Q-Pilot: Field Programmable Qubit Array Compilation with Flying Ancillas
Not on the map. Why?
Abstract (arXiv)
Neutral atom arrays have become a promising platform for quantum computing, especially the field programmable qubit array (FPQA) endowed with the unique capability of atom movement. This feature allows dynamic alterations in qubit connectivity during runtime, which can reduce the cost of executing long-range gates and improve parallelism. However, this added flexibility introduces new challenges in circuit compilation. Inspired by the placement and routing strategies for FPGAs, we propose to map all data qubits to fixed atoms while utilizing movable atoms to route for 2-qubit gates between data qubits. Coined flying ancillas, these mobile atoms function as ancilla qubits, dynamically generated and recycled during execution. We present Q-Pilot, a scalable compiler for FPQA employing flying ancillas to maximize circuit parallelism. For two important quantum applications, quantum simulation and the Quantum Approximate Optimization Algorithm (QAOA), we devise domain-specific routing strategies. In comparison to alternative technologies such as superconducting devices or fixed atom arrays, Q-Pilot effectively harnesses the flexibility of FPQA, achieving reductions of 1.4x, 27.7x, and 6.3x in circuit depth for 100-qubit random, quantum simulation, and QAOA circuits, respectively.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Nov 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 2; 2024: 0; 2025: 0; 2026: 1.
3 papers.
- 2023DGR: Tackling Drifted and Correlated Noise in Quantum Error Correction via Decoding Graph Re-weightingcited by 3
- 2023RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Trainingcited by 2
- 2026KQFuzz: Knowledge-Guided Fuzzing for Quantum Libraries via Large Language Modelscited by 1
- 2026KQFuzz: Knowledge-Guided Fuzzing for Quantum Libraries via Large Language Models28 Jul 2026
- 2023DGR: Tackling Drifted and Correlated Noise in Quantum Error Correction via Decoding Graph Re-weighting27 Nov 2023
- 2023RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training27 Nov 2023