COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |

University of Cambridge > Talks.cam > Information Theory Seminar > Approximate fixed points of classical and quantum channels and robustness theory of quantum Markov chains

## Approximate fixed points of classical and quantum channels and robustness theory of quantum Markov chainsAdd to your list(s) Download to your calendar using vCal - Robert Salzmann, DAMTP, University of Cambridge
- Wednesday 26 April 2023, 14:00-15:00
- MR11 (B1.39), CMS Pavilion B.
If you have a question about this talk, please contact Prof. Ramji Venkataramanan. Room changed The talk will focus on some preliminary results about approximate fixed points of channels. In particular it concerns the following question: Given a quantum (or classical) channel and a quantum state (or probability distribution) which is almost a fixed point of given channel, can we find a new channel and state close to the original ones such that those satisfy an exact fixed point equation? This question can be asked under many interesting constraints where the original channel and state are assumed to have certain structures which the new channel and state are supposed to satisfy as well. In this talk I will present an affirmative answer in the fully classical case. Moreover, as a motivating application of the abstract fixed point equation, I will talk about the robustness theory of so-called quantum Markov chains, which is a long standing open problem in quantum information theory This talk is part of the Information Theory Seminar series. ## This talk is included in these lists:- All CMS events
- All Talks (aka the CURE list)
- CMS Events
- DPMMS Lists
- DPMMS info aggregator
- DPMMS lists
- Hanchen DaDaDash
- Information Theory Seminar
- Interested Talks
- MR11 (B1.39), CMS Pavilion B
- School of Physical Sciences
- Statistical Laboratory info aggregator
- bld31
Note that ex-directory lists are not shown. |
## Other listsCambridge Public Policy Workshops BioLunch Why Deep Neural Networks Are Promising for Speech Recognition## Other talksThe Liquid Tensor Experiment Synthetic control of peptide and protein architectures Royal Statistical Society’s Statistical Ambassadors Programme Probabilistic Learning on Manifolds (with Applications) Using adjoints to efficiently train a digital twin of air pollution in Kampala LMB Seminar: The Extraordinary Life and Legacy of Sir John C. Kendrew |