Visible quantum compression with free shared randomness at the Holevo rate

Unsolved ID op_1ab8b10386bddd66 Last edited 14 September 2026
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Problem

Does free shared classical randomness make the Holevo information achievable for visible compression of every finite mixed-state ensemble? Let \(p\) be a probability distribution with full support on a finite alphabet \(\mathcal X\), and let \(W_x\) be density operators on a finite-dimensional system \(B\). Alice knows the independent and identically distributed label sequence \(x^n\), with probability \(p^n(x^n)\); the target is \(W_{x^n}:=\bigotimes_{t=1}^nW_{x_t}\). Alice and Bob share a finite random variable \(S_n\), independent of \(x^n\), with arbitrary distribution \(q_n\) and no bound on its size. For each seed \(s\), Alice prepares a density operator \(\tau_{x^n,s}\) on a quantum message system \(M_n\) and sends it through a noiseless quantum channel. Bob applies a completely positive trace-preserving map \(\mathcal D_{n,s}:\mathcal L(M_n)\to\mathcal L(B^{\otimes n})\). No initially shared entanglement or additional communication is available. The reproduced state and block error are

\begin{equation} \widehat W_{x^n}:=\sum_s q_n(s)\mathcal D_{n,s}(\tau_{x^n,s}),\qquad \varepsilon_n:=\frac12\sum_{x^n}p^n(x^n)\|W_{x^n}-\widehat W_{x^n}\|_1. \tag{1} \end{equation}

Thus the shared seed is averaged before taking the trace norm in Eq. (1). Define the rate, in qubits per signal, and the ensemble Holevo information by

\begin{equation} R_{\mathrm{vis},q,\mathrm{cr}}(p,W):=\inf_{\{\text{codes}:\varepsilon_n\to0\}}\limsup_{n\to\infty}\frac1n\log_2\dim M_n, \qquad \chi(p,W):=S\!\left(\sum_xp_xW_x\right)-\sum_xp_xS(W_x), \tag{2} \end{equation}

where \(S\) is the von Neumann entropy in bits. Is \(R_{\mathrm{vis},q,\mathrm{cr}}(p,W)=\chi(p,W)\) in Eq. (2) for every ensemble, or is there a finite ensemble with a strict gap?

Source

This is the free-randomness communication-rate part of Winter’s Conjecture 23, p. 11, with the visible quantum model defined in Eqs. (15)–(16) of [Win02]. The original conjecture additionally specifies a shared-randomness rate of \(\sum_xp_xS(W_x)\); the present question leaves that resource unrestricted and is consequently weaker.

Progress

  • The converse \(R_{\mathrm{vis},q,\mathrm{cr}}(p,W)\ge\chi(p,W)\) follows from Holevo information and data processing, consistent with Winter’s quantum lower bounds [Win02], Theorems 20–21. For the shared-randomness model specifically, independence of \(S_n\) and the labels gives \(I(X^n;M_nS_n)=I(X^n;M_n\mid S_n)\le\log_2\dim M_n\); vanishing block error and entropy continuity then yield the claimed asymptotic converse.

  • For the analogous protocol with a classical message, Nator and Pereg’s Corollary 3 gives

    \begin{equation} R_{\mathrm{vis},c,\mathrm{cr}}(p,W)=\min_{P(u\mid x),\theta_u:\,W_x=\sum_uP(u\mid x)\theta_u}I(X;U), \tag{3} \end{equation}

    where \(\theta_u\) are density operators, \(P_{XU}(x,u)=p_xP(u\mid x)\), and one may take \(|\mathcal U|\le |\mathcal X|^2(\dim B)^2+1\). Their joint-state trace-norm criterion, Eqs. (3)–(4), equals Eq. (1) by the trace norm of block-diagonal operators [NP24]. A classical message can be encoded in orthogonal quantum states, so Eq. (3) is an upper bound on the quantum rate. For commuting \(W_x\), this value is \(\chi(p,W)\), settling that subclass.

  • Without shared randomness, Hayashi’s main theorem, Eq. (8), identifies the visible qubit rate with \(E_P^\infty(\omega_{XB})\), where \(\omega_{XB}=\sum_xp_x|x\rangle\langle x|\otimes W_x\), \(E_P\) is the minimum entropy across a bipartition of a purification, and \(E_P^\infty(\omega):=\lim_{n\to\infty}E_P(\omega^{\otimes n})/n\). Ignoring shared randomness therefore gives the upper bound \(R_{\mathrm{vis},q,\mathrm{cr}}\le E_P^\infty(\omega_{XB})\). For pure signal states, Eq. (10) gives \(E_P^\infty(\omega_{XB})=S(\sum_xp_xW_x)=\chi(p,W)\), so that subclass is also settled [Hay06].

Comment

The remaining issue is quantum achievability at the Holevo rate for general noncommuting mixed signals. The classical communication formula in Eq. (3) settles a different resource restriction and does not supply this quantum coding theorem. Likewise, entanglement-assisted reverse Shannon protocols use a resource excluded here. This question is distinct from additivity of entanglement of purification: that problem controls the unassisted visible rate, whereas the present task supplies shared randomness [Hay06]. The placement of the average in Eq. (1) is essential: averaging the trace-norm errors of individual seeds would allow a good seed to be fixed separately at each blocklength, removing any benefit from shared randomness. Literature audited on 9 September 2026. The cited primary definitions and theorem passages were checked, and no full resolution was identified in the later sources examined.

References

[Win02]
A. Winter, “Compression of Sources of Probability Distributions and Density Operators,” arXiv preprint (2002).arXiv
[NP24]
H. Nator and U. Pereg, “Coordination Capacity for Classical-Quantum Correlations,” in 2024 IEEE Information Theory Workshop (ITW) (2024).DOIarXiv
[Hay06]
M. Hayashi, “Optimal Visible Compression Rate for Mixed States Is Determined by Entanglement of Purification,” Physical Review A 73, 060301(R) (2006).DOIarXiv

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@incollection{qiqcop_op_1ab8b10386bddd66,
  title = {Visible quantum compression with free shared randomness at the Holevo rate},
  booktitle = {Quantum Information and Quantum Computation Open Problem Zoo (QIQCOP Zoo)},
  year = {2026},
  howpublished = {\url{https://qiqc-op.com/problem/op_1ab8b10386bddd66/}},
  note = {Stable ID op_1ab8b10386bddd66; status: Unsolved; accessed 2026-09-16}
}

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“Visible quantum compression with free shared randomness at the Holevo rate,” Quantum Information and Quantum Computation Open Problem Zoo (QIQCOP Zoo), https://qiqc-op.com/problem/op_1ab8b10386bddd66/, ID op_1ab8b10386bddd66, accessed 2026-09-16.

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op_1ab8b10386bddd66
01M22MXHAJ50EYBHXWXX635JQK