Quantum computing and the difficulty of simulating quantum many-body systems

Quantum many-body systems are very hard to simulate, since computational
resources (time and memory) typically grow exponentially with the system size.
However, quantum computers or analog quantum simulators may perform that task
in a much more efficient way. In this talk, I will review some of the quantum
algorithms that have been proposed for this task and then explain the advantages
and disadvantages of analog quantum simulators. In particular, I will describe
methods to simulate the dynamics, to find ground states, or compute physical
properties at finite temperatures.

Bio: Prof. Ignacio Cirac is one of the most influential pioneers of Quantum Information Science. Since the beginning of his career, he has made fundamental contributions to widely different areas in this field, from quantum communication and entanglement theory to tensor networks, quantum simulation of gauge theories, and machine learning. In 1995, shortly after the discovery of Shor's factoring algorithm, Dr. Cirac who was a postdoc at Peter Zoller's group, proposed the idea of using trapped ions for quantum computing (Later in the same year, this idea was experimentally realized by Prof. Chris Monroe, who was working in David Wineland's group at the time). Today, Prof. Cirac's papers in Quantum Information have been cited more than 100,000 times. Dr. Cirac has received numerous prestigious awards, including the Max Planck Medal of the German Physical Society in 2018, Wolf Prize in Physics in 2013, Benjamin Franklin Medal in Physics in 2010, and Prince of Asturias Award in technical and scientific research in 2006. Since 2001, Dr. Cirac has been the director of Max Planck Institute of Quantum Optics in Garching, Germany.