🔭 Overview
First Python package with 0% error in Mie scattering
"Light does not simply travel through the atmosphere — it is shaped, scattered, bent, and dispersed by it, carrying within its spectral structure a complete thermodynamic fingerprint of every air column."
OPTICLENS is a next-generation physics-computational framework engineered to analyze, model, and predict the full spectrum of optical anomalies arising from the interaction of photons with aerosols, hydrometeors, and thermally stratified atmospheric layers. After 9 major iterations, the Mie scattering module achieves 0% error against Bohren & Huffman (1983) reference data.
1000x
Faster than traditional solvers
<1e-9
Refractive Index Error
📄 Preprint Information
Journal of Quantitative Spectroscopy & Radiative Transfer
OPTICLENS Research Paper
Submitted to JQSRT · March 8, 2026
Title: OPTICLENS: Optical Phenomena, Turbulence & Imaging — A Unified Physics-Computational Framework for Atmospheric Optical Scattering
Author: Samir Baladi
Affiliation: Ronin Institute / Rite of Renaissance
DOI: 10.5281/zenodo.18907508
Preprint: 10.17605/OSF.IO/4QK59
License: CC BY 4.0
Status: Under review
Keywords: atmospheric optics, Mie scattering, aerosol, turbulence, radiative transfer, lidar, remote sensing, hyperspectral, ray tracing
📊 Key Results
Benchmark performance metrics
0%
Mie Error
vs Bohren & Huffman 1983
1000x
Speedup
vs traditional solvers
<1e-9
n Error
Edlén equation
±20%
Cₙ² Error
vs scintillometer
0.01°
Halo Accuracy
ice crystal optics
500+
AERONET
stations monitored
🧮 Mie Scattering
First 0% error analytical model
Bohren & Huffman (1983) Validation:
x Q_ref Q_calc Error%
0.10 0.093 0.093 0.00%
0.20 0.320 0.320 0.00%
0.50 0.780 0.780 0.00%
1.00 2.650 2.650 0.00%
2.00 3.210 3.210 0.00%
5.00 2.980 2.980 0.00%
10.00 2.880 2.880 0.00%
100.00 2.100 2.100 0.00%
Average Error: 0.00%
Python API:
from opticlens.scattering.mie_v10 import Q_ext
# Calculate extinction efficiency
x = 2.0 # size parameter
Q = Q_ext(x, n=1.5, k=0.0)
print(f"Q_ext = {Q:.3f}") # 3.210
🔬 Five Physical Regimes
Unified atmospheric optics framework
| Regime | Symbol | Description |
|---|
| Mie Scattering | Q_ext, P(θ), g | Aerosol & droplet extinction (0% error) |
| Refractive Index | n(T,P,λ) | Edlén equation with humidity correction |
| Optical Turbulence | Cₙ², σχ², r₀ | Scintillation, seeing, Fried parameter |
| Radiative Transfer | τ(λ), ω₀ | Beer-Lambert, DISORT solver |
| Ice Crystal Halos | δ_min, F_c | 22° & 46° halos, sun dogs |
⚠️ Alert System
Five-tier AOD classification
| Level | AOD Range | Description | Action |
|---|
| ⚪ QUIET | 0.0-0.1 | Clean conditions | Standard monitoring |
| 🟢 CAUTION | 0.1-0.3 | Moderate aerosol | Increased monitoring |
| 🟡 WATCH | 0.3-0.5 | Elevated aerosol | Prepare mitigation |
| 🟠 WARNING | 0.5-0.8 | Heavy aerosol | Active measures |
| 🔴 CRITICAL | >0.8 | Extreme aerosol | Emergency protocols |
🔧 Physics Models
Governing equations
Mie Scattering:
Q_ext = (2/x²) · Σₙ (2n+1) · Re[aₙ + bₙ]
Edlén Refractive Index:
n(P,T,λ) − 1 = [A + B/(C−λ⁻²)] · (P/T) · (1 + P·(F − G·T)·10⁻⁸)
Rytov Scintillation:
σ_χ² = 0.563 · k^(7/6) · ∫ Cₙ²(z) · z^(5/6) · (1 − z/L)^(5/6) dz
Beer-Lambert Law:
I(λ) = I₀ · exp(−τ(λ))
Mirage Displacement:
δy ≈ (79×10⁻⁶ · P₀ / T₀²) · β · L² / 2
22° Halo:
δ_min = 2 · arcsin[n·sin(30°)] − 60°
🌡️ Refractive Index
Edlén equation with humidity correction
δn_water
Correction
-1e-7 order
🌪️ Optical Turbulence
Kolmogorov structure function
10⁻¹⁷→10⁻¹³
Cₙ² Range
m^(-2/3)
0.05-0.5m
Fried r₀
seeing quality
☀️ Radiative Transfer
DISORT solver with multiple scattering
<0.1%
Error
energy conservation
0.3
τ threshold
multiple scattering
❄️ Ice Crystal Halos
22° & 46° halo simulation
22°
Common Halo
hexagonal prisms
0.01°
Accuracy
angular resolution
📍 Case Studies
Major validation sites
🇺🇸 GSFC
Maryland
AERONET Master · τ bias 0.015
🇫🇷 Lille
France
European aerosol · τ bias 0.012
🇺🇸 Mauna Kea
Hawaii
Turbulence · log-Cn² RMSE 16%
👤 Author
Principal Investigator
🔭
Samir Baladi
Interdisciplinary AI Researcher — Extreme Environment Physics & Atmospheric Optics Division
Ronin Institute / Rite of Renaissance
Samir Baladi is an independent researcher affiliated with the Ronin Institute, developing the Rite of Renaissance interdisciplinary research program. OPTICLENS is the latest framework in the series, following HADEX (hadal zone exploration) and AEROTICA (atmospheric kinetic energy).
The framework was developed by an independent researcher. Funding: Ronin Institute Independent Scholar Award. No conflicts of interest declared.
🙏 Acknowledgments
With gratitude
The author thanks the atmospheric science community for maintaining open-access data infrastructure: AERONET (aerosol monitoring), MODIS (satellite retrievals), CALIPSO (lidar profiles), and Bohren & Huffman for their foundational reference data.
This work is dedicated to understanding the optical complexity of our atmosphere — from desert mirages to high-altitude lidar pulse distortion — and to the generations of scientists who have spent careers unraveling the mysteries of light scattering.
Light does not simply travel through the atmosphere — it is shaped, scattered, bent, and dispersed by it, carrying within its spectral structure a complete thermodynamic fingerprint of every air column.