QCE 2026 (IEEE International Conference on Quantum Computing and Engineering) is an academic conference held in Toronto, Ontario, Canada on 2026-09-13. The paper submission deadline is 2026-04-27.
Quantum Applications (QAPP) Paper Track Chairs
Rudy Raymond, JPMorgan Chase — [email protected]
Martin Schulz, Technical University of Munich (TUM) — [email protected]
The practice of solving problems with quantum computers.
Towards Quantum Advantage
Towards fault tolerance and realization of quantum error correction at the application level
Quantum Machine Learning (QML) applications
Fault-tolerant applications
Quantum simulation of physical systems
Applications — chemistry, machine learning, finance, optimization, biological sciences, and other science & engineering applications
Applications of quantum annealing
Quantum for generative AI
Integrated high-performance computing (HPC) and quantum applications
Performance evaluation of quantum algorithms
Optimization problems—transportation, supply chain & logistics
Quantum AI & decision making
Quantum medical applications & precision health applications
Quantum DNA and protein sequencing
Quantum finance
Quantum End-to-end Hybrid Case Studies (QECS) Paper Track Chairs
Steven Rayan, University of Saskatchewan — [email protected]
Alexandre Choquette, IBM Quantum — [email protected]
The design and implementation of domain-specific quantum computing case studies to demonstrate quantum utility.
Domain-specific end-to-end quantum case studies
Domain-specific problems and results
Small-scale experiments
Practical quantum simulation case studies in chemistry, materials, biology, or physics
Domain-specific quantum optimization workflows, including combinatorial optimization, scheduling, or control problems, implemented using hybrid quantum–classical techniques.
Data-driven insights from hybrid quantum experiments
Validation through recovery of classical results, using known solutions
Identification of nearby or approximate solutions, demonstrating how quantum methods can uncover useful suboptimal
Error mitigation and robustness strategies applied within realistic end-to-end case studies, rather than in isolation
Pathways to scale-up, including algorithmic generalization, problem size growth, hardware evolution, and integration with distributed or modular quantum systems
Software engineering and tooling for hybrid case studies, including workflow orchestration, utility frameworks, reproducibility practices, and open-source implementations
Quantum–GenAI Co-Design & Co-Discovery (QGDD) Paper Track Chairs
Yuri Alexeev, NVIDIA — [email protected]
Foutse Khomh, Polytechnique, Montréal — [email protected]
The practice of combining quantum computing and generative AI for innovative applications.
Agentic quantum–generative AI systems and workflows
Quantum-Generative AI co-design frameworks
Quantum simulation data generation
Drug discovery, materials science, biology, energy, or optimization enabled by QGDD pipelines
Large quantitative models (LQMs) for domain-specific genAI
Closed-loop discovery pipelines where genAI proposes candidates and quantum computers validate, refine, or falsify them
Hybrid quantum-classical-AI system architectures
Quantum-enhanced generative models, including variational quantum circuits, quantum Boltzmann machines, or hybrid quantum-AI generators
Benchmarking, metrics, and evaluation methodologies for quantum–GenAI discovery workflows and co-designed systems
Data representations and interfaces connecting quantum simulators, hardware backends, and generative AI models
Quantum Algorithms (QALG) Paper Track Chairs
Ulrike Stege, University of Victoria — [email protected]
Stefan Woerner, IBM Quantum Zurich — [email protected]
The theory of solving problems with quantum computers.
Quantum information science
Quantum algorithm structures and patterns
Quantum algorithms and complexity
Near-term quantum algorithms
Error correction and mitigation algorithms
Fault-tolerant quantum algorithms
Advances in hybrid variational algorithms
Advances in hybrid QAOA algorithms
Quantum solver approaches
Quantum linear algebra
Tensor network algorithms
Encoding and learning quantum algorithms
Hamiltonian dynamics
Quantum cryptography
Secure quantum computing
Privacy-preserving quantum computing
Quantum Technologies and Systems Engineering (QTEM) Paper Track Chairs
Kasra Nowrouzi, QuNorth — [email protected]
Anthony Przybysz, Northrop Grumman — [email protected]
Tanay Roy, Fermi National Laboratory — [email protected]
The design and architecture of quantum technologies and systems engineering for computation and sensing.
