PALO ALTO, Calif., Dec. 10, 2019 /PRNewswire/ -- QC Ware, a quantum computing-as-a-service company, is working in collaboration with Goldman Sachs to gain in-depth knowledge on the near term impact of quantum computers and on the development of new algorithms that will enable quantum computers to outperform concurrent classical computers for computational finance applications. The primary goal is to stay current and develop in-house quantum expertise to gain a "quantum advantage" once the technology is ready for commercial use.
"During the past year, researchers at QC Ware and Goldman Sachs have worked on analyzing the effect of noise on the accuracy of quantum algorithms for approximate counting," said Paul Burchard, lead researcher for R&D at Goldman Sachs. "The research confirmed that the current state-of-the-art quantum algorithms for Monte Carlo sampling and approximate counting will eventually lead to more efficient simulation, but that these algorithms are sensitive to noise in current quantum hardware. As a result, implementing these algorithms on near term quantum hardware will depend on techniques analogous to importance sampling that reduce the circuit depth of these algorithms."
"QC Ware's work with Goldman Sachs is essential to gaining a better understanding of how quantum computing algorithms can eventually be used in finance and how to make the practical use of quantum computing a reality faster," said Matt Johnson, CEO, QC Ware.
"QC Ware believes that quantum computing will significantly impact the future of finance," said Wim van Dam, Head of Quantum Algorithms, QC Ware. "Current quantum computers are limited in the number of qubits and the circuit depth that they support. We are focused on applying QC Ware's expertise in meeting this challenge by delivering access to QC Ware's Forge cloud service to test near-term quantum applications and help build in-house quantum computing skills."
Paul Burchard will discuss the company's adoption of quantum computing, including the collaboration with QC Ware, on the Finance Panel at the Q2B conference on December 12 at the Fairmont Hotel in San Jose, CA.
About Goldman Sachs
The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
About QC Ware
QC Ware is a quantum computing-as-a-service company building enterprise solutions that run on quantum computing hardware. The company's objective is to make quantum computing easily accessible to classically-trained data scientists and to offer performance speed-ups on near-term hardware. QC Ware is working towards that goal with one of the world's strongest teams of quantum algorithms scientists. The company is based in Palo Alto, it recently opened an office in Paris, and it plans to launch a Tokyo office in 2020. For more information, please visit qcware.com. QC Ware also hosts the annual "Q2B - Practical Quantum Computing" conference each December in Silicon Valley.
The three-day conference brings industry, government and research institutions together to stimulate application discovery and development. For more information, please visit q2bconference.com
About QC Ware's Forge cloud service
QC Ware recently launched the public beta of its cloud service, Forge, to enable large enterprises and public-sector organizations to start building quantum skills and prepare for the potential disruption that quantum computing will bring to the market. Forge allows enterprise users with no presumed quantum computing expertise to run problems on a wide range of quantum computing hardware platforms and simulators. Forge users can access end-to-end implementations of proprietary and open-source algorithms for binary optimization, chemistry simulation, and machine learning.
SOURCE QC Ware Corp.