Galaxy clustering in the DESI Legacy Survey and its imprint on the CMB

We use data from the DESI Legacy Survey imaging to probe the galaxy density field in tomographic slices covering the redshift range $0<z<0.8$. After careful consideration of completeness corrections and galactic cuts, we obtain a sample of $4.9\times 10^7$ galaxies covering 17 739 deg$^2$. We derive photometric redshifts with precision $\sigma_z/(1+z)=0.012 - 0.015$, and compare with alternative estimates. Cross-correlation of the tomographic galaxy maps with Planck maps of CMB temperature and lensing convergence probe the growth of structure since $z=0.8$. The signals are compared with a fiducial Planck $\Lambda$CDM model, and require an overall scaling in amplitude of $A_\kappa=0.901\pm 0.026$ for the lensing cross-correlation and $A_{\rm ISW} = 0.984 \pm 0.349$ for the temperature cross-correlation, interpreted as the Integrated Sachs-Wolfe effect. The ISW amplitude is consistent with the fiducial $\Lambda$CDM prediction, but lies significantly below the prediction of the AvERA model of R\'acz et al. (2017), which has been proposed as an alternative explanation for cosmic acceleration. Within $\Lambda$CDM, our low amplitude for the lensing cross-correlation requires a reduction either in fluctuation normalization or in matter density compared to the Planck results, so that $\Omega_m^{0.78}\sigma_8=0.297\pm 0.009$. In combination with the total amplitude of CMB lensing, this favours a shift mainly in density: $\Omega_m=0.274\pm0.024$. We discuss the consistency of this figure with alternative evidence. A conservative compromise between lensing and primary CMB constraints would require $\Omega_m=0.296\pm0.006$, where the 95% confidence regions of both probes overlap.Comment: 18 pages, 18 figures, revised to match the accepted version on MNRA

Galaxy and Mass Assembly (GAMA): probing galaxy-group correlations in redshift space with the halo streaming model

We have studied the galaxy-group cross-correlations in redshift space for the Galaxy And Mass Assembly (GAMA) Survey. We use a set of mock GAMA galaxy and group catalogues to develop and test a novel ‘halo streaming’ model for redshift-space distortions. This treats 2-halo correlations via the streaming model, plus an empirical 1-halo term derived from the mocks, allowing accurate modelling into the non-linear regime. In order to probe the robustness of the growth rate inferred from redshift-space distortions, we divide galaxies by colour, and divide groups according to their total stellar mass, calibrated to total mass via gravitational lensing. We fit our model to correlation data, to obtain estimates of the perturbation growth rate, fσ8, validating parameter errors via the dispersion between different mock realizations. In both mocks and real data, we demonstrate that the results are closely consistent between different subsets of the group and galaxy populations, considering the use of correlation data down to some minimum projected radius, rmin. For the mock data, we can use the halo streaming model to below rmin = 5 h−1 Mpc, finding that all subsets yield growth rates within about 3 per cent of each other, and consistent with the true value. For the actual GAMA data, the results are limited by cosmic variance: fσ8 = 0.29 ± 0.10 at an effective redshift of 0.20; but there is every reason to expect that this method will yield precise constraints from larger data sets of the same type, such as the Dark Energy Spectroscopic Instrument (DESI) bright galaxy surve

Testing theories of large scale structure formation and growth using galaxy surveys

