Trinity’s quantum physicists, in collaboration with IBM Dublin, have made a groundbreaking advance in the field of quantum simulation. By utilizing a quantum computer, they successfully simulated super diffusion in a system of interacting quantum particles. This achievement marks a significant step towards conducting complex quantum transport calculations on quantum hardware.
While quantum computing is still in its early stages, it holds immense potential for commercial applications in the coming decade. Beyond its commercial implications, quantum computers can address profound fundamental questions. In this study, the team at Trinity and IBM Dublin focused on the concept of quantum simulation.
To understand the significance of their work, it is crucial to grasp the challenges posed by simulating complex quantum systems on conventional computers. Simulating the dynamics of a quantum system with multiple interacting constituents is a formidable task for classical computers. As the number of qubits (the building blocks of quantum logic) increases, the demands on classical resources grow exponentially. For instance, describing a system with 27 qubits would require approximately 134 million coefficients, stored in memory. This number becomes unmanageable as the system scales up to hundreds of qubits.
Quantum systems, however, offer a solution to this predicament. Nobel prize-winning physicist Richard Feynman proposed that quantum systems are best simulated using quantum systems themselves. Quantum computers, described by wave functions, circumvent the need for exponential classical resources required by their classical counterparts.
In this pioneering study, the team used a quantum computer consisting of 27 superconducting qubits to simulate the behavior of a Heisenberg chain, a simple non-trivial quantum system. They focused on the long-time behavior of spin excitations and their transport across the system. In this regime, quantum many-body systems enter a hydrodynamic regime, and the transport is described by equations akin to those describing classical fluids.
The researchers specifically examined the regime where super diffusion occurs, driven by the Kardar-Parisi-Zhang equation. This equation characterizes the stochastic growth of a surface or interface, which results in faster transport as the system size increases. Remarkably, the same equations governing phenomena like the growth of snow during a snowstorm also emerge in quantum systems. The team successfully used the quantum computer to verify this phenomenon.
Programming quantum computers, however, poses challenges due to the presence of noise and sensitivity to disturbances from the laboratory environment. Minimizing runtime becomes crucial to mitigate errors and disturbances that might affect the results. Nathan Keenan, an IBM-Trinity predoctoral scholar who programmed the device for this project, highlighted these challenges.
IBM, with its extensive research and commercial quantum program, has been a driving force in advancing quantum computing technology. Through collaborations, such as the MSc for Quantum Science and Technology and PhD program with Trinity College Dublin, IBM continues to deliver promising results.
As the world enters a new era of quantum simulation, Trinity’s quantum physicists remain at the forefront of research. Their work in quantum simulation is a key focus of the newly established Trinity Quantum Alliance, led by Professor John Goold. This alliance includes prominent industrial partners like IBM, Microsoft, Algorithmiq, Horizon, and Moody’s Analytics.
FAQs
Q: What is quantum simulation?
A: Quantum simulation is the process of using quantum computers to simulate the behavior and dynamics of complex quantum systems.
Q: How do quantum systems overcome the limitations of classical computers?
A: Quantum systems, described by wave functions, naturally avoid the need for exponential classical resources required for simulating quantum systems on classical computers.
Q: What is super diffusion?
A: Super diffusion is a phenomenon where transport becomes faster as the size of the system increases. It is characterized by the stochastic growth of a surface or interface, described by the Kardar-Parisi-Zhang equation.
Q: What are the challenges in programming quantum computers?
A: The presence of noise and sensitivity to disturbances pose challenges in programming quantum computers. Minimizing runtime becomes crucial to mitigate errors and disturbances that can affect the results.
Sources:
– [IBM Research](https://www.research.ibm.com/)