Speaker: Kavan Modi Monash University
Time: 2018-11-06 10:20-2018-11-06 11:20
Venue: MMW S327

Abstract:

In science, we often want to characterise dynamical processes to identify the underlying physics and predict the future states of the system. If the state of the system at any time depends only on the state of the system at the previous time-step and some predetermined rule then the dynamics are characterised with relative ease. For instance, the dynamics of quantum mechanical systems in isolation is described in this way. However, when a quantum system repeatedly interacts with an environment, the environment often ’remembers’ information about the system's past. This leads to non-Markovian processes, which depend nontrivially on the state of the system at all times during its evolution. Such dynamics are not, in general, be easily characterised using conventional techniques. Indeed, since the early days of quantum mechanics it has been a challenge to describe non-Markovian processes. Here we will show, using operational tools from quantum information theory, how to fully characterise any non-Markovian process. Using this we give an unambiguous criterion for quantum Markov processes. Next, we construct a mapping from a multi-time process to a many-body state using linear (in the number of time steps) amount of bipartite entanglement. The many-body state can be measured to any desired precision, thus the process can be characterised to any desired precision. Finally, we will discuss some preliminary results exposing the non-Markovianity of the IBM five qubit computer.

 

Short Bio:

Kavan Modi obtained his PhD from The University of Texas at Austin and spent time as a Research Fellow at National University of Singapore and University of Oxford. Kavan Modi is now the Principal investigator of Monash Quantum Information Science Group. His research focuses on several related areas of quantum physics, using the tools of quantum information theory to understand and characterise quantum dynamics, probing, metrology, computation, thermodynamics, and relativity.