# SQARL: A Size-Agnostic Reinforcement Learning approach for Circuit Allocation in Distributed Quantum Architectures Source: [SQARL: A Size-Agnostic Reinforcement Learning approach for Circuit Allocation in Distributed Quantum Architectures]() Collection index: [llms.txt]() Data updated: 2026-05-28T05:00:13.160Z Authors: V\\'ictor Carballo, J\\'ulia L\\'opez-Closa, Mario Martin Published: 2026-05-26T13:48:28.000Z ## Abstract The scaling of quantum processors is currently limited by technical challenges such as decoherence and cross-talk. As the number of qubits grows, interference increases the computational noise. Distributed quantum computing addresses these limitations by interconnecting smaller, easier-to-handle quantum processors (cores), but it introduces the challenge of minimizing slow, error-prone inter-core communication. The task of distributing quantum circuits across cores while minimizing communication costs is known as the Qubit Allocation problem. This work focuses on developing a deep learning approach to this problem, emphasizing flexibility to quantum hardware topology and improving state-of-the-art performance. Heuristic and non-learning algorithms, such as the Hungarian Qubit Allocation (HQA), currently represent the state of the art. Reinforcement Learning (RL) approaches leverage learned allocation policies but often lack flexibility, requiring retraining when hardware configurations change, and they fall short of the solution quality achieved by non-learning methods. However, learning mechanisms could outperform human-crafted heuristics. To overcome these limitations, this work proposes a flexible, transformer-based architecture that can handle arbitrary numbers of qubits and cores without retraining. Results show that the trained policy consistently outperforms the previous RL state of the art and narrows the gap between RL and HQA for the most common circuits. It achieves a 33% reduction in allocation cost relative to the HQA for the Cuccaro Adder and 25% on average for random circuits. These findings show that learning-based approaches can effectively match the performance of hand-crafted heuristics, a crucial step towards their application in real-world scenarios. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Circuit Allocation on Draper Adder 50 qubits](): Circuit Allocation; Draper Adder 50 qubits; Inter-core Communications: 332. - [Circuit Allocation on Random Avg 50 qubits](): Circuit Allocation; Random Avg 50 qubits; Inter-core Communications: 163. - [Circuit Allocation on Cuccaro Adder 100 Qubits](): Circuit Allocation; Cuccaro Adder 100 Qubits; Inter-core Communications: 74. - [Circuit Allocation on Draper Adder 100 Qubits](): Circuit Allocation; Draper Adder 100 Qubits; Inter-core Communications: 841. - [Circuit Allocation on Random Avg 100 Qubits](): Circuit Allocation; Random Avg 100 Qubits; Inter-core Communication Overhead: 273. - [Circuit Allocation on Cuccaro Adder 50 qubits](): Circuit Allocation; Cuccaro Adder 50 qubits; Inter-core Communications: 50. - [Circuit Allocation on Deutsch Jozsa 50 qubits](): Circuit Allocation; Deutsch Jozsa 50 qubits; Inter-core Communications: 16. - [Circuit Allocation on Graph State 50 qubits](): Circuit Allocation; Graph State 50 qubits; Inter-core Communication: 418. - [Circuit Allocation on QFT 50 qubits](): Circuit Allocation; QFT 50 qubits; Inter-core Communications: 323. - [Circuit Allocation on Quantum Volume 50 qubits](): Circuit Allocation; Quantum Volume 50 qubits; Inter-core Communication Overhead: 874. - [Circuit Allocation on Deutsch Jozsa 100 Qubits](): Circuit Allocation; Deutsch Jozsa 100 Qubits; Inter-core Communication Overhead: 36. - [Circuit Allocation on Graph State 100 Qubits](): Circuit Allocation; Graph State 100 Qubits; Inter-core Communication Overhead: 1990. - [Circuit Allocation on QFT 100 Qubits](): Circuit Allocation; QFT 100 Qubits; Inter-core Communications: 1586. - [Circuit Allocation on QNN 100 Qubits](): Circuit Allocation; QNN 100 Qubits; Inter-core Comms.: 3349. - [Circuit Allocation on Quantum Volume 100 Qubits](): Circuit Allocation; Quantum Volume 100 Qubits; Inter-core Communication Overhead: 4241. - [Circuit Allocation on QNN 50 qubits](): Circuit Allocation; QNN 50 qubits; Inter-core Communication Overhead: 671. ## Original sources and implementation [Original paper]() [PDF]()