Fault-Tolerant Quantum Simulations of Chemistry in First Quantization
Yuan Su, Dominic W. Berry, Nathan Wiebe, Nicholas Rubin, Ryan Babbush

TL;DR
This paper analyzes and optimizes resource requirements for first quantized quantum algorithms in chemistry, providing explicit circuits, improvements, and comparisons to second quantization, demonstrating potential practical advantages.
Contribution
It offers the first explicit circuit implementations for first quantized quantum chemistry simulations and introduces optimizations reducing circuit complexity significantly.
Findings
First quantized algorithms can outperform second quantized methods in certain scenarios.
Optimizations reduce circuit complexity by about a thousandfold for modest systems.
Qubitized algorithms often require less surface code spacetime volume for large-scale simulations.
Abstract
Quantum simulations of chemistry in first quantization offer important advantages over approaches in second quantization including faster convergence to the continuum limit and the opportunity for practical simulations outside the Born-Oppenheimer approximation. However, as all prior work on quantum simulation in first quantization has been limited to asymptotic analysis, it has been impossible to compare the resources required for these approaches to those for more commonly studied algorithms in second quantization. Here, we analyze and optimize the resources required to implement two first quantized quantum algorithms for chemistry from Babbush et al that realize block encodings for the qubitization and interaction picture frameworks of Low et al. The two algorithms we study enable simulation with gate complexities and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