The distribution of galaxies in the Universe is not random: rather, galaxies cluster in a structured way. The formation and growth of these large-scale structures (LSS) provides powerful dynamical probes for cosmology. This thesis explores two of these probes, namely redshift-space distortion (RSD) and the imprints of LSS on the Cosmic Microwave Background (CMB). Using galaxy surveys, I test the theory of structure growth in the context of the ΛCDM cosmological model. RSD probes the velocity field of LSS, which is influenced by the growth of matter fluctuations. I use the galaxy and group catalogues in GAMA survey to test the robustness of RSD in recovering unbiased growth rate fσ8 with different tracers. Specifically, galaxies are split into red and blue subsamples, and groups are divided into three stellar mass bins. The 2D group-galaxy cross-correlation function between these subsamples are interpreted by a linear model and a small-scale Finger of God convolution. Given an appropriate minimum fitting scale, I show that the subsamples give consistent growth rate, fσ8 = 0.25 ± 0.15, also in agreement with the Planck 2018 results. The imprints of LSS on the CMB correspond to the effects of weak gravitational lensing and the Integrated Sachs-Wolfe (ISW) effect. I measure these effects using the public DESI Legacy Survey, exploiting its large sky coverage and substantial depth for tomographic studies. After careful selection of galaxies and correction for various systematic effects, I assign photometric redshifts to galaxies based on g − r, r − z, and z − W1 colours, and construct four tomographic redshift bins in 0 < z < 0.8. The photo-z errors are accounted for using the galaxy auto- and cross-correlations between these redshift bins. Having a clean galaxy sample, I measure the cross-correlation C` between the galaxy density fields and the Planck CMB temperature and lensing convergence maps. The amplitudes of these measurements relative to the ΛCDM prediction using the fiducial Planck 2018 best-fit cosmology are Aκ = 0.901 ± 0.026 and AISW = 0.98 ± 0.35. While the ISW result is consistent with the fiducial cosmology, the CMB lensing result is noticeably lower. This low amplitude is interpreted in terms of a lower Ωm in combination with the total CMB lensing constraints. Finally, to address the excess stacked ISW signal from supervoids claimed in literature, I construct a superstructure catalogue using the four tomographic bins in the DESI Legacy Survey, and measure their stacked CMB lensing and ISW signals. The results are compared to the ΛCDM prediction from a mock catalogue that is based on N-body simulations and carefully matched to the data. I find a similar discrepancy in the lensing amplitude as in the cross-correlation scenario. Here, it is mainly contributed by density peaks at the higher redshift end. I also show that the detection of ISW signal from superstructure stacking is only mild, but is consistent with the ΛCDM prediction with a 95% upper limit of AISW = 1.51 using the full sample. Testing a range of superstructure subsamples, I demonstrate that the claimed excess signal may be due to look-elsewhere effec

Galaxy and Mass Assembly (GAMA): Probing galaxy-group correlations in redshift space with the halo streaming model

We have studied the galaxy-group cross-correlations in redshift space for the Galaxy And Mass Assembly (GAMA) Survey. We use a set of mock GAMA galaxy and group catalogues to develop and test a novel 'halo streaming' model for redshift-space distortions. This treats 2-halo correlations via the streaming model, plus an empirical 1-halo term derived from the mocks, allowing accurate modelling into the nonlinear regime. In order to probe the robustness of the growth rate inferred from redshift-space distortions, we divide galaxies by colour, and divide groups according to their total stellar mass, calibrated to total mass via gravitational lensing. We fit our model to correlation data, to obtain estimates of the perturbation growth rate, $f\sigma_8$, validating parameter errors via the dispersion between different mock realizations. In both mocks and real data, we demonstrate that the results are closely consistent between different subsets of the group and galaxy populations, considering the use of correlation data down to some minimum projected radius, $r_{\rm min}$. For the mock data, we can use the halo streaming model to below $r_{\rm min} = 5h^{-1}$ Mpc, finding that all subsets yield growth rates within about 3% of each other, and consistent with the true value. For the actual GAMA data, the results are limited by cosmic variance: $f\sigma_8=0.29\pm 0.10$ at an effective redshift of 0.20; but there is every reason to expect that this method will yield precise constraints from larger datasets of the same type, such as the DESI bright galaxy survey

Galaxy and Mass Assembly (GAMA): Probing galaxy-group correlations in redshift space with the halo streaming model

