Cross-Correlation of spectroscopic and photometric galaxy surveys: cosmology from lensing and redshift distortions

Cosmological galaxy surveys aim at mapping the largest volumes to test models with techniques such as cluster abundance, cosmic shear correlations or baryon acoustic oscillations (BAO), which are designed to be independent of galaxy bias. Here we explore an alternative route to constrain cosmology: sampling more moderate volumes with the cross-correlation of photometric and spectroscopic surveys. We consider the angular galaxy-galaxy autocorrelation in narrow redshift bins and its combination with different probes of weak gravitational lensing (WL) and redshift space distortions (RSD). Including the cross-correlation of these surveys improves by factors of a few the constraints on both the dark energy equation of state w(z) and the cosmic growth history, parametrized by \gamma. The additional information comes from using many narrow redshift bins and from galaxy bias, which is measured both with WL probes and RSD, breaking degeneracies that are present when using each method separately. We show forecasts for a joint w(z) and \gamma figure of merit using linear scales over a deep (i<24) photometric survey and a brighter (i<22.5) spectroscopic or very accurate (0.3%) photometric redshift survey. Magnification or shear in the photometric sample produce FoM that are of the same order of magnitude of those of RSD or BAO over the spectroscopic sample. However, the cross-correlation of these probes over the same area yields a FoM that is up to a factor 100 times larger. Magnification alone, without shape measurements, can also be used for these cross-correlations and can produce better results than using shear alone. For a spectroscopic follow-up survey strategy, measuring the spectra of the foreground lenses to perform this cross-correlation provides 5 times better FoM than targeting the higher redshift tail of the galaxy distribution to study BAO over a 2.5 times larger volume.Comment: Small cosmetic changes to match MNRAS published versio

Directed cell migration in the presence of obstacles

BACKGROUND: Chemotactic movement is a common feature of many cells and microscopic organisms. In vivo, chemotactic cells have to follow a chemotactic gradient and simultaneously avoid the numerous obstacles present in their migratory path towards the chemotactic source. It is not clear how cells detect and avoid obstacles, in particular whether they need a specialized biological mechanism to do so. RESULTS: We propose that cells can sense the presence of obstacles and avoid them because obstacles interfere with the chemical field. We build a model to test this hypothesis and find that this naturally enables efficient at-a-distance sensing to be achieved with no need for a specific and active obstacle-sensing mechanism. We find that (i) the efficiency of obstacle avoidance depends strongly on whether the chemotactic chemical reacts or remains unabsorbed at the obstacle surface. In particular, it is found that chemotactic cells generally avoid absorbing barriers much more easily than non-absorbing ones. (ii) The typically low noise in a cell's motion hinders the ability to avoid obstacles. We also derive an expression estimating the typical distance traveled by chemotactic cells in a 3D random distribution of obstacles before capture; this is a measure of the distance over which chemotaxis is viable as a means of directing cells from one point to another in vivo. CONCLUSION: Chemotactic cells, in many cases, can avoid obstacles by simply following the spatially perturbed chemical gradients around obstacles. It is thus unlikely that they have developed specialized mechanisms to cope with environments having low to moderate concentrations of obstacles

DESI Survey Validation Spectra Reveal an Increasing Fraction of Recently Quenched Galaxies at z∼1z\sim1

We utilize $\sim17000$ bright Luminous Red Galaxies (LRGs) from the novel Dark Energy Spectroscopic Instrument Survey Validation spectroscopic sample, leveraging its deep ($\sim2.5$ hour/galaxy exposure time) spectra to characterize the contribution of recently quenched galaxies to the massive galaxy population at $0.4<z<1.3$. We use Prospector to infer non-parametric star formation histories and identify a significant population of post-starburst galaxies that have joined the quiescent population within the past $\sim1$ Gyr. The highest redshift subset (277 at $z>1$) of our sample of recently quenched galaxies represents the largest spectroscopic sample of post-starburst galaxies at that epoch. At $0.4<z<0.8$, we measure the number density of quiescent LRGs, finding that recently quenched galaxies constitute a growing fraction of the massive galaxy population with increasing lookback time. Finally, we quantify the importance of this population amongst massive ($\mathrm{log}(M_\star/M_\odot)>11.2$) LRGs by measuring the fraction of stellar mass each galaxy formed in the Gyr before observation, $f_{\mathrm{1 Gyr}}$. Although galaxies with $f_{\mathrm{1 Gyr}}>0.1$ are rare at $z\sim0.4$ ($\lesssim 0.5\%$ of the population), by $z\sim0.8$ they constitute $\sim3\%$ of massive galaxies. Relaxing this threshold, we find that galaxies with $f_\mathrm{1 Gyr}>5\%$ constitute $\sim10\%$ of the massive galaxy population at $z\sim0.8$. We also identify a small but significant sample of galaxies at $z=1.1-1.3$ that formed with $f_{\mathrm{1 Gyr}}>50\%$, implying that they may be analogues to high-redshift quiescent galaxies that formed on similar timescales. Future analysis of this unprecedented sample promises to illuminate the physical mechanisms that drive the quenching of massive galaxies after cosmic noon.Comment: Submitted to ApJ Letters after DESI Collaboration Review. 14 pages, 5 figures, comments welcome

