arXiv subjects

A. M. Buckley

Publications and source records attributed to A. M. Buckley.

3 recordsLinked to original sources

arXiv2006

On the similarity of Information Energy to Dark Energy

Information energy is shown here to have properties similar to those of dark energy. The energy associated with each information bit of the universe is found to be defined identically to the characteristic energy of a cosmological constant. Two independent methods are used to estimate the universe information content of ~10^91 bits, a value that provides an information energy total comparable to that of the dark energy. Information energy is also found to have a significantly negative equation of state parameter, w < -0.4, and thus exerts a negative pressure, similar to dark energy.

astro-ph↗

arXiv2005

Sampling errors of correlograms with and without sample mean removal for higher-order complex white noise with arbitrary mean

We derive the bias, variance, covariance, and mean square error of the standard lag windowed correlogram estimator both with and without sample mean removal for complex white noise with an arbitrary mean. We find that the arbitrary mean introduces lag dependent covariance between different lags of the correlogram estimates in spite of the lack of covariance in white noise for non-zeros lags. We provide a heuristic rule for when the sample mean should be, and when it should not be, removed if the true mean is not known. The sampling properties derived here are useful is assesing the general statistical performance of autocovariance and autocorrelation estimators in different parameter regimes. Alternatively, the sampling properties could be used as bounds on the detection of a weak signal in general white noise.

physics.data-an↗

arXiv2005

Deriving the sampling errors of correlograms for general white noise

We derive the second-order sampling properties of certain autocovariance and autocorrelation estimators for sequences of independent and identically distributed samples. Specifically, the estimators we consider are the classic lag windowed correlogram, the correlogram with subtracted sample mean, and the fixed-length summation correlogram. For each correlogram we derive explicit formulas for the bias, covariance, mean square error and consistency for generalised higher-order white noise sequences. In particular, this class of sequences may have non-zero means, be complexed valued and also includes non-analytical noise signals. We find that these commonly used correlograms exhibit lag dependent covariance despite the fact that these processes are white and hence by definition do not depend on lag.

physics.data-an↗