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Last modified: 14 June 2013

URL: http://cxc.harvard.edu/iris/intro/features.html

Iris 2.0 Features


NED Data Access

The Iris SED analysis tool allows the astronomer to search the VO-registered NED astronomical database for SED data associated with extragalactic sources of interest, as an alternative to loading data from file into the application. SED data from NED may be directly imported into Iris via the Load File option:

[Iris Load File window]

The "Loading Data into Iris" section of the Iris How-to Guide provides detailed instructions on how to use this feature.

Data Visualization and Customization

As the Iris user interface is an adaptation of the Specview spectral visualization and analysis interface, it is equipped with several of the data display preferences offered by Specview. Most notably, one can build a wide-band SED for a source by overplotting or combining data taken with different instruments across multiple spectral bands.

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The "Visualizing SED Data in Iris" section of the Iris How-to Guide describes the various options available for displaying and customizing SED data in Iris.

Spectral Model Fitting

Iris allows for robust modeling and fitting of SED data through association with Sherpa, an extensible, Python-based, multi-waveband modeling and fitting application for astronomers.

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Within Iris, the user is provided with an extensive list of preset emission and absorption models from which to choose for building custom model expressions for fitting, as well as a variety of fit statistics and optimization methods. There is also the option to load custom model table, template, and Python function user models.

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The best-fit SED model parameter values, and confidence limits on them, returned by a fit in Iris may be saved to file. The "Modeling and Fitting SED Data" section of the Iris How-to Guide describes the features of the Iris Fitting Tool, including instructions on defining model expressions with preset or custom model components, setting initial model parameter values and ranges, choosing an appropriate fit statistic and method, and saving fit parameters.

Conversion Tool for Non-native Data Formats

As one of the primary functions of Iris is building multi-segment SEDs, it is expected that users will input multiple SED spectra and/or photometric points in various file formats. To address this need, the SED Builder tool within Iris is equipped to convert user SED data files in non-native formats into one of the two file formats natively supported by Iris, IVOA-compliant VOTable and FITS. Files in any of the following formats may be loaded into Iris for analysis; when a file is input in a non-native format, an extra step is required of the user in order to convert the data to a compatible format.

  • ASCII
  • CSV
  • FITS (standard and non-standard)
  • VOTable (standard and non-standard)
  • IPAC
  • TST
[SED Builder        screenshot]

The SED Builder is also a robust interface for constructing and managing the various pieces of the aggregate SED. It can tie together multiple, separate SED data segments and points associated with a given source and display them together in the Iris Visualizer. The user may also maintain separate SEDs and analysis sessions within the SED Builder, whether associated with the same source or different sources. The "Building and Managing SEDs" section of the Iris How-to Guide describes the features of the SED Builder.

Science Features

The Iris SED analysis tool includes a toolkit for SED analysis and manipulation. In order to start the toolkit click on the "Shift, Interpolate, Integrate" button on the Iris desktop.

Redshift

SEDs can be shifted by using the Redshift tab in the Science Tool. Just specify the initial and final redshift and click on "Create new SED" in order to create the redshifted SED. Iris will conserve the energy of the SED, so the SED will be not only shifted but also scaled accordingly.

Interpolation

Users can interpolate an SED by specifiying the spectral range in which the SED must be interpolated, the interpolation algorithm, and also some other auxiliary options: whether the resulting SED should be normalized; whether a smoothing algorithm (boxcar) should be applied to the interpolated SED and the box dimension; the number of bins of the resulting SED, and the type of binning (linear or logarithmic).

Integration

Users can integrate SEDs defining passbands manually of from a searchable list of >2100 photometric filters. The resulting points can be saved to file, or be part of a new SED.


Last modified: 14 June 2013
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