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QSW 2026: IEEE International Conference on Quantum Software

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QSW
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截稿日期:
2026-03-08
通知日期:
2026-05-10
会议日期:
2026-07-13
会议地点:
Sydney, Australia
届数:
5
浏览: 13206   关注: 1   参加: 0

会伴指数 (CP-I)

44.1 / 100
全站第 3,084 名 / 共 5,650 个会议 · 前 55%

软件工程 第 175 / 245

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
48
社区关注 (10%)
17
资料公开度 (15%)
35

用到的输入: 有据可查的届次：5 · 在会伴关注它的研究者：1 人 · 过去 24 个月打开过本页的研究者：3 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-06

征稿

QSW 2026 (IEEE International Conference on Quantum Software) is an academic conference held in Sydney, Australia on 2026-07-13. The paper submission deadline is 2026-03-08. Acceptance notifications are sent on 2026-05-10.

The IEEE International Conference on Quantum Software (IEEE QSW 2026) is the premier venue dedicated to establishing quantum software as a rigorous engineering and scientific discipline. QSW focuses on the methods, abstractions, languages, tools, systems, and theories required to design, build, analyze, deploy, and evolve quantum and hybrid quantum-classical software systems. Unlike physics- or hardware-centric venues, QSW emphasizes software-level contributions: programming models, languages, compilers, runtimes, validation & verification techniques, system architectures, lifecycle methodologies, and reproducible software artifacts. The conference explicitly targets the gap between quantum algorithms and operational quantum systems. QSW welcomes contributions from academia and industry that demonstrate technical depth, explicit assumptions, and clear software relevance. The conference solicits high-quality submissions in the following areas, including but not limited to: Foundations of Quantum Software ● Formal semantics of quantum and hybrid quantum-classical programs ● Type systems and correctness-by-construction approaches ● Resource-aware programming models (qubits, depth, noise, communication) ● Software-level cost models beyond gate counts ● Program equivalence, refinement, and transformation ● Abstractions for NISQ and post-NISQ software systems Quantum Software Development and Toolchains ● Quantum programming languages and intermediate representations ● Compilers, transpilers, simulators, optimizers, and code generators ● Circuit synthesis and decomposition techniques with software guarantees ● Simulation and emulation frameworks ● Design patterns and best practices for quantum software ● Data preparation and classical-quantum interfacing ● Development process and lifecycle models for quantum software Verification, Validation, and Quality Assurance ● Testing methodologies for quantum and hybrid applications ● Statistical verification with confidence guarantees ● Fault models at different software abstraction levels ● Specification languages for quantum behavior ● Regression testing and evolution of quantum software ● Software metrics, KPIs, and performance models Hybrid Quantum-Classical Systems and Infrastructure Software ● Architectures for hybrid quantum-classical applications ● Orchestration, scheduling, and resource management ● Runtime systems for heterogeneous platforms ● Cross-stack optimization (application-compiler-runtime-execution) ● Deployment, monitoring, and lifecycle management Quantum Software in the Cloud and at Scale ● Quantum Computing as a Service (QCaaS) software architectures ● Interoperability and portability across platforms and vendors ● Cloud-native quantum development environments ● Automation of deployment and execution pipelines ● Cost-aware execution and optimization strategies High-Performance Computing and Quantum Integration ● Integration of quantum accelerators into HPC workflows ● System software for quantum-enhanced HPC ● Performance modeling of quantum-classical workflows ● Co-design of HPC and quantum software stacks AI-Assisted Quantum Software Engineering ● AI-based circuit optimization and synthesis ● AI-assisted error mitigation and noise adaptation ● Data efficiency, generalization, and limits of ML-based approaches ● Comparisons against analytical and compiler-based baselines ● Formal guarantees or failure analyses of AI-assisted techniques Quantum Internet and Distributed Quantum Software ● Programming models for distributed quantum systems ● Network-aware compilation and execution ● Entanglement management and abstraction layers ● Simulation and emulation of quantum networks ● End-to-end quantum internet applications from a software perspective Quantum Software Applications and Experience Reports ● Transition from prototypes to production-grade quantum software ● Scalability analyses with realistic constraints ● Migration across quantum technologies and platforms ● Reproducible experience reports with generalizable insights ● Negative results, failure analyses, and lessons learned
由 Dou Sun 最后更新于

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