We have studied the galaxy-group cross-correlations in redshift space for the Galaxy And Mass Assembly (GAMA) Survey. We use a set of mock GAMA galaxy and group catalogues to develop and test a novel 'halo streaming' model for redshift-space distortions. This treats 2-halo correlations via the streaming model, plus an empirical 1-halo term derived from the mocks, allowing accurate modelling into the nonlinear regime. In order to probe the robustness of the growth rate inferred from redshift-space distortions, we divide galaxies by colour, and divide groups according to their total stellar mass, calibrated to total mass via gravitational lensing. We fit our model to correlation data, to obtain estimates of the perturbation growth rate, $f\sigma_8$, validating parameter errors via the dispersion between different mock realizations. In both mocks and real data, we demonstrate that the results are closely consistent between different subsets of the group and galaxy populations, considering the use of correlation data down to some minimum projected radius, $r_{\rm min}$. For the mock data, we can use the halo streaming model to below $r_{\rm min} = 5h^{-1}$ Mpc, finding that all subsets yield growth rates within about 3% of each other, and consistent with the true value. For the actual GAMA data, the results are limited by cosmic variance: $f\sigma_8=0.29\pm 0.10$ at an effective redshift of 0.20; but there is every reason to expect that this method will yield precise constraints from larger datasets of the same type, such as the DESI bright galaxy survey

Galaxy and Mass Assembly (GAMA): Probing galaxy-group correlations in redshift space with the halo streaming model

We have studied the galaxy-group cross-correlations in redshift space for the Galaxy And Mass Assembly (GAMA) Survey. We use a set of mock GAMA galaxy and group catalogues to develop and test a novel 'halo streaming' model for redshift-space distortions. This treats 2-halo correlations via the streaming model, plus an empirical 1-halo term derived from the mocks, allowing accurate modelling into the nonlinear regime. In order to probe the robustness of the growth rate inferred from redshift-space distortions, we divide galaxies by colour, and divide groups according to their total stellar mass, calibrated to total mass via gravitational lensing. We fit our model to correlation data, to obtain estimates of the perturbation growth rate, $f\sigma_8$, validating parameter errors via the dispersion between different mock realizations. In both mocks and real data, we demonstrate that the results are closely consistent between different subsets of the group and galaxy populations, considering the use of correlation data down to some minimum projected radius, $r_{\rm min}$. For the mock data, we can use the halo streaming model to below $r_{\rm min} = 5h^{-1}$ Mpc, finding that all subsets yield growth rates within about 3% of each other, and consistent with the true value. For the actual GAMA data, the results are limited by cosmic variance: $f\sigma_8=0.29\pm 0.10$ at an effective redshift of 0.20; but there is every reason to expect that this method will yield precise constraints from larger datasets of the same type, such as the DESI bright galaxy survey.Comment: 17 pages, 12 figure

Value of folate receptor-positive circulating tumour cells in the clinical management of indeterminate lung nodules: A non-invasive biomarker for predicting malignancy and tumour invasivenessResearch in context

Background: Non-invasive lung adenocarcinoma could benefit from limited resection, nonetheless, there is a lack of method to determine preoperative tumour invasiveness. We aimed to investigate whether folate receptor-positive circulating tumour cells (FR+-CTCs) in combination with maximum tumour diameter (MTD) determines, before surgery, the invasiveness of small-sized, indeterminate solitary pulmonary nodules (SPNs). Methods: A total of 382 patients with suspicious lung adenocarcinoma on computed tomography who were expected to undergo lung resection were enrolled in this study at three participating institutes and randomly assigned into training and validation cohorts. Before surgery, 3 mL peripheral blood was collected from all participants. FR+-CTCs were analyzed using immunomagnetic leukocyte depletion and quantitated by ligand-targeted PCR method. After surgery, the resected tissues were diagnosed by pathologists according to IASLC/ATS/ERS classification. Findings: FR+-CTC levels in the peripheral blood can differentiate benign from malignant nodules with a sensitivity of 78·6%–82·7% and a specificity of 68·8%–78·4%. Both FR+-CTC and MTD are independent predictive indices of invasive tumours for lung adenocarcinoma ≤2 cm based on multivariate analyses. Further, FR+-CTC count in combination with MTD can differentiate non-invasive cancers from invasive cancers with a sensitivity of 63·6%–81·8% and a specificity of 71·4%–89·7%. Interpretation: Detection of FR+-CTC is a reliable method to differentiate malignancy of indeterminate SPNs. Combining of FR+-CTC count and MTD could possibly enhance preoperative determination of the invasiveness of lung nodules and guide surgeons to select limited lung resection and avoid overtreatment for patients with non-invasive lesions. Fund: None. Keywords: Circulating tumour cells, Folate receptor, Non-small cell lung cancer, Tumour invasiveness, Limited lung resectio