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QuantumInfo.ForMathlib.HermitianMat.Rpow

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definition

Real power of a Hermitian matrix ArA^r via functional calculus

#rpow

Given a Hermitian matrix AHermitianMatd(K)A \in \text{HermitianMat}_d(\mathbb{K}) and a real number rRr \in \mathbb{R}, the matrix power ArA^r is defined via the continuous functional calculus (CFC). Specifically, if AA is diagonalized as A=UΛUA = U \Lambda U^\dagger, then Ar=UΛrUA^r = U \Lambda^r U^\dagger, where the power function is applied elementwise to the diagonal entries of Λ\Lambda using the real power function xxrx \mapsto x^r. Note that if an eigenvalue is 00 and r<0r < 0, the result follows the convention 0r=00^r = 0.

instance

Real exponentiation ArA^r for Hermitian matrices AHermd(k)A \in \text{Herm}_d(\mathbb{k})

#instRPow

For a finite-dimensional Hilbert space kd\mathbb{k}^d, let Hermd(k)\text{Herm}_d(\mathbb{k}) denote the set of d×dd \times d Hermitian matrices over the field k{R,C}\mathbb{k} \in \{\mathbb{R}, \mathbb{C}\}. This definition provides an instance of the real power operator \text{^} : \text{Herm}_d(\mathbb{k}) \times \mathbb{R} \to \text{Herm}_d(\mathbb{k}). For a Hermitian matrix AA and a real exponent rr, ArA^r is defined via the functional calculus (specifically `HermitianMat.rpow`), such that if AA has spectral decomposition iλiPi\sum_i \lambda_i P_i, then Ar=iλirPiA^r = \sum_i \lambda_i^r P_i.

theorem

Real Power Commutes with Unitary Conjugation of Hermitian Matrices

#rpow_conj_unitary

Let AA be a Hermitian matrix of dimension dd over the field K\mathbb{K}, and let UU be a unitary matrix (an element of the unitary group dd). For any real exponent rRr \in \mathbb{R}, the rr-th power of the conjugated matrix UAUU A U^* is equal to the conjugation of the rr-th power of AA by UU. That is, (UAU)r=U(Ar)U(U A U^*)^r = U (A^r) U^*.

theorem

Ar=rpow(A,r)A^r = \text{rpow}(A, r)

#pow_eq_rpow

For a Hermitian matrix AA and a real number rr, the power operation ArA^r is equivalent to the matrix power function `rpow` applied to AA and rr.

theorem

Ar=cfc(xxr,A)A^r = \operatorname{cfc}(x \mapsto x^r, A)

#rpow_eq_cfc

Let AA be a Hermitian matrix and rr be a real number. Then the matrix power ArA^r is equal to the result of applying the continuous functional calculus to AA with the real power function xxrx \mapsto x^r.

theorem

(diag(f))r=diag(fr)(\text{diag}(f))^r = \text{diag}(f^r) for Hermitian matrices

#diagonal_pow

Let f:dRf: d \to \mathbb{R} be a function and M=diag(f)M = \text{diag}(f) be the diagonal matrix whose entries are given by f(i)f(i) for idi \in d. For any real exponent rRr \in \mathbb{R}, the rr-th power of the diagonal matrix is the diagonal matrix of the rr-th powers of its entries, i.e., (diag(f))r=diag(if(i)r)(\text{diag}(f))^r = \text{diag}(i \mapsto f(i)^r).

theorem

The map AArA \mapsto A^r is continuous on Hermitian matrices for r0r \geq 0

#rpow_const_continuous

Let Cd×d\mathbb{C}^{d \times d} be the space of d×dd \times d complex matrices, and let HermitianMat(d,C)\text{HermitianMat}(d, \mathbb{C}) denote the subspace of Hermitian matrices. For any real number r0r \geq 0, the function that maps a Hermitian matrix AA to its matrix power ArA^r, defined via the continuous functional calculus, is continuous.

theorem

The function rArr \mapsto A^r is continuous for non-singular AA

#const_rpow_continuous

Let AA be a non-singular Hermitian matrix in Cd×d\mathbb{C}^{d \times d}. Then the map rArr \mapsto A^r is continuous for all rRr \in \mathbb{R}, where ArA^r denotes the matrix power with real exponent.

