Autocorrelation evaluation from clipped photon detection.

Area of Science:

• Photon statistics
• Optical measurements
• Signal processing

Background:

• Autocorrelation function is crucial for characterizing light sources.
• Existing methods for estimating autocorrelation can be complex or have limitations.
• Clipped photocount data offers an alternative data source.

Purpose of the Study:

• To introduce two new techniques for estimating the autocorrelation function.
• To evaluate the performance and signal-to-noise ratio of these novel methods.
• To provide simpler and more effective tools for optical signal analysis.

Main Methods:

• Estimating autocorrelation via the mean number of clipped photocounts.
• Calculating the second-order factorial moment from clipped data.
• Comparing the signal-to-noise ratio of the proposed techniques with existing methods.

Main Results:

• The first technique (mean number of clipped photocounts) is simple to implement.
• The first technique yields a lower signal-to-noise ratio.
• The second technique (second-order factorial moment) provides a significantly better signal-to-noise ratio.

Conclusions:

• Two new, distinct methods for autocorrelation estimation from clipped photocounts are presented.
• The factorial moment method offers a high signal-to-noise ratio, outperforming known techniques.
• These methods provide valuable alternatives for optical signal analysis, particularly in challenging conditions.