[hpc-announce] CfP: PhysQ’26 Workshop at ICS 2026

[Stefano Markidis]

PhysQ’26: Physics-Driven Approaches to Quantum Computing
>From Device Physics to Simulation and Co-Design with High-Performance Computing
https://urldefense.us/v3/__https://sites.google.com/view/physq26/__;!!G_uCfscf7eWS!Z3RhJTlnvTvnisRAo4wexnKEP4JKurU9eIVKQ8qXqwWX8oFs0nrZIUEWVKagvtX-rR5Sjx-6MUZhpfN8b7Fdl8ll$  

Date: July 6, 2026
Venue: Belfast, Northern Ireland, United Kingdom, co-located with ACM International Conference on Supercomputing (ICS) 2026.

# Workshop Scope
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 and software.

## Topics of interest (including, but not limited to):
* 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).

## Paper Submission
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://urldefense.us/v3/__https://www.acm.org/publications/proceedings-template__;!!G_uCfscf7eWS!Z3RhJTlnvTvnisRAo4wexnKEP4JKurU9eIVKQ8qXqwWX8oFs0nrZIUEWVKagvtX-rR5Sjx-6MUZhpfN8b9KwiWzH$ . Two submission types are possible: 
* Regular papers: 6-8 pages max (including references)
* Short papers: up to 4 pages max (including references)
Submissions are handled via EasyChair: https://urldefense.us/v3/__https://easychair.org/conferences/?conf=physq26__;!!G_uCfscf7eWS!Z3RhJTlnvTvnisRAo4wexnKEP4JKurU9eIVKQ8qXqwWX8oFs0nrZIUEWVKagvtX-rR5Sjx-6MUZhpfN8b38o9WoS$ 

The best papers will be invited to submit an extended version for a special issue of the journal Future Generation Computing Systems. 

## Important Dates 
* Submission deadline: April 15, 2026
* Notification: May 1, 2026
* Workshop: July 6, 2026

## Organizers
* 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