Classifying light by photo statistics - poissonian, sub, super poissonian?

In summary, the counting statistics for starlight and a discharge lamp are expected to be super-poissonian, while for laser light it depends on the type of laser and the intensity of the beam.
  • #1
jeebs
325
4
I've got three types of light:
- star light
- light from a discharge lamp
- light from a laser emitted high above threshold
and I need to decide on which type of counting statistics are expected for the detection of each source: poissonian, super poissonian or sub-poissonian. However, I'm unsure about how to do this.

The definitions of the counting statistics are:
[tex] \Delta n > \sqrt{\bar{n}} - superpoissonian[/tex][tex] \Delta n = \sqrt{\bar{n}} - poissonian [/tex][tex] \Delta n < \sqrt{\bar{n}} - sub-poissonian[/tex]where the variance is on the left hand side, and the root of the average count is on the right hand side.

So, with star light, we've got light of more than one wavelength, and fluctuating intensity. I'm guessing that sub-possonian can immediately be ruled out. That leaves poissonian and super poissonian, but without actual numbers I can't do calculations using the above equations, so I'm a bit lost as to classify this. I'm leaning towards superpoissonian because it just seems like a very random source of light, but I'm really not certain.

The same things apply to the discharge lamp - I've read in a book that it's apparently super-poissonian, but again I'm not sure where to draw the line between poissonian and superpoissonian.

As for the laser light, we've got light of a single wavelength, emitted as a coherent beam. However, I'm thinking that sub-poissonian light has to be emitted at a constant intensity down to very short timescales, so wouldn't this depend on the type of laser used?
ie. am I right in thinking that a gas laser will have emission at fairly random times compared to, say, a semiconductor laser diode?

How do I classify these things?

PS. exam tomorrow, so I'm grateful for fast replies.
 
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  • #2
For starlight, it is likely to be super-poissonian as the intensity of the light fluctuates and there is more than one wavelength.For the discharge lamp, it is likely to be super-poissonian, as the light emitted is chaotic and not constant. For the laser, it depends on the type of laser used and the intensity of the beam. If the beam is very strong and the laser is operating above threshold, then it is likely to be super-poissonian. If the beam is weaker, or the laser is operating below threshold, then it is likely to be poissonian or sub-poissonian.
 

1. What is the definition of "poissonian" in the context of classifying light?

In the context of classifying light, "poissonian" refers to a statistical distribution of photons where each photon has an equal and independent probability of being detected at any given time.

2. How is light classified as "sub-poissonian"?

Light is classified as "sub-poissonian" when the number of photons detected is less than the expected number based on a poissonian distribution. This indicates that the photons are arriving at a lower rate than expected, possibly due to coherence or correlations between them.

3. What does it mean for light to be classified as "super-poissonian"?

"Super-poissonian" light refers to a statistical distribution of photons where the number of photons detected is greater than the expected number based on a poissonian distribution. This suggests that the photons are arriving at a higher rate than expected, possibly due to amplification or photon bunching.

4. How can we determine if light is poissonian, sub-poissonian, or super-poissonian?

To determine the classification of light, we can analyze the statistical distribution of photon counts over a period of time. If the distribution follows a poissonian pattern, the light can be classified as poissonian. If the distribution is narrower than a poissonian distribution, it is sub-poissonian, and if it is wider, it is super-poissonian.

5. What are the practical applications of classifying light by photo statistics?

Classifying light by photo statistics has various practical applications, including in fields such as telecommunications, quantum optics, and astronomical observations. It can also provide valuable insights into the properties of light and its interactions with matter.

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