From c78d2a3988e96e87e2cf2e53756f3758c4225c18 Mon Sep 17 00:00:00 2001 From: Purvansh Joshi Date: Wed, 8 Jul 2026 15:05:51 +0530 Subject: [PATCH] docs: add Known Assumptions and Simplifications section to README and paper - Documents three key simplifications: DM geometric coupling (recon.c), synthetic turbulence data (synthetic_shwfs.py), microbenchmark-only latency figures - Each assumption cross-referenced to the code location that encodes it - Added to both README.md and docs/paper/rippra_paper.tex - Fixes #33 --- README.md | 17 +++++++++++++++++ docs/paper/rippra_paper.tex | 14 ++++++++++++++ 2 files changed, 31 insertions(+) diff --git a/README.md b/README.md index aab84ff..1019ce0 100644 --- a/README.md +++ b/README.md @@ -284,6 +284,23 @@ Open `notebook/kaggle_synthetic_shwfs_generator.ipynb` to customize parameters, ### 2. Spot Deviation on Detector due to Distorted Wavefront ![Spot Deviation](./visualizations/Schematic%20showing%20spot%20deviation%20on%20detector%20due%20to%20distorted%20wavefront.webp) +## Known Assumptions and Simplifications + +The following simplifications are documented for reviewers and downstream users: + +### DM Coupling Model +The inter-actuator coupling matrix uses a **geometric nearest-neighbor model** — self-coupling 1.0, adjacent-actuator coupling by the configurable `coupling` coefficient, and diagonal coupling by `coupling²`. This is not a measured influence function. See `rippra/src/recon.c` (`rippra_dm_setup`, `rippra_dm_map`). + +A physical DM requires either manufacturer-provided influence matrices or interferometric calibration to replace this model. + +### Turbulence Data +All training and evaluation datasets are **synthetically generated** using a Kolmogorov turbulence model with Taylor frozen-flow temporal evolution (AR(1)). This has not been validated against experimental atmospheric data. See `rippra/ml/synthetic_shwfs.py`. + +When real SH-WFS measurements become available, the synthetic data generation parameters should be re-calibrated. + +### Latency Benchmarks +Performance figures reported are from **microbenchmarks** on a desktop system (see [Performance Documentation](docs/performance.md)). A production AO pipeline incurs additional overhead from camera readout, DMA transfers, and DM DAC settling times not modeled here. + ## Acknowledgements - ISRO Bharatiya Antariksh Hackathon 2026 for the problem statement and evaluation framework. diff --git a/docs/paper/rippra_paper.tex b/docs/paper/rippra_paper.tex index 00da9c4..58b1784 100644 --- a/docs/paper/rippra_paper.tex +++ b/docs/paper/rippra_paper.tex @@ -333,6 +333,20 @@ \section{Visualization Dashboard} Additional dashboards provide Zernike modal weight tracking (20 coefficients), low-order time-series (500 frames), turbulence telemetry ($r_0$, $\tau_0$), regime classification, and a 6-panel system performance monitor. +\section{Known Assumptions and Simplifications} +\label{sec:assumptions} + +The following simplifying assumptions are made in this work and should be noted before deployment on real hardware: + +\paragraph{DM Coupling Model (Section~\ref{sec:dm}):} +The inter-actuator coupling matrix $\mathbf{M}$ is modeled as a geometric nearest-neighbor rule: self-coupling~1.0, adjacent-actuator coupling~$\gamma$, and diagonal-actuator coupling~$\gamma^2$ (see \texttt{recon.c}, \texttt{rippra\_dm\_setup}). A physical DM's influence function deviates from this idealization and requires either manufacturer-provided influence matrices or interferometric calibration. + +\paragraph{Turbulence Data (Section~\ref{sec:dataset}):} +All training and evaluation data are generated synthetically from a Kolmogorov model with Taylor frozen-flow temporal evolution (AR(1) process). The synthetic pipeline (see \texttt{synthetic\_shwfs.py}) has not been validated against experimental atmospheric data. When real SH-WFS measurements become available, the synthetic data generation parameters should be re-calibrated. + +\paragraph{Latency Benchmarks (Section~\ref{sec:perf}):} +Performance figures presented in this paper are obtained from microbenchmarks on a desktop system (Section~\ref{sec:impl}). A production AO pipeline incurs additional overhead from camera readout, DMA transfers, and DM DAC settling times that are not modeled here. + \section{Conclusion} \label{sec:conclusion}