Goldman Sachs provided the financial expertise, QC Ware engineers wrote the algorithm and IonQ supplied the hardware. The goal was to test the ability of quantum computers to run Monte Carlo simulations. The partners submitted a research paper for peer review on Tuesday that claims quantum computers are now powerful enough to run these simulations that could solve business problems in finance, robotics, climate change and drug discovery.
The QC Ware and Goldman Sachs teams are designing quantum algorithms companies can use to evaluate risk and simulate prices for a variety of financial instruments.
“You could use this work to compare Apple stock to Microsoft stock, to figure out when Apple moves, what happens to Microsoft stock,” Peter Chapman, IonQ’s president, said. “We’re finding that quantum computers capture the finer points in the model that classical computers are missing.”
Monte Carlo simulations estimate possible outcomes of an uncertain event. This approach makes it easier to see the impact of an individual factor on a particular outcome. These simulations often are run thousands of times to provide a range of possible results.
William Zeng, head of quantum research at Goldman Sachs, said in a press release that working with IonQ has been essential to accelerating the company’s timeline.
“We are working toward enterprise use cases that could have significant impact on strategic investing decisions,” he said.
Iordanis Kerenidis, head of quantum algorithms, international at QC Ware, said in a press release that this latest research shows how the combination of algorithms that reduce hardware requirements and more powerful near-term quantum computers makes it possible to run these simulations.
“While QC Ware has designed novel practical quantum software for enterprise implementation, IonQ has built unique hardware with quantum gates of high enough quality to run these algorithms,” he said.
According to Chapman, Goldman Sachs tried to run the Monte Carlo simulation on other quantum hardware but the only successful attempt was on IonQ’s system.
The experiment was performed on the newest generation IonQ quantum processing unit (QPU), which features improved fidelity and throughput compared to previous generations. This allows for deeper circuits with many shots to be run over a significantly shorter period of time than previously possible, according to the company. The combination of these features makes it possible for the first time to run algorithms of this nature.
Machine learning and quantum computing
Chapman said the work on Monte Carlo simulations is the company’s latest experiment with machine learning and quantum computing. IonQ has recently tested its quantum computers in image recognition and the generation of synthetic data with partner Fidelity Center of Applied Technology.
He sees machine learning as the first way for quantum computing investments to generate ROI.
“Machine learning is looking pretty good on quantum computers,” Chapman said.
The ML projects are in the proof of concept phase, Chapman said, and will need more qubits to be commercially viable.
“The Fidelity work was a comparison of two variables and you really need 10 variables to be commercially viable,” he said.
IonQ also recently announced a research partnership with the University of Maryland and a business consulting partnership with Accenture. Chapman said that IonQ is the most collaborative company in the quantum industry.
“Competition is good for customers and we need to work together because this is going to be a huge market,” he said. “There’s not going to be just one company at the end.”
The technical details of the Monte Carlo simulation are outlined in a new research paper that has been submitted for peer review. The paper, “Low depth amplitude estimation on a trapped ion quantum computer,” was written by Tudor Giurgica-Tiron and William Zeng of Goldman Sachs; Sonika Johri, Jason Nguyen, Neal Pisenti, Ksenia Sosnova and Ken Wright and of IonQ; and Iordanis Kerenidis and Anupam Prakash of QC Ware.
QC Ware is a quantum-as-a-service company focused on building applications for near-term quantum computing hardware. The company’s global enterprise and government sector customers include Aisin Group, Airbus, BMW Group, Equinor and Total.