# Min-entropy

The min-entropy, in information theory, is the smallest of the Rényi family of entropies, corresponding to the most conservative way of measuring the unpredictability of a set of outcomes, as the negative logarithm of the probability of the most likely outcome. The various Rényi entropies are all equal for a uniform distribution, but measure the unpredictability of a nonuniform distribution in different ways. The min-entropy is never greater than the ordinary or Shannon entropy (which measures the average unpredictability of the outcomes) and that in turn is never greater than the Hartley or max-entropy, defined as the logarithm of the number of outcomes with nonzero probability.

As with the classical Shannon entropy and its quantum generalization, the von Neumann entropy, one can define a conditional version of min-entropy. The conditional quantum min-entropy is a one-shot, or conservative, analog of conditional quantum entropy.

To interpret a conditional information measure, suppose Alice and Bob were to share a bipartite quantum state $\rho _{AB}$ . Alice has access to system $A$ and Bob to system $B$ . The conditional entropy measures the average uncertainty Bob has about Alice's state upon sampling from his own system. The min-entropy can be interpreted as the distance of a state from a maximally entangled state.

This concept is useful in quantum cryptography, in the context of privacy amplification (See for example ).

## Definitions

Definition: Let $\rho _{AB}$ be a bipartite density operator on the space ${\mathcal {H}}_{A}\otimes {\mathcal {H}}_{B}$ . The min-entropy of $A$ conditioned on $B$ is defined to be

$H_{\min }(A|B)_{\rho }\equiv -\inf _{\sigma _{B}}D_{\max }(\rho _{AB}\|I_{A}\otimes \sigma _{B})$ where the infimum ranges over all density operators $\sigma _{B}$ on the space ${\mathcal {H}}_{B}$ . The measure $D_{\max }$ is the maximum relative entropy defined as

$D_{\max }(\rho \|\sigma )=\inf _{\lambda }\{\lambda :\rho \leq 2^{\lambda }\sigma \}$ The smooth min-entropy is defined in terms of the min-entropy.

$H_{\min }^{\epsilon }(A|B)_{\rho }=\sup _{\rho '}H_{\min }(A|B)_{\rho '}$ where the sup and inf range over density operators $\rho '_{AB}$ which are $\epsilon$ -close to $\rho _{AB}$ . This measure of $\epsilon$ -close is defined in terms of the purified distance

$P(\rho ,\sigma )={\sqrt {1-F(\rho ,\sigma )^{2}}}$ where $F(\rho ,\sigma )$ is the fidelity measure.

These quantities can be seen as generalizations of the von Neumann entropy. Indeed, the von Neumann entropy can be expressed as

$S(A|B)_{\rho }=\lim _{\epsilon \rightarrow 0}\lim _{n\rightarrow \infty }{\frac {1}{n}}H_{\min }^{\epsilon }(A^{n}|B^{n})_{\rho ^{\otimes n}}~.$ This is called the fully quantum asymptotic equipartition theorem. The smoothed entropies share many interesting properties with the von Neumann entropy. For example, the smooth min-entropy satisfy a data-processing inequality: 

$H_{\min }^{\epsilon }(A|B)_{\rho }\geq H_{\min }^{\epsilon }(A|BC)_{\rho }~.$ ## Operational interpretation of smoothed min-entropy

Henceforth, we shall drop the subscript $\rho$ from the min-entropy when it is obvious from the context on what state it is evaluated.

### Min-entropy as uncertainty about classical information

Suppose an agent had access to a quantum system $B$ whose state $\rho _{B}^{x}$ depends on some classical variable $X$ . Furthermore, suppose that each of its elements $x$ is distributed according to some distribution $P_{X}(x)$ . This can be described by the following state over the system $XB$ .

$\rho _{XB}=\sum _{x}P_{X}(x)|x\rangle \langle x|\otimes \rho _{B}^{x},$ where $\{|x\rangle \}$ form an orthonormal basis. We would like to know what the agent can learn about the classical variable $x$ . Let $p_{g}(X|B)$ be the probability that the agent guesses $X$ when using an optimal measurement strategy

$p_{g}(X|B)=\sum _{x}P_{X}(x)tr(E_{x}\rho _{B}^{x}),$ where $E_{x}$ is the POVM that maximizes this expression. It can be shown[citation needed] that this optimum can be expressed in terms of the min-entropy as

