Description
Speaker:
Prof Manoj Joshi
IQOQI Innsbruck & Singapore University of Technology and Design (SUTD)
Abstract:
Quantum simulators and quantum computers are progressing toward solving complex problems in science. Trapped ions are one of the key platforms, offering unprecedented qubit control. At this conference, I will present recent advancements in quantum simulation using long ion chains in a radio-frequency trap in Innsbruck. In particular, I will discuss Hamiltonian and Liouvillian learning (Lindbladian learning) techniques used to quantitatively validate experimentally implemented Hamiltonians in trapped-ion systems. For this purpose, a broad set of ansatz terms is incorporated into the analysis to identify the Hamiltonian that best captures the observed dynamics. Once the optimal candidate is determined, statistical noise and estimation bias are carefully analyzed to obtain reliable estimates of the Hamiltonian parameters. These studies are carried out on a trapped-ion quantum simulator consisting of ion strings with up to N=51 ions. I will also present a practical perspective on Hamiltonian learning methods and their role in establishing trust in analog quantum simulations. Furthermore, I will discuss potential future research directions for my group in Singapore using trapped ions.