QuantumInfo.ForMathlib.HermitianMat.Proj
63 declarations
Orthogonal projector onto a submodule
#projectorGiven a submodule of the Euclidean space (where is or ), the projector is the Hermitian matrix representing the orthogonal projection onto . It satisfies , acts as the identity on vectors , and maps any vector in the orthogonal complement to zero.
For any submodule of the Euclidean space , the sum of the orthogonal projector onto and the orthogonal projector onto its orthogonal complement is equal to the identity matrix . In other words, .
Trace of a Projector is its Rank
#trace_projectorLet be a submodule of the Euclidean space , where is an `RCLike` field (such as or ). Let be the Hermitian matrix representing the orthogonal projection onto . Then the trace of is equal to the rank of the submodule over , viewed as a real number:
Orthogonal projector onto the support of
#supportProjGiven a Hermitian matrix acting on the Euclidean space (where is or ), `supportProj` is the Hermitian matrix representing the orthogonal projection onto the support of . Here, the support of is defined as the submodule spanned by the eigenvectors corresponding to the non-zero eigenvalues of , which is equivalent to the range of . In other words, this is the orthogonal projector onto .
Orthogonal projector onto the kernel of a Hermitian matrix
#kerProjLet be a Hermitian matrix in , where is either or . The kernel projector of , denoted as , is the Hermitian matrix representing the orthogonal projection onto the kernel (null space) of . Specifically, it is defined as the projector onto the submodule .
Let be a Hermitian matrix in . Let (denoted by `kerProj`) be the orthogonal projector onto the kernel of , and let (denoted by `supportProj`) be the orthogonal projector onto the support of (the subspace spanned by eigenvectors with non-zero eigenvalues). Their sum is equal to the identity matrix:
The kernel projector of a non-singular Hermitian matrix is zero
#kerProj_of_nonSingularLet be a Hermitian matrix. If is non-singular, then its kernel projector is the zero matrix. Here, the kernel projector denotes the Hermitian matrix representing the orthogonal projection onto the kernel (null space) of .
The support projector of a non-singular Hermitian matrix is .
#supportProj_of_nonSingularLet be a Hermitian matrix in . If is non-singular, then its support projector (the projector onto the subspace spanned by eigenvectors with non-zero eigenvalues) is equal to the identity matrix .
The orthogonal projector equals the sum of outer products of an orthonormal basis of
#projector_eq_sum_rankOneLet be a submodule of the Euclidean space (where is or ) and let be an orthonormal basis for . The matrix representation of the orthogonal projector onto the submodule is equal to the sum over of the outer products of the basis vectors, i.e., where is the inclusion of the basis vector into , and denotes its conjugate transpose.
The support projector of equals the sum of rank-one projections onto eigenvectors with non-zero eigenvalues
#projector_support_eq_sumLet be a Hermitian matrix of size over (where is or ). The matrix representing the orthogonal projector onto the support of (the subspace spanned by eigenvectors with non-zero eigenvalues) is given by the sum: where are the eigenvalues of , are the corresponding orthonormal eigenvectors, denotes the conjugate transpose of , and the coefficient is if and if .
Let be a Hermitian matrix. The orthogonal projector onto the support of , denoted , is equal to the result of the continuous functional calculus applied to with the indicator function that is if and otherwise. That is, where .
Projector onto the non-negative eigenspace of
#projLEGiven two Hermitian matrices and , the function (denoted as ) returns the Hermitian matrix representing the orthogonal projector onto the subspace spanned by the eigenvectors of corresponding to non-negative eigenvalues. Specifically, it is defined by applying the continuous functional calculus to the matrix with the indicator function . This operator is the unique maximum projector (satisfying ) such that holds in the Loewner order.
Projector onto the positive eigenspace of (denoted )
#projLTGiven two Hermitian matrices and in the space , the projector onto the positive eigenspace of is defined as the result of applying the continuous functional calculus to with the indicator function . This operator projects onto the subspace spanned by the eigenvectors of corresponding to strictly positive eigenvalues.
The projector onto the non-negative eigenspace
#term{_≥ₚ_}For two Hermitian matrices and , the notation represents the Hermitian projector onto the subspace spanned by the eigenvectors of corresponding to non-negative eigenvalues.
