Spatially coupled inversion of spectro-polarimetric image data I: Method and first results

When inverting solar spectra, image degradation effects that are present in the data are usually approximated or not considered. We develop a data reduction method that takes these issues into account and minimizes the resulting errors. By accounting for the diffraction PSF of the telescope during the inversions, we can produce a self-consistent solution that best fits the observed data, while simultaneously requiring fewer free parameters than conventional approaches. Simulations using realistic MHD data indicate that the method is stable for all resolutions, including those with pixel scales well beyond those that can be resolved with a 0.5m telescope, such as the Hinode SOT. Application of the presented method to reduce full Stokes data from the Hinode spectro-polarimeter results in dramatically increased image contrast and an increase in the resolution of the data to the diffraction limit of the telescope in almost all Stokes and fit parameters. The resulting data allow for detecting and interpreting solar features that have so far only been observed with 1m class ground-based telescopes. The new inversion method allows for accurate fitting of solar spectro-polarimetric imaging data over a large field of view, while simultaneously improving the noise statistics and spatial resolution of the results significantly.Comment: A&A, accepte

Non-parametric mass reconstruction of A1689 from strong lensing data with SLAP

We present the mass distribution in the central area of the cluster A1689 by fitting over 100 multiply lensed images with the non-parametric Strong Lensing Analysis Package (SLAP, Diego et al. 2004). The surface mass distribution is obtained in a robust way finding a total mass of 0.25E15 M_sun/h within a 70'' circle radius from the central peak. Our reconstructed density profile fits well an NFW profile with small perturbations due to substructure and is compatible with the more model dependent analysis of Broadhurst et al. (2004a) based on the same data. Our estimated mass does not rely on any prior information about the distribution of dark matter in the cluster. The peak of the mass distribution falls very close to the central cD and there is substructure near the center suggesting that the cluster is not fully relaxed. We also examine the effect on the recovered mass when we include the uncertainties in the redshift of the sources and in the original shape of the sources. Using simulations designed to mimic the data, we identify some biases in our reconstructed mass distribution. We find that the recovered mass is biased toward lower masses beyond 1 arcmin (150 kpc) from the central cD and that in the very center we may be affected by degeneracy problems. On the other hand, we confirm that the reconstructed mass between 25'' and 70'' is a robust, unbiased estimate of the true mass distribution and is compatible with an NFW profile.Comment: 11 pages, 12 figures. MNRAS submitted. A full resolution of the paper can be found in http://darwin.physics.upenn.edu/SLAP

A determination of H_0 with the CLASS gravitational lens B1608+656: II. Mass models and the Hubble constant from lensing

EDITED FROM PAPER: We present mass models of the four-image gravitational lens system B1608+656. A mass model for the lens galaxies has been determined that reproduces the image positions, two out of three flux-density ratios and the model time delays. Using the time delays determined by Fassnacht et al. (1999a), we find that the best isothermal mass model gives H_0=59^{+7}_{-6} km/s/Mpc for Omega_m=1 and Omega_l=0.0, or H_0=(65-63)^{+7}_{-6} km/s/Mpc for Omega_m=0.3 and Omega_l = 0.0-0.7 (95.4% statistical confidence). A systematic error of +/-15 km/s/Mpc is estimated. This cosmological determination of H_0 agrees well with determinations from three other gravitational lens systems (i.e. B0218+357, Q0957+561 and PKS1830-211), SNe Ia, the S-Z effect and local determinations. The current agreement on H_0 from four out of five gravitational lens systems (i) emphasizes the reliability of its determination from isolated gravitational lens systems and (ii) suggests that a close-to-isothermal mass profile can describe disk galaxies, ellipticals and central cluster ellipticals. The average of H_0 from B0218+357, Q0957+561, B1608+656 and PKS1830-211, gives H_0(GL)=69 +/-7 km/s/Mpc for a flat universe with Omega_m=1 or H_0(GL)=74 +/-8 km/s/Mpc for Omega_m=0.3 and Omega_l=0.0-0.7. When including PG1115+080, these values decrease to 64 +/-11 km/s/Mpc and 68 +/-13 km/s/Mpc (2-sigma errors), respectively.Comment: Accepted for publication in ApJ. 34 pages, 4 figure

Imfit: A Fast, Flexible New Program for Astronomical Image Fitting

I describe a new, open-source astronomical image-fitting program called Imfit, specialized for galaxies but potentially useful for other sources, which is fast, flexible, and highly extensible. A key characteristic of the program is an object-oriented design which allows new types of image components (2D surface-brightness functions) to be easily written and added to the program. Image functions provided with Imfit include the usual suspects for galaxy decompositions (Sersic, exponential, Gaussian), along with Core-Sersic and broken-exponential profiles, elliptical rings, and three components which perform line-of-sight integration through 3D luminosity-density models of disks and rings seen at arbitrary inclinations. Available minimization algorithms include Levenberg-Marquardt, Nelder-Mead simplex, and Differential Evolution, allowing trade-offs between speed and decreased sensitivity to local minima in the fit landscape. Minimization can be done using the standard chi^2 statistic (using either data or model values to estimate per-pixel Gaussian errors, or else user-supplied error images) or Poisson-based maximum-likelihood statistics; the latter approach is particularly appropriate for cases of Poisson data in the low-count regime. I show that fitting low-S/N galaxy images using chi^2 minimization and individual-pixel Gaussian uncertainties can lead to significant biases in fitted parameter values, which are avoided if a Poisson-based statistic is used; this is true even when Gaussian read noise is present.Comment: pdflatex, 27 pages, 19 figures. Revised version, accepted by ApJ. Programs, source code, and documentation available at: http://www.mpe.mpg.de/~erwin/code/imfit