Welcome to another episode of The New Quantum Era Podcast hosted by Kevin Rowney and Sebastian Hassinger. Today, they are joined by James Whitfield, who's a professor at Dartmouth College and is a colleague of Sebastian’s at Amazon Web Services’ quantum team. James has a quantum chemistry background, and, as a result, he brings that sensibility to his work in quantum information science.In today’s episode, they cover three main topics:
They talk about the specific areas of quantum chemistry where progress in quantum computation can be seen towards cracking key problems.
They address the intuitive nature of perceiving entanglement within quantum states and how those manifest in quantum algorithms (excellent material for people trying to get on top of that challenging concept).
James shares his perspectives on enhancing pedagogy in Quantum Information Science, both in the K -12 range and at the graduate level. 
Key Takeaways:[4:06] James talks about his background.[6:37] What's the simplest way to explain what quantum chemistry is?[8:18] James shares framing remarks on the merit of quantum computing in these early phases regarding its applicability to physical chemistry. [10:30] James talks about the concept of time evolution.[11:13] James explains the differences between the dynamical nature and the optimization nature of a problem.[13:06] James speaks of what happens inside of quantum time evolution.[14:54] Geometry optimization is only one problem that people discuss.[16:47] James talks about the ‘clamped nuclei’ approximation.[17:33] James describes the two ways of thinking about the Schrodinger equation.[19:59] What types of things would we be able to do if we could model time intervals? [24:09] Does James think that, in terms of time evolutions,  fairly large numbers of fault-tolerant qubits are needed to do useful calculations? Or is there a class of problems that NISQ or even Analog Devices like QuEra could be helpful with?[27:13] What is entanglement entropy? And what does that mean for computation?[30:48] Why do people believe in the extra power of quantum computing?[32:37] James defines coherence and decoherence.[34:25] James explains why measuring the growth rate of entanglement entropy over time is one way to capture the richness of the other quantum state.[36:42] James talks about the application of quantum chemistry.[42:55] James believes that, eventually, these will all converge.[43:54] James shares one of his projects about how we use quantum computers to benchmark what people do today.[45:37] The hard part is not the implementation; James explains why.[47:53] James uses the analogy of the robotics challenge.[48:41] James talks about the event called: Quantum Computing Quantum Chemistry Benchmark. 2023.[49:25] Is there an optimum starting point for quantum education? [52:45] James works with no negative probabilities.[55:05] James talks about quantum mechanics and atomic physics.[56:25] Quantum and AI often get grouped into the same category in terms of technology.[57:46] James shares what he enjoys the most about his work.[59:30] Does James think that eventually, software will eat all of these disciplines of science related to quantum information, and we will end up with scientists writing code, and that code will solve problems in chemistry, physics, or other scientific areas through writing software?[1:02:40] Kevin and Sebastian share the highlights of a fantastic conversation with James Whitfield.Mentioned in this episode:Visit The New Quantum Era PodcastComputational Complexity in Electronic Structure James Whitfield, Peter J. Love, Alan Aspuru-GuzikLimitations of Linear Cross-Entropy as a Measure for Quantum Advantage Xun Gao, Marcin Kalinowski, Chi-Ning Chou, Mikhail D. Lukin, Boaz Barak, Soonwon Choi2023 Quantum Chemistry on Quantum Computers Benchmarking ContestTweetables and Quotes:“To actually get what the strength of that spring should be, you need to know what the electrons are doing, and that's whe