Notation for the projector onto the nonnegative eigenspace of
#term{_≤ₚ_}For any two Hermitian matrices and (of type `HermitianMat`), the notation represents the orthogonal projector onto the nonnegative eigenspace of the operator .
Projector onto the positive eigenspace of
#term{_>ₚ_}For two Hermitian matrices and , the notation (or ) represents the projector onto the positive eigenspace of the Hermitian matrix . This is equivalent to `projLT B A`.
Notation for the projector onto the positive eigenspace of
#term{_<ₚ_}This is a scoped notation used to represent the projector onto the positive eigenspace of the difference of two Hermitian matrices and . Specifically, the notation denotes the operator `projLT A B`, which is the Hermitian matrix projecting onto the subspace spanned by the eigenvectors of corresponding to strictly positive eigenvalues.
Definition of the Projector via Functional Calculus
#projLE_defFor any two Hermitian matrices and , the projector onto the nonnegative eigenspace of , denoted as , is defined as the result of applying the continuous functional calculus to the matrix with the indicator function .
Definition of the Projector via Functional Calculus
#projLT_defFor any two Hermitian matrices and , the projector onto the positive eigenspace of is defined as the continuous functional calculus of with the indicator function .
The Nonnegative Eigenspace Projector is Idempotent
#projLE_sqLet and be Hermitian matrices of size over a field . Let denote the projector onto the nonnegative eigenspace of the difference , defined via the continuous functional calculus as . Then, this operator is idempotent, satisfying .
The projector is idempotent
#projLT_sqLet and be Hermitian matrices of size over a field . Let denote the projector onto the positive eigenspace of the Hermitian matrix . Then, is idempotent, specifically .
equals the functional calculus of by the indicator of
#projLE_zero_cfcLet be a Hermitian matrix in . The projector onto the nonnegative eigenspace of , denoted by , is equal to the result of applying the continuous functional calculus to with the indicator function .
Let be a Hermitian matrix. The projector onto the positive eigenspace of , denoted by , is equal to the result of applying the continuous functional calculus to with the indicator function .
as a Continuous Functional Calculus of
#projLE_zero_cfc'For a Hermitian matrix , the projector onto the non-positive eigenspace, denoted by , is equal to the continuous functional calculus of applied to the indicator function of the interval . That is, , where if and otherwise.
Representation of via functional calculus on with
#projLT_zero_cfc'Let be a Hermitian matrix. The projector onto the positive eigenspace of (denoted by ) is equal to the result of the continuous functional calculus applied to with the indicator function of the negative real numbers .
The projector is positive semidefinite
#projLE_nonnegLet and be Hermitian matrices of size over a field . Let denote the projector onto the nonnegative eigenspace of the difference , defined via the continuous functional calculus as the indicator function of the interval . Then is a positive semidefinite matrix, i.e., in the Loewner partial order.
The Projector is Positive Semidefinite
#projLT_nonnegLet and be Hermitian matrices in . Let denote the projector onto the positive eigenspace of the difference . Then is a positive semidefinite matrix, i.e., in the Loewner partial order.
The projector is bounded above by the identity matrix in the Loewner order.
#projLE_le_oneLet and be Hermitian matrices in . Let (denoted in Lean as `projLE A B`) be the Hermitian projector onto the nonnegative eigenspace of the difference . Then , where is the identity matrix and denotes the Loewner partial order.
The product of the projector and is non-negative
#projLE_mul_nonnegLet be a natural number and be a field. For any two Hermitian matrices , let denote the projector onto the nonnegative eigenspace of . Then the product of the matrix and the matrix is a positive semidefinite matrix, i.e., .
Compatibility of the projector with the inequality
#projLE_mul_leLet and be Hermitian matrices of size over a field . Let be the projector onto the nonnegative eigenspace of the matrix . Then, the product of and is less than or equal to the product of and in terms of their underlying matrices, i.e., .
Let and be Hermitian matrices in . Let denote the projector onto the positive eigenspace of , and let denote the projector onto the non-negative eigenspace of . Then the sum of these two projectors is the identity matrix , i.e., .
for Hermitian matrices
#conj_lt_add_conj_leLet be a Hermitian matrix in . Let denote the projector onto the negative eigenspace of , and let denote the projector onto the nonnegative eigenspace of . Then the sum of the conjugations of these projectors by satisfies: where represents the action of the matrix on a projector via conjugation, and the notation and refers to the projectors onto the strictly negative and nonnegative parts of the spectrum of , respectively.
