Comment: 12 pages, 3 figures; fixed typo in meta-data title and paper author

Foreground Subtraction in Intensity Mapping with the SKA

21cm intensity mapping experiments aim to observe the diffuse neutral hydrogen (HI) distribution on large scales which traces the Cosmic structure. The Square Kilometre Array (SKA) will have the capacity to measure the 21cm signal over a large fraction of the sky. However, the redshifted 21cm signal in the respective frequencies is faint compared to the Galactic foregrounds produced by synchrotron and free-free electron emission. In this article, we review selected foreground subtraction methods suggested to effectively separate the 21cm signal from the foregrounds with intensity mapping simulations or data. We simulate an intensity mapping experiment feasible with SKA phase 1 including extragalactic and Galactic foregrounds. We give an example of the residuals of the foreground subtraction with a independent component analysis and show that the angular power spectrum is recovered within the statistical errors on most scales. Additionally, the scale of the Baryon Acoustic Oscillations is shown to be unaffected by foreground subtraction

Carbohydrate and protein contents of grain dusts in relation to dust morphology.

Grain dusts contain a variety of materials which are potentially hazardous to the health of workers in the grain industry. Because the characterization of grain dusts is incomplete, we are defining the botanical, chemical, and microbial contents of several grain dusts collected from grain elevators in the Duluth-Superior regions of the U.S. Here, we report certain of the carbohydrate and protein contents of dusts in relation to dust morphology. Examination of the gross morphologies of the dusts revealed that, except for corn, each dust contained either husk or pericarp (seed coat in the case of flax) fragments in addition to respirable particles. When viewed with the light microscope, the fragments appeared as elongated, pointed structures. The possibility that certain of the fragments within corn, settled, and spring wheat were derived from cell walls was suggested by the detection of pentoses following colorimetric assay of neutralized 2 N trifluoroacetic acid hydrolyzates of these dusts. The presence of pentoses together with the occurrence of proteins within water washings of grain dusts suggests that glycoproteins may be present within the dusts. With scanning electron microscopy, each dust was found to consist of a distinct assortment of particles in addition to respirable particles. Small husk fragments and "trichome-like" objects were common to all but corn dust

Erasing the Milky Way: new cleaning technique applied to GBT intensity mapping data

We present the first application of a new foreground removal pipeline to the current leading H I intensity mapping data set, obtained by the Green Bank Telescope (GBT). We study the 15- and 1-h-field data of the GBT observations previously presented in Mausui et al. and Switzer et al., covering about 41 deg2 at 0.6 < z < 1.0, for which cross-correlations may be measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the presented pipeline, we subtract the Galactic foreground continuum and the point-source contamination using an independent component analysis technique (FASTICA), and develop a Fourier-based optimal estimator to compute the temperature power spectrum of the intensity maps and cross-correlation with the galaxy survey data. We show that FASTICA is a reliable tool to subtract diffuse and point-source emission through the non-Gaussian nature of their probability distributions. The temperature power spectra of the intensity maps are dominated by instrumental noise on small scales which FASTICA, as a conservative subtraction technique of non-Gaussian signals, cannot mitigate. However, we determine similar GBT-WiggleZ cross-correlation measurements to those obtained by the singular value decomposition (SVD) method, and confirm that foreground subtraction with FASTICA is robust against 21 cm signal loss, as seen by the converged amplitude of these cross-correlation measurements. We conclude that SVD and FASTICA are complementary methods to investigate the foregrounds and noise systematics present in intensity mapping data sets

C8‐BTBT‐C8 Thin‐Film Transistors Based on Micro‐Contact Printed PEDOT:PSS/MWCNT Electrodes

Advances in organic materials manufacturing have enabled the creation of electronic devices using solution‐processing techniques by employing soluble materials with high conductivity grade. In this exploratory study, the use of micro‐contact for poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) polymer ink deposition as high‐quality structured electrodes for organic field‐effect transistors (OFETs) in top‐contact geometry is demonstrated. The optimized OFET's solution‐processed fabrication is a promising strategy to be realized in the simple, cost‐effective roll‐to‐roll manufacturing processes. The electrical performance of the fabricated devices is comparable to transistors with gold electrodes prepared via vacuum deposition, and even exceeding the values of the charge carriers’ mobilities and featuring lower contact resistance (Rc), due to lower charge‐carrier injection barrier for carbon‐based organic electrodes. An addition of multi‐walled carbon nanotubes to the PEDOT:PSS decreases Rc even further, changing the work function for better energy alignment with semiconductor materials