eminus — Pythonic electronic structure theory
Abstract
Domain fit: Niche / domain-specific · No strong AI-core implementation/artifact signals were detected from current providers.
In current electronic structure research endeavors such as warm dense matter or machine learning applications, efficient development necessitates non-monolithic software, providing an extendable and flexible interface. The open-source idea offers the advantage of having a source code base that can be reviewed and modified by the community. However, practical implementations can often diverge significantly from their theoretical counterpart. Leveraging the efforts of recent theoretical formulations and the features of Python, we try to mitigate these problems. We present eminus , an education- and development-friendly electronic structure package designed for convenient and customizable workflows, yet built with intelligible and modular implementations. • Pythonic implementation of density functional theory. • Customizable workflows and developer-friendly code. • Minimal dependencies and large platform support. • Comparable and reproducible calculations. • Example notebooks showcasing educational usage.
Results and benchmarks
In current electronic structure research endeavors such as warm dense matter or machine learning applications, efficient development necessitates non-monolithic software, providing an extendable and flexible interface.
Benchmark evidence is limited
Evidence graph: 2 refs, 1 links.
Utility signals: depth 65/100, grounding 58/100, status medium.
Implementation
No direct implementation yet
Maintained implementation evidence is not confirmed for this paper yet.
Use the implementation status and reproduction sections for the current action plan.
No verified maintained repo yet
There is no verified maintained implementation yet. Use this baseline plan to decide whether to prototype now or defer.
- No direct maintained implementation was found. Use the paper PDF and citation graph to design a baseline reproduction.
- Start from related paper: QEpy: Quantum ESPRESSO in Python.
- Track assumptions and missing details in an experiment log before coding.
Time to first repro: a few days
Recommendation evidence is currently too limited for a maintained-repo choice. Use Implementation Status and Reproduction Path for a practical baseline plan.
- Estimate is based on paper-only reproduction flow
Reproduction readiness
No repo
No verified implementation available
- No maintained repository has been identified for this paper. Check adjacent implementations or HF artifacts below.
Hardware requirements
- Expect multi-day setup/compute for meaningful reproduction based on current guidance.
Validation caveat
Hugging Face artifacts
No trustworthy direct or curated related Hugging Face artifacts were found yet. Use targeted searches to quickly locate candidate models, datasets, and demos.
Datasets
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Research context
0
Citations
72
References
Tasks
Computer science, electronic structure theory, density functional theory, Python, open source software, warm dense matter, Physical Sciences
Methods
None detected
Domains
machine learning applications, Physics and Astronomy, Atomic and Molecular Physics, and Optics
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