For any Hermitian matrix , the projector onto the support of (the subspace spanned by eigenvectors with non-zero eigenvalues), denoted by , is equal to the sum of the projector onto the negative eigenspace of (denoted by ) and the projector onto the positive eigenspace of (denoted by ).
The positive part of a Hermitian matrix \( A^+ \)
#instPosPartFor a Hermitian matrix \( A \in \text{HermitianMat}_n(\mathbb{k}) \), its positive part \( A^+ \) is defined as the application of the continuous functional calculus to \( A \) with the function \( f(x) = \max(x, 0) \). This corresponds to the projection of the matrix onto the subspace spanned by its positive eigenvalues.
The negative part of a Hermitian matrix \( A^- \)
#instNegPartFor a Hermitian matrix \( A \) in the space of \( n \times n \) Hermitian matrices over a field \( \mathbb{k} \), the negative part \( A^- \) is defined using the continuous functional calculus (CFC) as \( A.cfc(f) \), where \( f(x) = \max(-x, 0) \). This corresponds to the projection of the matrix onto the subspace spanned by its negative eigenvalues.
Let be a Hermitian matrix (represented as `HermitianMat n 𝕜`). The positive part of , denoted as , is equal to the result of applying the continuous functional calculus to with the function (written as ).
equals for
#negPart_eq_cfc_minLet be a Hermitian matrix. The negative part of , denoted , is equal to the result of applying the continuous functional calculus to with the function .
The positive part equals for via CFC
#posPart_eq_cfc_iteLet be a Hermitian matrix. The positive part of , denoted , is equal to the result of applying the continuous functional calculus to with the function .
Negative part of a Hermitian matrix equals for
#negPart_eq_cfc_iteLet be a Hermitian matrix. The negative part of , denoted , is equal to the result of applying the continuous functional calculus to with the function .
Agreement of Positive Part for `HermitianMat` and `Matrix`:
#posPart_eq_posPart_toMatLet be a Hermitian matrix. The positive part of as defined on the type of Hermitian matrices, denoted , is equal to the positive part of its underlying matrix representation, denoted . This theorem establishes that the specific `PosPart` instance for `HermitianMat` is consistent with the standard `PosPart` instance on general matrices.
Agreement of Negative Part for `HermitianMat` and `Matrix`:
#negPart_eq_negPart_toMatLet be a Hermitian matrix. The negative part of as defined on the type of Hermitian matrices, denoted , is equal to the negative part of its underlying matrix representation, denoted . This theorem establishes that the specific `NegPart` instance for `HermitianMat` is consistent with the standard `NegPart` instance on general matrices.
for Hermitian matrices
#posPart_eq_cfc_ltLet be a Hermitian matrix. The positive part of , denoted , is equal to the result of applying the continuous functional calculus to with the function . This implies that the positive part can be equivalently defined using either a strict inequality () or a non-strict inequality () within the functional calculus.
Negative part of a Hermitian matrix equals for
#negPart_eq_cfc_ltLet be a Hermitian matrix. The negative part of , denoted , is equal to the result of applying the continuous functional calculus to with the function .
Decomposition of a Hermitian matrix into positive and negative parts
#posPart_add_negPartFor any Hermitian matrix , the difference between its positive part and its negative part is equal to the matrix itself, i.e., . Here, is the projection of onto its nonnegative eigenvalues, and is the projection of onto its nonnegative eigenvalues (corresponding to the absolute value of the negative eigenvalues of ).
Let be a Hermitian matrix in the space . If is positive semidefinite (denoted as in the Loewner partial order), then its positive part is equal to .
The positive part of a Hermitian matrix is non-negative ()
#posPart_nonnegLet be a Hermitian matrix in . Let denote the positive part of , which is the result of applying the functional calculus to with the function . Then is a positive semidefinite matrix, i.e., .
