How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
A non-negative operator is equivalently self-adjoint with nonnegative eigenvalues, a positive semidefinite matrix in an orthonormal basis, or an operator of the form S^*S
Statement
Let be a finite-dimensional real or complex inner product space and let be linear. The following are equivalent:
- is non-negative.
- is self-adjoint and every eigenvalue of is a nonnegative real number.
- Some orthonormal basis makes the matrix of diagonal with nonnegative real diagonal entries.
- There exists a linear map such that .
Facts & Assumptions
Given: A finite-dimensional real or complex inner product space and a linear endomorphism .
A self-adjoint operator on a finite-dimensional real inner product space has an orthonormal eigenbasis (Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis).
A normal operator on a finite-dimensional complex inner product space has an orthonormal eigenbasis (Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely).
Every nonnegative real number has a unique nonnegative square root (Square roots exist: a unique with ; the positives are ).
Proof
Assume is non-negative. Then is self-adjoint by Non-negative and positive operators. If is real, [L1] gives an orthonormal eigenbasis; if is complex, the identity yields , so [L2] gives an orthonormal eigenbasis. For any eigenvector with , the equality and non-negativity give , and self-adjointness makes real. Thus claim 1 implies claim 2.
Assume claim 3. If the diagonal entries are , then [L3] gives square roots ; the diagonal operator with diagonal entries satisfies . Thus claim 3 implies claim 4.
Assume claim 2, so is self-adjoint. If is real, [L1] gives an orthonormal eigenbasis. If is complex, implies , so [L2] gives an orthonormal eigenbasis. In either case the matrix of in this basis is diagonal, and its diagonal entries are nonnegative real numbers by claim 2. Thus claim 2 implies claim 3.
Assume claim 4, so . Then for every one has , and for all one has . Hence is self-adjoint and non-negative. Thus claim 4 implies claim 1.
Depends on
Non-negative and positive operators
Over the reals, non-negative and positive operators correspond exactly to positive semidefinite and positive definite symmetric forms
Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely
Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis
Square roots exist: a unique with ; the positives are