Classical capacity and entropy inequalities for generalized amplitude dampingResearch Paper
Motivation: the classical capacity of a thermal qubit channel
A quantum channel models how a physical system, used to carry information, is corrupted by its environment. The classical capacity of a channel is the largest rate, in bits per use, at which classical messages can be sent with vanishing error when the sender may encode into arbitrary — possibly entangled — states of many uses and the receiver may measure all outputs jointly. The Holevo–Schumacher–Westmoreland coding theorem (Holevo 1998; Schumacher–Westmoreland 1997) expresses this capacity as a regularized limit of the Holevo information over ever larger blocks of uses. Since Holevo information is not additive in general (Hastings 2009), computing the capacity of any specific channel requires a channel-specific additivity argument, and exact formulas are known only for a few families.
Generalized amplitude damping is the standard model of a qubit relaxing toward a thermal state: it loses or gains an excitation with probabilities set by a damping strength and a stationary excited population , and its coherences decay. It is one of the basic noise models of quantum information theory.
Background timeline
- 1996–1998 — Coding theorems for pure and mixed signals establish the regularized capacity formula (Hausladen et al. 1996; Schumacher–Westmoreland 1997; Holevo 1998).
- 2002 — Additivity for unital qubit channels (King 2002) and for entanglement-breaking channels (Shor 2002) settles some parameter regions of the family; Bennett, Shor, Smolin and Thapliyal describe the two-signal optimization for ordinary amplitude damping (BSST 2002).
- 2005 — Giovannetti and Fazio derive the optimized one-use expression for ordinary amplitude damping (Giovannetti–Fazio 2005); Berry studies qubit channels achieving capacity with two states (Berry 2005).
- 2007 — Hou and Fang characterize the one-use Holevo optimum of the generalized channel (Hou–Fang 2007).
- 2009 — Hastings shows that Holevo information is not additive in general (Hastings 2009).
- 2018 — Leditzky, Kaur, Datta and Wilde note that the unrestricted classical capacity of amplitude damping had not been determined (LKDW 2018).
- 2020 — Khatri, Sharma and Wilde collect upper bounds for the generalized family (KSW 2020).
- 2026 — Tang, Zhu, Bai and Wang prove additivity for qubit channels with a pure output, including ordinary amplitude damping (arXiv:2609.28592); Fang gives a close converse bound for the generalized family (arXiv:2609.14621).
- 2026 — An OpenAI preprint, Classical capacity and entropy inequalities for generalized amplitude damping (OpenAI Math Release, September 24, 2026), claims the capacity for all . The preprint has not been peer reviewed, and its results are not formally verified.
Setting
For the generalized amplitude-damping channel acts on a qubit density matrix by
and independent uses act as on matrices. With , the Holevo information in bits is
over all finite ensembles of input states (entangled across uses when ). The classical capacity is the supremum of rates for which there are -use codes — arbitrary input states for each of equiprobable messages and one joint measurement of all outputs — with average error tending to zero and ; there is no shared entanglement or feedback. Write for binary entropy in nats, and .
Formalization targets
Goal: additivity and capacity formula (Theorem 1.1)
For all and every ,
the maximum is attained, , and for every maximizer the equiprobable independent products of the two signals attain at every block length. The goal is published on the platform with status Open.
Significance
The result itself. The theorem gives a closed one-variable formula for the classical capacity of every generalized amplitude-damping channel, removing the regularization over block lengths: entangled input signals across uses give no advantage, and a simple product code with two signals per use is optimal. This settles the ordinary amplitude-damping case listed as open by LKDW 2018 and extends beyond the pure-output criterion of Tang et al. to the thermal regime, where the channel has no pure output. The source further proves additivity of Holevo capacity, minimum output entropy and classical capacity when the channel is used in parallel with any finite-dimensional partner channel (Corollary 1.2); that corollary is not part of this goal.
Formalizing it. The goal ties together an operational capacity (codes and error probabilities), an entropic quantity (a supremum over unrestricted ensembles on -dimensional matrices), and a scalar optimization. A machine-checked proof would certify both the matrix entropy inequality at the heart of the argument and the converse direction of the coding theorem. Mathlib does not currently contain quantum channel capacity theory, so the definitions here are new infrastructure.
Difficulty
Optimizing a single use gives a lower bound on capacity; the difficulty is the matching upper bound for all simultaneously, where an input may be entangled across all uses. Holevo additivity is false for general channels, so no abstract argument applies, and for interior thermal occupation with the channel has no pure output, which rules out the recent pure-output criterion. The proof needs a lower bound on the entropy of the output of an arbitrary entangled block input, i.e. a matrix entropy inequality for block-structured states that is tight on product inputs. Identifying the capacity with the regularized Holevo quantity also requires the full coding theorem and a Fano-type converse.
