.. include:: ../references.txt .. _references: Glossary and references ======================= .. _glossary: Glossary -------- .. glossary:: 1D Analysis 1D analysis or spectral analysis where data are reduced to a simple 1D geometry along the reconstructed energy axis. In Cherenkov astronomy, this is classically performed with an OFF background measurement, see WStat. 3D Analysis 3D analysis or cube analysis, where data are reduced to a 3D cube with spatial coordinates and energy axes [Stewart2009]_. In Gammapy, these cube are represented by `Map` objects (see :ref:`maps`) and contained in a `MapDataset` object. Aeff Short for "effective area": it is the IRF representing the detector collection area. See :ref:`irf` and :ref:`irf-aeff`. Bkg Short for "background": it is the IRF representing the residual background rate per solid angle. See :ref:`irf` and :ref:`irf-bkg`. Cash The Cash statistic is a Poisson fit statistic usually used when signal and background can be modeled. It is defined as :math:`2 \times log(L)`. See :ref:`cash` in :ref:`fit statistics `. Dataset In Gammapy a dataset bundles the data, IRFs, model and a likelihood function. Based on the model and IRFs the predicted number of counts are computed and compared to the measured counts using the likelihood. See :ref:`datasets` DL3 Short for "data level 3": it is used to mention or describe science-ready data, ie the event list (with basically a Time, an arrival direction and an energy) and the four IRFs (Aeff, EDisp, PSF, Bkg). See :ref:`data flow `. DL4 Short for "data level 4": it is used to mention or describe binned-science data, ie N-dim maps (multi-dimensional histograms) of the spatial, temporal and/or spectral components of the DL3 data in instrumental units (e.g. counts). See :ref:`maps` and :ref:`data flow `. DL5 Short for "data level 5": it is used to mention or describe advanced-science data, ie N-dim maps of the spatial, temporal and/or spectral astrophysical quantities in physical units (e.g. cm-2 s-1). See :ref:`data flow `. DL6 Short for "data level 6": it is used to mention or describe catalogs of sources, with their spectral and spatial properties. See :ref:`data flow `. EDisp Short for "energy dispersion": it is the IRF that represents the probability of measuring a given reconstructed energy as a function of the true photon energy. See :ref:`irf` and :ref:`irf-edisp`. Estimator Gammapy utility classes to compute astrophysical quantities based on a model. They are used for the computation of DL5 products from the DL4 ones. See :ref:`modeling` and the :ref:`data flow `. FoV Short for "field of view": it indicates the angular aperture (sometimes also the solid angle) on the sky that is visible by the instrument with a single pointing. FoV Background Background estimation method typically used for the 3D analysis. See :ref:`makers`. HLI Short for "high level interface: this API aims to realize most of the analysis types using YAML configuration files. See :ref:`analysis` GADF Short for "Gamma Astro Data Format". The `open initiative GADF `_ provides a Data Format for gamma-ray data that is currently used by many IACT experiments and by HAWC. Gammapy I/O functions are compliant with this format. GTI Short for "good time interval": it indicates a continuous time interval of data acquisition. In CTA, it also represents a time interval in which the IRFs are supposed to be constant. IRF Short for "instrument response function": they are used to model the probability to detect a photon with a number of measured characteristics. See :ref:`irf`. Joint Analysis A joint fit across multiple datasets implies that each dataset is handled independently during the data reduction stage, and the statistics combined during the likelihood fit. The likelihood is computed for each dataset and summed to get the total fit statistic. See :ref:`joint` Maker Gammapy utility classes performing data reduction of the DL3 data to binned datasets (DL4). See :ref:`makers` and the :ref:`data flow `. MET Short for "mission elapsed time". see also :ref:`MET_definition` in :ref:`time_handling`. PSF Short for "point spread function": it is the IRF representing the probability density of the angular separation between true and reconstructed directions. See :ref:`irf` and :ref:`irf-psf`. Reco Energy The reconstructed (or measured) energy (often written `e_reco`) is the energy of the measured photon by contrast with its actual true energy. Measured quantities such as counts are represented along a reco energy axis. Reflected Background Background estimation method typically used for spectral analysis. See :ref:`makers`. Ring Background Background estimation method typically used for image analysis. See :ref:`makers`. RoI Short for "region of interest": it indicates the spatial region in which the data are analyzed. In practice, at each energy it corresponds with the sky region in which the dataset mask is True. Stacked Analysis In a stacked analysis individual observations are reduced to datasets which are then stacked to produce a single reduced dataset. The latter is then used to obtain physical information through model fitting. Some approximations must be made to perform dataset stacking (e.g. loss of individual background normalization, averaging of instrument responses, loss of information outside region of interest etc), but this can reduce very significantly the computing and memory cost. For details, see :ref:`stack` True Energy The true energy (often written `e_true`) is the energy of the incident photon by contrast with the energy reconstructed by the instrument. Instrument response functions are represented along a true energy axis. TS Short for "test statistics". See :ref:`ts` and :ref:`fit-statistics`. WStat The WStat is a Poisson fit statistic usually used for ON-OFF analysis. It is based on the profile likelihood method where the unknown background parameters are marginalized. See :ref:`wstat` in :ref:`fit statistics `. .. _publications: References ---------- This is the bibliography containing the literature references for the implemented methods referenced from the Gammapy docs. .. [Abdalla2018] `H.E.S.S. Collaboration (2018) `_, "The H.E.S.S. Galactic plane survey" .. [Albert2007] `Albert et al. (2007) `_, "Unfolding of differential energy spectra in the MAGIC experiment", .. [Berge2007] `Berge et al. (2007) `_, "Background modelling in very-high-energy gamma-ray astronomy" .. [Cash1979] `Cash (1979) `_, "Parameter estimation in astronomy through application of the likelihood ratio" .. [Cousins2007] `Cousins et al. (2007) `_, "Evaluation of three methods for calculating statistical significance when incorporating a systematic uncertainty into a test of the background-only hypothesis for a Poisson process" .. [Feldman1998] `Feldman & Cousins (1998) `_, "Unified approach to the classical statistical analysis of small signals" .. [Lafferty1994] `Lafferty & Wyatt (1994) `_, "Where to stick your data points: The treatment of measurements within wide bins" .. [LiMa1983] `Li & Ma (1983) `_, "Analysis methods for results in gamma-ray astronomy" .. [Meyer2010] `Meyer et al. (2010) `_, "The Crab Nebula as a standard candle in very high-energy astrophysics" .. [Mohrmann2019] `Mohrmann et al. (2019) `_, "Validation of open-source science tools and background model construction in γ-ray astronomy" .. [Naurois2012] `de Naurois (2012) `_, "Very High Energy astronomy from H.E.S.S. to CTA. Opening of a new astronomical window on the non-thermal Universe", .. [Piron2001] `Piron et al. (2001) `_, "Temporal and spectral gamma-ray properties of Mkn 421 above 250 GeV from CAT observations between 1996 and 2000", .. [Rolke2005] `Rolke et al. (2005) `_, "Limits and confidence intervals in the presence of nuisance parameters", .. [Stewart2009] `Stewart (2009) `_, "Maximum-likelihood detection of sources among Poissonian noise"