Operators change form for density matrix equations?

In summary, operators in density matrix equations are mathematical representations of physical properties or observables in a quantum mechanical system. They change form in these equations to simplify them and play a crucial role in calculating the expectation values of observables, which can then be compared to experimental results. They affect the density matrix by producing a new one, and can be simplified through mathematical techniques to gain a better understanding of the system's behavior.
  • #1
Agrippa
78
10
Imagine applying an operator to a wave-function:


[itex] \psi_t(x_1, x_2, ..., x_n) \rightarrow \frac{L_n(x)\psi_t(x_1, x_2, ..., x_n)}{||\psi_t(x_1, x_2, ..., x_n)||} [/itex]


Where ## \psi _t(x_1, x_2, ..., x_n) ## is initial system state vector, denominator is normalization factor, and Ln(x) is a linear operator equal to:


[itex] L_n(x) = \frac{1}{(\pi r^2_c)^{3/4}}e^{-(q_n - x)^2 / 2r^2_c} [/itex]


So, position wave-function is multiplied by a Gaussian (with width ##r_c##; ##q_n## is position operator for nth particle, and x is random spatial variable where Gaussian multiplication is centred).

When this exact same equation is presented in a master equation for density matrix we get:


[itex] \frac{d}{dt}\rho(t) = -\frac{i}{\hbar}[H, \rho(t)] - T[\rho(t)] [/itex]


where H is standard quantum Hamiltonian and T[] represents effect of the operator. In position representation:


[itex] <x|T[\rho(t)]|y> = [1 - e^{-(x - y)^2 / 4r^2_c}]<x|T[\rho(t)]|y> [/itex]


Clearly, form of Gaussian function has changed, but why? Standard presentations (e.g. pp.30-33) never explain the change.
Is there anyone out there who knows the math well enough to be able to explain why all the changes occur e.g. why do we replace the initial fraction with "1 - "? And why replace ##2r^2_c## with ##4r^2_c##?


What would go wrong if we simply replaced ##1 - e^{-(x - y)^2 / 4r^2_c}## with ##\frac{1}{(\pi r^2_c)^{3/4}}e^{-(q_n - x)^2 / 2r^2_c}## ?
 
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  • #2


it is important to understand the underlying mathematical principles and concepts behind any equation or formula. In this case, it is important to understand the concept of the density matrix and its relation to the wave-function.

The density matrix is a mathematical tool used in quantum mechanics to describe the state of a quantum system. It contains information about the probabilities of different states that the system can be in. The density matrix is defined as the outer product of the wave-function with itself:

\rho (t) = |\psi_t><\psi_t|

This means that the density matrix is a function of the wave-function, and any operator acting on the wave-function will also affect the density matrix.

In the given equation, the operator L_n(x) is acting on the wave-function, and therefore, it will also affect the density matrix. The reason for the changes in the Gaussian function is because the operator L_n(x) is a position operator, and as we know, position and momentum are conjugate variables in quantum mechanics. This means that when one is measured with high precision, the other becomes uncertain.

In the given equation, the Gaussian function is modified to take into account this uncertainty. The factor of "1 - " is a normalization factor, which ensures that the density matrix remains traceless (i.e. the sum of the diagonal elements of the matrix is equal to 1). This factor is necessary because the operator L_n(x) introduces additional uncertainty in the position of the particle, and hence, the density matrix needs to be adjusted accordingly.

Similarly, the factor of 4 in the denominator of the exponential term is also a result of the uncertainty in position. The uncertainty in position is related to the width of the Gaussian function, which is given by 2r_c. This width is then squared to account for the uncertainty in both the position of the particle and the random spatial variable x.

If we simply replaced the modified Gaussian function with the original one, it would not accurately represent the uncertainty in position introduced by the operator L_n(x). This could lead to incorrect predictions or results when solving the master equation.

In conclusion, the changes in the Gaussian function in the master equation are necessary to accurately represent the uncertainty in position introduced by the operator acting on the wave-function. It is important to understand the mathematical reasoning behind these changes in order to correctly use and interpret the master equation in quantum mechanics.
 

FAQ: Operators change form for density matrix equations?

1. What are operators in density matrix equations?

Operators in density matrix equations are mathematical representations of physical properties or observables in a quantum mechanical system. They act on the density matrix to produce a new density matrix, which represents the state of the system after the operator has been applied.

2. Why do operators change form in density matrix equations?

Operators change form in density matrix equations because they are written in a different basis than the original density matrix. This is done to simplify the equations and make them easier to manipulate. The relationship between the original operator and the transformed operator is known as a transformation or change of basis.

3. What is the significance of operators in density matrix equations?

Operators play a crucial role in density matrix equations because they allow us to calculate the expectation values of observables in a quantum system. These expectation values can then be compared to experimental results to verify the accuracy of the theory.

4. How do operators affect the density matrix?

Operators affect the density matrix by changing its form and producing a new density matrix that represents the state of the system after the operator has been applied. This new density matrix can then be used to calculate the expectation values of observables in the system.

5. Can operators in density matrix equations be simplified?

Yes, operators in density matrix equations can be simplified through various mathematical techniques such as diagonalization and unitary transformations. These simplifications can make the equations more manageable and help us gain a better understanding of the system's behavior.

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