<i>SymPhas</i>—General Purpose Software for Phase‐Field, Phase‐Field Crystal, and Reaction‐Diffusion Simulations
Bibliographic record
Abstract
Abstract This work develops a new open source application programming interface (API) and software package called SymPhas for simulations of phase‐field, phase‐field crystal, and reaction‐diffusion models, supporting up to three dimensions and an arbitrary number of fields. SymPhas delivers two novel program capabilities: 1) User specification of models from the associated dynamical equations in an unconstrained form and 2) extensive support for integrating user‐developed discrete‐grid‐based numerical solvers into the API. The capability to specify general phase‐field models is primarily achieved by developing a novel symbolic algebra functionality that can formulate mathematical expressions at compile time; is able to apply rules of symbolic algebra such as distribution, factoring, and automatic simplification; and support user‐driven expression tree manipulation. A modular design based on the C++ template meta‐programming paradigm is applied to the symbolic algebra library and general API implementation to minimize application runtime and increase the accessibility of the API for third party development. SymPhas is written in C/C++ and emphasizes high‐performance capabilities via parallelization with OpenMP and the C++ standard library. SymPhas is equipped with a forward Euler solver and a semi‐implicit Fourier spectral solver. Sample implementations and simulations of several phase‐field models are presented, generated using the semi‐implicit Fourier spectral solver.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".