Maestro: Intelligent Execution for Quantum Circuit Simulation

Fuente: arXiv
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Autores principales: Bertomeu, Oriol, Ghayas, Hamzah, Roman, Adrian, DiAdamo, Stephen
Formato: Preprint
Publicado: 2025
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author Bertomeu, Oriol
Ghayas, Hamzah
Roman, Adrian
DiAdamo, Stephen
author_facet Bertomeu, Oriol
Ghayas, Hamzah
Roman, Adrian
DiAdamo, Stephen
contents Quantum circuit simulation remains essential for developing and validating quantum algorithms, especially as current quantum hardware is limited in scale and quality. However, the growing diversity of simulation methods and software tools creates a high barrier to selecting the most suitable backend for a given circuit. We introduce Maestro, a unified interface for quantum circuit simulation that integrates multiple simulation paradigms - state vector, MPS, tensor network, stabilizer, GPU-accelerated, and p-block methods - under a single API. Maestro includes a predictive runtime model that automatically selects the optimal simulator based on circuit structure and available hardware, and applies backend-specific optimizations such as multiprocessing, GPU execution, and improved sampling. Benchmarks across heterogeneous workloads demonstrate that Maestro outperforms individual simulators in both single-circuit and large batched settings, particularly in high-performance computing environments. Maestro provides a scalable, extensible platform for quantum algorithm research, hybrid quantum-classical workflows, and emerging distributed quantum computing architectures.
format Preprint
id arxiv_https___arxiv_org_abs_2512_04216
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Maestro: Intelligent Execution for Quantum Circuit Simulation
Bertomeu, Oriol
Ghayas, Hamzah
Roman, Adrian
DiAdamo, Stephen
Quantum Physics
Mathematical Software
Software Engineering
Quantum circuit simulation remains essential for developing and validating quantum algorithms, especially as current quantum hardware is limited in scale and quality. However, the growing diversity of simulation methods and software tools creates a high barrier to selecting the most suitable backend for a given circuit. We introduce Maestro, a unified interface for quantum circuit simulation that integrates multiple simulation paradigms - state vector, MPS, tensor network, stabilizer, GPU-accelerated, and p-block methods - under a single API. Maestro includes a predictive runtime model that automatically selects the optimal simulator based on circuit structure and available hardware, and applies backend-specific optimizations such as multiprocessing, GPU execution, and improved sampling. Benchmarks across heterogeneous workloads demonstrate that Maestro outperforms individual simulators in both single-circuit and large batched settings, particularly in high-performance computing environments. Maestro provides a scalable, extensible platform for quantum algorithm research, hybrid quantum-classical workflows, and emerging distributed quantum computing architectures.
title Maestro: Intelligent Execution for Quantum Circuit Simulation
topic Quantum Physics
Mathematical Software
Software Engineering
url https://arxiv.org/abs/2512.04216