ARGUS distribution

Parameters cut-off (real)
curvature (real)
PDF see text
CDF see text

where I1 is the Modified Bessel function of the first kind of order 1, and is given in the text.

In physics, the ARGUS distribution, named after the particle physics experiment ARGUS,[1] is the probability distribution of the reconstructed invariant mass of a decayed particle candidate in continuum background.


The probability density function (pdf) of the ARGUS distribution is:

for 0 ≤ x < c. Here χ, and c are parameters of the distribution and

and Φ(·), ϕ(·) are the cumulative distribution and probability density functions of the standard normal distribution, respectively.

Differential equation

The pdf of the ARGUS distribution is a solution of the following differential equation:

Cumulative distribution function

The cumulative distribution function (cdf) of the ARGUS distribution is


Parameter estimation

Parameter c is assumed to be known (the kinematic limit of the invariant mass distribution), whereas χ can be estimated from the sample X1, …, Xn using the maximum likelihood approach. The estimator is a function of sample second moment, and is given as a solution to the non-linear equation


The solution exists and is unique, provided that the right-hand side is greater than 0.4; the resulting estimator is consistent and asymptotically normal.

Generalized ARGUS distribution

Sometimes a more general form is used to describe a more peaking-like distribution:

where Γ(·) is the gamma function, and Γ(·,·) is the upper incomplete gamma function.

Here parameters c, χ, p represent the cutoff, curvature, and power respectively.

The mode is:

p = 0.5 gives a regular ARGUS, listed above.


  1. Albrecht, H. (1990). "Search for hadronic b→u decays". Physics Letters B. 241 (2): 278–282. Bibcode:1990PhLB..241..278A. doi:10.1016/0370-2693(90)91293-K. (More formally by the ARGUS Collaboration, H. Albrecht et al.) In this paper, the function has been defined with parameter c representing the beam energy and parameter p set to 0.5. The normalization and the parameter χ have been obtained from data.

Further reading

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