We reformulate the Rényi entanglement of purification as a constrained minimum output Rényi entropy problem. Equivalently, for
p>1, this formulation can be expressed in terms of a constrained maximal output Schatten
p-norm. More precisely, for a completely positive map
Ω:L(B′)→L(A), we consider the quantity
υp(Ω) defined by optimizing
∥(Ω⊗idE)(σB′E)∥p over all bipartite states
σB′E whose
B′-marginal is maximally mixed. We focus on the case
p=2. First, we compute
υ2 for the transpose-depolarizing channel and prove that it is multiplicative under tensor powers. We then establish a general multiplicativity criterion: whenever a completely positive map
N:L(B′)→L(A) satisfies
N†∘N=aidA+bTr[⋅]Id for some constants
a,b≥0, where
N† denotes the Hilbert-Schmidt adjoint of
N, the quantity
υ2(N) is multiplicative under tensor powers. Examples of channels satisfying this criterion include the transpose-depolarizing channel, the depolarizing channel, and their respective complementary channels. Furthermore, we show that, for every completely positive map
Ω, multiplicativity of
υp(Ω) implies multiplicativity for its complementary map. This yields the corresponding additivity statements for the associated Rényi-2 entanglement of purification.
We study the convergence of states under continuous-time depolarizing channels with full rank fixed points in terms of the relative entropy. The optimal exponent of an upper bound on the relative entropy in this case is given by the log-Sobolev-1 constant. Our main result is the computation of this constant. As an application, we use the log-Sobolev-1 constant of the depolarizing channels to improve the concavity inequality of the von Neumann entropy. This result is compared to similar bounds obtained recently by Kim and we show a version of Pinsker’s inequality, which is optimal and tight if we fix the second argument of the relative entropy. Finally, we consider the log-Sobolev-1 constant of tensor-powers of the completely depolarizing channel and use a quantum version of Shearer’s inequality to prove a uniform lower bound.