Probability of measuring muons is a particular setup

In summary: I forgot the 1-p probability. The total number is given by the binomial (p + q)^n with [n=4] and [k=4] and it's the sum of the success cases: S_4= \begin{pmatrix} 4 \\ 4 \end{pmatrix} p^4 + \begin{pmatrix} 4 \\ 3 \end{pmatrix} p^3 q + \begin{pmatrix} 4 \\ 2 \end{pmatrix} p^2 q^2 + \begin{pmatrix} 4 \\ 1 \end{pmatrix} p q^3 + \begin{pmatrix
  • #1
ChrisVer
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Homework Statement



You want to measure the momentum of muons with the help of a proportional chamber, that is a chamber
that applies an electric field inside its cavity and produces a signal current when a charged particle passes
through it. The probability of generation such a signal for a single chamber is 97%. For a momentum
measurement you need to measure the position of a muon in at least three points inside the detector, i.e.
three proportional chambers provide a signal. What is the minimum number of chambers required to provide
a momentum measurement for at least 99% of muons that pass through your detector?

Homework Equations

The Attempt at a Solution



The probability of a signal of a muon per chamber is: [itex] p = 0.97 \times \frac{1}{3} = 0.323[/itex].
My problem however is that I don't know the number of the muons... Any feedback of what method I could use? I thought about using a Gaussian and integrating it from [itex]0.99N[/itex] to [itex]N[/itex] ([itex]N[/itex] is the total number of muons passing through and an unknown parameter).
 
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  • #2
ChrisVer said:
The probability of a signal of a muon per chamber is: [itex] p = 0.97 \times \frac{1}{3} = 0.323[/itex].
It is not. It is 97 % as given in the problem statement.

My problem however is that I don't know the number of the muons...
How would that matter? If you have a coin that shows head 50 % of the time, do you need the number of coin tosses to use that value of 50 %?

Any feedback of what method I could use? I thought about using a Gaussian and integrating it from [itex]0.99N[/itex] to [itex]N[/itex] ([itex]N[/itex] is the total number of muons passing through and an unknown parameter).
You are overthinking this.

What is the probability to detect a muon three times if you have three chambers (assuming muons pass through all of them)?
 
  • #3
mfb said:
It is not. It is 97 % as given in the problem statement.

Oops sorry, I was wrong.

mfb said:
What is the probability to detect a muon three times if you have three chambers (assuming muons pass through all of them)?

If I have 3 chambers the probability is [itex]p= (0.97)^3[/itex] and also that's the probability of a single signal. Now if I have to do it three times... I guess I can use the binomial [itex]B= \begin{pmatrix} n \\ k \end{pmatrix} p^n (1-p)^{n-k} [/itex] with [itex]n=3[/itex] but I don't understand what's the meaning of [itex]k[/itex] here.
In the coin toss example, [itex]k[/itex] stands for the number of successes in [itex]n[/itex] trials.
 
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  • #4
ChrisVer said:
If I have 3 chambers the probability is [itex]p= (0.97)^3[/itex] and also that's the probability of a single signal.
Let's call it "probability to get a momentum measurement" as signal is used for single chambers in the problem statement.
Right. 0.97^3 < 0.99 so three chambers are not sufficient.

What is the probability to detect a muon three or four times if you have four chambers (assuming muons pass through all of them)?
The decimal number could be interesting here.
 
  • #5
It's that probability times the probability to get the right number of 3 signals out of 4 chambers?
 
  • #6
No. You try 4 times, with 0.97 success probability each time. What is the probability to succeed 3 or 4 times?
 
  • #7
[itex]0.97^3[/itex] or [itex]0.97^4[/itex]...

My conceptual problem comes when I add more chambers though... Because with four chambers I have the possible outcomes:
x : no signal ... o : signal in each chamber:

x x x x - fail
x x x o +3 permutations of o = fail
x x o o + 4 permutations of o = fail
x o o o + 3 permutations of x = success
o o o o = sucessThe appearence of each o is 97% probable... Looking at this scheme then the probability would be:
[itex] p^4 + 4 p^3[/itex] ? (this doesn't look right)

I think I'm trying to build up that:
[itex] \begin{pmatrix} 4 \\ 4 \end{pmatrix} p^4 + \begin{pmatrix} 4 \\ 3 \end{pmatrix} p^3 [/itex]
But I'm missing the [itex]q=1-p[/itex] probability in this.
 
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  • #8
ChrisVer said:
[itex]0.97^3[/itex] or [itex]0.97^4[/itex]...

My conceptual problem comes when I add more chambers though... Because with four chambers I have the possible outcomes:
x : no signal ... o : signal in each chamber:

x x x x - fail
x x x o +3 permutations of o = fail
x x o o + 4 permutations of o = fail
x o o o + 3 permutations of x = success
o o o o = sucessThe appearence of each o is 97% probable...
ChrisVer said:
[itex]0.97^3[/itex] or [itex]0.97^4[/itex]...

