My IBM Quantum colleague Dr. Andrew Wack and I are hosting a minitrack at the Hawaii International Conference on System Sciences (HICSS) 2022.
The description of the minitrack is:
There is no question that quantum computing will be a technology that will spur breakthroughs in natural science, AI, and computational algorithms such as those used in finance. IBM, Google, Honeywell, and several startups are working hard to create the next generation of “supercomputers” based on universal quantum technology.
What exactly is quantum computing, how does it work, how do we teach it, how do we leverage it in education and research, and what will it take to achieve these quantum breakthroughs?
The purpose of this minitrack is to bring together educators and researchers who are working to bring quantum computing into the mainstream.
We are looking for reports that
- improve our understanding of how to integrate quantum computing into business, machine learning, computer science, and applied mathematics university curriculums,
- describe hands-on student experiences with the open-source Qiskit quantum software development kit, and
- extend computational techniques for business, finance, and economics from classical to quantum systems.
It is part of the Decision Analytics and Service Science track at HICSS.
Please consider submitting a report and sharing this Call for Papers with your colleagues.
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Dancing with Qubits: Quantum Computing and Finance update
In section 1.5 of my quantum computing book Dancing with Qubits, I discuss potential applications of the technology to financial services. An excellent survey article by my IBM Quantum colleagues is now on arXiv that updates and goes into much greater detail than what I covered.
“Quantum computing for Finance: state of the art and future prospects” by Daniel J. Egger, Claudio Gambella, Jakub Marecek, Scott McFaddin, Martin Mevissen, Rudy Raymond, Andrea Simonetto, Stefan Woerner, and Elena Yndurain has this abstract:
This paper outlines our point of view regarding the applicability, state of the art, and potential of quantum computing for problems in finance. We provide an introduction to quantum computing as well as a survey on problem classes in finance that are computationally challenging classically and for which quantum computing algorithms are promising. In the main part, we describe in detail quantum algorithms for specific applications arising in financial services, such as those involving simulation, optimization, and machine learning problems. In addition, we include demonstrations of quantum algorithms on IBM Quantum back-ends and discuss the potential benefits of quantum algorithms for problems in financial services. We conclude with a summary of technical challenges and future prospects.
I highly recommend it.
