arXiv subjects

Francisco Romão

Publications and source records attributed to Francisco Romão.

4 recordsLinked to original sources

arXiv2026

MultiQ: Multi-Programming Neutral Atom Quantum Architectures

Neutral atom Quantum Processing Units (QPUs) are emerging as a popular quantum computing technology due to their large qubit counts and flexible connectivity. However, performance challenges arise as large circuits experience significant fidelity drops, while small circuits underutilize hardware and face initialization latency issues. To tackle these problems, we propose $\textit{multi-programming on neutral atom QPUs}$, allowing the co-execution of multiple circuits by logically partitioning the qubit array. This approach increases resource utilization and mitigates initialization latency while maintaining result fidelity. Currently, state-of-the-art compilers for neutral atom architectures do not support multi-programming. To fill this gap, we introduce MultiQ, the first system designed for this purpose. MultiQ addresses three main challenges: (i) it compiles circuits into a $\textit{virtual zone layout}$ to optimize spatio-temporal hardware utilization; (ii) it parallelizes the execution of co-located circuits, allowing single hardware instructions to operate on different circuits; and (iii) it includes an algorithm to verify the functional independence of the bundled circuits. MultiQ functions as a cross-layer system comprising a compiler, controller, and checker. Our compiler generates \emph{virtual zone layouts} to enhance performance, while the controller efficiently maps these layouts onto the hardware and resolves any conflicts. The checker ensures the correct bundling of circuits. Experimental results show a throughput increase from 3.8$\times$ to 12.3$\times$ when multi-programming 4 to 14 circuits, with fidelity largely maintained, ranging from a 1.3% improvement for four circuits to only a 3.5% loss for fourteen circuits. Overall, MultiQ facilitates concurrent execution of multiple quantum circuits, boosting throughput and hardware utilization.

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arXiv2025

Qonductor: A Cloud Orchestrator for Quantum Computing

We describe Qonductor, a cloud orchestrator for hybrid quantum-classical applications that run on heterogeneous hybrid resources. Qonductor abstracts away the complexity of hybrid programming and resource management by exposing the Qonductor API, a high-level and hardware-agnostic API. The resource estimator strategically balances quantum and classical resources to mitigate resource contention and the effects of hardware noise. The hybrid scheduler automates job scheduling on hybrid resources and balances the tradeoff between users' objectives of QoS and the cloud operator's objective of resource efficiency. We implement an open-source prototype and evaluate Qonductor using more than 7000 real quantum runs on the IBM quantum cloud to simulate real cloud workloads. Qonductor achieves up to 54% lower job completion times (JCTs) while sacrificing 3% execution quality, balances the load across QPU, which increases quantum resource utilization by up to 66%, and scales with growing system sizes and loads.

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arXiv2025

Weaver: A Retargetable Compiler Framework for FPQA Quantum Architectures

While the prominent quantum computing architectures are based on superconducting technology, new quantum hardware technologies are emerging, such as Trapped Ions, Neutral Atoms (or FPQAs), Silicon Spin Qubits, etc. This diverse set of technologies presents fundamental trade-offs in terms of scalability, performance, manufacturing, and operating expenses. To manage these diverse quantum technologies, there is a growing need for a retargetable compiler that can efficiently adapt existing code to these emerging hardware platforms. Such a retargetable compiler must be extensible to support new and rapidly evolving technologies, performant with fast compilation times and high-fidelity execution, and verifiable through rigorous equivalence checking to ensure the functional equivalence of the retargeted code. To this end, we present $Weaver$, the first extensible, performant, and verifiable retargetable quantum compiler framework with a focus on FPQAs due to their unique, promising features. $Weaver$ introduces WQASM, the first formal extension of the standard OpenQASM quantum assembly with FPQA-specific instructions to support their distinct capabilities. Next, $Weaver$ implements the WOptimizer, an extensible set of FPQA-specific optimization passes to improve execution quality. Last, the WChecker automatically checks for equivalence between the original and the retargeted code. Our evaluation shows that $Weaver$ improves compilation times by $10^3\times$, execution times by $4.4\times$, and execution fidelity by $10\%$, on average, compared to superconducting and state-of-the-art (non-retargetable) FPQA compilers.

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arXiv2025

QOS: A Quantum Operating System

Quantum computers face challenges due to hardware constraints, noise errors, and heterogeneity, and face fundamental design tradeoffs between key performance metrics such as \textit{quantum fidelity} and system utilization. This substantially complicates managing quantum resources to scale the size and number of quantum algorithms that can be executed reliably in a given time. We introduce QOS, a cloud operating system for managing quantum resources while mitigating their inherent limitations and balancing the design tradeoffs of quantum computing. QOS exposes a hardware-agnostic API for transparent quantum job execution, mitigates hardware errors, and systematically multi-programs and schedules the jobs across space and time to achieve high quantum fidelity in a resource-efficient manner. To achieve this, it leverages two key insights: First, to maximize utilization and minimize fidelity loss, some jobs are more compatible than others for multi-programming on the same quantum computer. Second, sacrificing minimal fidelity can significantly reduce job waiting times. We evaluate QOS on real quantum devices hosted by IBM, using 7000 real quantum runs of more than 70.000 benchmark instances. We show that the QOS achieves 2.6--456.5$\times$ higher fidelity, increases resource utilization by up to 9.6$\times$, and reduces waiting times by up to 5$\times$ while sacrificing only 1--3\% fidelity, on average, compared to the baselines.

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