Our expertise lies at the intersection of industry’s intractable problems and the latest advancements in the quantum and classical hardware ecosystem. 1QBit provides industry-leading partners in finance, hardware manufacturing, health care, energy, advanced materials, and the life sciences with solutions to high-value optimization, simulation, hardware design, and machine learning problems.
1QBit’s teams work closely with our industry partners to identify high-value problems that can be better solved with new approaches on advanced hardware. Through our relationships with the world’s leading hardware providers and research institutions, we research, benchmark, and prototype applications on the most advanced quantum and classical architectures in development to understand which industry problems they can address more efficiently than the prevailing technology.
Our professional services team works with Fortune 100 clients in the life sciences, finance, health care, advanced materials, and energy industries. Our core services build on 1QBit’s proprietary technology to develop new methods for solving our partners’ highest-value problems. 1QBit typically works with our partners’ internal teams in a four-stage process: discovery, problem identification and (re)casting, hardware matching, and solution delivery.
1QBit’s solutions are delivered in the form of APIs built on our hardware-agnostic platform, which has been built to leverage quantum chips as coprocessors to offload calculations poorly suited to classical hardware and advanced classical devices.
We conduct in-depth research on the various hardware architectures in development around the world and develop a strong understanding of the types of industry problems each is best suited to solve. 1QBit’s software solutions deliver best-in-class results using the optimal mix of classical and quantum solvers, based on their current processing capabilities and applicability. Our hardware-agnostic platform is continually updated by our research and software teams to integrate the latest hardware at the solver level, allowing our partners to continually benefit from computational progress without the need to refactor their original applications.
Quantum Opportunity Assessment
1QBit begins each engagement by gaining an understanding of the computationally intensive problems faced by our partners. We identify which problems can benefit from the various quantum computing architectures, and provide a recommendation for which technologies will have an impact on our partners’ businesses and their industries.
We prototype the identified solutions by reformulating them to run on the classical and quantum hardware that is best suited to solve them. The prototype includes the best possible classical solution, which is often quantum-inspired, as well as the best possible formulation for the quantum architecture that has demonstrated the strongest near-term results. Our industry partners are able to test the results of the proof of concept against their existing solutions and provide feedback on the output, prior to software production.
The validated algorithms from our proof of concept are developed into production-level code that is implemented on our hardware-agnostic platform. We provide our partners with an API endpoint which integrates with their existing application to deliver superior results. Our hardware-agnostic platform enables the API to access a growing set of algorithms and hardware integrations maintained by 1QBit’s team. As quantum hardware and our interfacing techniques improve, the API endpoint is continually updated and our partners benefit from advances in hardware without the need to refactor their applications.
“By and large, I rejected many interesting paths to portfolio optimization and risk management just because they were incredibly hard to solve, if not impossible, with the tools at hand. It is a mind-set change to now seek out the nearly impossible to solve problems with quantum computing, rather than to avoid them as a waste of research.”
– Bluford Putnam, Chief Economist and Head of Data Science Operations, CME