The DESI One-Percent Survey: Evidence for Assembly Bias from Low-Redshift Counts-in-Cylinders Measurements

We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z=0.1-0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey (BGS). In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab, which enables the rapid, precise prediction of CiC for any HOD model available in halotools. This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in $z\sim0.15$ samples with limiting absolute magnitude $M_r < -20.0$ and $M_r < -20.5$ samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter $M_r < -21.0$ sample at $z\sim0.25$ (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at $z\sim0.15$. We provide our constraints for each threshold sample's characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3

Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies

We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter fNL. Our sample comprises over 12 million targets, covering 14,000 square degrees of the sky, with redshifts in the range 0.2< z < 1.35. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against log-normal simulations with and without fNL and systematics, showing superior performance of the neural network treatment in reducing remaining systematics. Assuming the universality relation, we find fNL $= 47^{+14(+29)}_{-11(-22)}$ at 68\%(95\%) confidence. With a more aggressive treatment, including regression against the full set of imaging maps, our maximum likelihood value shifts slightly to fNL$\sim 50$ and the uncertainty on fNL increases due to the removal of large-scale clustering information. We apply a series of robustness tests (e.g., cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. Despite extensive efforts to mitigate systematics, our measurements indicate fNL > 0 with a 99.9 percent confidence level. This outcome raises concerns as it could be attributed to unforeseen systematics, including calibration errors or uncertainties associated with low-\ell systematics in the extinction template. Alternatively, it could suggest a scale-dependent fNL model--causing significant non-Gaussianity around large-scale structure while leaving cosmic microwave background scales unaffected. Our results encourage further studies of fNL with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics.Comment: 19 pages, 15 figures, 6 tables (Appendix excluded). Submitted to MNRA

Associations between tamoxifen, estrogens, and FSH serum levels during steady state tamoxifen treatment of postmenopausal women with breast cancer

<p>Abstract</p> <p>Background</p> <p>The cytochrome P450 (CYP) enzymes 2C19, 2D6, and 3A5 are responsible for converting the selective estrogen receptor modulator (SERM), tamoxifen to its active metabolites 4-hydroxy-tamoxifen (4OHtam) and 4-hydroxy-<it>N</it>-demethyltamoxifen (4OHNDtam, endoxifen). Inter-individual variations of the activity of these enzymes due to polymorphisms may be predictors of outcome of breast cancer patients during tamoxifen treatment. Since tamoxifen and estrogens are both partly metabolized by these enzymes we hypothesize that a correlation between serum tamoxifen and estrogen levels exists, which in turn may interact with tamoxifen on treatment outcome. Here we examined relationships between the serum levels of tamoxifen, estrogens, follicle-stimulating hormone (FSH), and also determined the genotypes of CYP2C19, 2D6, 3A5, and SULT1A1 in 90 postmenopausal breast cancer patients.</p> <p>Methods</p> <p>Tamoxifen and its metabolites were measured by liquid chromatography-tandem mass spectrometry. Estrogen and FSH levels were determined using a sensitive radio- and chemiluminescent immunoassay, respectively.</p> <p>Results</p> <p>We observed significant correlations between the serum concentrations of tamoxifen, <it>N</it>-dedimethyltamoxifen, and tamoxifen-<it>N</it>-oxide and estrogens (p < 0.05). The genotype predicted CYP2C19 activity influenced the levels of both tamoxifen metabolites and E1.</p> <p>Conclusions</p> <p>We have shown an association between tamoxifen and its metabolites and estrogen serum levels. An impact of CYP2C19 predicted activity on tamoxifen, as well as estrogen kinetics may partly explain the observed association between tamoxifen and its metabolites and estrogen serum levels. Since the role of estrogen levels during tamoxifen therapy is still a matter of debate further prospective studies to examine the effect of tamoxifen and estrogen kinetics on treatment outcome are warranted.</p

A Review of the Urban Development and Transport Impacts on Public Health with Particular Reference to Australia: Trans-Disciplinary Research Teams and Some Research Gaps

Urbanization and transport have a direct effect on public health. A transdisciplinary approach is proposed and illustrated to tackle the general problem of these environmental stressors and public health. Processes driving urban development and environmental stressors are identified. Urbanization, transport and public health literature is reviewed and environmental stressors are classified into their impacts and which group is affected, the geographical scale and potential inventions. Climate change and health impacts are identified as a research theme. From an Australian perspective, further areas for research are identified