Formalization scope
- Matrices are indexed by
Fin n → Fin 2; the -use channel is given by tensor products of the four standard Kraus operators of generalized amplitude damping, which reproduce the displayed action exactly. - Entropy is
Tr (cfc negMulLog P)(nats, ); Holevo values are divided by (bits).holevo γ ν nis thesSupover all finite ensembles of arbitrary -dimensional states, with no product or purity restriction. capacityis thesSupof operationally achievable rates: codes with any positive number of messages, arbitrary state encodings, an arbitrary POVM decoder, average error tending to , and the liminf rate condition. It is defined operationally, not by regularization, so the identity includes the coding theorem.- The scalar objective uses
Real.binEntropy(nats); the maximizer is over . The final clause also asserts that the phase-product signals are states. - Parameters range over the closed square , including boundary cases (identity channel at , full replacement at ).
- Needed infrastructure: matrix entropy and its concavity, CPTP maps and Kraus representations, Holevo's bound, Fano's inequality, the HSW coding theorem for finite ensembles, and Fekete-type superadditivity. These are reusable for any quantum Shannon-theory mission.
Selected references
- P. Hausladen, R. Jozsa, B. Schumacher, M. Westmoreland, W. K. Wootters, Classical information capacity of a quantum channel, Phys. Rev. A 54 (1996), 1869–1876. https://doi.org/10.1103/PhysRevA.54.1869
- B. Schumacher and M. D. Westmoreland, Sending classical information via noisy quantum channels, Phys. Rev. A 56 (1997), 131–138. https://doi.org/10.1103/PhysRevA.56.131
- A. S. Holevo, The capacity of the quantum channel with general signal states, IEEE Trans. Inf. Theory 44 (1998), 269–273. https://doi.org/10.1109/18.651037
- C. King, Additivity for unital qubit channels, J. Math. Phys. 43 (2002), 4641–4653. https://doi.org/10.1063/1.1500791
- P. W. Shor, Additivity of the classical capacity of entanglement-breaking quantum channels, J. Math. Phys. 43 (2002), 4334–4340. https://doi.org/10.1063/1.1498000
- C. H. Bennett, P. W. Shor, J. A. Smolin, A. V. Thapliyal, Entanglement-assisted capacity of a quantum channel and the reverse Shannon theorem, IEEE Trans. Inf. Theory 48 (2002), 2637–2655. https://doi.org/10.1109/TIT.2002.802612
- V. Giovannetti and R. Fazio, Information-capacity description of spin-chain correlations, Phys. Rev. A 71 (2005), 032314. https://doi.org/10.1103/PhysRevA.71.032314
- D. W. Berry, Qubit channels that achieve capacity with two states, Phys. Rev. A 71 (2005), 032334. https://doi.org/10.1103/PhysRevA.71.032334
- L.-Z. Hou and M.-F. Fang, The Holevo capacity of a generalized amplitude-damping channel, Chinese Physics 16 (2007), 1843–1847. https://doi.org/10.1088/1009-1963/16/7/006
- M. B. Hastings, Superadditivity of communication capacity using entangled inputs, Nature Physics 5 (2009), 255–257. https://doi.org/10.1038/nphys1224
- F. Leditzky, E. Kaur, N. Datta, M. M. Wilde, Approaches for approximate additivity of the Holevo information of quantum channels, Phys. Rev. A 97 (2018), 012332. https://doi.org/10.1103/PhysRevA.97.012332
- S. Khatri, K. Sharma, M. M. Wilde, Information-theoretic aspects of the generalized amplitude-damping channel, Phys. Rev. A 102 (2020), 012401. https://doi.org/10.1103/PhysRevA.102.012401
- Z. Tang, C. Zhu, G. Bai, X. Wang, Classical capacity and entanglement cost of the amplitude damping channel, arXiv:2609.28592 (2026). https://arxiv.org/abs/2609.28592v1
- K. Fang, A pretty-tight converse on the classical capacity of generalized amplitude-damping channels, arXiv:2609.14621 (2026). https://arxiv.org/abs/2609.14621v1
- OpenAI, Classical capacity and entropy inequalities for generalized amplitude damping, OpenAI Math Release preprint, September 24, 2026 (Theorem 1.1, p. 3). https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Classical-capacity-and-entropy-inequalities-for-generalized-amplitude-damping-September-24-2026/paper.pdf