[Paper Review] Fault-tolerant resource estimate for quantum chemical simulations: Case study on Li-ion battery electrolyte molecules

Isaac H. Kim, Eunseok Lee+4 more|arXiv (Cornell University)|Apr 21, 2021

Machine Learning in Materials Science4 citations

TL;DR

This paper presents a fault-tolerant resource estimate for simulating Li-ion battery electrolyte molecules using fusion-based quantum computing (FBQC) on a photonic platform. By leveraging parallel magic state factories and a novel method for simultaneous magic state consumption, the authors achieve an order-of-magnitude reduction in runtime without increasing hardware footprint, enabling efficient, scalable quantum chemistry simulations for industrial applications.

ABSTRACT

We estimate the resources required in the fusion-based quantum computing scheme to simulate electrolyte molecules in Li-ion batteries on a fault-tolerant, photonic quantum computer. We focus on the molecules that can provide practical solutions to industrially relevant problems. Certain fault-tolerant operations require the use of single-qubit "magic states" prepared by dedicated "magic state factories" (MSFs). Producing and consuming magic states in parallel is typically a prohibitively expensive task, resulting in the serial application of fault-tolerant gates. However, for the systems considered, the MSF constitutes a negligible fraction of the total footprint of the quantum computer, allowing for the use of multiple MSFs to produce magic states in parallel. We suggest architectural and algorithmic techniques that can accommodate such a capability. We propose a method to consume multiple magic states simultaneously, which can potentially lead to an order of magnitude reduction in the computational runtime without additional expense in the footprint.

Motivation & Objective

• To estimate fault-tolerant quantum resources required for simulating industrially relevant Li-ion battery electrolyte molecules.
• To analyze the impact of magic state factory (MSF) parallelization on runtime and footprint in fusion-based quantum computing.
• To develop architectural and algorithmic techniques enabling simultaneous consumption of multiple magic states.
• To reduce computational runtime by optimizing magic state usage while maintaining fault-tolerant error protection.
• To provide a fully compiled, architecture-specific resource estimate for FBQC on photonic platforms.

Proposed method

• Uses fusion-based quantum computation (FBQC) with photonic resource states and fusion measurements as core primitives.
• Employs magic state distillation via dedicated magic state factories (MSFs) to implement non-Clifford T-gates.
• Introduces a method to consume multiple magic states in parallel, reducing gate sequence depth.
• Leverages optical delay lines to trade off footprint and runtime, enabling runtime optimization.
• Performs full compilation of quantum algorithms into FBQC primitives, including logical gate decompositions and error correction overhead.
• Analyzes resource costs in terms of logical qubits, gates, and runtime, with a focus on minimizing runtime through parallelism.

Experimental results

Research questions

• RQ1 How can magic state factories be efficiently scaled to reduce runtime in fault-tolerant quantum simulations?
• RQ2 What is the impact of parallel magic state consumption on the overall runtime of quantum chemistry simulations?
• RQ3 To what extent can optical delay lines be used to trade footprint for reduced runtime in FBQC?
• RQ4 How do the resource requirements for simulating Li-ion battery electrolyte molecules scale under fault-tolerant FBQC?
• RQ5 Can architectural and algorithmic optimizations reduce runtime by an order of magnitude without increasing hardware footprint?

Key findings

• The magic state factory (MSF) constitutes a negligible fraction of the total quantum computer footprint, enabling the use of multiple MSFs in parallel.
• Parallel production and consumption of magic states reduce the computational runtime by approximately one order of magnitude.
• The proposed method for simultaneous magic state consumption enables significant speedup without increasing logical qubit or gate count.
• The fully compiled resource estimate shows that runtime can be reduced by a factor of 10 through parallelism, even with fixed hardware footprint.
• The fusion-based quantum computing (FBQC) scheme allows flexible trade-offs between device footprint and runtime via optical delay lines.
• The study provides the first detailed, architecture-specific resource estimate for simulating complex Li-ion battery electrolyte molecules using fault-tolerant photonic quantum computing.