Statistical Power, the Bispectrum and the Search for Non-Gaussianity in the CMB Anisotropy

We use simulated maps of the cosmic microwave background anisotropy to quantify the ability of different statistical tests to discriminate between Gaussian and non-Gaussian models. Despite the central limit theorem on large angular scales, both the genus and extrema correlation are able to discriminate between Gaussian models and a semi-analytic texture model selected as a physically motivated non-Gaussian model. When run on the COBE 4-year CMB maps, both tests prefer the Gaussian model. Although the bispectrum has comparable statistical power when computed on the full sky, once a Galactic cut is imposed on the data the bispectrum loses the ability to discriminate between models. Off-diagonal elements of the bispectrum are comparable to the diagonal elements for the non-Gaussian texture model and must be included to obtain maximum statistical power.Comment: Accepted for publication in ApJ; 20 pages, 6 figures, uses AASTeX v5.

Textures and Newtonian Gravity

Newtonian theory is used to study the gravitational effects of a texture, in particular the formation of massive structures.Comment: 4 pages, 4 ps figures, REVTEX, accepted for publication in PR

A roadmap for gene functional characterisation in wheat

To adapt to the challenges of climate change and the growing world population, it is vital to increase global crop production. Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite the importance of wheat, which provides 20 % of the calories consumed by humankind, a lack of genomic information and resources has hindered the functional characterisation of genes in this species. The recent release of a high-quality reference sequence for wheat underpins a suite of genetic and genomic resources that support basic research and breeding. These include accurate gene model annotations, gene expression atlases and gene networks that provide background information about putative gene function. In parallel, sequenced mutation populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources to study gene function in wheat and thereby accelerate improvement in this important crop. We hope that this review provides a helpful guide for plant scientists, especially those expanding into wheat research for the first time, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of wheat, a complex polyploid crop, of vital importance for food and nutrition security

Exploring cosmic origins with CORE : Inflation

We forecast the scientific capabilities to improve our understanding of cosmic inflation of CORE, a proposed CMB space satellite submitted in response to the ESA fifth call for a medium-size mission opportunity. The CORE satellite will map the CMB anisotropies in temperature and polarization in 19 frequency channels spanning the range 60-600 GHz. CORE will have an aggregate noise sensitivity of 1.7 mu K.arcmin and an angular resolution of 5' at 200 GHz. We explore the impact of telescope size and noise sensitivity on the inflation science return by making forecasts for several instrumental configurations. This study assumes that the lower and higher frequency channels suffice to remove foreground contaminations and complements other related studies of component separation and systematic effects, which will be reported in other papers of the series "Exploring Cosmic Origins with CORE." We forecast the capability to determine key inflationary parameters, to lower the detection limit for the tensor-to-scalar ratio down to the 10(-3) level, to chart the landscape of single field slow-roll inflationary models, to constrain the epoch of reheating, thus connecting inflation to the standard radiation-matter dominated Big Bang era, to reconstruct the primordial power spectrum, to constrain the contribution from isocurvature perturbations to the 10(-3) level, to improve constraints on the cosmic string tension to a level below the presumptive GUT scale, and to improve the current measurements of primordial non-Gaussianities down to the f(NL)(local) <1 level. For all the models explored, CORE alone will improve significantly on the present constraints on the physics of inflation. Its capabilities will be further enhanced by combining with complementary future cosmological observations.Peer reviewe

The Gene Networks Involved in Wheat Drought Response

Trabajo presentado en el PAG Asia 2019 (The International conference on the Status of Plant & Animal Genome Research), celebrado en Futian Shangri-La Shenzhen (China) del 6 al 8 de junio de 2019.Wheat can adapt to most agricultural conditions across temperate regions. Although drought is a major cause of yield and quality losses, the adaptive mechanisms and gene networks underlying drought responses in the field remain largely unknown. Interdisciplinary studies involving field water status phenotyping now provide a basis for interpreting gene expression analyses and show that changes at the transcriptional level were reflected in the remote sensing physiological data from the field. The dehydrin family of genes provided a focus for the study and indicated that the genes located on the group 6 chromosomes were particularly important in drought response

Optimization study for the experimental configuration of CMB-S4

The CMB Stage 4 (CMB-S4) experiment is a next-generation, ground-based experiment that will measure the cosmic microwave background (CMB) polarization to unprecedented accuracy, probing the signature of inflation, the nature of cosmic neutrinos, relativistic thermal relics in the early universe, and the evolution of the universe. CMB-S4 will consist of O(500,000) photon-noise-limited detectors that cover a wide range of angular scales in order to probe the cosmological signatures from both the early and late universe. It will measure a wide range of microwave frequencies to cleanly separate the CMB signals from galactic and extra-galactic foregrounds. To advance the progress towards designing the instrument for CMB-S4, we have established a framework to optimize the instrumental configuration to maximize its scientific output. The framework combines cost and instrumental models with a cosmology forecasting tool, and evaluates the scientific sensitivity as a function of various instrumental parameters. The cost model also allows us to perform the analysis under a fixed-cost constraint, optimizing for the scientific output of the experiment given finite resources. In this paper, we report our first results from this framework, using simplified instrumental and cost models. We have primarily studied two classes of instrumental configurations: arrays of large-aperture telescopes with diameters ranging from 2-10 m, and hybrid arrays that combine small-aperture telescopes (0.5-m diameter) with large-aperture telescopes. We explore performance as a function of telescope aperture size, distribution of the detectors into different microwave frequencies, survey strategy and survey area, low-frequency noise performance, and balance between small and large aperture telescopes for hybrid configurations. Both types of configurations must cover both large (∼ degree) and small (∼ arcmin) angular scales, and the performance depends on assumptions for performance vs. angular scale. The configurations with large-aperture telescopes have a shallow optimum around 4-6 m in aperture diameter, assuming that large telescopes can achieve good performance for low-frequency noise. We explore some of the uncertainties of the instrumental model and cost parameters, and we find that the optimum has a weak dependence on these parameters. The hybrid configuration shows an even broader optimum, spanning a range of 4-10 m in aperture for the large telescopes. We also present two strawperson configurations as an outcome of this optimization study, and we discuss some ideas for improving our simple cost and instrumental models used here. There are several areas of this analysis that deserve further improvement. In our forecasting framework, we adopt a simple two-component foreground model with spatially varying power-law spectral indices. We estimate de-lensing performance statistically and ignore non-idealities such as anisotropic mode coverage, boundary effect, and possible foreground residual. Instrumental systematics, which is not accounted for in our analyses, may also influence the conceptual design. Further study of the instrumental and cost models will be one of the main areas of study by the entire CMB-S4 community. We hope that our framework will be useful for estimating the influence of these improvements in the future, and we will incorporate them in order to further improve the optimization

