National Research Council–Division of Biology and Agriculture1: Summary of Activities, 1956–57

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Response to "To what extent, and how, might uncertainty be defined" by Norgon, Brown, and Mysiak

In a previous issue of Integrated Assessment (Vol. 4, No. 1), we proposed an uncertainty analysis framework, the aim of which was to provide a conceptual basis for the systematic treatment of uncertainty in model-based decision support activities, such as policy analysis, integrated assessment, and risk assessment. In the current issue, Norton, et al. present a critique and evaluation of the framework. This Disciplinary Perspective responds to their critique

Defining Uncertainty: A Conceptual Basis for Uncertainty Management in Model-Based Decision Support

The aim of this paper is to provide a conceptual basis for the systematic treatment of uncertainty in model-based decision support activities such as policy analysis, integrated assessment and risk assessment. It focuses on the uncertainty perceived from the point of view of those providing information to support policy decisions (i.e., the modellers’ view on uncertainty) – uncertainty regarding the analytical outcomes and conclusions of the decision support exercise. Within the regulatory and management sciences, there is neither commonly shared terminology nor full agreement on a typology of uncertainties. Our aim is to synthesise a wide variety of contributions on uncertainty in model-based decision support in order to provide an interdisciplinary theoretical framework for systematic uncertainty analysis. To that end we adopt a general definition of uncertainty as being any deviation from the unachievable ideal of completely deterministic knowledge of the relevant system. We further propose to discriminate among three dimensions of uncertainty: location, level and nature of uncertainty, and we harmonise existing typologies to further detail the concepts behind these three dimensions of uncertainty.We propose an uncertainty matrix as a heuristic tool to classify and report the various dimensions of uncertainty, thereby providing a conceptual framework for better communication among analysts as well as between them and policymakers and stakeholders. Understanding the various dimensions of uncertainty helps in identifying, articulating, and prioritising critical uncertainties, which is a crucial step to more adequate acknowledgement and treatment of uncertainty in decision support endeavours and more focused research on complex, inherently uncertain, policy issues

Measurement of Z/gamma*+jet+X angular distributions in ppbar collisions at sqrt{s}=1.96 TeV

We present the first measurements at a hadron collider of differential cross sections for Z+jet+X production in delta phi(Z, jet), |delta y(Z, jet)| and |y_boost(Z, jet)|. Vector boson production in association with jets is an excellent probe of QCD and constitutes the main background to many small cross section processes, such as associated Higgs production. These measurements are crucial tests of the predictions of perturbative QCD and current event generators, which have varied success in describing the data. Using these measurements as inputs in tuning event generators will increase the experimental sensitivity to rare signals.Comment: Published in Physics Letters B 682 (2010), pp. 370-380. 15 pages, 6 figure

Measurement of the ratios of the Z/G* + >= n jet production cross sections to the total inclusive Z/G* cross section in ppbar collisions at sqrt(s) = 1.96 TeV

We present a study of events with Z bosons and jets produced at the Fermilab Tevatron Collider in ppbar collisions at a center of mass energy of 1.96 TeV. The data sample consists of nearly 14,000 Z/G* -> e+e- candidates corresponding to the integrated luminosity of 0.4 fb-1 collected using the D0 detector. Ratios of the Z/G* + >= n jet cross sections to the total inclusive Z/G* cross section have been measured for n = 1 to 4 jet events. Our measurements are found to be in good agreement with a next-to-leading order QCD calculation and with a tree-level QCD prediction with parton shower simulation and hadronization.Comment: 7 pages, 2 figures, slightly modified, submitted to Phys. Lett.

Primordial Nucleosynthesis for the New Cosmology: Determining Uncertainties and Examining Concordance

Big bang nucleosynthesis (BBN) and the cosmic microwave background (CMB) have a long history together in the standard cosmology. The general concordance between the predicted and observed light element abundances provides a direct probe of the universal baryon density. Recent CMB anisotropy measurements, particularly the observations performed by the WMAP satellite, examine this concordance by independently measuring the cosmic baryon density. Key to this test of concordance is a quantitative understanding of the uncertainties in the BBN light element abundance predictions. These uncertainties are dominated by systematic errors in nuclear cross sections. We critically analyze the cross section data, producing representations that describe this data and its uncertainties, taking into account the correlations among data, and explicitly treating the systematic errors between data sets. Using these updated nuclear inputs, we compute the new BBN abundance predictions, and quantitatively examine their concordance with observations. Depending on what deuterium observations are adopted, one gets the following constraints on the baryon density: OmegaBh^2=0.0229\pm0.0013 or OmegaBh^2 = 0.0216^{+0.0020}_{-0.0021} at 68% confidence, fixing N_{\nu,eff}=3.0. Concerns over systematics in helium and lithium observations limit the confidence constraints based on this data provide. With new nuclear cross section data, light element abundance observations and the ever increasing resolution of the CMB anisotropy, tighter constraints can be placed on nuclear and particle astrophysics. ABRIDGEDComment: 54 pages, 20 figures, 5 tables v2: reflects PRD version minor changes to text and reference