HPCwire Person to Watch Marco Pistoia wears a lot of hats at JPMorgan Chase & Co.: managing director, distinguished engineer, head of global technology applied research and head of quantum computing. That work with JPMorgan started in 2020; prior to that, Pistoia was a senior manager, distinguished research staff member and master inventor at IBM’s Thomas J. Watson Research Center, where he worked for 24 years. 

Congratulations on your selection as a 2023 HPCwire Person to Watch. The financial services sector has long been an early adopter of advanced technology. What are the top nearest-term use cases on which quantum computing will be applied? Of those cases, which will JPMorgan Chase deploy first and when do you expect will that happen?

Indeed, the financial services sector lends itself to quantum computing, for two main reasons: the abundance of use cases, and the fact that in finance, time is of the essence. Markets are very volatile, and for this reason financial applications need to be executed in real time without sacrificing accuracy. At JPMorgan Chase, we are particularly interested in derivative pricing, various optimization problems (particularly for financial portfolios), and use cases in the domain of machine learning, such as extractive text summarization. In general, any use case that exhibits exponential complexity are of interest to us, because quantum computing has the potential to reduce the complexity of problems, making them more scalable.

Data security is critical in financial services and the prospect of quantum computers using some form of Shor’s algorithm to break conventional RSA codes is terrifying. Last fall you talked about accelerating efforts to use quantum computers for decryption purposes, and cited a study that suggested just 13,436 qubits could be used to break a public/private key encryption although it would take almost 6 months to do so. Meanwhile, quantum hardware providers are already showing the prospect of thousands of qubits in their roadmaps. What’s your sense of the imminence of that data security threat posed by quantum computers? How close is it and what is JPM Chase doing to prepare?

It is hard to predict when quantum computers will become sufficiently powerful to break today’s asymmetric cryptography. Indeed, quantum hardware providers are making significant progress, showing roadmaps that promise usable computers with hundreds of high-quality qubits (if not thousands), coming in the next few years. Unfortunately, quantum threats are already present today. The advent of quantum computing is enabling a new type of cyber-attack, which the National Security Agency (NSA) defined as “harvest now, decrypt later,” indicating that attackers do not need to wait for a powerful quantum computer to break today’s cryptography; they can—and they are already known to be doing this—take a snapshot of confidential data encrypted today, with the intent of decrypting it when a sufficiently powerful quantum computer becomes available.

To this end, JPMorgan Chase is simultaneously pursuing two complementary solutions: (a) Post Quantum Cryptography (PQC), consisting of new, classical cryptographic algorithms that were designed be resistant to known quantum attacks, and (b) Quantum Key Distribution (QKD), the only cryptographic protocol mathematically proven to be unconditionally secure. QKD leverages principles of quantum mechanics and allows two parties to generate and use the same secret key for secure communication, with the very desirable property of instantaneous detection of eavesdroppers. In 2022, JPMorgan Chase, Toshiba and Ciena demonstrated the first QKD network capable of supporting production-quality, mission-critical applications, including Blockchain.

Recently a number of quantum-inspired approaches have begun to be applied to optimization (and other) problems in finance and other areas. What is your take on the prospects for use of quantum-informed algorithms and techniques on classical systems as practical, near-term alternatives to using pure quantum computers?

At this time, quantum computers are not yet usable in production because they do not have the number of qubits necessary to surpass classical computers, and error correction is still at the prototype level. The value of research in quantum algorithms is not just about developing new quantum methods, but also about the careful investigation of complex classical tasks and existing bottlenecks. Quantum Computing may also inspire new classical algorithms beyond the current state of the art. We welcome the prospect of using quantum-inspired algorithms that work better than traditional classical algorithms to solve high-complexity problems, while we wait for quantum computers to become sufficiently powerful. Generally, quantum computing will be applied to very complex use cases, where classical computing poses unavoidable limitations.y

What technology trends – and in particular emerging trends – do you find most notable? Any areas you are concerned about, or identify as in need of more attention/investment?

Beyond quantum computing, there are other areas of research that we are pursuing at JPMorgan Chase to address notable emerging trends. For example, JPMorgan Chase is making a significant effort towards transitioning some of its use cases to Augmented and Virtual Reality (AR/VR) to maximize their efficiency and user experience. We are also enhancing our working environment with Internet of Things (IoT) and 5G technology, which is another area of active research aiming to enable connectivity and productivity in working environments.

What inspired you to pursue a career in STEM and what advice would you give to young people wishing to follow in your footsteps?

I always found myself interested in science and technology. I earned my Bachelor of Science and Master of Science degrees in Mathematics from the University of Rome, Italy, and my Ph.D., also in Mathematics, from New York University. Math is the foundation of any scientific discipline. Therefore, my recommendation to my own children, as well to anyone who wants to work in science and technology, is to invest as much time and energy as they can in learning math well.

Outside of the professional sphere, what can you tell us about yourself – unique hobbies, favorite places, etc.? Is there anything about you your colleagues might be surprised to learn?

I am a passionate body builder. I lift heavy weights every day and I scrupulously watch my diet to make sure I maximize protein intake and minimize fats and carbs. Body building is not just a hobby for me, but a discipline that I use to feel better about myself, discharge stress/negativity, and live a healthier lifestyle.

Pistoia is one of 12 HPCwire People to Watch for 2023. You can read the interviews with the other honorees at this link.