ArticleJournal of chemical theory and computation2024
Tensor Network State Algorithms on AI Accelerators.
Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Mixed-PrecisionJournal of chemical theory and computation · 2026Article
- Assessing the Reliability of Truncated Coupled Cluster Wave Function: Estimating the Distance from the Exact Solution.Journal of chemical theory and computation · 2025Article
- QCMaquis 4.0: Multipurpose Electronic, Vibrational, and Vibronic Structure and Dynamics Calculations with the Density Matrix Renormalization Group.The journal of physical chemistry. A · 2025Article
- Orbital Optimization of Large Active Spaces via AI-Accelerators.Journal of chemical theory and computation · 2025Article
- Massively Parallel Tensor Network State Algorithms on Hybrid CPU-GPU Based Architectures.Journal of chemical theory and computation · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce novel algorithmic solutions for hybrid CPU-multiGPU tensor network state algorithms utilizing non-Abelian symmetries building on AI-motivated state-of-the-art hardware and software technologies. The presented numerical simulations on the FeMo cofactor, which plays a crucial role in converting atmospheric nitrogen to ammonia, are far beyond the scope of traditional approaches. Our large-scale
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.