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Tabby: A Synthesis-Aided Compiler for High-Performance Zero-Knowledge Proof Circuits

Junrui Liu, Jiaxin Song, Yanning Chen, Hanzhi Liu, Hongbo Wen, Luke Pearson, Yanju Chen, Yu Feng

Abstract

Zero-knowledge proof (ZKP) applications require translating high-level programs into arithmetic circuits—a process that demands both correctness and efficiency. While recent DSLs improve usability, they often yield suboptimal circuits, and hand-optimized implementations remain difficult to construct and verify. We present Tabby, a synthesis-aided compiler that automates the generation of high-performance ZK circuits from high-level code. Tabby introduces a domain-specific intermediate representation designed for symbolic reasoning and applies sketch-based program synthesis to derive optimized low-level implementations. By decomposing programs into reusable components and verifying semantic equivalence via SMT-based reasoning, Tabby ensures correctness while achieving substantial performance improvements. We evaluate Tabby on a suite of real-world ZKP applications and demonstrate significant reductions in proof generation time and circuit size against mainstream ZK compilers.

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