12-24-2025, 06:26 AM
I'm a researcher in computational chemistry, and I'm trying to get a practical grasp on the current state of quantum computing for simulating molecular systems, beyond the theoretical hype. I've read about variational quantum eigensolvers and other NISQ-era algorithms, but it's unclear how these translate to real-world utility on today's noisy hardware. For those working at the intersection of quantum computing and applied science, what are the most promising near-term applications that could actually outperform classical supercomputers? How do you approach algorithm design and error mitigation for problems like catalyst discovery or protein folding, and which cloud-based quantum processors or simulators have you found most effective for prototyping and benchmarking these approaches?