  Continuously time variable sources are often characterized by their power
spectral density and flux distribution. These quantities can undergo dramatic
changes over time if the underlying physical processes change. However, some
changes can be subtle and not distinguishable using standard statistical
approaches. Here, we report a methodology that aims to identify distinct but
similar states of time variability. We apply this method to the Galactic
supermassive black hole, where 2.2 um flux is observed from a source associated
with SgrA*, and where two distinct states have recently been suggested. Our
approach is taken from mathematical finance and works with conditional flux
density distributions that depend on the previous flux value. The discrete,
unobserved (hidden) state variable is modeled as a stochastic process and the
transition probabilities are inferred from the flux density time series. Using
the most comprehensive data set to date, in which all Keck and a majority of
the publicly available VLT data have been merged, we show that SgrA* is
sufficiently described by a single intrinsic state. However the observed flux
densities exhibit two states: a noise-dominated and a source-dominated one. Our
methodology reported here will prove extremely useful to assess the effects of
the putative gas cloud G2 that is on its way toward the black hole and might
create a new state of variability.