My conceptual problem comes when I add more chambers though... Because with four chambers I have the possible outcomes:
x : no signal ... o : signal in each chamber:

x x x x - fail
x x x o +3 permutations of o = fail
x x o o + 4 permutations of o = fail
x o o o + 3 permutations of x = success
o o o o = sucessThe appearence of each o is 97% probable... Looking at this scheme then the probability would be:
[itex] p^4 + 4 p^3[/itex] ? (this doesn't look right)

I think I'm trying to build up that:
[itex] \begin{pmatrix} 4 \\ 4 \end{pmatrix} p^4 + \begin{pmatrix} 4 \\ 3 \end{pmatrix} p^3 [/itex]
But I'm missing the [itex]q=1-p[/itex] probability in this.

Right, because you copied down the ##B##-formula incorrectly. Go back and read your post #3 again, putting in ##n = 4## and ##k = 3## plus ##k = 4##.
 
  • #9
My problem then is why didn't 1-p appear? Where did I lose it in the logic?
 
  • #10
You just forgot to add it? It was present in the original formula.
 
  • #11
Yes it was...
So for 4 chambers I obtain:
[itex] 0.97^4 + 4 \times 0.97^4 \times (0.03) =0.991..[/itex]
I think I got the idea of the problem: "need the k>=3 success in n trials probability to be > 99%"...
 
  • #12
ChrisVer said:
My problem then is why didn't 1-p appear? Where did I lose it in the logic?

As I said: go back and read your own post #3 again. Really do it, and carefully this time.
 
  • #13
Ray Vickson said:
As I said: go back and read your own post #3 again. Really do it, and carefully this time.

No it's OK... In each row I didn't count the probability (when it appeared) that the muon wouldn't interact, and that's why I was losing the (1-p) factors...:wink:

Eg for this: o o - o , I would have p*p*(1-p)*p ...
 
  • #14
Well the solution would be:

[itex] 0.99 \le P = \sum_{k=3}^n \begin{pmatrix} n \\ k \end{pmatrix} p^k (1-p)^{n-k} = 1 - \sum_{k=0}^2 \begin{pmatrix} n \\ k \end{pmatrix} p^k (1-p)^{n-k} [/itex]

Where I would have to solve for ##x## (and ##p=0.97##):

[itex] (1-p)^x + p (1-p)^{x-1} x +\frac{x(x-1)}{2} p^2 (1-p)^{x-2} \le 0.01[/itex]

Wolfram solves this with [itex] x \in [0.00202302, 0.936647][/itex] (which actually doesn't make sense since the number of chambers must be an integer... and [itex]x\ge 3.77 ... [/itex] whose right next integer is 4 (verifying the result of 0.991... I got above)
 
  • #15
ChrisVer said:
Well the solution would be:

[itex] 0.99 \le P = \sum_{k=3}^n \begin{pmatrix} n \\ k \end{pmatrix} p^k (1-p)^{n-k} = 1 - \sum_{k=0}^2 \begin{pmatrix} n \\ k \end{pmatrix} p^k (1-p)^{n-k} [/itex]

Where I would have to solve for ##x## (and ##p=0.97##):

[itex] (1-p)^x + p (1-p)^{x-1} x +\frac{x(x-1)}{2} p^2 (1-p)^{x-2} \le 0.01[/itex]

Wolfram solves this with [itex] x \in [0.00202302, 0.936647][/itex] (which actually doesn't make sense since the number of chambers must be an integer... and [itex]x\ge 3.77 ... [/itex] whose right next integer is 4 (verifying the result of 0.991... I got above)

For your given ##p## the equation ##P_n \equiv (1-p)^n + p(1-p)^{n-1}\,n + \frac{1}{2} p^2 (1-p)^{n-1} \,n(n-1) = 0.01## has three solutions for ##n \geq 0##, namely, ##n \doteq 0.002023##, ##n \doteq.93616## and ##n \doteq 3.77439##. Wolfram has found the two smallest and has taken the interval between the two. Algebraically, that is correct, but probabilistically it is invalid. If there is a way in Wolfram to tell it to restrict n to ##n \geq 1## then it should find the other root, and all ##n## values greater than that root will satisfy the inequality (because of the shape of the graph of ##P_n## vs. ##n##.

In Maple, the command 'fsolve(Pn = 0.01, n=1..10)' finds the largest root; here Pn is the formula above, with p = 0.97 and q = 0.03 in it.
 
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Related to Probability of measuring muons is a particular setup

1. What is the probability of measuring muons in a particular setup?

The probability of measuring muons in a particular setup is dependent on several factors such as the energy and intensity of the muon beam, the detection efficiency of the setup, and the cross-section of the particles interacting with the detector.

2. How is the probability of measuring muons calculated?

The probability of measuring muons in a particular setup can be calculated by using the Poisson distribution, which takes into account the average number of muons expected to be detected and the probability of detecting a muon in a single trial.

3. What is the difference between the probability of measuring muons and the detection efficiency?

The probability of measuring muons refers to the likelihood of detecting a muon in a specific setup, while the detection efficiency is the percentage of muons that are actually detected out of all the muons that pass through the setup.

4. Can the probability of measuring muons be increased?

The probability of measuring muons can be increased by adjusting the setup parameters, such as increasing the intensity of the muon beam or improving the detection efficiency of the setup. However, the probability cannot be increased beyond the limits set by the laws of physics.

5. How important is the probability of measuring muons in experimental research?

The probability of measuring muons is a crucial factor in experimental research as it helps determine the significance and validity of the results. A higher probability of measuring muons means a higher likelihood of obtaining accurate and reliable data, which is essential for drawing conclusions and making scientific advancements.

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