Superconducting quantum technologies
Quantum annealing technologies
Trapped ion quantum technologies
Silicon quantum technologies
Quantum dot technologies
Neutral atom quantum technologies
Topological quantum technologies
Hardware-software stack for quantum annealers, trapped ions, superconducting, photonics, neutral atoms, and others
Quantum characterization, verification & validation: benchmarking and tomography
Qubit design and control
Packaging and cooling
Cryogenics
Quantum electronics
Pulse-level control of qubits
Sensing and metrology
Characterization and hardware mitigation of noise, state preparation and measurement errors
Quantum System Software (QSYS) Paper Track Chairs
Shaukat Ali, Simula Labs — [email protected]
Amir Shehata, Oak Ridge National Laboratory — [email protected]
The design, architecture, and operation of full-stack quantum computing systems.
Full quantum software stack: compilers, runtimes, workflows, languages, transpilers, profilers
Quantum programming, development kits (QDKs), test harnesses, debuggers
Quantum languages and intermediate representations (IRs)
Quantum simulators
Quantum software engineering
Generative AI in quantum software development and systems software
Software for co-design
Hybrid quantum-classical systems
Resource estimation
Quantum control software
Interfacing classical control and quantum hardware through software
Error correction and mitigation
Fault-tolerant computing at the system software level
Testing, validation, and verification of quantum programs and systems
Benchmarking of quantum systems, quantum volume and other metrics
Software techniques for error correction and noise mitigation
Hardware-software stacks for error mitigation
Quantum software in enterprise systems
Secure quantum systems
Privacy-preserving quantum systems
Quantum Photonics (QPHO) Paper Track Chairs
Luu Nguyen, PsiQuantum — [email protected]
Jaqui Romero, University of Queensland — [email protected]
The design and architecture of quantum photonic technologies and systems engineering.
Quantum photonic information science and technology
Quantum computing with photonic systems
Quantum entanglement and teleportation
Optical quantum computing
Photonic quantum technologies
Photonic quantum computers
Integrated quantum photonics
Photonics-based qubit technologies
Photonic quantum simulation
Silicon photonic devices
Photon sources and detectors
Quantum sensing and metrology
Quantum Machine Learning (QML) Paper Track Chairs
Sarah Chehade, University of Tennessee at Chattanooga — [email protected]
Arno Jacobsen, University of Toronto — [email protected]
The practice of combining quantum computing and machine learning for innovative application development.
Quantum algorithms for machine learning tasks
AI-assisted quantum information science
Quantum-enhanced machine learning
Quantum-inspired models and machine learning
Quantum Boltzmann Machines
Quantum Neural Networks (QNNs)
Quantum Support Vector Machines (QSVMs)
Quantum Generative Adversarial Networks (QGANs)
Quantum Generative AI
Training machine learning models
Quantum algorithms for reinforcement learning
Quantum clustering and classification
Advances in encoding and learning algorithms
Benchmarking of quantum systems, quantum volume and other metrics
Quantum machine learning theory
Quantum error correction and mitigation
Fault-tolerant QML applications
Quantum state tomography
Quantum machine learning applications
QML software and libraries
QML benchmarks
Quantum Networking & Communications (QNET) Paper Track Chairs
Angela Sara Cacciapuoti, University of Naples Federico II — [email protected]
Rajkumar Kettimuthu, Argonne National Laboratory — [email protected]
Quantum techniques and technologies for networking and communications
Quantum internet
Quantum networking
Quantum switches, routers, repeaters, and other hardware components
Signal processing algorithms for quantum communication
Optical quantum communications
Intra-chip and inter-chip communication
Secure communication in quantum networks
Quantum cryptography
Quantum key distribution (QKD)
Post-quantum cryptography
Distributed quantum computing
Cloud quantum computing
Secure quantum computing
Privacy-preserving quantum protocols
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