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P2 Compiling Quantum Regular Language States

编译量子正则语言态
OOPSLA 10(OOPSLA2)2026匹配度 2/10 · 论文属于量子计算与自动机理论交叉,提出量子态制备编译器,与用户核心关注的PL→AI、AI→PL、浮点程序分析、贝叶斯程序分析均无直接关联;虽涉及形式化界限和自动机,但应用场景为量子态制备,偏离研究方向。引用 0 inbox
Armando Bellante, Reinis Irmejs, Marta Florido-Llinàs, María Cea Fernández, Marianna Crupi, Matthew Kiser, J. Ignacio Cirac
crossref: 2026-10-02

AI 速览

一句话:提出面向正则语言态及其补集的量子态制备编译器,以最小化 DFA 到最优 MPS 的中间表示统一简洁规格与资源保证。

现有量子态制备编译器要么把目标态当作不透明振幅向量,要么只支持少数已知态族的定制构造,难以兼顾结构化规格与资源保证。本文面向正则语言态(RLS)及其补集设计并实现态制备编译器:用户以比特串集合、正则表达式或 DFA 描述目标态,编译器将其最小化并映射为最优矩阵积态(MPS)作为中间表示,暴露并压缩隐藏结构,使 RLS 与其补集以相同的渐近资源与编译时间制备。作者给出两种硬件感知后端:SeqRLSP 在线性近邻架构上生成线性深度、无辅助位电路,TreeRLSP 借助树张量网络在全连接下达到对数深度;并证明电路深度、门数及编译时间的界随系统规模与最大 Schmidt 秩缩放。实验在 Dicke 态、W 态、随机均匀叠加与补集态上与通用、稀疏态及专用基线对比。

问题
通用量子态制备编译器把目标态视为不透明振幅向量,或仅提供针对少数已知态族的定制构造,无法同时接受结构化规格并给出可预测的资源保证。
方法
设计并实现 RLS 编译器:把比特串集合、正则表达式或 DFA(可带补集标志)前端输入翻译为 DFA 并最小化,再映射为最优 MPS 作为中间表示;后端包括基于顺序生成的 SeqRLSP(线性近邻、线性深度、无辅助位)与基于树张量网络的 TreeRLSP(全连接、对数深度)。
评估
实现完整编译流水线,在 Dicke 态、W 态、随机均匀叠加和补集态上与通用、稀疏态及专用基线进行比较;理论上证明电路深度、门数与编译时间的界随系统规模和最大 Schmidt 秩缩放。
原文摘要(Abstract)

State preparation compilers for quantum computers typically sit at two extremes: general-purpose routines that treat the target as an opaque amplitude vector, and bespoke constructions for a handful of well-known state families. We ask whether a compiler can instead accept simple, structure-aware specifications while providing predictable resource guarantees. We answer this by designing and implementing a quantum state-preparation compiler for regular language states (RLS): uniform superpositions over bitstrings accepted by a regular description, and their complements. Users describe the target state via (i) a finite set of bitstrings, (ii) a regular expression, or (iii) a deterministic finite automaton (DFA), optionally with a complement flag. By translating the input to a DFA, minimizing it, and mapping it to an optimal matrix product state (MPS), the compiler obtains an intermediate representation (IR) that exposes and compresses hidden structure. The efficient DFA representation and minimization offloads expensive linear algebra computation in exchange of simpler automata manipulations. The combination of the regular-language frontend and this IR gives concise specifications not only for RLS but also for their complements that might otherwise require exponentially large state descriptions. This enables state preparation of an RLS or its complement with the same asymptotic resources and compile time, which to our knowledge is not supported by existing compilers. We outline two hardware-aware backends: SeqRLSP, which yields linear-depth, ancilla-free circuits for linear nearest-neighbor architectures via sequential generation, and TreeRLSP, which achieves logarithmic depth on all-to-all connectivity via a tree tensor network. On the theory side, we prove circuit-depth and gate-count bounds that scale with the system size and the maximal Schmidt rank of the target state, and we give compile-time bounds that expose the benefit of the initial DFA representation. We implement the full pipeline and evaluate it on Dicke and W states, random uniform superpositions, and complement states, comparing against general-purpose, sparse-state, and specialized baselines.

链接与引用

DOI 原文 · arXiv · PDF(开放获取) · DBLP

BibTeX
@article{abs-2602-02698,
  title = {Compiling Quantum Regular Language States},
  author = {Armando Bellante and Reinis Irmejs and Marta Florido-Llinàs and María Cea Fernández and Marianna Crupi and Matthew Kiser and J. Ignacio Cirac},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {10},
  number = {OOPSLA2},
  year = {2026},
  doi = {10.1145/3839458}
}