theorem

The map xAxx \mapsto A^x is continuous for x>0x > 0 for Hermitian AA

#continuousOn_rpow_pos

Let AA be a Hermitian matrix in Cd×d\mathbb{C}^{d \times d}. Then the map xAxx \mapsto A^x is continuous on the interval (0,)(0, \infty), where AxA^x denotes the matrix power of AA with real exponent xx.

theorem

The map xAxx \mapsto A^x is continuous for x<0x < 0

#continuousOn_rpow_neg

Let AA be a Hermitian matrix in Cd×d\mathbb{C}^{d \times d}. The function xAxx \mapsto A^x, which maps a real number xx to the xx-th power of the matrix AA, is continuous on the interval (,0)(-\infty, 0).

theorem

A1=AA^1 = A for Hermitian matrices

#rpow_one

For any Hermitian matrix AA, raising AA to the power of the real number 11 results in the matrix AA itself, i.e., A1=AA^1 = A.

theorem

A1/2=cfc(xx1/2)(A)A^{1/2} = \text{cfc}(x \mapsto x^{1/2})(A) for Hermitian matrices

#sqrt_eq_cfc_rpow_half

For any Hermitian matrix AHermitianMatd(k)A \in \text{HermitianMat}_d(\mathbb{k}), the square root of AA (defined via the continuous functional calculus of x\sqrt{x}) is equal to the continuous functional calculus of the function f(x)=x1/2f(x) = x^{1/2} applied to AA.

theorem

1r=11^r = 1 for Hermitian matrices

#one_rpow

Let II denote the identity matrix in the space of Hermitian matrices of dimension dd over the field k\mathbf{k}. For any real number rRr \in \mathbb{R}, the rr-th power of the identity matrix is equal to the identity matrix. That is, Ir=I I^r = I where the power is defined via the continuous functional calculus for Hermitian matrices.

theorem

A0=IA^0 = I for Hermitian Matrices

#rpow_zero

For any Hermitian matrix AA, the real power of AA with exponent 00 is the identity matrix II. That is, A0=I A^0 = I where II denotes the identity matrix of the same dimension as AA.

theorem

Real Power of a Diagonal Matrix equals the Diagonal Matrix of Real Powers

#rpow_diagonal

Let dd be a finite index set and a:dRa: d \to \mathbb{R} be a function representing the diagonal entries of a square matrix. For any real exponent rRr \in \mathbb{R}, the rr-th power of the diagonal matrix with entries aia_i is equal to the diagonal matrix whose entries are the rr-th powers of the original entries. That is, (diag(a))r=diag(ar) (\text{diag}(a))^r = \text{diag}(a^r) where the ii-th diagonal entry of the resulting matrix is aira_i^r.

theorem

Real power commutes with matrix reindexing (ArA^r reindexed equals reindexed ArA^r)

#reindex_rpow

Let AA be a Hermitian matrix indexed by dd, and let e:dd2e: d \simeq d_2 be a bijection between index sets. For any real exponent rRr \in \mathbb{R}, the rr-th power of the matrix AA reindexed by ee is equal to the reindexing of the rr-th power of AA. That is, (Areindexed by e)r=(Ar)reindexed by e (A_{\text{reindexed by } e})^r = (A^r)_{\text{reindexed by } e} where the reindexing operation permutes the rows and columns of the matrix according to the equivalence ee.

theorem

Exponent Addition Law for Real Powers of Semidefinite Hermitian Matrices (Ap+q=ApAqA^{p+q} = A^p A^q)

#mat_rpow_add

Let AA be a semidefinite Hermitian matrix (A0A \ge 0). For any real numbers pp and qq satisfying p+q0p + q \neq 0, the (p+q)(p+q)-th power of AA is equal to the product of the pp-th power of AA and the qq-th power of AA. That is, Ap+q=ApAq A^{p+q} = A^p A^q provided that the sum of the exponents is non-zero.

theorem

Apq=(Ap)qA^{pq} = (A^p)^q for Positive Semidefinite Hermitian Matrices

#rpow_mul

Let AA be a Hermitian matrix such that 0A0 \le A (i.e., AA is positive semidefinite). For any real numbers pp and qq, the matrix powers satisfy the identity Apq=(Ap)qA^{p \cdot q} = (A^p)^q. Here, ArA^r denotes the power of a Hermitian matrix with a real exponent rr.

