Why choose traceless matrices as basis?

In summary, physicists use traceless hermitian matrices as the basis for SU(2) due to the consequences of unitarity and determinant one. Skew-Hermitian is a result of unitarity, while traceless is a result of determinant one. These properties are important in the study of SU(2) and its representations. More information on the computation for the determinant and some remarks on SU(2) can be found in the provided links.
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phoenix95
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While writing down the basis for SU(2), physicists often choose traceless hermitian matrices as such, often the Pauli matrices. Why is this? In particular why traceless, and why hermitian?
 
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Skew-Hermitian is a consequence of unitary, traceless of determinant one:
$$
U^\dagger U = I \Longrightarrow D(U^\dagger U) = U^\dagger \cdot I + I \cdot U = U^\dagger + U = D(I) = 0\\
\det U = 1 \Longrightarrow D(\det U) = \operatorname{tr}U = D(1) = 0
$$
Here's the computation for the determinant in detail:
https://www.physicsforums.com/insights/pantheon-derivatives-part-iv/
and here are some remarks on ##\operatorname{SU}(2)##:
https://www.physicsforums.com/insights/representations-precision-important/
https://www.physicsforums.com/insights/journey-manifold-su2-part-ii/
 
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Related to Why choose traceless matrices as basis?

1. Why are traceless matrices commonly used as a basis for scientific models?

Traceless matrices, also known as Hermitian matrices, have the property that their trace (the sum of the elements on the main diagonal) is equal to zero. This makes them useful as a basis because they simplify calculations and allow for more elegant and compact representations of equations.

2. How do traceless matrices make calculations easier?

The traceless property of these matrices means that certain operations, such as taking the determinant or finding the eigenvalues, become simpler. Additionally, they have a more regular structure compared to general matrices, making it easier to identify patterns and relationships between different elements.

3. Are there any specific applications where traceless matrices are particularly useful?

Yes, traceless matrices are commonly used in quantum mechanics, where they represent operators that correspond to physical observables. They also have applications in fields such as signal processing, control theory, and statistical mechanics.

4. Can traceless matrices be used for any type of data?

No, the use of traceless matrices is primarily limited to data that can be represented in a matrix form. This includes data from fields such as physics, engineering, and economics, but may not be applicable to other types of data.

5. Are there any disadvantages to using traceless matrices as a basis?

One potential drawback of using traceless matrices is that they can be more complex to understand and work with compared to standard matrices. They also have specific rules and properties that must be followed in order to maintain their traceless nature, which may require additional effort and attention during calculations.

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