University of Portsmouth

About: University of Portsmouth is a education organization based out in Portsmouth, Portsmouth, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 5452 authors who have published 14256 publications receiving 424346 citations. The organization is also known as: Portsmouth and Gosport School of Science and Art & Portsmouth and Gosport School of Science and the Arts.

Dark energy and dark gravity: theory overview

Abstract: Observations provide increasingly strong evidence that the universe is accelerating. This revolutionary advance in cosmological observations confronts theoretical cosmology with a tremendous challenge, which it has so far failed to meet. Explanations of cosmic acceleration within the framework of general relativity are plagued by difficulties. General relativistic models are nearly all based on a dark energy field with fine-tuned, unnatural properties. There is a great variety of models, but all share one feature in common—an inability to account for the gravitational properties of the vacuum energy. Speculative ideas from string theory may hold some promise, but it is fair to say that no convincing model has yet been proposed. An alternative to dark energy is that gravity itself may behave differently from general relativity on the largest scales, in such a way as to produce acceleration. The alternative approach of modified gravity (or dark gravity) provides a new angle on the problem, but also faces serious difficulties, including in all known cases severe fine-tuning and the problem of explaining why the vacuum energy does not gravitate. The lack of an adequate theoretical framework for the late-time acceleration of the universe represents a deep crisis for theory—but also an exciting challenge for theorists. It seems likely that an entirely new paradigm is required to resolve this crisis.

Neural-Network-Based Decentralized Adaptive Output-Feedback Control for Large-Scale Stochastic Nonlinear Systems

Abstract: This paper focuses on the problem of neural-network-based decentralized adaptive output-feedback control for a class of nonlinear strict-feedback large-scale stochastic systems. The dynamic surface control technique is used to avoid the explosion of computational complexity in the backstepping design process. A novel direct adaptive neural network approximation method is proposed to approximate the unknown and desired control input signals instead of the unknown nonlinear functions. It is shown that the designed controller can guarantee all the signals in the closed-loop system to be semiglobally uniformly ultimately bounded in a mean square. Simulation results are provided to demonstrate the effectiveness of the developed control design approach.

FLR: an open-source framework for the evaluation and development of management strategies

Abstract: The FLR framework (Fisheries Library for R) is a development effort directed towards the evaluation of fisheries management strategies. The overall goal is to develop a common framework to facilitate collaboration within and across disciplines (e.g. biological, ecological, statistical, mathematical, economic, and social) and, in particular, to ensure that new modelling methods and software are more easily validated and evaluated, as well as becoming widely available once developed. Specifically, the framework details how to implement and link a variety of fishery, biological, and economic software packages so that alternative management strategies and procedures can be evaluated for their robustness to uncertainty before implementation. The design of the framework, including the adoption of object-orientated programming, its feasibility to be extended to new processes, and its application to new management approaches (e.g. ecosystem affects of fishing), is discussed. The importance of open source for promoting transparency and allowing technology transfer between disciplines and researchers is stressed.

Measurement of baryon acoustic oscillations in the Lyman-α forest fluctuations in BOSS data release 9

Abstract: We use the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 9 (DR9) to detect and measure the position of the Baryonic Acoustic Oscillation (BAO) feature in the three-dimensional correlation function in the Lyman-α flux fluctuations at a redshift zeff = 2.4. The feature is clearly detected at significance between 3 and 5 sigma (depending on the broadband model and method of error covariance matrix estimation) and is consistent with predictions of the standard ΛCDM model. We assess the biases in our method, stability of the error covariance matrix and possible systematic effects. We fit the resulting correlation function with several models that decouple the broadband and acoustic scale information. For an isotropic dilation factor, we measure 100 × (αiso − 1) = −1.6+2.0 +4.3 +7.4−2.0 −4.1 −6.8 (stat.) ±1.0 (syst.) (multiple statistical errors denote 1,2 and 3 sigma confidence limits) with respect to the acoustic scale in the fiducial cosmological model (flat ΛCDM with Ωm = 0.27, h = 0.7). When fitting separately for the radial and transversal dilation factors we find marginalised constraints 100 × (α|| − 1) = −1.3+3.5 +7.6 +12.3−3.3 −6.7 −10.2 (stat.) ±2.0 (syst.) and 100 × (α⊥ − 1) = −2.2+7.4 +17−7.1 −15 (stat.) ±3.0 (syst.). The dilation factor measurements are significantly correlated with cross-correlation coefficient of ~ −0.55. Errors become significantly non-Gaussian for deviations over 3 standard deviations from best fit value. Because of the data cuts and analysis method, these measurements give tighter constraints than a previous BAO analysis of the BOSS DR9 Lyman-α sample, providing an important consistency test of the standard cosmological model in a new redshift regime.

The Effect of Host Galaxies on Type Ia Supernovae in the SDSS-II Supernova Survey

Abstract: We present an analysis of the host galaxy dependencies of Type Ia Supernovae (SNe Ia) from the full three year sample of the SDSS-II Supernova Survey. We re-discover, to high significance, the strong correlation between host galaxy type and the width of the observed SN light curve, i.e., fainter, quickly declining SNe Ia favor passive host galaxies, while brighter, slowly declining Ia's favor star-forming galaxies. We also find evidence (at between 2 to 3{sigma}) that SNe Ia are {approx_equal} 0.1 magnitudes brighter in passive host galaxies, than in star-forming hosts, after the SN Ia light curves have been standardized using the light curve shape and color variations: This difference in brightness is present in both the SALT2 and MCLS2k2 light curve fitting methodologies. We see evidence for differences in the SN Ia color relationship between passive and star-forming host galaxies, e.g., for the MLCS2k2 technique, we see that SNe Ia in passive hosts favor a dust law of R{sub V} {approx_equal} 1, while SNe Ia in star-forming hosts require R{sub V} {approx} 2. The significance of these trends depends on the range of SN colors considered. We demonstrate that these effects can be parameterized using the stellar mass of themore » host galaxy (with a confidence of > 4{sigma}) and including this extra parameter provides a better statistical fit to our data. Our results suggest that future cosmological analyses of SN Ia samples should include host galaxy information.« less