Statistics and Modeling for Complex Data
Matrix product representation is an efficient way of representing quantum states in exponentially large Hilbert spaces, and it has been used in various fields such as quantum computation, quantum state estimation, and condensed matter physics.
In this talk, after briefly reviewing basics of matrix product representation, I will show our recent result about
the trace-preserving property of the quantum Markov process associated with the matrix used in matrix product representation.
I will also explain an application of this result to measurement-based quantum computation.
Joint work with Dr. Keisuke Fujii (Osaka University, Japan)