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Astronomy & space · Advanced university

Poisson photon-count signal-to-noise

Assume independent source and background Poisson noise and a background expectation known without extra uncertainty.

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Method and conditions

Assume independent source and background Poisson noise and a background expectation known without extra uncertainty.

SNR ≈ S/sqrt(S+B)

Worked examples

A photon-count model expects S=1000 source counts and B=220 background counts. Use SNR=S/sqrt(S+B), neglecting other noise. Find SNR. Round the final result to 4 decimal places if needed.

Poisson variances add: total variance is 1220; divide source signal by its square root.

28.6299

A photon-count model expects S=930 source counts and B=115 background counts. Use SNR=S/sqrt(S+B), neglecting other noise. Find SNR. Round the final result to 4 decimal places if needed.

Poisson variances add: total variance is 1045; divide source signal by its square root.

28.769

Try it

  1. A photon-count model expects S=540 source counts and B=485 background counts. Use SNR=S/sqrt(S+B), neglecting other noise. Find SNR. Round the final result to 4 decimal places if needed.

  2. A photon-count model expects S=770 source counts and B=410 background counts. Use SNR=S/sqrt(S+B), neglecting other noise. Find SNR. Round the final result to 4 decimal places if needed.

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Answers and marking notes
  1. 16.8668

    Poisson variances add: total variance is 1025; divide source signal by its square root.

  2. 22.4156

    Poisson variances add: total variance is 1180; divide source signal by its square root.

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