Concerned about the rising energy footprint of classical AI infrastructure?
Built for engineering and innovation leaders architecting the future of high-performance computing, this report provides a practical framework for deploying low-power neutral-atom processors to address the infrastructure demands of the AI era.
“The use of hybrid HPC/quantum computing […] could lead first for some specific workloads to an energy quantum advantage by perhaps running algorithms 10x slower at the beginning but requiring 100 to 1000x less energy.”
Pasqal’s Whitepaper on quantum for sustainability
Key Inside Insights:
Published in collaboration with GENCI, Jülich Forschungszentrum, Blaise Pascal Advisors, and the Open Quantum Institute, this second edition delivers verified data on the intersection of quantum processing and sustainability:
- Low Power Modality: Analysis of Pasqal’s neutral-atom processor, which operates at room temperature with low power requirements of up to 2–3 kW.
- 80% Parameter Reduction: Technical overview of the Quantum-Train workflow, demonstrating a massive 80% reduction in trainable parameters for AI-driven climate applications.
- Targeted Environmental Workloads: Real-world case studies detailing quantum heuristics for electrical grid optimization, wildfire containment modeling, and typhoon path forecasting.
