In a recent Physical Review Research paper, scientists from several institutes in Taiwan tried to address a significant challenge in quantum physics: the simulation of large-scale quantum systems. The researchers focused on near-term quantum devices, or the current generation of quantum computers that are in the developmental stage, characterized by a relatively small number of qubits (the quantum equivalent of classical bits) and the presence of errors and noise in their operations.
Simulating quantum physics is notoriously difficult due to the exponential growth of a quantum system’s Hilbert space (a mathematical framework that allows scientists to describe and analyze the state and behavior of quantum systems comprehensively) as more components are added. This growth requires massive computational resources, exceeding the capabilities of traditional computers. Traditionally, analog quantum simulation (AQS) has been used, where a less controllable system’s Hamiltonian, or total energy, is mapped onto a well-controlled quantum system. While successful, these AQS implementations often require elaborate and inaccessible quantum experimental platforms.
Quantum Computing Platforms for Quantum Simulation
The rise of programmable quantum computing platforms, accessible via online interfaces, has opened new avenues for public engagement and theoretical experimentation in quantum mechanics. These platforms have successfully demonstrated fundamental quantum principles yet struggle with significant noise and connectivity issues. This makes simulating large-scale materials on these platforms challenging, especially for near-term quantum computers in the noisy intermediate-scale quantum (NISQ) era.
In this study, the researchers propose an alternative AQS approach tailored for near-term quantum devices. This method overcomes performance limitations by adaptively partitioning the simulation into several groups based on the capabilities of the quantum devices. The approach is demonstrated by simulating an electron spin’s free induction decay (FID)—the process where the signal from electrons spinning in a magnetic field gradually decreases or “decays” over time due to a loss of synchronization among the spins after an initial pulse has disturbed their uniform state—in a special environment within the diamond called an NV-center, a system coupled to numerous nuclei. This simulation, which investigates the nonclassicality induced by nuclear spin polarization, was conducted using IBM quantum computers and simulators.
This method allows for the simulation of large-scale materials on noisy quantum computers and does so without the errors typically introduced in traditional simulation methods like Trotterization. The researchers also applied their approach to address nonclassical noise caused by qubit crosstalk, suggesting a method to mitigate this common source of error.
This study offers a flexible, error-resistant method for simulating large-scale materials on near-term quantum computers. It represents a significant step forward in harnessing the capabilities of current quantum technologies, opening doors to new explorations and understandings in quantum physics. The approach has the potential to significantly influence the quantum computing industry by enabling more accurate and feasible simulations of complex quantum systems.
Kenna Hughes-Castleberry is a staff writer at Inside Quantum Technology and the Science Communicator at JILA (a partnership between the University of Colorado Boulder and NIST). Her writing beats include deep tech, quantum computing, and AI. Her work has been featured in Scientific American, Discover Magazine, New Scientist, Ars Technica, and more.