The Time Independence of Normalization

In summary, on page 13 of Griffith's "Introduction to Quantum Mechanics 2nd ed", David discusses the proof for why a normalized pair of quantum state vectors will remain normalized at a later time. This is achieved by showing that the normalization is not time-dependent, even when the wave function is a linear combination of eigenfunctions. While it is legitimate to demonstrate this using the unitary operator exp(-iHt), Griffiths does not introduce this concept until later in the book. Instead, he shows that the integral of the Hamiltonian over the wave function is real, which implies that the normalization remains constant in time.
  • #1
kq6up
368
13
On page 13 of Griffith's "Introduction to Quantum Mechanics 2nd ed" David goes into a long (relatively speaking) proof of why a normalized pair of quantum state vectors will not at some time later become "un-normalized". It seems like just putting the Psi's in a braket the e^(-it) "time dependence" term would just cancel out -- showing that normalization is not time dependent. Could anyone take a shot at why this is not the case -- other than the fact he has not developed braket notation or shown that the time dependence a separate exponent factor? Maybe I just answered my own question :D Is there anything wrong with showing it this way?

Thanks,
Chris Maness
 
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  • #2
The general wave function is built of a linear combination of the eigenfunctions. When you do this, the exponential time-dependent phases do not cancel out. When he shows that the normalization remains constant in time, he shows it for a general wave function that is a solution of just the Schrodinger equation, and not the eigenvalue equation in general.
 
  • #4
  • #5
Jorriss said:
While this is true, Griffiths does not introduce unitary operators, the time evolution operator, etc I believe and he certainly does not do it by page 13.

Well, it's enough to know that

[itex]\int \psi^* H \psi dx[/itex]

is real. That's because Schrodinger's equation implies that:

[itex]\dfrac{d}{dt} \int \psi^* \psi dx = \dfrac{2}{\hbar} Im(\int \psi^* H \psi dx)[/itex]

where [itex]Im[/itex] means the imaginary part.
 

Related to The Time Independence of Normalization

What is normalization and why is it important?

Normalization is the process of organizing data in a database in a way that reduces redundancy and dependency. It ensures data consistency and improves data integrity, making it easier to retrieve and manipulate data. Normalization is important because it helps to avoid data duplication and inconsistencies, which can lead to errors and data corruption.

What is the purpose of the time independence of normalization?

The time independence of normalization ensures that the database structure is not affected by changes in the data over time. This means that even if new data is added or old data is modified, the database structure will remain intact and the data will remain consistent and reliable.

How does the time independence of normalization impact data analysis?

The time independence of normalization makes it easier to analyze data over time. This is because the database structure remains consistent, making it easier to compare data from different time periods. It also ensures that the data is accurate and reliable, which is essential for making informed decisions based on the analysis.

Can the time independence of normalization be violated?

Yes, the time independence of normalization can be violated if the database is not properly designed or if data is added or modified without following the rules of normalization. This can lead to data inconsistencies and errors, making it difficult to retrieve accurate information from the database.

What are the potential consequences of violating the time independence of normalization?

If the time independence of normalization is violated, it can lead to data corruption, errors, and inconsistencies. This can make it difficult to retrieve accurate information from the database, which can have serious consequences for decision making and data analysis. It can also lead to a loss of data integrity and make it difficult to maintain the database over time.

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