Quantum Computing May Fine Prove To Be Helpful Sooner Than Expected

Description of Quantum Computing May Fine Prove To Be Helpful Sooner Than Expected

With the right algorithms, even error-prone quantum devices could be useful, especially for financial professionals.
For most scientists, a quantum computer capable of solving large-scale business problems remains a prospect that is distant in the future, and will not be realized for at least another decade. However, researchers from the American banking giant Goldman Sachs and the quantum computing company QC Ware have already designed new quantum algorithms which, according to them, could considerably improve the efficiency of certain critical financial operations, on material that could be available in just five years.
Rather than wait for a real quantum computer, financial professionals could start running the new algorithms on quantum hardware in the short term and reap the benefits of the technology, even if the quantum devices are not yet developed.
For many years, Goldman Sachs has studied the potential of quantum technologies to disrupt the financial industry. In particular, the researchers of the American giant have explored the means of using quantum computing to optimize what are called Monte Carlo simulations, which consist in fixing the price of financial assets according to the evolution of the price. other related assets over time, and therefore to take into account the risk inherent in the various options, stocks, currencies and commodities.
Technology closely scrutinized
Due to the vast array of possibilities, this is one of the most IT-intensive financial tasks, requiring a lot of predictions about different market movements. Quantum computing has long been seen as a potential way to speed up these risk assessments thanks to the extraordinary computing power that this technology is expected to bring compared to conventional approaches.
There are many quantum algorithms already in existence that have been found to multiply up to 1,000 times the speed of Monte Carlo calculations that could transform the way financial markets work - but only once these algorithms are deployed. on a quantum device capable of running the program and getting precise results. Previous work, conducted by Goldman Sachs in conjunction with IBM, for example, estimated that to gain a quantum advantage, one would need a device supporting 7,500 logical qubits. By way of comparison, IBM is currently working on bringing a 127-qubit processor to market this year.
Faster than music?
It's not just about counting qubits: for quantum computers to reliably solve calculations, devices will also need to be optimized to avoid errors. Today's quantum processors have very high error rates, and according to QC Ware, it will be 10 to 20 years before the error-correcting quantum hardware needed to effectively perform Monte Carlo simulations becomes available.
"How can we cut the current lead time in half while still achieving significant acceleration?" The company's researchers ask in a blog post describing the new research. To achieve this goal, the team sacrificed some computational speed in exchange for some hardware gains. Scientists have devised two new quantum algorithms that increase the speed from 1,000 times to 100 times - but they also require a smaller circuit, which is expected to be available within the next five to ten years.
“Research teams at Goldman Sachs and QC Ware have taken an innovative approach to the design of quantum Monte Carlo algorithms by trading acceleration in performance for reduced error rates,” said Iordanis Kerenidis, Head of Algorithms at QC Ware. “Through rigorous analysis and empirical simulations, we have demonstrated that our shallow Monte Carlo algorithms could result in the ability to perform Monte Carlo simulations on quantum hardware that could be available in five to ten years.”
No matter what mistakes
The acceleration, although more moderate than that of other quantum algorithms such as Monte Carlo without QFT, remains significant; and according to scientists, the method will effectively cut the use time in half.
Goldman Sachs and QC Ware's plans in this area reflect an industry that is increasingly focusing on the short-term benefits of quantum computing, despite imperfections that still hold back quantum devices.
Whether its changing algorithms, combining quantum and classical techniques, or testing and comparing different approaches to quantum computing, researchers and companies are working to find the methods that will make quantum computers useful in one minimum time. The two algorithms devised by Goldman Sachs and QC Ware are therefore a further step towards the goal of finding quantum algorithms compatible with the noisy mid-scale devices characteristic of the present day.