Optimization study for the experimental configuration of CMB-S4

The CMB Stage 4 (CMB-S4) experiment is a next-generation, ground-based experiment that will measure the cosmic microwave background (CMB) polarization to unprecedented accuracy, probing the signature of inflation, the nature of cosmic neutrinos, relativistic thermal relics in the early universe, and the evolution of the universe. CMB-S4 will consist of O(500,000) photon-noise-limited detectors that cover a wide range of angular scales in order to probe the cosmological signatures from both the early and late universe. It will measure a wide range of microwave frequencies to cleanly separate the CMB signals from galactic and extra-galactic foregrounds. To advance the progress towards designing the instrument for CMB-S4, we have established a framework to optimize the instrumental configuration to maximize its scientific output. The framework combines cost and instrumental models with a cosmology forecasting tool, and evaluates the scientific sensitivity as a function of various instrumental parameters. The cost model also allows us to perform the analysis under a fixed-cost constraint, optimizing for the scientific output of the experiment given finite resources. In this paper, we report our first results from this framework, using simplified instrumental and cost models. We have primarily studied two classes of instrumental configurations: arrays of large-aperture telescopes with diameters ranging from 2-10 m, and hybrid arrays that combine small-aperture telescopes (0.5-m diameter) with large-aperture telescopes. We explore performance as a function of telescope aperture size, distribution of the detectors into different microwave frequencies, survey strategy and survey area, low-frequency noise performance, and balance between small and large aperture telescopes for hybrid configurations. Both types of configurations must cover both large (∼ degree) and small (∼ arcmin) angular scales, and the performance depends on assumptions for performance vs. angular scale. The configurations with large-aperture telescopes have a shallow optimum around 4-6 m in aperture diameter, assuming that large telescopes can achieve good performance for low-frequency noise. We explore some of the uncertainties of the instrumental model and cost parameters, and we find that the optimum has a weak dependence on these parameters. The hybrid configuration shows an even broader optimum, spanning a range of 4-10 m in aperture for the large telescopes. We also present two strawperson configurations as an outcome of this optimization study, and we discuss some ideas for improving our simple cost and instrumental models used here. There are several areas of this analysis that deserve further improvement. In our forecasting framework, we adopt a simple two-component foreground model with spatially varying power-law spectral indices. We estimate de-lensing performance statistically and ignore non-idealities such as anisotropic mode coverage, boundary effect, and possible foreground residual. Instrumental systematics, which is not accounted for in our analyses, may also influence the conceptual design. Further study of the instrumental and cost models will be one of the main areas of study by the entire CMB-S4 community. We hope that our framework will be useful for estimating the influence of these improvements in the future, and we will incorporate them in order to further improve the optimization

Hotspots in the genomic architecture of field drought responses in wheat as breeding targets

Wheat can adapt to most agricultural conditions across temperate regions. This success is the result of phenotypic plasticity conferred by a large and complex genome composed of three homoeologous genomes (A, B, and D). Although drought is a major cause of yield and quality loss in wheat, the adaptive mechanisms and gene networks underlying drought responses in the field remain largely unknown. Here, we addressed this by utilizing an interdisciplinary approach involving field water status phenotyping, sampling, and gene expression analyses. Overall, changes at the transcriptional level were reflected in plant spectral traits amenable to field-level physiological measurements, although changes in photosynthesis-related pathways were found likely to be under more complex post-transcriptional control. Examining homoeologous genes with a 1:1:1 relationship across the A, B, and D genomes (triads), we revealed a complex genomic architecture for drought responses under field conditions, involving gene homoeolog specialization, multiple gene clusters, gene families, miRNAs, and transcription factors coordinating these responses. Our results provide a new focus for genomics-assisted breeding of drought-tolerant wheat cultivars.This work was funded by project P12-AGR-0482 from Junta de Andalucía, Spain (Co-funded by FEDER); projects BIO2011-15237-E, AGL2016-77149-C2-1-P, and CGL2016-79790-P from MINECO (Spanish Ministry of Economy, Industry and Competitiveness); UK Biotechnology and Biological Sciences Research Council (BBSRC) through Designing Future Wheat (BB/P016855/1), GEN (BB/P013511/1), and an Anniversary Future Leaders Fellowship to PB (BB/M014045/1). HB was supported by the Montana Plant Science Endowment fund.Peer reviewe