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Continuously time variable sources are often characterized by their powerspectral density and flux distribution. These quantities can undergo dramaticchanges over time if the underlying physical processes change. However, somechanges can be subtle and not distinguishable using standard statisticalapproaches. Here, we report a methodology that aims to identify distinct butsimilar states of time variability. We apply this method to the Galacticsupermassive black hole, where 2.2 um flux is observed from a source associatedwith SgrA*, and where two distinct states have recently been suggested. Ourapproach is taken from mathematical finance and works with conditional fluxdensity distributions that depend on the previous flux value. The discrete,unobserved (hidden) state variable is modeled as a stochastic process and thetransition probabilities are inferred from the flux density time series. Usingthe most comprehensive data set to date, in which all Keck and a majority ofthe publicly available VLT data have been merged, we show that SgrA* issufficiently described by a single intrinsic state. However the observed fluxdensities exhibit two states: a noise-dominated and a source-dominated one. Ourmethodology reported here will prove extremely useful to assess the effects ofthe putative gas cloud G2 that is on its way toward the black hole and mightcreate a new state of variability.

A formal method for identifying distinct states of variability in time-varying sources: SgrA* as an example