The new paper, published in Nature, explores near and medium-term possibilities for quantum simulation on analogue and digital platforms to help evaluate the potential of this area. “There has been a great deal of exciting progress in analogue and digital quantum simulation in recent years, and quantum simulation is one of the most promising fields of quantum information processing. It is already quite mature, both in terms of algorithm development, and in the availability of significantly advanced analogue quantum simulation experiments internationally”, said Andrew Daley, who has spent many years researching in Innsbruck and has been a professor at the University of Strathclyde in Scotland since 2013.
In computing history, classical analogue and digital computing co-existed for more than half a century, with a gradual transition towards digital computing. “We expect the same thing to happen with the emergence of quantum simulation”, said Daley. “As a next step along the development of this technology, it is now important to discuss ‘practical quantum advantage,’ the point at which quantum devices will solve problems of practical interest that are not tractable for traditional supercomputers.”
From materials science to quantum chemistry
Many of the most promising short-term applications of quantum computers fall under the umbrella of quantum simulation: modelling the quantum properties of microscopic particles that are directly relevant to understanding modern materials science, high-energy physics, and quantum chemistry.
Quantum simulation should be possible in the future on fault-tolerant digital quantum computers with more flexibility and precision, but it can also already be done today for specific models through special-purpose analogue quantum simulators. This happens in an analogous way to the study of aerodynamics, which can be conducted either in a wind tunnel or through simulations on a digital computer. Where aerodynamics often use a smaller scale model to understand something big, analogue quantum simulators often take a larger scale model to understand something even smaller.
Best advantages of both sides
Analogue quantum simulators are now moving from providing qualitative demonstrations of physical phenomena to providing quantitative solutions for native problems. A particularly exciting way forward in the near term is the development of a range of programmable quantum simulators hybridizing digital and analogue techniques. “This holds great potential because it combines the best advantages of both sides by making use of the native analogue operations to produce highly entangled states”, said Innsbruck physicist Peter Zoller.
But how can we verify that a quantum simulation gives the correct result when a classical computer can no longer predict it? In the article, Christian Kokail and Peter Zoller show that a new method, so-called Hamiltonian learning, can play an important role in verifying a quantum advantage. This involves reconstructing the parameters of the quantum system from measurement results of the simulation. “If these match, the simulation was successful,” says Christian Kokail. “The number of necessary measurements does not grow exponentially with the number of particles, which is why the method is also suitable for large quantum systems and thus for demonstrating the quantum advantage.” The authors demonstrate the application of the method for fermions in an optical lattice, a very interesting and highly relevant model for practical applications.
Successful partnership
All of partners on this perspective article from the University of Innsbruck, the Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, the Max Planck Institute of Quantum Optics, Ludwig Maximilians University in Munich, Munich Center for Quantum Science and Technology, the University of Strathclyde, and Microsoft Corporation have large, active programmes involving both theory of architectures and algorithms, as well as development of platforms for analogue quantum simulation and digital quantum computing. The partners have been collaborating as part of the Horizon 2020 EU Quantum Technologies Flagship project PASQuanS.