The results show that an unmodified frontier LLM can produce working, correct, and competitive shuttling compilers without additional manual algorithmic engineering, thus reducing the development time for new architectures from several months to a few days.
Abstract
Trapped-ion quantum computers rely on shuttling compilers, which cast an input algorithm into a sequence of ion-qubit movements within a given architecture. We present the first study in which a single frontier large language model (LLM), Claude Opus 4.7, generates and iteratively refines the full Python code of shuttling compilers from written specifications. We start with a compiler for (i) a linear segmented trap, extend it to (ii) a trap with junctions, and finally achieve efficient compilation for (iii) a broad class of connected trap graphs. The compilers for the more general cases are seeded with code from the previous ones. We benchmark the LLM-generated compilers against state-of-the-art hand-crafted ones using a common suite of quantum circuits. The number of shuttling timesteps is reduced by up to 76% for (i) and up to 39% for (ii). For the broad case (iii) of freely connected architectures, we find large variations in the required number of shuttling timesteps, depending on the connectivity. A densely connected, junction-rich architecture yields an order-of-magnitude reduction in shuttling timesteps compared to a corridor-like one. Repeating the complete generation and evaluation with a second frontier LLM, Claude Fable 5, reproduces these findings, with the Fable 5 compilers surpassing the hand-crafted ones more often on the largest circuits. Our results show that an unmodified frontier LLM can produce working, correct, and competitive shuttling compilers without additional manual algorithmic engineering, thus reducing the development time for new architectures from several months to a few days.
A measurement of what diagrammatic post-processing recovers from structural redundancy in the Solovay-Kitaev algorithm, which optimizes for numerical convergence rather than circuit economy, and its output carries structural redundancy that a gate-level compiler cannot see.
Dulari De Silva, A. Mahasinghe, Chon-Fai Kam et al.· 0 citations
Quantum annealers solve problems by finding the lowest-energy (ground) state of a programmable physical system, a 2-local Ising model, whose energy function is the Hamiltonian. We compile recursive Datalog programs into such models so that the ground state projects onto the program's minimal Herbrand model. The compiler has four stages: binarization, grounding, reduction to a Min-Ones SAT formula, and Ising encoding. Each rule becomes an energy penalty on the one assignment that violates it, and a small uniform cost on every true atom selects the minimal model. We contribute both in theory and in practice with per-stage correctness lemmas and a correspondence theorem, verified in Lean 4, establishing that the ground state of the compiled model projects onto the program's minimal Herbrand model. We map the compiled models onto the topologies of commercial annealers and characterize, under classical and simulated-quantum annealing, whether and when that certified ground state is attained.
Bruno Vicente Alves de Lima, Victor Henrique Cabral Pinheiro, Evgenii Dolzhkov et al.· 0 citations
Automatic uncomputation aims to provide programming-language-level support to facilitate the correct and safe use of ancilla qubits in quantum computing, but efforts have only been made for clean ancillas, leaving dirty ancillas unexplored. We present a unified formalization of the uncomputation of both clean and dirty ancillas. For the first time, we prove that checking the existence of uncomputation is coNP-hard. We introduce two complementary synthesis-oriented existence-checking methods: a rewrite-based normalization algorithm (RwUn) and a template-based reasoning system (TpUn) that guarantees uncomputation through structured Store-Use patterns. We implement prototypes of both methods in Qiskit and Python. Compared to the state-of-the-art Reqomp~\cite{reqomp}, RwUn achieves 100% coverage on practical complex-dependency benchmarks, twice the coverage on random classical circuits, and about 50% coverage on random quantum circuits beyond the scope of existing methods, demonstrating broader applicability.
Motivated by recent breakthroughs in the development of spin-based quantum processing units based on exchange-only (EO) spin qubits, we provide a roadmap for the implementation of quantum algorithms on the EO platform, ranging from the NISQ to the fault-tolerant era. To provide an algorithm-driven perspective on the scaling of quantum chips, we consider a range of applications targeting different stages of hardware maturity and formulate requirements for a successful realization. We show that the compilation method Parity Twine perfectly complements the hardware's capabilities to perform tasks such as the quantum Fourier transform or QAOA. Furthermore, we describe an error detection technique native to Parity Twine, which EO qubits can leverage in a unique and advantageous way to improve algorithm performance. Finally, since both near-term algorithmic benchmarks and a long-term perspective can be found in digital quantum simulation, we specifically discuss the fermionic fast Fourier transform and the simulation of Fermi-Hubbard models. The latter is explicitly discussed in the context of quantum error correction and a partially fault-tolerant realization. By providing detailed resource estimates and identifying scaling bottlenecks on each level, our work offers a quantitative perspective on EO-based quantum computing and will inform future hardware design choices.
F. Lohof, Florian Ginzel, Wolfgang Lechner· 0 citations
The compilation of an algorithm can vary significantly with the choice of physical hardware platform and error correction model. Yet, current compilation frameworks typically commit to a single architecture-hardware configuration, making it difficult to assess resource estimates across platforms. We present a platform-aware compilation framework that re-compiles a quantum circuit into a hardware-compatible instruction set as well as fault-tolerant operations and provides end-to-end resource estimates in terms of physical-qubit count, time-to-solution, and classical processing time. We benchmark the framework by obtaining end-to-end resource estimates for different compilers, each tailored to the functionalities of specific hardware modalities: connectivity, clock speed, and noise model. As part of this framework, we introduce a transversal active volume (t-AV) compilation architecture designed for the efficient execution of fault-tolerant operations in platforms supporting long-range logical connectivity. We benchmark the framework for Hamiltonian simulation of the 2D Fermi Hubbard model as well as for eigenenergy estimation of a small molecule (trimethylenemethane) as a candidate for early fault-tolerant demonstration of quantum chemistry. For the latter, we show that end-to-end quantum simulations can be achieved with $\sim10^4$ physical qubits and runtimes ranging from $10^2$ ms (photonics, superconducting) to $10^5$ ms (neutral atoms).
Srushti Patil, Susan X. Chen, Andreas Juul Bay-Smidt et al.· 0 citations
This paper presents Ankhdjet, an open-source compiler that lowers a HuggingFace ternary checkpoint to a via-mask program of a fixed compute-in-ROM macro on the open SKY130 PDK, verified end to end with open tools.
Mohnish Pai· 0 citations
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