statistics

Poisson distribution

Photon counting statistics at the interferometer ports follow a Poisson distribution.
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Description

The Poisson distribution is a probability distribution that describes the number of events occurring in a fixed interval of time or space, given that these events happen independently and at a constant average rate. In optics and quantum physics, it is the natural statistical model for counting photons: when a coherent light source, such as a laser, illuminates a detector, the number of photons detected in a given time follows a Poisson distribution. This is a cornerstone of quantum optics, where the particle-like nature of light is observed through such counting statistics.

History

The distribution was introduced by Siméon Denis Poisson in 1837 in his work on the probability of court rulings, though it was later applied to many other fields, including physics.

How it works

The distribution is characterized by a single parameter, λ, which is the average number of events in the interval. The probability of observing exactly k events is given by P(k) = (λ^k · e^(−λ)) / k!. For photons, λ is proportional to the light intensity and the detection time. The key property is that the variance equals the mean, which distinguishes Poissonian light from other types, such as thermal light, which has a broader distribution.

In practice

Poisson statistics are used in photon counting detectors for quantum cryptography, in analyzing cosmic ray showers, and in calibrating photodetectors in astronomy and medical imaging.

Fun fact

The Poisson distribution emerges naturally from the quantum theory of coherent states, which are the closest quantum analog to a classical electromagnetic wave.

Concept graph →

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