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Diff — Eigenvalues and eigenvectors

Revision #1177 → #1817 · back to history

modifiedEquivalence of matrix and linear-transformation definitions7ce8580ec1d3
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note`LinearMap.spectrum_toMatrix` and `Matrix.spectrum_toLin` show the spectra agree under `toMatrix`/`toLin`.`LinearMap.spectrum_toMatrix` shows the spectra agree under `toMatrix`/`toLin`.
modifiedCharacteristic equation via determinant1aa582c83f5d
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noteEigenvalues are exactly the roots of the characteristic polynomial; equivalently `det(λI − A) = 0` via `eval_charpoly`.Eigenvalues are exactly the roots of the characteristic polynomial, equivalently `det(λI − A) = 0`.
modifiedFactoring the characteristic polynomial2258deabe732
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note`charpoly_natDegree` gives degree `n`; `Polynomial.card_roots_le_degree` bounds the roots.`charpoly_natDegree` gives degree `n`; combined with degree bounds on root counts, this matches the at-most-n claim.
modifiedComplex conjugate eigenvalue pairsf140fe9cec43
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mathlib.declPolynomial.isRoot_conj_of_isRootPolynomial.aeval_conj
mathlib.moduleMathlib.Analysis.Complex.Polynomial.BasicMathlib.Analysis.RCLike.Lemmas
noteGeneral fact about conjugate roots of real polynomials exists; not specialized to eigenvalues.`Polynomial.aeval_conj` shows `aeval (conj z) p = conj (aeval z p)` for real polynomials, implying conjugate pairs of non-real roots; not specialized to eigenvalues.
modifiedAlgebraic multiplicityfb7068b487d5
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mathlib.moduleMathlib.Algebra.Polynomial.RingDivisionMathlib.Algebra.Polynomial.Div
modifiedEigenspace of a matrix8f6b1cbef8f3
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note`eigenspace` applied to `Matrix.toLin'`; e.g. `iSup_eigenspace_toLin'_diagonal_eq_top`.`eigenspace` applied to `Matrix.toLin'`; e.g. `Matrix.iSup_eigenspace_toLin'_diagonal_eq_top`.
modifiedGeometric multiplicity846f11b9e70e
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mathlib.declModule.finrankModule.End.eigenspace
modifiedEigenbasis from total geometric multiplicity2c2bf355d5af
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noteFor semisimple endomorphisms over an algebraically closed field the eigenspaces span; combined with `eigenspaces_iSupIndep` they form a direct sum decomposition.For semisimple endomorphisms the eigenspaces span; combined with `eigenspaces_iSupIndep` they form a direct sum decomposition.
modifiedDeterminant equals product of eigenvalues95583262f462
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noteAlso `Matrix.det_eq_prod_roots_charpoly` for algebraically closed fields.Determinant is the product of charpoly roots when it splits.
modifiedDefiniteness gives sign of eigenvalues133eeb37e571
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note`PosSemidef.eigenvalues_nonneg` and `IsHermitian.posSemidef_iff_eigenvalues_nonneg` cover the positive case.`PosSemidef.eigenvalues_nonneg` covers the positive case.
modifiedUnitary matrix eigenvalues have absolute value one06ff04121a14
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mathlib.declUnitary.spectrum_subset_circlespectrum.norm_eq_one_of_unitary
note`Unitary.spectrum_subset_circle` and `spectrum.norm_eq_one_of_unitary` give |λ|=1 for unitary elements in C*-algebras, applying to unitary matrices.`spectrum.norm_eq_one_of_unitary` and `Unitary.spectrum_subset_circle` give |λ|=1 for unitary elements in C*-algebras, applying to unitary matrices.
modifiedDefective matrix and Jordan normal form52f3757be9c0
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mathlib.moduleMathlib.LinearAlgebra.JordanChevalleyMathlib.LinearAlgebra.Eigenspace.Basic
noteGeneralized eigenspaces and `JordanChevalley` decomposition exist; full Jordan normal form and `defective` predicate are not formalized.Generalized eigenspaces exist and Jordan–Chevalley decomposition is formalized; full Jordan normal form and `defective` predicate are not.
modifiedDiagonal matrix example65e3b5a11aaf
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mathlib.declMatrix.spectrum_diagonalspectrum_diagonal
note`spectrum_diagonal` shows `spectrum R (diagonal d) = Set.range d`.`spectrum_diagonal` shows `spectrum R (Matrix.diagonal d) = Set.range d`.
modifiedGeometric multiplicity (general)481dd30ed58c
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mathlib.declModule.finrankModule.End.eigenspace
modifiedAbel–Ruffini limits explicit eigenvalue formulas1ea850c3750b
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mathlib.declnot_solvable_by_radisSolvable_gal_of_irreducible
noteAbel–Ruffini is formalized for polynomials; not specialized to eigenvalues.Abel–Ruffini (`isSolvable_gal_of_irreducible`) is formalized for polynomials; not specialized to eigenvalues.
addedEigenvectors of different eigenvalues are linearly independent6944762ed5e9
addedAt most n distinct eigenvalues in dimension n34e9947f1947
addedEigenvalues of the inverse are reciprocals00ffc4baf231
addedReal symmetric matrices have real eigenvalues6f56152a60d5