Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 134 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 29 tok/s Pro
GPT-4o 79 tok/s Pro
Kimi K2 188 tok/s Pro
GPT OSS 120B 434 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

A Blahut-Arimoto Type Algorithm for Computing Classical-Quantum Channel Capacity (1904.11188v1)

Published 25 Apr 2019 in quant-ph, cs.IT, and math.IT

Abstract: Based on Arimoto's work in 1978, we propose an iterative algorithm for computing the capacity of a discrete memoryless classical-quantum channel with a finite input alphabet and a finite dimensional output, which we call the Blahut-Arimoto algorithm for classical-quantum channel, and an input cost constraint is considered. We show that to reach $\varepsilon$ accuracy, the iteration complexity of the algorithm is up bounded by $\frac{\log n\log\varepsilon}{\varepsilon}$ where $n$ is the size of the input alphabet. In particular, when the output state ${\rho_x}{x\in \mathcal{X}}$ is linearly independent in complex matrix space, the algorithm has a geometric convergence. We also show that the algorithm reaches an $\varepsilon$ accurate solution with a complexity of $O(\frac{m3\log n\log\varepsilon}{\varepsilon})$, and $O(m3\log\varepsilon\log{(1-\delta)}\frac{\varepsilon}{D(p*||p{N_0})})$ in the special case, where $m$ is the output dimension and $D(p*||p{N_0})$ is the relative entropy of two distributions and $\delta$ is a positive number.

Citations (18)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (2)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube