Astrometric signal profile fitting for Gaia

A tool for representation of the one-dimensional astrometric signal of Gaia is described and investigated in terms of fit discrepancy and astrometric performance with respect to number of parameters required. The proposed basis function is based on the aberration free response of the ideal telescope and its derivatives, weighted by the source spectral distribution. The influence of relative position of the detector pixel array with respect to the optical image is analysed, as well as the variation induced by the source spectral emission. The number of parameters required for micro-arcsec level consistency of the reconstructed function with the detected signal is found to be 11. Some considerations are devoted to the issue of calibration of the instrument response representation, taking into account the relevant aspects of source spectrum and focal plane sampling. Additional investigations and other applications are also suggested.Comment: 13 pages, 21 figures, Accepted by MNRAS 2010 January 29. Received 2010 January 28; in original form 2009 September 3

Chromaticity in all-reflective telescopes for astrometry

Chromatic effects are usually associated with refractive optics, so reflective telescopes are assumed to be free from them. We show that all-reflective optics still bears significant levels of such perturbations, which is especially critical to modern micro-arcsecond astrometric experiments. We analyze the image formation and measurement process to derive a precise definition of the chromatic variation of the image position, and we evaluate the key aspects of optical design with respect to chromaticity. The fundamental requirement related to chromaticity is the symmetry of the optical design and of the wavefront errors. Finally, we address some optical engineering issues, such as manufacturing and alignment, providing recommendations to minimize the degradation that chromaticity introduces into astrometry.Comment: 10 pages, 8 figure

Precision Measurements of the 7Be(p,gamma)8B Reaction with Radioactive Beams and the 8B Solar Neutrino Flux

The 7Be(p,gamma)8B reaction is one of the major source of uncertainties in estimating the 8B solar neutrino flux and is critical for undertsanding the Solar Neutrino Problem and neutrinos. The main source of uncertainty is the existence of conflicting data with different absolute normalization. Attempts to measure this reaction rate with 7Be beams are under way by the UConn-LLN collaboration, and we discuss a newly emerging method to extract this cross section from the Coulomb dissociation of the radioactive beam of 8B. We discuss some of the issues relevant for this study including the question of the E2 contribution to the Coulomb dissociation process which was measured to be small. The Coulomb dissociation appears to provide a viable alternative method for measuring the 7Be(p,gamma)8B reaction rate, with a weighted average of the RIKEN1, RIKEN2 and GSI1 published results of S17(0) = 19.4 +/- 1.3 eV-b.Comment: 8 pages, 4 Figures Work Supported by USDOE Grant No. DE-FG02-94ER40870 To Be published in Prog. Part. Nucl. Phy

Asteroseismic Stellar Modelling with AIMS

The goal of AIMS (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm -- interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. AIMS is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.Comment: 11 pages, 4 figures. Tutorial presented at the IVth Azores International Advanced School in Space Sciences on "Asteroseismology and Exoplanets: Listening to the Stars and Searching for New Worlds" (arXiv:1709.00645), which took place in Horta, Azores Islands, Portugal in July 201

Three-Dimensional Analysis of Wakefields Generated by Flat Electron Beams in Planar Dielectric-Loaded Structures

An electron bunch passing through dielectric-lined waveguide generates $\check{C}$erenkov radiation that can result in high-peak axial electric field suitable for acceleration of a subsequent bunch. Axial field beyond Gigavolt-per-meter are attainable in structures with sub-mm sizes depending on the achievement of suitable electron bunch parameters. A promising configuration consists of using planar dielectric structure driven by flat electron bunches. In this paper we present a three-dimensional analysis of wakefields produced by flat beams in planar dielectric structures thereby extending the work of Reference [A. Tremaine, J. Rosenzweig, and P. Schoessow, Phys. Rev. E 56, No. 6, 7204 (1997)] on the topic. We especially provide closed-form expressions for the normal frequencies and field amplitudes of the excited modes and benchmark these analytical results with finite-difference time-domain particle-in-cell numerical simulations. Finally, we implement a semi-analytical algorithm into a popular particle tracking program thereby enabling start-to-end high-fidelity modeling of linear accelerators based on dielectric-lined planar waveguides.Comment: 12 pages, 2 tables, 10 figure

Neural network correction of astrometric chromaticity

In this paper we deal with the problem of chromaticity, i.e. apparent position variation of stellar images with their spectral distribution, using neural networks to analyse and process astronomical images. The goal is to remove this relevant source of systematic error in the data reduction of high precision astrometric experiments, like Gaia. This task can be accomplished thanks to the capability of neural networks to solve a nonlinear approximation problem, i.e. to construct an hypersurface that approximates a given set of scattered data couples. Images are encoded associating each of them with conveniently chosen moments, evaluated along the y axis. The technique proposed, in the current framework, reduces the initial chromaticity of few milliarcseconds to values of few microarcseconds.Comment: 9 pages, 8 figures Accepted by Monthly Notices of the Royal Astronomical Societ