How Does an Extra Factor of i Affect Quantum Probability Calculations?

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Homework Help Overview

The discussion revolves around quantum probability calculations, specifically focusing on the implications of an extra factor of i in the context of eigenstates and probabilities. Participants are analyzing the eigenvectors of a matrix A and their relation to a Hamiltonian, while exploring how these factors affect calculated probabilities.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the calculation of eigenvectors and their corresponding eigenvalues, questioning how an additional factor of i influences probability values. They explore the relationship between the Hamiltonian and the matrix A, and how to apply the time evolution formula without having the eigenstates of the Hamiltonian explicitly provided.

Discussion Status

Some participants have provided calculations and expressed uncertainty about the impact of the factor of i on probabilities. Others have pointed out the importance of relative phases in quantum states and how they affect the overall state representation. The discussion is ongoing, with various interpretations and calculations being shared.

Contextual Notes

Participants are working under the constraints of a homework assignment, which may limit the information available regarding the Hamiltonian and its eigenstates. There is also a noted confusion regarding the applicability of certain formulas to the problem at hand.

davon806
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Homework Statement


b.jpg

I am not sure about (c) and (d). Firstly, I calculated the eigenvector of A :
|v_1> = ( |2 > - |1> )/ √(2) ,eigenvalue -2
|v_2> = ( |2> + |1>) / √(2) , eigenvalue 2

For (c), basically it follows from part (b) where the probability of a_1 is given by the formula | <v_1 | ψ > |^2 , and similarly for a_2 ( using v_2)

However, I don't see any reason that an extra factor of i will change the value of those probabilities ? ( I've calculated a_1 and a_2 which are both 1/2, in (b) )

For(d), I would like to use the formula ψ(t) = e^(-iEt/h) ψ(0). However, the eigenstates of the Hamiltonian was not provided. Given the fact that we only have |1> , |2> , |v_1> and |v_2> : How can I use this formula?

Homework Equations


In the general case, the Hamiltonian of the system can be written as a 2 × 2 matrix, where the elements of the matrix are given by: H_ij = < i | H | j > . So for example, <2 | A | 1 > = A_21 = 2. Actually A is not the Hamiltonian so I am not even sure whether it is applicable to part (a). Nevertheless I use this in (a). If I was wrong please correct me !

The Attempt at a Solution


Incorporated in question
 
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davon806 said:

Homework Statement


Firstly, I calculated the eigenvector of A :
|v_1> = ( |2 > - |1> )/ √(2) ,eigenvalue -2
|v_2> = ( |2> + |1>) / √(2) , eigenvalue 2
OK

For (c), basically it follows from part (b) where the probability of a_1 is given by the formula | <v_1 | ψ > |^2 , and similarly for a_2 ( using v_2) However, I don't see any reason that an extra factor of i will change the value of those probabilities ? ( I've calculated a_1 and a_2 which are both 1/2, in (b) )
The factor of ##i## does make a difference. Did you try calculating the probabilities for this case?

For(d), I would like to use the formula ψ(t) = e^(-iEt/h) ψ(0). However, the eigenstates of the Hamiltonian was not provided.
Actually, the eigenstates of H are essentially given. Note that the form of the matrix given for H is for the original basis {|1>, |2>}. What do you get for H|1>?
Actually A is not the Hamiltonian so I am not even sure whether it is applicable to part (a). Nevertheless I use this in (a). If I was wrong please correct me !
You are OK here.
 
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TSny said:
OK

The factor of ##i## does make a difference. Did you try calculating the probabilities for this case?

Actually, the eigenstates of H are essentially given. Note that the form of the matrix given for H is for the original basis {|1>, |2>}. What do you get for H|1>?
You are OK here.

Hi TSny ,

For (b), firstly I rewrite | ψ > = (1/2√2) ( |v_2> - |v_1> + i√3 |v_1> + i√3 |v_2>)
then I calculated P_a1 = | < v_1 | Ψ > | ^2 = (1/8) | -1 + √3 i |^2 = (1/8) *4 = 1/2 .

Hence we can calculate Φ in a similar way : | Φ > = (1/2√2) ( |v_2> - |v_1> + √3 |v_1> + √3 |v_2>) , so
new P_a1 = | < v_1 | Φ > | ^2 = (1/8) (-1 + √3 )^2 = (1/8) *(2+2√3 ) = (1+√3 )/ 4 > old P_a1?

What is the physical reason behind this? (As asked in (c))

For(d), write |1> = (x y) . H |1> = (E1 0 E2 0) ( x y) = (E1x E2y) ≠ λ|1> ?
 
davon806 said:
For (b), firstly I rewrite | ψ > = (1/2√2) ( |v_2> - |v_1> + i√3 |v_1> + i√3 |v_2>)
then I calculated P_a1 = | < v_1 | Ψ > | ^2 = (1/8) | -1 + √3 i |^2 = (1/8) *4 = 1/2 .
OK

Hence we can calculate Φ in a similar way : | Φ > = (1/2√2) ( |v_2> - |v_1> + √3 |v_1> + √3 |v_2>) , so
new P_a1 = | < v_1 | Φ > | ^2 = (1/8) (-1 + √3 )^2 = (1/8) *(2+2√3 ) = (1+√3 )/ 4 > old P_a1?
OK, except you didn't quite calculate (-1 + √3 )^2 correctly.

What is the physical reason behind this? (As asked in (c))
I don't think I can give you a decent physical reason. But it's important to understand that when you expand a state in terms of basis vectors, the relative phases of the coefficients of the expansion are very important. Changing the relative phase changes the state. So, the state (1/√2)( |1> + |2> ) is a different state than (1/√2)( |1> + i |2> ), even though the magnitudes of the coefficients are the same in each state.

For example, if |1> represents the spin state of a spin 1/2 particle where the spin is definitely "up along the z-direction" and if |2> represents the state of the particle where the spin is definitely "down along the z-direction", then (1/√2)( |1> + |2> ) is the state where the spin is definitely along the +x direction while (1/√2)( |1> + i |2> ) is the state where the spin is definitely along the +y direction. So, the presence of the i makes a big difference.

For(d),
write |1> = (x y) . H |1> = (E1 0 E2 0) ( x y) = (E1x E2y) ≠ λ|1> ?
You are working with matrices that are written with respect to the basis vectors |1> and |2>. So, the column vector that represents |1> would be (1 0)T.
 
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del
 
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