(By Becky Bracken) As part of its ongoing effort to recruit organizations to use their quantum systems to solve real-world challenges, IBM is touting its latest quantum speed record, which they have clocked at a 120-times faster previous versions.
The team previously demonstrated in 2017 the ability of the IBM Quantum System to simulate the behavior of lithium hydride.
“However, the process of modeling the LiH molecule would take 45 days with today’s quantum computing services, as circuits repeatedly passed back-and-forth between a classical and quantum processor and introduced large latencies,” they explained.
With a few tweaks, IBM was able to condense that 45 days into just 9 hours, “… a 120x speedup,” they added.
The IBM team explained they were able to squeeze the performance boost out of their system thanks to few different tweaks.
Algorithm, Software, Processor Improvements
Improvements to their algorithm “…reduced the number of iterations of the algorithm required to receive a final answer by two to 10 times,” IBM said. System software improvements shaved around 17 seconds off each iteration and processor performance advancements cut down the “…number of shots, or repeated circuit runs, required by each iteration of the algorithm,” they added.
Gains in control system performance cut the time needed to execute “each batch of a few dozen circuits) from 1,000 microseconds to 70 microseconds.”
Quantum Cloud Services
IBM has also introduced a new Qiskit Runtime cloud execution environment for quantum developers.
“Rather than building up latencies as code passes between a user’s device and the cloud-based quantum computer, developers can run their program in the Qiskit Runtime execution environment, where the IBM hybrid cloud handles the work for them,” IBM said.
It also provides easy, worldwide access to IBM’s latest quantum solutions.
“We hope that this speedup will allow more developers to experiment with quantum applications in chemistry—and beyond. For example, the Qiskit Runtime will allow users to try out our powerful new quantum kernel alignment algorithm, which searches for an optimal quantum kernel with which to perform machine learning tasks,” they added. “We recently used this algorithm to prove that quantum computers will demonstrate a rigorous speedup over classical computers for supervised machine learning.”