9,256 research outputs found
KLEVER: An experiment to measure \boldmath{} at the CERN SPS
The KLEVER experiment aims to measure , supplementing the ongoing NA62 measurement of , to provide new input on CKM unitarity and
potentially new physics. KLEVER is undergoing continuous development, with
particular efforts focused on the design of the target and the beamline. As
described here, adaptations are required relative to the K12 beamline in its
current format, and a series of simulations has been performed to ensure that
an adequate particle flux can be achieved while simultaneously suppressing
problematic backgrounds.Comment: Published under licence CC-BY in Journal of Physics: Conference
Series (JPCS) by IOP Publishing Ltd, proceedings of 6th Symposium on
Prospects in the Physics of Discrete Symmetries, DISCRETE 2018, 26-30 Nov.
2018, Vienna, Austri
Scattering in one dimension: The coupled Schroedinger equation, threshold behaviour and Levinson's theorem
We formulate scattering in one dimension due to the coupled Schr\"{o}dinger
equation in terms of the matrix, the unitarity of which leads to
constraints on the scattering amplitudes. Levinson's theorem is seen to have
the form , where is the phase of
the matrix at zero energy, the number of bound states with nonzero
binding energy, the number of half-bound states, and the number of
coupled equations. In view of the effects due to the half-bound states, the
threshold behaviour of the scattering amplitudes is investigated in general,
and is also illustrated by means of particular potential models.Comment: to appear in Journal of Mathematic Physics, RevTex, 16 pages, 3
figures (PostScript
Novel applications of the ât-amino effectâ in heterocyclic chemistry; synthesis of 5H-pyrrolo- and 1H,6H-pyrido[1,2-a][3,1]benzoxazines
Trifluoroacetylated N,N-dialkylanilines react in refluxing 1-butanol to benzoxazine derivatives via an intramolecular] [1, 5] hydrogen shift and subsequent cyclization of the dipolar intermediate
Evidence on a DSGE Business Cycle model subject to Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging
The empirical support for a DSGE type of real business cycle model with two technology shocks is evaluated using a Bayesian model averaging procedure that makes use of a finite mixture of many models within the class of vector autoregressive (VAR) processes. The linear VAR model is extended to permit equilibrium restrictions and restrictions on long-run responses to technology shocks apart from having a range of lag structures and deterministic processes. These model features are weighted as posterior probabilites and computed using MCMC and analytical methods. Uncertainty exists as to the most appropriate model for our data, with five models receiving significant support. The model set used has substantial implications for the results obtained. We do find support for a number of features implied by the real business cycle model. Business cycle volatility seems more due to investment specific technology shocks than neutral technology shocks and this result is robust to model specification. These techonolgy schocks appear to account for all stochastic trends in our system after 1984. we provide evidence on the uncertainty bands associated with these results.
Organischestofvoorziening niet in de knel door Minas
Voor representatieve bouwplannen op zand en op klei zijn modelberekeningen uitgevoerd m.b.t. de aan- en afvoer van (effectieve) organische stof. Op grond daarvan is voor verschillende soorten organische mest (varkensdrijfmest, runderdrijfmest, slachtkuikenmest en GFT-compost) de maximale plaatsingssruimte op bedrijfsniveau bepaald, rekening houdend met de Minas-verliesnormen voor fosfaat en stikstof, en (bij volledige benutting van de mestruimte) de aanvoer van effectieve organische stof, werkzame N, P2O5 en K2O. Bij gebruik van varkensdrijfmest blijkt de organischestofvoorziening vaak krap te zijn; groenbemesters, inwerken van graanstro, voorjaarstoediening van mest, of andere mestsoorten kunnen dan een oplossing zij
Model Uncertainty and Bayesian Model Averaging in Vector Autoregressive Processes
Economic forecasts and policy decisions are often informed by empirical analysis based on econometric models. However, inference based upon a single model, when several viable models exist, limits its usefulness. Taking account of model uncertainty, a Bayesian model averaging procedure is presented which allows for unconditional inference within the class of vector autoregressive (VAR) processes. Several features of VAR process are investigated. Measures on manifolds are employed in order to elicit uniform priors on subspaces defined by particular structural features of VARs. The features considered are the number and form of the equilibrium economic relations and deterministic processes. Posterior probabilities of these features are used in a model averaging approach for forecasting and impulse response analysis. The methods are applied to investigate stability of the "Great Ratios" in U.S. consumption, investment and income, and the presence and effects of permanent shocks in these series. The results obtained indicate the feasibility of the proposed method.Posterior probability; Grassman manifold; Orthogonal group; Cointegration; Model averaging; Stochastic trend; Impulse response; Vector autoregressive model.
Improper priors with well defined Bayes Factors
While some improper priors have attractive properties, it is generally claimed that Bartlettâs paradox implies that using improper priors for the parameters in alternative models results in Bayes factors that are not well defined, thus preventing model comparison in this case. In this paper we demonstrate, using well understood principles underlying what is already common practice, that this latter result is not generally true and so expand the class of priors that may be used for computing posterior odds to two classes of improper priors: the shrink age prior; and a prior based upon a nesting argument. Using a new representation of the issue of undefined Bayes factors, we develop classes of improper priors from which well defined Bayes factors result. However, as the use of such priors is not free of problems, we include discussion on the issues with using such priors for model comparison.Improper prior; Bayes factor; marginal likelihood; shrinkage prior; measure
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