Questions

What I’m more interested in lies closer to the top of the list. There is roughly an inverse correlation with my level of expertise.

• What made some research labs, small or large, so successful, and can these same principles be applied to a quantum computing-specific lab?
• What is the best way for training someone to ask and answer new & important questions? Similarly, can we formalize what it takes to have “good taste in research”, or good meta-decision-making abilities? Is there a correlation between choosing good research problems vs. being able to solve them?
• Which best practices for conducting research should be formalized and taught to new researchers?
• What would the equivalent of a Hippocratic oath but for scientists look like? (My take is here.) Should scientists push for one, and how would they advocate for its adoption amidst the forces of industry research labs, publishers, and academia?
• Apparently, the impact of research is more incremental than before, and this can be linked to “a narrowing in the use of previous knowledge." How much new knowledge is produced per unit of research output, and how much previous knowledge is used to generate it, now vs. before? More generally, how can the sum total of knowledge be quantified, so as to quantify research progress?
• What are examples of deep technologies where interest & investment (from the government, investors, and the public) came at the right time and in the right quantities?
• What cultural differences in research are there, and how can these gaps be bridged?
• At which length scales are physical phenomena hardest to probe?
• Historically, how useful has it been in industry to simulate materials and molecules from first principles? Do we expect improved simulation capabilities to make a substantial difference? (Some light research on this topic here.)
• On the path toward large-scale & fault-tolerant quantum computers, which quantum simulations can be executed to demonstrate checkpoints?
• Is it possible to achieve a practical quantum advantage before fault tolerance?
• Non-equilibrium quantum dynamics is often cited as the first field where we expect a quantum advantage. What is the path from learning something fundamental about non-equilibrium quantum dynamics to practical utility?
• How can a machine learning model be used to discover new physical phenomena, other than serving as a null hypothesis?
• Is there a simple way to quantify the overhead of simulating non-native many-body systems on an analogue quantum computer?
• What is the most efficient way to encode mixed fermion-boson systems on a qubit-based quantum computer?
• Is vibrational polariton chemistry a real & measurable effect, what is its origin, and can it be harnessed under practical scenarios?