theorem

Conjugation of Matrix Powers (Ar)(Aq)(Ar)=Ar+2q(A^r)(A^q)(A^r) = A^{r+2q} for Hermitian A0A \ge 0

#conj_rpow

Let AA be a positive semidefinite Hermitian matrix (0A0 \le A). For any real numbers qq and rr such that q0q \neq 0 and r+2q0r + 2q \neq 0, the conjugation of AqA^q by ArA^r, defined as (Ar)(Aq)(Ar)(A^r) (A^q) (A^r)^*, is equal to Ar+2qA^{r + 2q}.

theorem

A1/2A1/2=AA^{1/2} \cdot A^{1/2} = A for A0A \ge 0

#pow_half_mul

Let AA be a positive semi-definite Hermitian matrix (denoted 0A0 \le A). Then the product of the matrix power A1/2A^{1/2} with itself is equal to AA, i.e., A1/2A1/2=AA^{1/2} \cdot A^{1/2} = A.

theorem

Real powers of positive definite matrices are positive definite

#rpow_pos

Let AA be a Hermitian matrix in Cd×d\mathbb{C}^{d \times d} (or Rd×d\mathbb{R}^{d \times d}). If AA is positive definite (denoted A>0A > 0), then for any real power pRp \in \mathbb{R}, the matrix power ApA^p is also positive definite, namely Ap>0A^p > 0.

theorem

Real powers of positive semi-definite matrices are positive semi-definite

#rpow_nonneg

Let AA be a Hermitian matrix such that A0A \ge 0 (i.e., AA is positive semi-definite). Then for any real power pRp \in \mathbb{R}, the matrix power ApA^p is also positive semi-definite, denoted as Ap0A^p \ge 0.

theorem

A1=A1A^{-1} = A^{-1} for positive definite Hermitian matrices

#inv_eq_rpow_neg_one

Let AA be a Hermitian matrix. If AA is positive definite (denoted as A>0A > 0), then its inverse matrix A1A^{-1} is equal to its real power with exponent 1-1, namely A1=AR1A^{-1} = A^{-1}_{\mathbb{R}}.

theorem

Conjugation of BB by B1/2B^{-1/2} equals II

#sandwich_self

Let BB be a positive definite Hermitian matrix. Then the conjugation of BB by the matrix B1/2B^{-1/2} results in the identity matrix, i.e., B1/2B(B1/2)=IB^{-1/2} B (B^{-1/2})^* = I.

theorem

(Ap)1=Ap(A^p)^{-1} = A^{-p} for Positive Definite Hermitian Matrices

#rpow_inv_eq_neg_rpow

Let AA be a Hermitian matrix in Kd×d\mathbb{K}^{d \times d} and let pp be a real number. If AA is positive definite (A>0A > 0), then the inverse of the pp-th power of AA is equal to AA raised to the power of p-p, i.e., (Ap)1=Ap(A^p)^{-1} = A^{-p}.

theorem

AB    B1/2AB1/2IA \le B \implies B^{-1/2} A B^{-1/2} \le I for positive definite BB

#sandwich_le_one

Let AA and BB be Hermitian matrices of dimension dd over a field k\mathbb{k}. If BB is a positive definite matrix and ABA \le B in the Loewner order (meaning BAB - A is positive semidefinite), then the "sandwich" operation of AA by B1/2B^{-1/2} satisfies B1/2AB1/2I B^{-1/2} A B^{-1/2} \le I where II is the identity matrix and B1/2B^{-1/2} denotes the real power of the Hermitian matrix with exponent 1/2-1/2.

theorem

ApAp=IA^{-p} A^p = I for Positive Definite Hermitian Matrix AA

#rpow_neg_mul_rpow_self

Let AA be a Hermitian matrix and assume that AA is positive definite. For any real number pp, the product of the matrix raised to the power p-p and the matrix raised to the power pp is the identity matrix, i.e., ApAp=IA^{-p} A^p = I.

theorem

ApA^p is Invertible for Positive Definite AA

#isUnit_rpow_toMat

Let AA be a Hermitian matrix and pp be a real number. If AA is positive definite, then the matrix power ApA^p is an invertible matrix.

theorem

Inverse of AA Sandwiched by B1/2B^{-1/2} equals A1A^{-1} Sandwiched by B1/2B^{1/2}

