# Inverse-Transpilation: Reverse-Engineering Quantum Compiler Optimization Passes from Circuit Snapshots

arXiv: https://arxiv.org/abs/2504.19113 · HTML: https://mlsanity.com/paper/2504.19113/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 21 references that are in the map.
- First posted on arXiv 27 Apr 2025.

## Builds on (most cited first, 2 of 2)

- [Security Attacks Abusing Pulse-level Quantum Circuits](https://mlsanity.com/paper/2406.05941/) (2024)
- [Quantum Circuit Compiler for a Shuttling-Based Trapped-Ion Quantum Computer](https://mlsanity.com/paper/2207.01964/) (2022)

## Built on by (most cited first, 1 of 1)

- [Neural Guided Sampling for Quantum Circuit Optimization](https://mlsanity.com/paper/2510.12430/) (2025)

## Abstract (arXiv)

Circuit compilation, a crucial process for adapting quantum algorithms to hardware constraints, often operates as a ``black box,'' with limited visibility into the optimization techniques used by proprietary systems or advanced open-source frameworks. Due to fundamental differences in qubit technologies, efficient compiler design is an expensive process, further exposing these systems to various security threats. In this work, we take a first step toward evaluating one such challenge affecting compiler confidentiality, specifically, reverse-engineering compilation methodologies. We propose a simple ML-based framework to infer underlying optimization techniques by leveraging structural differences observed between original and compiled circuits. The motivation is twofold: (1) enhancing transparency in circuit optimization for improved cross-platform debugging and performance tuning, and (2) identifying potential intellectual property (IP)-protected optimizations employed by commercial systems. Our extensive evaluation across thousands of quantum circuits shows that a neural network performs the best in detecting optimization passes, with individual pass F1-scores reaching as high as 0.96. Thus, our initial study demonstrates the viability of this threat to compiler confidentiality and underscores the need for active research in this area.