Schmidt Decomposition as Linear Algebra
The Schmidt decomposition is the singular value decomposition of a bipartite coefficient matrix, translated back into tensor-product notation.
This page focuses on the finite-dimensional linear algebra. The physics-facing theorem, reduced states, entanglement criterion, and infinite-dimensional cautions live in Schmidt Decomposition.
Helpful background. tensor products for product bases and coefficient arrays; singular value decomposition for orthonormal singular vectors and nonnegative singular values.
Coefficient Matrix of a Bipartite Vector
Section titled “Coefficient Matrix of a Bipartite Vector”Let and be finite-dimensional Hilbert spaces with orthonormal bases
Every vector in the tensor product has an expansion
The numbers form a matrix . Normalization of the vector is the Frobenius-norm condition
This coefficient matrix depends on the chosen product bases. Its singular values do not depend on local unitary changes of basis.
SVD Derivation
Section titled “SVD Derivation”Take the singular value decomposition of :
If the positive singular values are , then
Define vectors in the two Hilbert spaces by
Because the columns of and are orthonormal, the vectors and are orthonormal sets. Substituting the SVD into the product-basis expansion gives
This is the Schmidt decomposition. The Schmidt coefficients are the singular values of .
Why a Complex Conjugate Appears
Section titled “Why a Complex Conjugate Appears”The factor in comes from the in the matrix SVD. It is a convention consequence of writing a bipartite vector with kets on both sides rather than with one side already dualized.
The important invariant statement is simple: local basis changes multiply by unitary matrices on the left and right, so the singular values are unchanged.
For example, an active local unitary
changes the coefficient matrix as
Both and are unitary, so the singular values of are invariant.
Schmidt Rank and Matrix Rank
Section titled “Schmidt Rank and Matrix Rank”The Schmidt rank is the number of nonzero Schmidt coefficients:
Since the are the positive singular values of ,
Thus a bipartite pure state is product exactly when its coefficient matrix has rank one. The physics-facing rank invariant is developed in Schmidt Rank.
Reduced States from the Matrix
Section titled “Reduced States from the Matrix”The reduced state on subsystem has matrix elements
In matrix notation,
With the coefficient convention used here, tracing out gives
Here means entrywise conjugation. The transpose matters for matrix entries and eigenvectors, although and have the same eigenvalues.
Using gives
so the nonzero eigenvalues of are
The same nonzero eigenvalues occur for . This is the linear-algebra reason the squared Schmidt coefficients are the probabilities used in Entanglement Entropy.
Product States as Rank-One Matrices
Section titled “Product States as Rank-One Matrices”If
with
then
The coefficient matrix is an outer product:
It has rank one when both factors are nonzero. Conversely, if has rank one, it can be written as an outer product, and the bipartite vector factors. This is the linear-algebra core of the pure-state product criterion.
Example: Product State Hidden by the Basis
Section titled “Example: Product State Hidden by the Basis”Consider
In the computational product basis,
Then
The singular values are and . Therefore the Schmidt rank is one. Indeed,
The original expansion had two product-basis terms, but the state was still a product vector.
Example: Bell State
Section titled “Example: Bell State”For
the coefficient matrix is
The singular values are
Therefore the Schmidt rank is two, and
The two equal singular values give one bit of bipartite entanglement entropy.
Degeneracy and Basis Freedom
Section titled “Degeneracy and Basis Freedom”The Schmidt coefficients are unique up to ordering, because singular values are unique. The Schmidt vectors need not be unique.
If a singular value is nondegenerate, the two corresponding Schmidt kets are fixed up to opposite phase choices:
If several singular values are equal, there is a larger unitary freedom inside the degenerate Schmidt subspace. The state is unchanged, but the displayed Schmidt basis is not unique.
Common Mistakes
Section titled “Common Mistakes”- Treating the coefficient matrix as basis-independent. The matrix changes under local basis changes; its singular values do not.
- Forgetting the complex conjugate in the second Schmidt basis when translating into kets.
- Counting product-basis terms instead of computing matrix rank or singular values.
- Confusing Schmidt coefficients with reduced-state eigenvalues .
- Applying the bipartite coefficient-matrix derivation to multipartite states without qualification.
- Applying pure-state Schmidt language directly to mixed density operators.
- Treating degenerate Schmidt vectors as unique.
References
Section titled “References”- G. H. Golub and C. F. Van Loan, Matrix Computations, 4th ed., Johns Hopkins University Press, 2013.
- R. A. Horn and C. R. Johnson, Matrix Analysis, 2nd ed., Cambridge University Press, 2013.
- M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information, Cambridge University Press, 2010.
- E. Schmidt, “Zur Theorie der linearen und nichtlinearen Integralgleichungen. I. Teil,” Mathematische Annalen 63, 433-476, 1907.
- J. Watrous, The Theory of Quantum Information, Cambridge University Press, 2018.
Exercises
Section titled “Exercises”- Write the coefficient matrix for
and find its Schmidt coefficients.
Solution
The coefficient matrix is
It is already diagonal with nonnegative entries, so the Schmidt coefficients are
- Show from the coefficient matrix that
is a product state.
Solution
The coefficient matrix is
It has rank one, so the Schmidt rank is one. Explicitly,
- For
compute and the Schmidt coefficients.
Solution
Compute
The eigenvalues of are and , so the Schmidt coefficients are
- Let . Find and , and check the sign of its upper-right entry.
Solution
The coefficient matrix and reduced state are
This agrees with for . Using without the transpose would give the conjugate state. The Schmidt coefficients alone would not detect that mistake because both states have the same spectrum.