PhysQ'26
Physics-Driven Approaches to Quantum Computing
From Device Physics to Simulation and Co-Design with High-Performance Computing
From Device Physics to Simulation and Co-Design with High-Performance Computing
July 6, Belfast, Northern Ireland, United Kingdom
Venue: co-located with ACM International Conference on Supercomputing (ICS) 2026.
Quantum computing is often framed in terms of abstract qubits, circuits, and algorithms, but real quantum devices are physical systems with specific Hamiltonians, open-system dynamics, control constraints, and thermodynamic costs. At the same time, the design, simulation, and operation of these devices increasingly rely on advanced classical computation, from device-level modeling to hybrid quantum-HPC workflows and physics-informed QML. PhysQ’26 focuses on physics-driven approaches to quantum computing, treating physics as a primary design and analysis tool, while highlighting the role of clusters, accelerators, and supercomputers in enabling these investigations and translating them into usable architectures, software, and QML pipelines.
Device-level simulation & co-design on advanced computing platforms (hardware-specific simulation; multiscale modeling; co-design loops; toolchains).
Quantum simulation and quantum computing for physical sciences (quantum simulation algorithms and benchmarks; applications to physics simulations, materials science, and quantum chemistry; verification/validation)
Physics-informed machine learning for quantum computing systems (e.g., device/system identification, calibration and drift tracking, control and pulse optimization, noise modeling, readout mitigation, error mitigation, decoding for error correction, and hybrid physics/ML workflows for characterization and verification).
Physics-aware quantum machine learning (noise/control-informed QML; hybrid QML + HPC; benchmarks and methodology)
Analog, continuous-variable (CV) & Hamiltonian computing (models, encodings, simulation; comparisons to digital/circuit approaches; hybrid schemes).
Advanced computing & quantum hardware workflows/infrastructure (experiment-simulation pipelines; data management; co-scheduling; computing-center experiences).
Open quantum systems, noise & reservoir engineering (microscopic noise models; non-Markovian effects; physics-based mitigation; large-scale studies).
Thermodynamics, energetics & fundamental limits (costs of control/measurement; energy-speed–fidelity trade-offs; cost models for hybrid workflows).
All submitted papers should be formatted using the ACM Proceedings Style with the sigconf format (please use the current version). The necessary document can be found at https://www.acm.org/publications/proceedings-template.
Three submission types are possible:
Regular papers: 6-8 pages max (including references)
Short papers: up to 4 pages max (including references)
Extended abstract: 1 page (not appearing in conference proceedings, not archived)
Submissions are handled via EasyChair: https://easychair.org/conferences/?conf=physq26.
The best papers will be invited to submit an extended version for a special issue of the Future Generation Computing Systems journal.
S̶u̶b̶m̶i̶s̶s̶i̶o̶n̶ ̶D̶e̶a̶d̶l̶i̶n̶e̶ ̶-̶ ̶A̶p̶r̶i̶l̶ ̶1̶5̶,̶ ̶2̶0̶2̶6̶
Extended Deadline - April 21, 2026 SUBMISSIONS ARE OPEN
Notifications - May 4, 2026
Workshop - July 6, 2026
Stefano Markidis (KTH Royal Institute of Technology, Sweden)
Salvatore Mandrà (Google Quantum AI, USA)
Oleksandr Kyriienko (The University of Sheffield, UK)
Stefano Mensa (NVIDIA, UK)
Erik M. Åsgrim (KTH Royal Institute of Technology, Sweden)