# Source Variability

Source variability within an observation is assessed by three methods: (1) the Kolmogorov-Smirnov (K-S) test, (2) the Kuiper's test, and (3) computation of the Gregory-Loredo variability probability, all based on the source region counts. Intra-observation source variability within any contributing observations to a master source entry is assessed according to the highest level of variability seen within any single contributing observation. Inter-observation source variability between any contributing observations to a master source entry is assessed by application of a $$\chi^{2}$$ hypothesis test applied to the source region photon fluxes observed in the contributing observations.

## Properties of Individual Per-Observation Detections

### Gregory-Loredo Variability Probability

var_prob

The probability that the source region count rate lightcurve is better described by multiple, uniformly sampled time bins with potentially different rates in each bin, as opposed to being described by a single, uniform rate time bin. This probability is based upon the odds ratios (for describing the lightcurve with two or more bins of potentially different rates) calculated from a Gregory-Loredo analysis of the arrival times of the events within the source region. Corrections to the event rate are applied accounting for good time intervals and for the source region dithering across regions of variable exposure (e.g., chip edges) during the observation. Probability values are calculated for each science energy band.

### Kolmogorov-Smirnov (K-S) Test Probability

ks_prob

The probability that the arrival times of the events within the source region are inconsistent with a constant source count rate throughout the observation. High values of this quantity imply that the source is not consistent with a constant rate, and that the source is likely variable. The probability is computed by means of a hypothesis rejection test from a one-sample K-S test applied to the unbinned event data, with corrections applied for good time intervals and for the source region dithering across regions of variable exposure (e.g., chip edges) during the observation. Probability values are calculated for each science energy band. Note that this variability diagnostic does not treat the source and background separately.

### Kuiper's Test Probability

kp_prob

The probability that the arrival times of the events within the source region are inconsistent with a constant source count rate throughout the observation. High values of this quantity imply that the source is not consistent with a constant rate, and that the source is likely variable. The probability is computed by means of a hypothesis rejection test from a one-sample Kuiper's test applied to the unbinned event data, with corrections applied for good time intervals and for the source region dithering across regions of variable exposure (e.g., chip edges) during the observation. Probability values are calculated for each science energy band. Note that this variability diagnostic does not treat the source and background separately.

### Variability Index

var_index

An index in the range [0,10] that combines (a) the Gregory-Loredo variability probability with (b) the fractions of the multi-resolution light curve output by the Gregory-Loredo analysis that are within 3σ and 5σ of the average count rate, to evaluate whether the source region flux is uniform throughout the observation. See the Gregory-Loredo Probability How and Why topic for a definition of this index value, which is calculated for each science energy band.

### Count Rate Variability

var_mean, var_sigma, var_min, var_max

#### Mean Count Rate

The mean count rate (var_mean) is the time-averaged source region count rate derived from the multi-resolution light curve output by the Gregory-Loredo analysis. This value is calculated for each science energy band.

#### Count Rate Standard Deviation

The count rate standard deviation (var_sigma) is the time-averaged 1σ statistical variability of the source region count rate derived from the multi-resolution light curve output by the Gregory-Loredo analysis. This value is calculated for each science energy band.

#### Minimum Count Rate

The minimum count rate (var_min) is the minimum value of the source region count rate derived from the multi-resolution light curve output by the Gregory-Loredo analysis. This value is calculated for each science energy band.

#### Maximum Count Rate

The maximum count rate (var_max) is the maximum value of the source region count rate derived from the multi-resolution light curve output by the Gregory-Loredo analysis. This value is calculated for each science energy band.

### Dither Warning Flag

dither_warning_flag

The dither warning flag consists of a Boolean whose value is TRUE if the highest statistically significant peak in the power spectrum of the source region count rate, for the science energy band with the highest variability index, occurs either at the dither frequency of the observation or at a beat frequency of the dither frequency. Otherwise, the dither warning flag is FALSE. This value is calculated for each science energy band.

### Gregory-Loredo Light Curve File

see Data Products page

Each light curve file records the multi-resolution light curve output by the Gregory-Loredo analysis of the arrival times of the source events within the source region, per observation and science energy band. A background light curve with identical time-binning to the source light curve is derived from an analysis of the events within the background region. Note that the source lightcurve is not strictly a rate derived from binned counts. Instead, it is a probabilistic model of the lightcurve, derived from a probability weighted average of the lightcurve models calculated by the Gregory-Loredo algorithm at different uniform binnings.

## Master Source and Stacked Observation Detection Properties

### Intra-Observation:

#### Intra-Observation Gregory-Loredo, Kolmogorov-Smirnov, and Kuiper's Variability Probability

var_intra_prob, ks_intra_prob, kp_intra_prob

The Gregory-Loredo, Kolmogorov-Smirnov (K-S) test, and Kuiper's test intra-observation variability probabilities represent the highest values of the variability probabilities (var_prob, ks_prob, kp_prob) calculated for each of the contributing observations (i.e., the highest level of variability among the observations contributing to the master source entry).

#### Intra-Observation Variability Index

var_intra_index

The intra-observation variability index (var_intra_index) represents the highest value of the variability indices (var_index) calculated for each of the contributing observations.

### Inter-observation:

#### Inter-Observation Variability Probability

var_inter_prob

The inter-observation variability probability (var_inter_prob) is a value that records the probability that the source region photon flux varied between the contributing observations, based on the $$\chi^{2}$$ distribution of the photon fluxes and the errors (standard deviation) of the individual observations. In other words, (1 - var_inter_prob) is the probability that the measured fluxes are consistent with a non-varying source.

The reason for this careful definition is that the probabilities for intra-observation and inter-observation variability are, by necessity, of a different nature. Whereas one can say with reasonable certainty whether a source was variable during an observation covering a contiguous time interval, when comparing measured fluxes from different observations one knows nothing about the source's behavior during the intervening interval(s). Consequently, when the inter-observation variability probability is high (e.g., >0.7), one can confidently state that the source is variable on longer time scales, but when the probability is low, all one can say is that the observations are consistent with a constant flux.

#### Inter-Observation Variability Index

var_inter_index

The inter-observation variability index (var_inter_index) is an integer value in the range [0,10] that is derived from the inter-observation variability probability to evaluate whether the source region photon flux is constant between the observations. The degree of confidence in variability expressed by this index is similar to that of the intra-observation variability index.

#### Inter-Observation Count Rate Variability

var_inter_sigma

The inter-observation flux variability (var_inter_sigma) is the absolute value of the difference between the error weighted mean source region photon flux density of all the contributing observations and the mean source region photon flux density of the single observation for which the absolute value of the difference, divided by the standard deviation for that observation, is maximized:

Here, $$\left\langle F_{ew}\right\rangle$$ represents the inter-observation error weighted mean source region photon flux density; $$\left\langle f_{i=x}\right\rangle$$ is the intra-observation mean source region photon flux density for the single observation $$x$$; and $$\sigma_{i=x}$$ is the standard deviation corresponding to the observation $$x$$ [where $$x \in \left\{ k \in \mathbb{Z}^{+} | k \leq N \right\}$$ for $$N$$ contributing observations]. Of all contributing observations, observation $$x$$ yields the highest value for this equation, which is the value recorded by var_inter_sigma.