# ScaffCC: Scalable Compilation and Analysis of Quantum Programs

arXiv: https://arxiv.org/abs/1507.01902 · HTML: https://mlsanity.com/paper/1507.01902/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jul 2015.

## Built on by (most cited first, 5 of 5)

- [Recent advances for quantum classifiers](https://mlsanity.com/paper/2108.13421/) (2021)
- [Quantum Neural Network Classifiers: A Tutorial](https://mlsanity.com/paper/2206.02806/) (2022)
- [qgym: A Gym for Training and Benchmarking RL-Based Quantum Compilation](https://mlsanity.com/paper/2308.02536/) (2023)
- [Quantum compiling with a variational instruction set for accurate and fast quantum computing](https://mlsanity.com/paper/2203.15574/) (2022)
- [AutoQuREO: A Framework for Automated Quantum Resource Estimation and Optimization](https://mlsanity.com/paper/2608.12936/) (2026)

## Abstract (arXiv)

We present ScaffCC, a scalable compilation and analysis framework based on LLVM, which can be used for compiling quantum computing applications at the logical level. Drawing upon mature compiler technologies, we discuss similarities and differences between compilation of classical and quantum programs, and adapt our methods to optimizing the compilation time and output for the quantum case. Our work also integrates a reversible-logic synthesis tool in the compiler to facilitate coding of quantum circuits. Lastly, we present some useful quantum program analysis scenarios and discuss their implications, specifically with an elaborate discussion of timing analysis for critical path estimation. Our work focuses on bridging the gap between high-level quantum algorithm specifi- cations and low-level physical implementations, while providing good scalability to larger and more interesting problems