Search arXivSearch

arXiv · 1109.4506

Band-Pass and OH-Suppression Filters for the E-ELT - Design and Prototyping

Abstract

Optical filters are used for a variety of purposes at astronomical telescopes. In the near infrared region, from 0.8 to 2.5 um, bandpass and edge filters are used to separate the different astronomical channels, such as the J, H, and K bands. However, in the same wavelength range light emission generated in the earth's atmosphere is superimposed on the stellar radiation. Therefore, ground based astronomical instruments measure, in addition to the stellar light, also unwanted contributions from the earth's atmosphere. The characteristic lines of this OH emission are extremely narrow and distributed over the complete NIR spectral range. The sensitivity of future telescopes, like the European Extreme Large Telescope (E-ELT) which is currently being designed by ESO, can be dramatically improved if the atmospheric emission lines are effectively suppressed while the stellar radiation is efficiently transferred to the detector systems. For this task, new types of optical filters have to be developed. In this framework new design concepts and algorithms must be used, combining the measurement needs with practical restrictions. Certainly, the selected deposition process plays the key role in the manufacturing process. Precise and highly stable deposition systems are necessary to realise such filter systems with an appropriate homogeneity. Moreover, the production control techniques must be adapted to match the high level of precision required in the NIR range. Finally, the characterisation set-ups for such filters systems have to be provided. The manufacturing of such a filter system for a feasibility study of an E-ELT instrument is presented. The design development, the deposition with adapted Ion Beam Sputtering deposition plants, and the characterisation of such filters in the J-Band is described.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

S. Guenster, D. Ristau, R. Davies. 2011-09-21. Band-Pass and OH-Suppression Filters for the E-ELT - Design and Prototyping. https://doi.org/10.1117/12.896916

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The Simons Observatory: Development of a Pipeline to Detect Rapid Transients in Time-Ordered Data

We introduce a method for detecting astrophysical transients evolving on timescales of milliseconds to minutes using cosmic microwave background (CMB) survey telescopes. While previous transient searches in CMB data operate in map space, our pipeline directly processes the raw time-ordered data, enabling sensitivity to fast, dynamic signals. We integrate our detection approach into the Simons Observatory time-domain pipeline and assess the performance by injecting symmetric, stellar flare-like light curves into simulated observations. For events flaring with a timescale of 0.5 s, the pipeline detects $\gtrsim90$ % of events at flux densities of 800, 1150, 1650, and 4250\,mJy when measured in the 93, 145, 225, and 280 GHz bands respectively. At a fixed peak flux density, the pipeline more readily detects longer flares. The limiting flux density for 90 % completeness is four times lower for a $\ge5$ s flare than for a 0.5 s flare, while the flux density limits for $\gtrsim50$ % detection efficiency are comparable to the rms noise of the time-ordered data. We are able to determine the position of detected events in each observing band, with a positional uncertainty at the detection threshold comparable to the telescope resolution at that band. These results demonstrate the readiness of this pipeline for incorporation into upcoming Simons Observatory data analyses.

astro-ph.IM

Fitting Moving Objects in Up-The-Ramp Data with Applications to the Roman Space Telescope and JWST

A moving object breaks the fundamental property of constant per-pixel count rates in an astronomical image read out up-the-ramp. In this paper, we show how to fit a moving object's path across a detector as that detector is read out nondestructively. We write the full likelihood function for every pixel subject to a constant count rate plus a time-dependent count rate due to a moving source. Assuming the moving source to be point-like and assuming the effective point-spread function to be known, we are left with four parameters that enter the likelihood nonlinearly: two for position and two for velocity. All remaining parameters can be optimized using closed-form expressions. Our approach extracts maximal information on a moving source's position and speed and enables the source to be accurately removed from the image. We investigate the dependence of flux, position, and velocity precision on the target's speed and the readout pattern. We also find a small, positive bias on the recovered flux due to the need to fit for an uncertain position and speed. Our approach can be used for space-based images with minor Solar system bodies in the foreground, e.g.~from Roman and JWST, or for ground-based observations with satellites in the foreground. We demonstrate the promise of our method with a fit to an asteroid track observed serendipitously by the NIRISS instrument on JWST, comparing it to the performance of the JWST pipeline. Python code implementing our approach is available at https://github.com/t-brandt/moving_source. The total computational cost to fit the track of a moving object is $\sim$1 second on a 2023 Macbook Pro.

astro-ph.IM

Options for Compression of radio interferometry data: lossy compression of visibilities and lossless compression of uv-visibility grids for the MHONGOOSE survey

Next generation radio astronomy telescopes are challenging existing data reduction paradigms. With ever more antennas, larger bandwidths, and sometimes multiple primary beams, they often generate more observed data products than can readily be stored long-term. Thus, data storage becomes a major cost driver and processing constraint. In this paper, we test two methods of addressing this problem: grid-stacking, a two-stage lossless compression solution; and the lossy compression of the raw visibilities before traditional processing. To demonstrate these solutions we utilised a deep imaging pipeline based on software for the ASKAP telescope, ASKAPSoft, but applied to a strong source (NGC1566) from the deep MeerKAT HI spectral line project, MHONGOOSE. The grid-stacking solution reproduces the spectrum from traditional processing to within better than 0.7%, and also allows for the reconstruction of other weighting scales without significant computing costs. In comparison, image-stacking also reproduces the spectrum from the traditional processing, to within better than 3% but with worse image residuals in the cube. The lossy compression, even at a near ten-fold reduction in file size, reproduces the spectra almost perfectly (to better than ~0.01% in all cases). Thus both compression methods are promising solutions, and we discuss considerations for their application.

astro-ph.IM