Brian Gaucher (ERVA): Why engineering, not physics, now limits quantum progress

Yuval Boger interviews Brian Gaucher, an experienced engineer and IBM veteran who co-chaired ERVA’s report Engineering Research to Advance Quantum Technologies. Brian explains that while U.S. quantum science remains strong, global competition is accelerating and the key limiter is no longer physics discovery but engineering the path from “lab to fab”—scalable, manufacturable, reliable systems. They discuss why the U.S. should pursue a coordinated, semiconductor-like national strategy with shared pilot lines, standards, metrology, public-private investment, and a broader workforce—not just physicists. They also cover the report’s four pillars (materials, biology, computing, AI), the importance of domestic fabrication, and why biology and quantum sensing may deliver surprisingly near-term impact.

Transcript

​​Yuval: Hello, Brian, and thank you for joining me today.

Brian: My pleasure.

Yuval: So Brian, who are you and what do you do?

Brian: Oh, good question. It’s a long sordid story. I started off as an electrical engineer and hardware designer by background. And I spent probably 10 or 12 years at an aerospace and defense company doing military R&D for satellite and radar communications systems, and then moved to IBM where they wanted me to translate a million dollar communication system to something that would be cost effective in a laptop. That was fun. And that was back in the mid 90s. And I spent a long part of my career in what we call millimeter wave design and CMOS technologies. Eventually I managed a group of folks doing profit and loss on some of our chips up in Poughkeepsie and Fishkill, and then got a chance to come back to research and do a little bit of AI. When the quantum chance came around, it just seemed like a really good opportunity to look at a hard problem, both from a physics perspective, and by then in my career, looking at it from more of a systems and architectural perspective and seeing the challenges that are coming in a new technology and what we might be able to do to get out in front of it and see how we could get to a scalable system. You know, integration, reproducibility, and deployment become really important. And this NSF effort became a really interesting opportunity because they’re really looking at helping to translate deep technical advances into engineering frameworks for policymakers, industry researchers, et cetera. So, you know, there’s a lot of in-betweens all of that, but I’m pretty excited to have a chance to work on this report.