Trinity quantum physicists, in collaboration with IBM Dublin, have successfully simulated superdiffusion in a system of interacting quantum particles on a quantum computer. This is the first step towards performing highly complex quantum transport calculations on quantum hardware, and as the hardware evolves over time, such work promises to shed new light on condensed matter physics and materials science.

This work is based on the recently established and IBM’s Ph.D. Students as collaborators during shared leadership at Trinity. The article was recently published npj Quantum Information.

The early-stage quantum computer used in this research consists of 27 superconducting qubits (qubits are the building blocks of quantum logic) and is physically located in IBM’s lab in Yorktown Heights, New York, and is programmed remotely from Dublin.

Quantum computing is one of the most exciting technologies right now and is expected to approach commercial applications in the next decade. In addition to commercial applications, there are fascinating fundamental questions that quantum computers can help with. A team from Trinity and IBM Dublin addressed such a question in quantum modeling.

Explaining the importance of the work and the idea of ​​quantum simulation in general, Trinity Professor John Gould, director of the newly formed Trinity Quantum Alliance that spearheaded the research, said: “Overall, it’s a problem of modeling the dynamics of dynamics. A complex quantum system with many interacting components is a big deal for traditional computers. It’s a challenge.”

“Imagine 27 qubits in this particular device. In quantum mechanics, the state of such a system is described mathematically using an object called a wave function. To use a standard computer to describe this object, you need to have a large number of coefficients stored in memory, and the requirements multiply by the number of qubits.” scales up; about 134 million coefficients in this simulation case.”

“If you scale a system up to 300 qubits, you need more coefficients than the number of atoms in the observable universe to describe such a system, and no classical computer can accurately capture the state of the system. In other words, we hit a wall when modeling quantum systems,” said Gould.

“The idea of ​​using quantum systems to model quantum dynamics comes from Nobel Prize-winning American physicist Richard Feynman, who suggested that quantum systems can best be modeled using quantum systems. The reason is simple – naturally you take advantage of the fact that a quantum computer is described by a wave function, so you can use the exponential to store the state. you bypass the need for conventional resources.”

So what exactly was the team simulating? Professor Gould continues: “Some of the simplest non-trivial quantum systems are spin chains. These are loosely bound magnet systems called spins, which mimic more complex materials and are used to understand magnetism. We were interested in a model called the Heisenberg chain, and we were particularly interested in a system of spin excitations. At this long-term limit, quantum multi-body systems enter the hydrodynamic regime and transport is described by equations describing classical fluids.

“We were interested in a particular regime where something called super-diffusion occurs because fundamental physics is governed by something called the Cardar-Parisi-Jang equation. This is how snow grows during a blizzard, how a coffee stain on a fabric grows over time, or how fire comes out of a feather. “It’s an equation that describes the stochastic growth of a surface or interface, usually. The diffusion is known to result from super-diffusive transport.”

“A transport that accelerates as the size of the system increases. Surprisingly, the same equations governing these phenomena appear in quantum dynamics, and we were able to use a quantum computer to verify this. That was the robot’s main achievement.”

IBM-Trinity PhD scientist Nathan Keenan, who has programmed the device as part of the project, tells us about some of the challenges associated with programming quantum computers.

“The biggest challenge in programming quantum computers is performing useful calculations in the presence of noise,” he said. “Operations performed at the chip level are imperfect and the computer is very susceptible to interference from the lab environment. Ultimately, you want to minimize the execution time of the useful program, as this will reduce the time that these errors and hurdles can occur that impact your bottom line.”

Juan Bernabe-Moreno, director of research at IBM UK and Ireland, said: “IBM has a long history of developing quantum computing, not only through decades of research, but also by providing the largest and most expansive commercial quantum program and ecosystem. Trinity College Our collaboration with Dublin on the MA and PhD program in Quantum Science and Technology is an example of this and I am delighted that it is already yielding promising results.” Source