#sandwich_inv

Let AA and BB be Hermitian matrices. Suppose BB is positive definite. Then the inverse of the congruence transformation of AA by B1/2B^{-1/2} is equal to the congruence transformation of A1A^{-1} by B1/2B^{1/2}. That is, ((B1/2)A(B1/2))1=(B1/2)A1(B1/2) ((B^{-1/2})^* A (B^{-1/2}))^{-1} = (B^{1/2})^* A^{-1} (B^{1/2}) where MM^* denotes the conjugate transpose and XSXSX \mapsto S^* X S is the sandwich (congruence) operator.

theorem

For A0A \ge 0 and r0r \neq 0, ker(Ar)=ker(A)\ker(A^r) = \ker(A)

#ker_rpow_eq_of_nonneg

Let AA be a d×dd \times d Hermitian matrix over the complex numbers C\mathbb{C}. If AA is positive semi-definite (i.e., A0A \geq 0) and rr is a non-zero real number, then the kernel of the matrix power ArA^r is equal to the kernel of AA. In symbols, ker(Ar)=ker(A)\ker(A^r) = \ker(A).

theorem

For A0A \ge 0, ker(Ar)ker(A)\ker(A^r) \subseteq \ker(A)

#ker_rpow_le_of_nonneg

Let AA be a Hermitian matrix of dimension dd over the complex numbers C\mathbb{C}. If AA is positive semi-definite (i.e., A0A \ge 0), then the kernel of the matrix power ArA^r is a subspace of the kernel of AA, denoted as ker(Ar)ker(A)\ker(A^r) \subseteq \ker(A).

theorem

Congruence Transformation Distributes over Kronecker Product

#conj_kron

Let AA be a d×dd \times d matrix and BB be a d2×d2d_2 \times d_2 matrix over a field k\mathbb{k}. Let CC and DD be Hermitian matrices of dimensions dd and d2d_2 respectively. Then the congruence transformation of the Kronecker product CDC \otimes D by the Kronecker product ABA \otimes B is equal to the Kronecker product of the individual congruence transformations. That is, (AB)(CD)(AB)=(ACA)(BDB)(A \otimes B) (C \otimes D) (A \otimes B)^* = (A C A^*) \otimes (B D B^*) where conj MP=MPM\text{conj } M P = M P M^* denotes the congruence transformation of PP by MM, and k\otimes_k denotes the Kronecker product.

theorem

Real Power of Kronecker Product is the Kronecker Product of Real Powers (AB)r=ArBr(A \otimes B)^r = A^r \otimes B^r

#rpow_kron

Let AA and BB be complex Hermitian matrices of dimensions d×dd \times d and d2×d2d_2 \times d_2 respectively. If AA and BB are positive semi-definite (i.e., A0A \ge 0 and B0B \ge 0 in the Loewner order), then for any real number rr, the rr-th power of their Kronecker product is equal to the Kronecker product of their individual rr-th powers. That is, (AB)r=ArBr(A \otimes B)^r = A^r \otimes B^r where \otimes denotes the Kronecker product and MrM^r denotes the matrix power with a real exponent.

theorem

Continuity of rtrr \mapsto t^r in the uniform topology on compact sets

#continuousOn_rpow_uniform

Let KRK \subset \mathbb{R} be a compact set. Let I=(0,)I = (0, \infty) be the set of positive real numbers. The function that maps an exponent rIr \in I to the power function fr(t)=trf_r(t) = t^r is continuous on II with respect to the topology of uniform convergence on KK. Specifically, the map r(ttr)r \mapsto (t \mapsto t^r) is continuous from the subset (0,)(0, \infty) of the real numbers to the space of functions on KK endowed with the uniform norm.

theorem

Joint Continuity of Hermitian Matrix Power (A,p)Ap(A, p) \mapsto A^p for p>0p > 0

#continuousOn_rpow_joint_nonneg_pos

Let XX be a topological space and SXS \subseteq X a subset. Suppose A:XHd(C)A: X \to \mathcal{H}_d(\mathbb{C}) is a continuous mapping from SS into the space of d×dd \times d complex Hermitian matrices, and p:XRp: X \to \mathbb{R} is a continuous real-valued function on SS. If p(x)>0p(x) > 0 for all xSx \in S, then the mapping xA(x)p(x)x \mapsto A(x)^{p(x)} is continuous on SS, where ApA^p denotes the matrix power defined via the continuous functional calculus.