The negative part of a Hermitian matrix is non-negative ()
#negPart_nonnegLet be a Hermitian matrix in . The negative part of , denoted , is a positive semidefinite matrix, i.e., , where the inequality refers to the Loewner partial order.
for Hermitian matrices
#posPart_leLet be a Hermitian matrix in . Let denote the positive part of , which is the restriction of to its nonnegative eigenvalues (formally defined via the continuous functional calculus as the function applied to ). Then it holds that with respect to the Loewner partial order, meaning that is a positive semidefinite matrix.
Orthogonality of the Positive and Negative Parts of a Hermitian Matrix ()
#posPart_mul_negPartLet be a Hermitian matrix. Let and denote the positive and negative parts of , respectively, defined via the continuous functional calculus. Then the product of their underlying matrices is zero, i.e., .
for Hermitian matrices
#projLE_inner_nonnegLet and be Hermitian matrices with entries in an `RCLike` field . Let denote the projector onto the nonnegative eigenspace of the Hermitian matrix . Then the inner product of this projector and the difference is non-negative, i.e., , where the inner product is defined as the trace of the product of the matrices.
Let and be Hermitian matrices of the same dimension. Let denote the projector onto the nonnegative eigenspace of . Then the inner product of the projector and is less than or equal to the inner product of the projector and : where the inner product is defined as .
The inner product is non-negative
#inner_projLE_nonnegLet and be Hermitian matrices over an -clike field. Let denote the projector onto the nonnegative eigenspace of . The inner product of and , defined as , is non-negative.
The Inner Product of with is bounded by its Inner Product with
#inner_projLE_leLet and be Hermitian matrices over a field (such as or ). Let denote the projector onto the nonnegative eigenspace of the Hermitian matrix . Then the trace of the product of the projector with is less than or equal to the trace of its product with , i.e., where denotes the Frobenius inner product defined by .
The Positive Part Operator on Hermitian Matrices is Continuous
#posPart_ContinuousThe positive part operator , which maps a Hermitian matrix to its projection onto its positive eigenvalues (formally defined via the continuous functional calculus as where ), is a continuous function.
The negative part operator is continuous.
#negPart_ContinuousLet be the space of Hermitian matrices over the complex numbers. The negative part operator, denoted by , is continuous. Here, the negative part is defined via the continuous functional calculus as where .
Let and be Hermitian matrices. Let be the orthogonal projector onto the non-negative eigenspace of , and let be the orthogonal projector onto the positive eigenspace of . Then the identity matrix minus the projector onto the non-negative eigenspace of equals the projector onto the positive eigenspace of , i.e., .
for Hermitian matrices and
#projLT_mul_nonnegLet and be Hermitian matrices of size over a field . Let denote the projector onto the positive eigenspace of , defined via continuous functional calculus as . Then the product of this projector and the difference matrix is a positive semi-definite matrix, i.e., .
Let and be Hermitian matrices of size over a field . Let (denoted as `projLT A B`) be the Hermitian matrix that projects onto the positive eigenspace of . Then, the product of the matrix of this projector and is less than or equal to the product of the matrix of this projector and : where the inequality denotes the Loewner order (the difference of the matrices is positive semi-definite).
for Hermitian matrix
#inner_negPart_nonposFor any Hermitian matrix , the inner product between and its negative part is non-positive, i.e., . Here, the inner product is defined as and the negative part is the restriction of the matrix to its non-positive eigenvalues.
The inner product of the positive and negative parts of a Hermitian matrix is zero:
#posPart_inner_negPart_zeroLet be a Hermitian matrix. Let denote the positive part of and denote the negative part of . The inner product is equal to . Here, the inner product of two Hermitian matrices and is defined as .
Let be a Hermitian matrix and denote its negative part, which corresponds to the restriction of the matrix to its non-positive eigenvalues. Let be the Frobenius inner product on the space of Hermitian matrices. Then, the inner product of and its negative part is zero, , if and only if is positive semi-definite ().
Let be a Hermitian matrix. Its negative part is denoted by , and the inner product is defined as . Then the inner product between and its negative part is strictly negative, , if and only if is not positive semi-definite (i.e., ).
Let be a Hermitian matrix of size over a field (where is or ). Then is positive semi-definite () if and only if for every positive semi-definite Hermitian matrix , their Frobenius inner product is non-negative, i.e., . The inner product is defined as .
