Non-parametric Cosmology with Cosmic Shear

We present a method to measure the growth of structure and the background geometry of the Universe -- with no a priori assumption about the underlying cosmological model. Using Canada-France-Hawaii Lensing Survey (CFHTLenS) shear data we simultaneously reconstruct the lensing amplitude, the linear intrinsic alignment amplitude, the redshift evolving matter power spectrum, P(k,z), and the co-moving distance, r(z). We find that lensing predominately constrains a single global power spectrum amplitude and several co-moving distance bins. Our approach can localise precise scales and redshifts where Lambda-Cold Dark Matter (LCDM) fails -- if any. We find that below z = 0.4, the measured co-moving distance r (z) is higher than that expected from the Planck LCDM cosmology by ~1.5 sigma, while at higher redshifts, our reconstruction is fully consistent. To validate our reconstruction, we compare LCDM parameter constraints from the standard cosmic shear likelihood analysis to those found by fitting to the non-parametric information and we find good agreement.Comment: 13 pages. Matches PRD accepted versio

EVALUATING FARMLAND INVESTMENTS CONSIDERING DYNAMIC STOCHASTIC RETURNS AND FARMLAND PRICES

This paper examines farmland investment decisions using a stochastic dynamic programming framework. Consideration is given to the dynamic, stochastic nature of farmland returns, linkages between farmland returns and farmland prices, and the effects of the above dynamic factors on a farmÂ’s financial structure. Optimal decisions to purchase or sell farmland are found for a central Illinois farm with high quality farmland. Sizes and debt distributions are then determined, given that the optimal decision rule is followed. Decisions from the dynamic programming model also are compared to a capital budgeting model.Land Economics/Use,

Cost effective combined axial fan and throttling valve control of ventilation rate

This paper is concerned with Proportional-Integral-Plus (PIP) control of ventilation rate in mechanically ventilated agricultural buildings. In particular, it develops a unique fan and throttling valve control system for a 22m3 test chamber, representing a section of a livestock building or glasshouse, at the Katholieke Universiteit Leuven. Here, the throttling valve is employed to restrict airflow at the outlet, so generating a higher static pressure difference over the control fan. In contrast with previous approaches, however, the throttling valve is directly employed as a second control actuator, utilising airflow from either the axial fan or natural ventilation. The new combined fan/valve configuration is compared with a commercially available PID-based controller and a previously developed scheduled PIP design, yielding a reduction in power consumption in both cases of up to 45%

Increasing Transit Ridership: Lessons from the Most Successful Transit Systems in the 1990s, MTI Report-01-22

This study systematically examines recent trends in public transit ridership in the U.S. during the 1990s. Specifically, this analysis focuses on agencies that increased ridership during the latter half of the decade. While transit ridership increased steadily by 13 percent nationwide between 1995 and 1999, not all systems experienced ridership growth equally. While some agencies increased ridership dramatically, some did so only minimally, and still others lost riders. What sets these agencies apart from each other? What explains the uneven growth in ridership

MathWeb: A Concurrent Image Analysis Tool Suite for Multi-spectral Data Fusion

This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect cancer cell structures. The approach combines a multi-spectral microscope with an image analysis tool suite, MathWeb. The tool suite incorporates a concurrent Principal Component Transform (PCT) that is used to fuse the multi-spectral data. This paper describes the general approach and the concurrent PCT algorithm. The algorithm is evaluated from both the perspective of image quality and performance scalability

Preparing for the Cosmic Shear Data Flood: Optimal Data Extraction and Simulation Requirements for Stage IV Dark Energy Experiments

Upcoming photometric lensing surveys will considerably tighten constraints on the neutrino mass and the dark energy equation of state. Nevertheless it remains an open question of how to optimally extract the information and how well the matter power spectrum must be known to obtain unbiased cosmological parameter estimates. By performing a Principal Component Analysis (PCA), we quantify the sensitivity of 3D cosmic shear and tomography with different binning strategies to different regions of the lensing kernel and matter power spectrum, and hence the background geometry and growth of structure in the Universe. We find that a large number of equally spaced tomographic bins in redshift can extract nearly all the cosmological information without the additional computational expense of 3D cosmic shear. Meanwhile a large fraction of the information comes from small poorly understood scales in the matter power spectrum, that can lead to biases on measurements of cosmological parameters. In light of this, we define and compute a cosmology-independent measure of the bias due to imperfect knowledge of the power spectrum. For a Euclid-like survey, we find that the power spectrum must be known to an accuracy of less than 1% on scales with k = 7 h /Mpc This requirement is not absolute since the bias depends on the magnitude of modelling errors, where they occur in k-z space, and the correlation between them, all of which are specific to any particular model. We therefore compute the bias in several of the most likely modelling scenarios and introduce a general formalism and public code, RequiSim, to compute the expected bias from any non-linear model.Comment: 17 pages, 13 figures. Accepted and published in PR

Report from space plasma science

Space plasma science, especially plasma experiments in space, is discussed. Computational simulations, wave generation and propagation, wave-particle interactions, charged particle acceleration, particle-particle interactions, radiation transport in dense plasmas, macroscopic plasma flow, plasma-magnetic field interactions, plasma-surface interactions, prospects for near-term plasma science experiments in space and three-dimensional plasma experiments are among the topics discussed