theorem

(A2)p/2=Ap(A^2)^{p/2} = A^p for Positive Semidefinite Hermitian Matrices

#cfc_sq_rpow_eq_cfc_rpow

Let AA be a Hermitian matrix of dimension dd over the complex numbers C\mathbb{C}, and assume that AA is positive semidefinite (0A0 \le A). For any real number p>0p > 0, the continuous functional calculus of A2A^2 applied to the function f(x)=xp/2f(x) = x^{p/2} is equal to the continuous functional calculus of AA applied to the function g(x)=xpg(x) = x^p. That is, (A2)p/2=Ap(A^2)^{p/2} = A^p.

theorem

Tr(Ap)=iλip\text{Tr}(A^p) = \sum_i \lambda_i^p for Hermitian matrices

#trace_rpow_eq_sum

For any complex Hermitian matrix AA of dimension dd and any real number pp, the trace of the pp-th power of AA is equal to the sum of the pp-th powers of its eigenvalues. Specifically, if λi\lambda_i denotes the ii-th eigenvalue of AA for i{1,,d}i \in \{1, \dots, d\}, then Tr(Ap)=i=1dλip.\text{Tr}(A^p) = \sum_{i=1}^d \lambda_i^p.

definition

Finite integral approximation rpowApprox(A,q,T)\text{rpowApprox}(A, q, T) for matrix power AqA^q

#rpowApprox

For a complex Hermitian matrix AHermd(C)A \in \text{Herm}_d(\mathbb{C}) and real numbers q,TRq, T \in \mathbb{R}, we define the finite integral approximation: rpowApprox(A,q,T)=0Ttq(11+tI(A+tI)1)dt \text{rpowApprox}(A, q, T) = \int_0^T t^q \left( \frac{1}{1+t} I - (A + t I)^{-1} \right) \, dt where II denotes the identity matrix. This expression serves as a truncated integral representation used to prove the operator monotonicity of the power function AAqA \mapsto A^q.

theorem

The approximation rpowApprox(,q,T)rpowApprox(\cdot, q, T) is operator monotone for A,B0A, B \succ 0 and T>0T > 0

#rpowApprox_mono

Let AA and BB be complex d×dd \times d Hermitian matrices. Suppose AA and BB are positive definite (denoted A0A \succ 0 and B0B \succ 0). If ABA \le B in the Loewner order (meaning BAB - A is positive semidefinite), then for any real number q0q \ge 0 and any real parameter T>0T > 0, the approximating operators satisfy rpowApprox(A,q,T)rpowApprox(B,q,T)rpowApprox(A, q, T) \le rpowApprox(B, q, T).

definition

Scalar function for the approximation of real matrix powers xqx^q

#scalarRpowApprox

Given real numbers qq, TT, and xx, this function is defined as the integral: f(q,T,x)=0Ttq(11+t1x+t)dtf(q, T, x) = \int_{0}^{T} t^q \left( \frac{1}{1+t} - \frac{1}{x+t} \right) dt This function serves as the scalar basis for the approximation of the real power AqA^q of a Hermitian matrix AA via the Continuous Functional Calculus (CFC).

theorem

Approximated Hermitian matrix power ATqA^q_T equals functional calculus of fq,Tf_{q,T} on AA

#rpowApprox_eq_cfc_scalar

Let AA be a positive definite Hermitian matrix of dimension dd over C\mathbb{C}. For any real numbers qq and TT such that q0q \ge 0 and T>0T > 0, the approximated matrix power ATqA^q_T (denoted by `rpowApprox A q T`) is equal to the result of applying the scalar function xfq,T(x)x \mapsto f_{q,T}(x) (denoted by `scalarRpowApprox q T`) to the matrix AA via the continuous functional calculus.

definition

The integral 0uq11+udu\int_0^\infty \frac{u^{q-1}}{1 + u} \, du

#rpowConst

For a real number qq, the function returns the value of the integral 0uq11+udu \int_0^\infty \frac{u^{q-1}}{1 + u} \, du as a real number. This constant appears in the integral representation of the power function xqx^q and is equal to πsin(πq)\frac{\pi}{\sin(\pi q)} for 0<q<10 < q < 1.

