Quantum computers have the potential to outperform classical computers at many complex tasks, yet many challenges must be overcome before they can reach their full potential. Meanwhile, physicists and computer scientists have tried to estimate the realistic possibilities that quantum computing technologies will show in the near future.
Quantum simulations—the processes of realization of quantum systems demonstrated using programmable simulators—have proven particularly valuable in determining the near-term potential of quantum computers. One of the methods that can be investigated using quantum simulation It is quantum annealing, an optimization process based on geometric quantum fluctuations.
Researchers at D-Wave Systems and various institutes in Canada, the United States, and Japan recently simulated a quantum phase transition in a 2000-qubit 1D programmable model. Their findings, presented in a paper published in Nature Physicscould help in future quantum improvement and simulation efforts.
“Coherent annealing has been something we’ve been wanting to show for a long time,” Andrew King, one of the researchers who conducted the study, told Phys.org. “One of the reasons is that it allows us to compare the behavior of our programmable quantum system with idealized Schrödinger dynamics, providing strong evidence for and a criterion for quantum quantization. It has a well-known closed-form solution, which means we can solve it classically without comprehensively simulating quantum dynamics – a generally intractable classical task. “
The quantum simulation of 1D chain Ising has been previously carried out by other research teams, including group at Harvard University. However, King and colleagues’ simulations are the first to be performed using an annealing-based quantum computer. In addition, the researchers were able to perceive larger and more related states than those shown in the past.
“The key variable here in our experiment is the annealing time, which is the time it takes for the D-Wave processor to go from the initial quantum superposition state to the classical endpoint of the computation,” King explained. “Typically a speed limit of 500 nanoseconds is set on the system, to allow for tolerances in the control circuit. However, in this work, we went 100 times faster than this.”
Due to the high speeds reached by their system, King and his colleagues had to implement more stringent hardware requirements and use new software methods. This eventually allowed them to perfectly sync the thousands of qubits into their system.
The researchers ran their simulations using a highly programmable processor built into D-Wave systems. To test its effectiveness more reliably, they chose a very simple and well-understood quantum phase transition simulation.
“The excellent fit we see between experiments and an ideal quantum model with no environmental effects It’s a new development in the field of quantum annealing, King said. “It shows us that not only is the system clearly quantitative, but that we can program more complex systems in a quantum plasticizer and we would expect it to follow the true quantum dynamics of the Schrödinger equation, which in general cannot be classically simulated.”
Overall, the team found that their simulations were consistent with quantum theory predictions. In the future, their work could open up exciting new possibilities for studying different quantum phase transitions. In their next work, King and colleagues want to use programmable D-Wave processors to simulate even more exotic quantum phase transitions, which cannot be simulated using classical computers.
“Most people would like to use quantum annealing either for quantum simulation, which we’ve done here, or for optimization,” King added. “school book Quantum Phase Transition What we have considered in this work is only indirectly applicable to optimization, so it is important to link these two areas together. We already know that quantum annealing materials can solve optimization problems very quickly. Our next task will be to study this success using coherent annealing, to explain in detail the role of quantum critical dynamics in improving quantum annealing. ”
Andrew D. King et al, Coherent quantum annealing in a 2000-qubit programmable Ising chain, Nature Physics (2022). DOI: 10.1038 / s41567-022-01741-6
Jacek Dziarmaga, Quantum phase transition dynamics: the exact solution to the quantitative Ising model, physical review messages (2005). DOI: 10.1103/ PhysRevLett.95.245701
Alexander Keesling et al, Quantum Kibble-Zurek Mechanism and Critical Dynamics in a Programmable Rydberg Simulator, temper nature (2019). DOI: 10.1038 / s41586-019-1070-1
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