{"paper":{"title":"QuPort: Topology-, Port-, and Congestion-Aware Compilation for Modular Multi-QPU Quantum Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"QuPort's TPCCAP finds circuit partitions for multi-QPU systems that jointly minimize cut distance, port overflow, and link congestion on a three-level graph.","cross_cats":["cs.MS"],"primary_cat":"quant-ph","authors_text":"Soumyadip Sarkar, Subhasree Bhattacharjee","submitted_at":"2026-05-12T17:12:30Z","abstract_excerpt":"Modular quantum processors require a compiler to reason about two resources at the same time: local device connectivity and communication across QPUs. A mapping that is acceptable on a single coupling graph may be unsuitable for a modular machine if it creates excessive cross-QPU traffic, concentrates that traffic on a small number of interconnect links, or assigns many boundary qubits to a QPU with few communication ports. This paper presents QuPort, a Python and Qiskit-based compilation framework that studies this setting through an explicit three-level model: a weighted logical interaction "},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"The main partitioning method, TPCCAP, optimizes the implemented objective formed by weighted cut distance, communication-port overflow, and routed link-load congestion.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That minimizing the weighted combination of cut distance, port overflow, and congestion on the three-level graph model will produce mappings that are meaningfully better on actual modular quantum hardware, without any reported hardware validation or calibrated cost functions.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"QuPort introduces a three-level graph model and TPCCAP optimizer for compiling circuits on modular multi-QPU systems while balancing topology, port usage, and link congestion.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"QuPort's TPCCAP finds circuit partitions for multi-QPU systems that jointly minimize cut distance, port overflow, and link congestion on a three-level graph.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"0c8eafcf4d634c9273f55b2746b8c543055fd9d5c25c87c04e870f80abee84aa"},"source":{"id":"2605.12583","kind":"arxiv","version":1},"verdict":{"id":"2906af64-47ed-4541-a6c3-96314e107bee","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T20:41:40.836393Z","strongest_claim":"The main partitioning method, TPCCAP, optimizes the implemented objective formed by weighted cut distance, communication-port overflow, and routed link-load congestion.","one_line_summary":"QuPort introduces a three-level graph model and TPCCAP optimizer for compiling circuits on modular multi-QPU systems while balancing topology, port usage, and link congestion.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That minimizing the weighted combination of cut distance, port overflow, and congestion on the three-level graph model will produce mappings that are meaningfully better on actual modular quantum hardware, without any reported hardware validation or calibrated cost functions.","pith_extraction_headline":"QuPort's TPCCAP finds circuit partitions for multi-QPU systems that jointly minimize cut distance, port overflow, and link congestion on a three-level graph."},"references":{"count":14,"sample":[{"doi":"10.1016/j.comnet.2024.110672","year":2024,"title":"Distributed quantum computing: a survey","work_id":"f3ceabe9-99dc-4b8f-a9ba-1e4833255c46","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1103/physreva.59.4249","year":1999,"title":"Distributed quantum computation over noisy channels","work_id":"8d50fc90-f9a8-4556-9fb1-a71b31d37ee7","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1038/s41598-022-18989-w","year":2022,"title":"Scientific Reports12, 15421 (2022).https://doi","work_id":"1caa79c2-0b32-4cc1-9275-56fa28b7afad","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1109/tqe.2021.3053921","year":2021,"title":"IEEE Transactions on Quantum Engineering2, 1–20 (2021).https://doi.org/10.1109/TQE.2021.3053921","work_id":"a5215cc6-99e0-4228-8d38-69099758aab4","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1109/tqe.2023.3303935","year":2023,"title":"A modular quantum compilation framework for distributed quantum computing,","work_id":"d70fe7b8-3f38-4044-b2ea-0715aeea3496","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":14,"snapshot_sha256":"74be3e961a620ac0367483c7e548119f3e88e78d6145df03781deb33e07a67d1","internal_anchors":0},"formal_canon":{"evidence_count":1,"snapshot_sha256":"2243051693e2d573c22473f1338357b783bb9ab8f77dba56e266d49c52e3bec1"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}