statistics

noise subtraction

An algorithm subtracts sensor noise from images of entangled photon pairs.
23 related articles

Description

Noise subtraction is a signal-processing technique used to remove unwanted random fluctuations from measurements. In the context of imaging with entangled photon pairs, it refers to algorithms that exploit the strong correlations between paired photons to distinguish genuine signal from sensor noise. Because the two photons in an entangled pair are generated together, their detection events are correlated in time and sometimes in other properties; noise, by contrast, is typically uncorrelated. By comparing the two detection streams, the algorithm can identify and subtract the noise component, leaving a cleaner image.

How it works

The method relies on the fact that entangled photon pairs are detected in coincidence—when one photon is registered, its partner should be registered almost simultaneously. The algorithm builds a statistical model of the noise, which is assumed to be independent between the two detectors, and then uses the correlation structure to estimate how much of the measured signal is noise. This estimate is subtracted from the raw data, enhancing the signal-to-noise ratio of the final image.

In practice

It is used in quantum imaging and quantum communication systems, where low-light conditions make noise subtraction essential for extracting useful information from faint photon signals.

Fun fact

Entangled photon pairs can be used to image objects with fewer photons than classical light would require, a phenomenon sometimes called 'quantum illumination.'

Concept graph →

Related articles · 23

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