By James Mingo
Like tensor independence, free independence gives us rules for doing calculations. With random matrix models, we usually need tensor independence of the entries and some kind of group invariance of the joint distribution of the entries to get the (asymptotic) freeness necessary to apply the tools of free probability. A few years ago Mihai Popa and I found that the transpose also produces asymptotic freeness, i. e. a matrix could be asymptotically free from its own transpose. Since that we have expanded this work to the case of the partial transposes that arise in quantum information theory. In this talk, I will explain what happens when one transposes certain R-cyclic operators.
By Anthony Leverrier
By Zbigniew Puchała
By Benoit Collins
By Satya Majumdar
By Motohisa Fukuda
By Anand Natarajan
By Nilanjana Datta
By Daniel Stilck Franca
By Ke Li
By Radosław Adamczak
By Madalin Guta
By Antonio Acín
By Ashley Montanaro
By Ping Zhong
By James Mingo
By Camille Male
By Clément Delcamp
By Claudio Dappiaggi
By Alexander Strohmaier
By Misha Gromov
By Olivier Benoist
By Viviane Pons
