How does number density relate to probabilty density

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In summary, the conversation discusses the relationship between number density and probability density in particle physics. The Lorentz invariant phase space factor is defined as the probability density of a free relativistic particle, while the Lorentz invariant number density is calculated using the momentum and probability density of the particle. The question also explores the possibility of the probability density being a distribution function and how it relates to the wave function in non-relativistic quantum theory.
  • #1
thegirl
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I was just wondering how number density relates to probability density in general, within particle physics?

Thank you!
 
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  • #2
This question is way too vague.
 
  • #3
Khashishi said:
This question is way too vague.
I'm currently studying particle physics and when talking about the lorentz invariant phase space factor in the notes it starts off with the probability density of a free relativistic particle being p=2E|N|^2 and then goes on to say the lorentz invariant number density becomes dn=d^3r/(2pi)^3p where r is the momentum of the particle and p the probability density. I was just wondering why the probability density is included within the number density formula and how it related to the number density. The number density formula was derived from a single particle in a quantised box.
 
  • #4
are you sure p is probability density? I thought it was a distribution function ... giving the occupation within a volume in the 6D phase space (3 momenta and 3 positions). Such that the integral you have written [itex]N = \int n \diff^3x = \int \frac{\diff^3 p}{(2 \pi)^3} f(p) [/itex]
1. you already wrote how they are related...
 
  • #5
ChrisVer said:
are you sure p is probability density? I thought it was a distribution function ... giving the occupation within a volume in the 6D phase space (3 momenta and 3 positions). Such that the integral you have written [itex]N = \int n \diff^3x = \int \frac{\diff^3 p}{(2 \pi)^3} f(p) [/itex]
1. you already wrote how they are related...
p = <v|v> where v represents a wavefunction, can that also be a distribution function?
 
  • #7
A wave function (applicable in non-relativistic quantum theory or at very low-energy relativistic cases, where the non-relativistic approximation is not too bad) is always of the structure ##\langle a|\psi \rangle##, where ##|a \rangle## denotes a orthonormal system of (generalized) common eigenvectors of a complete set of compatible observables and ##|\psi \rangle## is a representing normalized vector of a pure state. An expression like ##\langle v|v \rangle## is just a scalar product of a vector with itself, i.e., its norm squared and cannot be a wave function, because it's just a single number.
 

1. What is number density?

Number density refers to the number of particles, molecules, or objects per unit volume in a given space. It is typically denoted by the symbol 'n' and is expressed in units of particles per cubic meter (m-3).

2. What is probability density?

Probability density is a measure of the likelihood of a continuous random variable taking on a specific value. It is represented by the symbol 'p' and is expressed in units of probability per unit of the variable (e.g. probability per meter or probability per second).

3. How are number density and probability density related?

Number density and probability density are related through the probability distribution function, which describes the probability of a particle being found in a specific location or having a specific value. The number density at a given point is proportional to the probability density at that point.

4. Can number density be used to calculate probability density?

No, number density and probability density are different types of measurements and cannot be directly converted into one another. However, they are related through the probability distribution function and can be used together to understand the behavior of a system.

5. Why is understanding the relationship between number density and probability density important in science?

The relationship between number density and probability density is essential in understanding the behavior of particles and objects in a given space. It is particularly important in fields such as physics, chemistry, and materials science, where the behavior of particles at the microscopic level can have significant implications on the overall properties and behavior of a system. By understanding this relationship, scientists can make more accurate predictions and better understand the underlying mechanisms at work.

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