How to use sample-based quantum diagonalization on IBM hardware
Explainer
Peter Hess
Physical Sciences
Our physical sciences researchers seek to understand materials and their properties through advanced characterization methods, explore novel devices and materials for new computational platforms, and apply physics to improve AI algorithms and interpretability.
Our work
Where the frontiers of high-speed racing and computing meet
ResearchKim Martineau and Dave MosherNext-generation algorithms could move fusion from the lab to the grid
ReleaseKim MartineauQuantum computers take a step into real materials science
NewsPeter HessTerraStackAI: Bringing Earth and space AI to Red Hat and the world
Technical noteCampbell Watson, Charles Wachira, Rosie Lickorish, Romeo Kienzler, Blair Edwards, and Michael JohnstonFrom atoms to chips: Thermonat models heat with unprecedented accuracy
NewsPeter Hess- See more of our work on Physical Sciences
Projects
Low-temperature scanning tunneling microscopy and atomic force microscopy.
Publications
Unsupervised Cycle Detection in Agentic Applications
- Felix George
- Divya Pathak
- et al.
- 2026
- ICPE 2026
Short paperMomentum-Accelerated Structured Preconditioning for Physics-Informed Neural Networks
- Indra Priyadarsini S
- Onur Boyar
- et al.
- 2026
- ICLR 2026
Workshop paperDiscovering Bäcklund Transformations with PDE Foundation Models
- 2026
- ICLR 2026
WorkshopTest-Time Tuned Language Models Enable End-to-end De Novo Molecular Structure Generation from MS/MS Spectra
- Laura Mismetti
- Marvin Alberts
- et al.
- 2026
- ICLR 2026
Workshop paperEfficient Quantum Gibbs Sampling with Local Circuits
- Dominik Hahn
- Ryan Sweke
- et al.
- 2026
- PRX Quantum
PaperTransition between cooperative emission regimes in giant perovskite nanocrystals
- Etsuki Kobiyama
- Gabriele Rainò
- et al.
- 2026
- Nature Materials
Paper