IBM Quantum System One from site

In conjunction with its virtual Think event, IBM today introduced an enhanced Qiskit Runtime Software for quantum computing, which it says demonstrated 120x speedup in simulating molecules. Qiskit is IBM’s quantum software development platform; the new containerized runtime software runs in the IBM Cloud where it leverages IBM classical hardware and proximity to IBM quantum processors to accelerate performance.

An IBM blog by researchers Blake Johnson and Ismael Faro said, “Last fall, we made the ambitious promise to demonstrate a 100x speedup of quantum workloads in our IBM Quantum roadmap for scaling quantum technology. Today, we’re pleased to announce that we didn’t just meet that goal; we beat it. The team demonstrated a 120x speedup in simulating molecules thanks to a host of improvements, including the ability to run quantum programs entirely on the cloud with Qiskit Runtime.”

The necessarily hybrid nature of quantum computing has spurred community-wide efforts to accelerate the classical portion of the work in recent years. Not only have there been improvements in the control elements handled by classical systems, but also there have been steady advancements in understanding how to break up the quantum algorithms themselves with portions of the algorithm run on classical systems. Co-or-nearby-location of classical and quantum compute systems has also shown advantages.

The latest IBM test demonstration repeated a past simulation of lithium hydride molecule. Here’s an excerpt from the blog:

“Back in 2017, the IBM Quantum team demonstrated that a quantum computer could simulate the behavior of the  lithium hydride molecule. 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. Now, we can solve the same problem in just nine hours — a 120x speedup.

“A host of improvements went into this feat. Algorithmic improvements reduced the number of iterations of the algorithm required to receive a final answer by two to 10 times. Improvements in system software removed around 17 seconds per iteration. Improved processor performance led to a 10x decrease in the number of shots, or repeated circuit runs, required by each iteration of the algorithm. And finally, improved control systems such as better readout and qubit reset performance reduced the amount of time per job execution (that is, execution of each batch of a few dozen circuits) from 1,000 microseconds to 70 microseconds.”

The researchers noted that until recently IBM mostly focused on the execution of quantum circuits, or sequences of quantum operations, on IBM Quantum systems. “However, real applications also require substantial amounts of classical processing. We use the term quantum program to describe this mixture of quantum circuits and classical processing. Some quantum programs have thousands or even millions of interactions between quantum and classical. Therefore, it is critical to build systems that natively accelerate the execution of quantum programs, and not just quantum circuits,” wrote the Johnson and Faro.

Paul Smith-Goodson, analyst-in-residence for quantum computing at Moor Insights & Strategy, agreed, “Not only is it more efficient, it is also more technically expedient to have classical resources in the cloud. The IBM classical machines are designed and maintained specifically for the process. In that way the end user doesn’t have to worry about such things such as control software, cloud software, capacity, etc.”

Providing context for the lithium hydride simulation, Smith-Goodson said, “Running chemistry simulations is a complicated process. You’re looking for the lowest energy state of the molecule. To find it requires a back and forth process between a classical computer and a quantum computer running many nested loops across the cloud. The process, called ansatz, allows a researcher to make calculations on the classical computer using iterative data from the quantum machine and making continuous adjustments until the ground state is found.

“This process takes a long time, depending on many factors including technical constraints/issues with the classical computer. Qiskit Runtime makes it much easier to run quantum algorithms like VQE (Variational Quantum Eigensolver) to simulate molecules,” said Smith-Goodson.

Along those lines, IBM reported the final boost in performance came from the introduction of the Qiskit Runtime, “Rather than building up latencies as code passes between a user’s device and the cloud-based quantum computer, developers could run their program in the Qiskit Runtime execution environment, where the IBM hybrid cloud handles the work for them. New software architectures and OpenShift Operators allow us to maximize the time spent computing, and minimize the time spent waiting,” wrote the researchers.

Big Blue reiterated its commitment to finding practical quantum computing use cases: “We hope that the Qiskit Runtime will allow users around the world to take full advantage of the 127 qubit IBM Quantum Eagle device slated for this year — or the 1,121-qubit Condor device planned for 2023. Qiskit Runtime is currently in beta for some members of the IBM Quantum Network.”

Overall, activity in quantum computing has mushroomed in recent years, particularly following launch of the U.S. National Quantum Initiative. There’s now a global race to achieve practical quantum computing.

Recent DOE work showcases some of the concrete progress being made. Consider this observation from Raphael Pooser, of Oak Ridge National Laboratory and a PI on DOE’s Quantum Testbed Pathfinder Project, “Two or three years ago, we were seeing that we could work really hard to get interesting results on quantum chemistry out of the quantum computers of the day. The concept of chemical accuracy, which is sort of the gold standard, was in a nutshell very hard to attain on the hardware if you didn’t have an in-house device that you’d built yourself. Fast forward to today, we just got through running this benchmark on the latest quantum computers from IBM, and we have some unpublished results from other devices. These systems’ performances have grown by leaps and bounds. It’s gone from being very hard to achieve chemical accuracy on those same problems three years ago to becoming routine now,” said Pooser. (See HPCwire coverage, Fast Pass Through (Some of) the Quantum Landscape with ORNL’s Raphael Pooser.)

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