Matrix Elements: LHO & Dirac Notation

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SUMMARY

In the discussion on matrix elements and Dirac notation, it is established that in the matrix element notation ##(a)_{i,j}##, the index ##j## consistently represents the column. This is crucial for maintaining clarity across different operators. The relationship between linear operators and matrices is also highlighted, emphasizing the importance of consistent definitions to avoid confusion in matrix equations. The use of Dirac notation, where kets are treated as columns and bras as rows, further clarifies this convention.

PREREQUISITES
  • Understanding of Dirac notation in quantum mechanics
  • Familiarity with linear operators and their matrix representations
  • Knowledge of matrix transposition and its implications
  • Basic concepts of quantum mechanics, specifically the linear harmonic oscillator
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  • Research the relationship between linear operators and matrices in quantum mechanics
  • Study the properties of matrix transposition and its effects on equations
  • Explore the implications of Dirac notation on quantum state representations
  • Review the FAQ post in the Math FAQ subforum regarding linear operators
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Quantum physicists, mathematicians, and students studying linear algebra and quantum mechanics will benefit from this discussion, particularly those interested in the application of Dirac notation and matrix representations of operators.

LagrangeEuler
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For matrix element ##(a)_{i,j}##
##j## represent column. Is this always the case? For example in case of linear harmonic oscillator ##(\hat{a}^+)_{1,0}=\langle 1|\hat{a}^+|0 \rangle =1##. It is easier to me to see this in Dirac notation, because kets are columns and bras are rows.
 
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I think that is why the comma is put in.
 
LagrangeEuler said:
For matrix element ##(a)_{i,j}##, ##j## represent column. Is this always the case?
Yes. It would be very confusing to use a different convention for different operators.

Suppose that x and y are vectors and that A is an operator. We want the matrix equation that corresponds to y=Ax to look like [y]=[A][x]. The transpose of this equation is [x]T[A]T=[y]T. So if we would define the matrix [A] (which represents the operator A) as the transpose of the matrix we'd normally use, the matrix equation that corresponds to y=Ax would be [y]T=[x]T[A]. I suppose we could change the definitions of [x] and [y] as well. Then we'd end up with [y]=[x][A], which is slightly prettier, but still has the factors on the right in the "wrong" order.

You might want to take a look at the FAQ post about the relationship between linear operators and matrices in the Math FAQ subforum of the General Math forum.
 

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