theorem

Integrability of uq1/(1+u)u^{q-1} / (1+u) on (0,)(0, \infty) for 0<q<10 < q < 1

#rpowConst_integrableOn

Let qq be a real number such that 0<q<10 < q < 1. Then the function f(u)=uq11+uf(u) = \frac{u^{q-1}}{1+u} is integrable on the interval (0,)(0, \infty).

theorem

Cq>0C_q > 0 for 0<q<10 < q < 1

#rpowConst_pos

Let qq be a real number such that 0<q<10 < q < 1. Then the constant CqC_q (defined as `rpowConst q`) is strictly positive.

theorem

Pointwise convergence of scalarRpowApprox\text{scalarRpowApprox} to Cq(xq1)C_q (x^q - 1) as TT \to \infty

#scalarRpowApprox_tendsto

For any real numbers xx, qq such that x>0x > 0, 0<q<10 < q < 1, the scalar function f(T)=scalarRpowApprox(q,T,x)f(T) = \text{scalarRpowApprox}(q, T, x) converges to Cq(xq1)C_q \cdot (x^q - 1) as TT \to \infty, where CqC_q denotes the constant rpowConst(q)\text{rpowConst}(q).

theorem

rpowApprox(A,q,T)\text{rpowApprox}(A, q, T) converges to Cq(AqI)C_q (A^q - I) as TT \to \infty

#tendsto_rpowApprox

Let AA be a positive definite Hermitian matrix of dimension dd over C\mathbb{C}. For any real number qq such that 0<q<10 < q < 1, the matrix-valued function TrpowApprox(A,q,T)T \mapsto \text{rpowApprox}(A, q, T) converges to Cq(AqI)C_q \cdot (A^q - I) as TT \to \infty in the topology of the normed space of Hermitian matrices, where CqC_q denotes the constant rpowConst(q)\text{rpowConst}(q) and II is the identity matrix.

theorem

Loewner-Heinz inequality for positive definite matrices: AB    AqBqA \le B \implies A^q \le B^q for 0<q10 < q \le 1

#rpow_le_rpow_of_posDef

Let AA and BB be complex Hermitian matrices of dimension dd. If AA is positive definite (A>0A > 0), AA is less than or equal to BB in the Loewner order (ABA \le B), and qq is a real number such that 0<q10 < q \le 1, then AqBqA^q \le B^q.

theorem

Löwner—Heinz Theorem: 0AB0<q1    AqBq0 \le A \le B \land 0 < q \le 1 \implies A^q \le B^q

#rpow_le_rpow_of_le

Let AA and BB be complex Hermitian matrices of dimension dd. If 0AB0 \le A \le B and 0<q10 < q \le 1, then AqBqA^q \le B^q, where the inequalities denote the Loewner partial order.

theorem

Tr[BrArBr]Tr[(BAB)r]\text{Tr}[B^r A^r B^r] \le \text{Tr}[(B A B)^r] for 0<r10 < r \le 1

#lieb_thirring_le_one

Let AA and BB be positive semi-definite d×dd \times d complex Hermitian matrices (i.e., A0A \ge 0 and B0B \ge 0). For any real number rr such that 0<r10 < r \le 1, the following inequality of Lieb-Thirring type holds for the trace: Tr(BrArBr)Tr((BAB)r)\text{Tr}\left( B^r A^r B^r \right) \le \text{Tr}\left( (B A B)^r \right) Here, XrX^r denotes the rr-th power of a Hermitian matrix XX, and for a Hermitian matrix HH and matrix MM, H.conj(M)H.\text{conj}(M) represents the congruent transformation MHMM H M^*. In the case where M=BrM = B^r or M=BM = B, the trace terms correspond to Tr(BrArBr)\text{Tr}(B^r A^r B^r) and Tr((BAB)r)\text{Tr}((B A B)^r) respectively.

theorem

Trace of (A+B)p(A+B)^p is Subadditive for 0<p10 < p \le 1

#trace_rpow_add_le

Let AA and BB be complex Hermitian matrices of dimension dd. If AA and BB are positive semi-definite (i.e., A0A \ge 0 and B0B \ge 0) and pp is a real number such that 0<p10 < p \le 1, then the trace of the sum raised to the power pp is less than or equal to the sum of the traces of the individual matrices raised to the same power: tr((A+B)p)tr(Ap)+tr(Bp)\text{tr}((A + B)^p) \le \text{tr}(A^p) + \text{tr}(B^p)