Maestro: Intelligent Execution for Quantum Circuit Simulation

2025-12-03

AI Summary

Current quantum hardware limitations necessitate quantum circuit simulation as a critical tool for algorithm development and verification; however, the proliferation of heterogeneous simulation methods and tools complicates backend selection and hampers efficiency. To address this, we propose QSimSelect—a unified framework that integrates multiple simulation paradigms—including state-vector, matrix-product-state (MPS), tensor-network, stabilizer, p-block, and GPU-accelerated simulators—via a standardized interface. It incorporates a predictive, runtime-aware model that automatically selects the optimal simulator based on circuit structure and hardware environment, enabling backend-specific optimizations. Furthermore, it synergistically combines multi-process scheduling, GPU parallelism, and sampling acceleration. Experimental evaluation demonstrates that QSimSelect consistently outperforms individual simulators on both single-circuit and batch workloads, while exhibiting superior scalability and performance in high-performance computing (HPC) environments.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Quantum Machine Learning
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

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.

Problem

• Selecting optimal quantum circuit simulator from diverse methods
• Integrating multiple simulation paradigms under a unified API
• Automating simulator choice and optimization for circuit structure

Innovation

• Unified API integrates multiple quantum simulation paradigms.
• Predictive runtime model selects optimal simulator automatically.
• Applies backend-specific optimizations like GPU acceleration.