In a new development that is most likely to establish a new industry standard, scientists at Cambridge Quantum (CQ) have created a new algorithm for solving combinatorial optimization problems that have become widespread in business and industry, like the travelling salesman, vehicle routing or job shop scheduling, “using near-term quantum computers.”
Mathematical conundrums such as these can be found at the core of a wide range of real-world optimization challenges like designing manufacturing processes, filling delivery trucks or even routing passenger jets.
As the level of automation in global businesses increases, optimization algorithms running on some of the most high-performance classical computers are “forced to trade accuracy for speed,” according to release shared with CI.
In this paper released on the pre-print repository arXiv, CQ scientists have introduced the Filtering Variational Quantum Eigensolver (F-VQE) “to make combinatorial optimization more efficient.”
Using the Honeywell System Model H1 quantum computer, the new approach managed to outperform current “gold standard” algorithms like the Quantum Approximate Optimization Algorithm (QAOA) and the original VQE, “reaching a good solution 10 to 100 times faster.”
The CQ research team has been led by Michael Lubasch, Ph.D. and David Amaro, Ph.D. with co-authors Carlo Modica, Ph.D., Matthias Rosenkranz, Ph.D., and Marcello Benedetti, Ph.D.. The scientists are reportedly a part of CQ’s Machine Learning and Quantum Algorithms team that is headed by Dr. Mattia Fiorentini.
F-VQE leverages a method shared in this paper by CQ in September last year, which showed how a quantum circuit may be “decomposed into smaller circuits and run using fewer qubits without losing quantum advantage.”
As explained in the release:
“As a result, a 23-qubit problem was solved by using only up to 6 hardware qubits at time. CQ’s scientists also demonstrated that the new approach is highly adaptable for use with noisy intermediate-scale quantum (NISQ) era machines. These advancements increase the scale of the optimisation problems that are within reach of today’s NISQ computers.”
Our scientists are “honing” in on workable methods for today’s quantum computers, Fiorentini stated.
Fiorentini also mentioned that they want enterprises and governments “to achieve quantum advantage for general purpose tasks more quickly, and our experience of working with large industrial partners facilitates a deep understanding of the needs of practitioners today.”
Fiorentini added that F-VQE has “distinct” advantages over previous quantum algorithms: “it finds good candidate solutions faster and uses quantum hardware much more efficiently.” He also noted that F-VQE could have “a transformative impact, helping to solve previously intractable problems across business and industry.”
Ilyas Khan, CEO of CQ, stated:
“Our team of scientists is relentlessly focused on closing the gap between the real-world limits of classical computation and the quantum advantage that will be available in the NISQ era. They are establishing new standards in quantum computing and their research will inspire rapid further progress.”
Tony Uttley, President of Honeywell Quantum Solutions, remarked:
“This project illustrates the exciting advances occurring in quantum computing. By developing algorithms that do more with fewer qubits and running them on the best hardware possible, we are making significant progress toward solving real-world problems sooner than expected.”
Established in 2014 and backed by the world’s leading quantum computing firms, CQ is an international leader in quantum software and quantum algorithms, “enabling clients to achieve the most out of rapidly evolving quantum computing hardware.”
CQ maintains business offices in Europe, USA, as well as Japan.
On 8 June 2021, CQ confirmed a merger with Honeywell Quantum Solutions which is expected to be finalized during Q3 2021. For additional information, check here.
It’s worth noting that quantum computing has advanced considerably during the past 2 decades and has vast applications in Fintech.
Giant Wall Street investment bank Goldman Sachs (NYSE:GS) recently revealed that it’s made a major quantum computing breakthrough. Goldman said that it’s working on computer algorithms that may be used on hardware that could be available within the next 5 years.
Goldman Sachs has reportedly been working closely with Silicon Valley firm QC Ware for several years. Both organizations have been exploring the use of quantum computing algorithms in finance applications. They’ve also looked into how the technology will be able to outperform traditional binary computers for financial software.
Researchers at Goldman and QC Ware have been studying how quantum computers can be tapped for the Monte Carlo algorithm – which is used to determine or assess risk and also to simulate market prices for various financial instruments.