$p_{g}(X|B)=2^{-H_{\min }(X|B)}~.$ If the state $\rho _{XB}$ is a product state i.e. $\rho _{XB}=\sigma _{X}\otimes \tau _{B}$ for some density operators $\sigma _{X}$ and $\tau _{B}$ , then there is no correlation between the systems $X$ and $B$ . In this case, it turns out that $2^{-H_{\min }(X|B)}=\max _{x}P_{X}(x)~.$ #### Min-entropy as distance from maximally entangled state

The maximally entangled state $|\phi ^{+}\rangle$ on a bipartite system ${\mathcal {H}}_{A}\otimes {\mathcal {H}}_{B}$ is defined as

$|\phi ^{+}\rangle _{AB}={\frac {1}{\sqrt {d}}}\sum _{x_{A},x_{B}}|x_{A}\rangle |x_{B}\rangle$ where $\{|x_{A}\rangle \}$ and $\{|x_{B}\rangle \}$ form an orthonormal basis for the spaces $A$ and $B$ respectively. For a bipartite quantum state $\rho _{AB}$ , we define the maximum overlap with the maximally entangled state as

$q_{c}(A|B)=d_{A}\max _{\mathcal {E}}F\left((I_{A}\otimes {\mathcal {E}})\rho _{AB},|\phi ^{+}\rangle \langle \phi ^{+}|\right)^{2}$ where the maximum is over all CPTP operations ${\mathcal {E}}$ and $d_{A}$ is the dimension of subsystem $A$ . This is a measure of how correlated the state $\rho _{AB}$ is. It can be shown that $q_{c}(A|B)=2^{-H_{\min }(A|B)}$ . If the information contained in $A$ is classical, this reduces to the expression above for the guessing probability.

### Proof of operational characterization of min-entropy

The proof is from a paper by König, Schaffner, Renner in 2008. It involves the machinery of semidefinite programs. Suppose we are given some bipartite density operator $\rho _{AB}$ . From the definition of the min-entropy, we have

$H_{\min }(A|B)=-\inf _{\sigma _{B}}\inf _{\lambda }\{\lambda |\rho _{AB}\leq 2^{\lambda }(I_{A}\otimes \sigma _{B})\}~.$ This can be re-written as

$-\log \inf _{\sigma _{B}}\operatorname {Tr} (\sigma _{B})$ subject to the conditions

$\sigma _{B}\geq 0$ $I_{A}\otimes \sigma _{B}\geq \rho _{AB}~.$ We notice that the infimum is taken over compact sets and hence can be replaced by a minimum. This can then be expressed succinctly as a semidefinite program. Consider the primal problem

${\text{min:}}\operatorname {Tr} (\sigma _{B})$ ${\text{subject to: }}I_{A}\otimes \sigma _{B}\geq \rho _{AB}$ $\sigma _{B}\geq 0~.$ This primal problem can also be fully specified by the matrices $(\rho _{AB},I_{B},\operatorname {Tr} ^{*})$ where $\operatorname {Tr} ^{*}$ is the adjoint of the partial trace over $A$ . The action of $\operatorname {Tr} ^{*}$ on operators on $B$ can be written as

$\operatorname {Tr} ^{*}(X)=I_{A}\otimes X~.$ We can express the dual problem as a maximization over operators $E_{AB}$ on the space $AB$ as

${\text{max:}}\operatorname {Tr} (\rho _{AB}E_{AB})$ ${\text{subject to: }}\operatorname {Tr} _{A}(E_{AB})=I_{B}$ $E_{AB}\geq 0~.$ Using the Choi–Jamiołkowski isomorphism, we can define the channel ${\mathcal {E}}$ such that

$d_{A}I_{A}\otimes {\mathcal {E}}^{\dagger }(|\phi ^{+}\rangle \langle \phi ^{+}|)=E_{AB}$ where the bell state is defined over the space $AA'$ . This means that we can express the objective function of the dual problem as

$\langle \rho _{AB},E_{AB}\rangle =d_{A}\langle \rho _{AB},I_{A}\otimes {\mathcal {E}}^{\dagger }(|\phi ^{+}\rangle \langle \phi ^{+}|)\rangle$ $=d_{A}\langle I_{A}\otimes {\mathcal {E}}(\rho _{AB}),|\phi ^{+}\rangle \langle \phi ^{+}|)\rangle$ as desired.

Notice that in the event that the system $A$ is a partly classical state as above, then the quantity that we are after reduces to

$\max P_{X}(x)\langle x|{\mathcal {E}}(\rho _{B}^{x})|x\rangle ~.$ We can interpret ${\mathcal {E}}$ as a guessing strategy and this then reduces to the interpretation given above where an adversary wants to find the string $x$ given access to quantum information via system $B$ .