An HPC-Inspired Blueprint for a Technology-Agnostic Quantum Middle Layer

2025-10-08

AI Summary

Quantum computing platforms are highly fragmented, hindering application portability across diverse hardware stacks and computational paradigms. Method: This paper proposes a backend-agnostic quantum intermediate layer inspired by high-performance computing. It decouples algorithmic logic from physical implementation by declaratively specifying computational intent via typed data and operator descriptions. Intent and context descriptors—portable, composable, and encoded in JSON—support heterogeneous backends, including gate-model and quantum-annealing architectures. A dual-backend prototype is implemented using Qiskit Aer and D-Wave Ocean. Results: Evaluated on the Max-Cut problem, the framework enables seamless hardware migration solely by switching operator representations and execution contexts. Its core contribution is the first demonstration of intent-level portability across computational paradigms (gate-model vs. quantum annealing), establishing an evolvable, abstraction-rich intermediate layer for the quantum software stack.

Technology Category

• Machine Learning: Quantum Machine Learning
• Knowledge Representation and Reasoning: Qualitative Reasoning
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

We present a blueprint for a quantum middle layer that supports applications across various quantum technologies. Inspired by concepts and abstractions from HPC libraries and middleware, our design is backend-neutral and context-aware. A program only needs to specify its intent once as typed data and operator descriptors. It declares what the quantum registers mean and which logical transformations are required, without committing to gates, pulses, continuous-variable routines, or anneal backend. Such execution details are carried separately in a context descriptor and can change per backend without modifying the intent artifacts. We develop a proof of concept implementation that uses JSON files for the descriptors and two backends: a gate-model path realized with IBM Qiskit Aer simulator and an annealing path realized with D-Wave Ocean's simulated annealer. On a Max-Cut problem instance, the same typed problem runs on both backends by varying only the operator formulation (Quantum Approximated Optimization Algorithm formulation vs. Ising Hamiltonian formulation) and the context. The proposed middle layer concepts are characterized by portability, composability, and its minimal core can evolve with hardware capabilities.

Problem

• Designing a backend-agnostic quantum middleware for cross-technology applications
• Separating computational intent from hardware-specific execution details
• Enabling portable quantum programs across gate-model and annealing systems

Innovation

• Backend-neutral quantum middle layer design
• Intent specification via typed data descriptors
• Context-aware execution with portable operator formulation