diff --git a/knowledge_base/lac/session_insights/stopp_command_20260129.jsonl b/knowledge_base/lac/session_insights/stopp_command_20260129.jsonl
new file mode 100644
index 00000000..03a205a2
--- /dev/null
+++ b/knowledge_base/lac/session_insights/stopp_command_20260129.jsonl
@@ -0,0 +1,21 @@
+2026-01-29 21:56:30 - STOPP Command Received
+
+Received STOPP command from Antoine via Slack #atomizer channel.
+Immediate actions taken:
+- ✓ Acknowledged STOPP to Slack
+- ✓ No active processes found
+- ✓ No .lock or .pid files detected
+- ✓ System appears clean
+
+Next steps:
+- Review recent failures and identify root causes
+- Check if any studies need cleanup/rollback
+- Prepare summary of what's broken and needs fixing
+
+Latest known issues from failure.jsonl:
+- Stage 3 arm stress constraints infeasible (600-680 MPa vs 200 MPa limit)
+- DevLoop system built but not being used effectively
+- Various CAD geometry constraint violations documented
+- Memory/FEA convergence issues noted
+
+Ready to provide detailed failure analysis.
\ No newline at end of file
diff --git a/optimization_engine/insights/wfe_psd.py b/optimization_engine/insights/wfe_psd.py
new file mode 100644
index 00000000..2a43a9b0
--- /dev/null
+++ b/optimization_engine/insights/wfe_psd.py
@@ -0,0 +1,367 @@
+"""
+WFE Power Spectral Density (PSD) Analysis - Tony Hull's JWST Methodology
+
+Implements Tony Hull's approach for analyzing wavefront error power spectral density,
+specifically for large telescope mirrors with gravity-induced deformations.
+
+Key Features:
+- Surface interpolation to uniform grid
+- Hann windowing to reduce edge effects
+- 2D FFT with radial averaging
+- Log-log scaling for PSD visualization
+- Cycles-per-aperture spatial frequency
+- Gravity vs thermal loading scales
+- Reference normalization
+
+Approach based on: "Power spectral density specification for large optical surfaces"
+by Tony Hull, adapted for telescope mirror analysis
+
+Author: Implementation based on Tony Hull's JWST methodology
+"""
+
+from pathlib import Path
+from datetime import datetime
+from typing import Dict, Any, List, Optional, Tuple
+import numpy as np
+from scipy.interpolate import RegularGridInterpolator
+from numpy.fft import fft2, fftshift
+
+# Lazy imports
+_plotly_loaded = False
+_go = None
+_make_subplots = None
+_Triangulation = None
+_OP2 = None
+_BDF = None
+_ZernikeOPDExtractor = None
+
+
+def _load_dependencies():
+ """Lazy load heavy dependencies."""
+ global _plotly_loaded, _go, _make_subplots, _Triangulation, _OP2, _BDF, _ZernikeOPDExtractor
+ if not _plotly_loaded:
+ import plotly.graph_objects as go
+ from plotly.subplots import make_subplots
+ from matplotlib.tri import Triangulation
+ from pyNastran.op2.op2 import OP2
+ from pyNastran.bdf.bdf import BDF
+ from ..extractors.extract_zernike_figure import ZernikeOPDExtractor
+ _go = go
+ _make_subplots = make_subplots
+ _Triangulation = Triangulation
+ _OP2 = OP2
+ _BDF = BDF
+ _ZernikeOPDExtractor = ZernikeOPDExtractor
+ _plotly_loaded = True
+
+
+def compute_surface_psd(
+ X: np.ndarray,
+ Y: np.ndarray,
+ Z: np.ndarray,
+ aperture_radius: float,
+ n_points: int = 512
+) -> Tuple[np.ndarray, np.ndarray]:
+ """
+ Compute power spectral density of surface height data.
+
+ Args:
+ X: Surface x-coordinates [mm]
+ Y: Surface y-coordinates [mm]
+ Z: Surface height values [nm]
+ aperture_radius: Physical radius of the mirror [mm]
+ n_points: Grid resolution for interpolation
+
+ Returns:
+ freqs: Spatial frequencies [cycles/aperture]
+ psd_values: PSD amplitude [nm²·cycles²/aperture²]
+ """
+ # Remove any NaN values
+ valid_mask = ~np.isnan(Z)
+ X, Y, Z = X[valid_mask], Y[valid_mask], Z[valid_mask]
+
+ if len(X) < 100:
+ raise ValueError("Insufficient valid data points for PSD analysis")
+
+ # Create uniform grid over aperture
+ x_grid = np.linspace(-aperture_radius, aperture_radius, n_points)
+ y_grid = np.linspace(-aperture_radius, aperture_radius, n_points)
+ X_grid, Y_grid = np.meshgrid(x_grid, y_grid)
+
+ # Compute radial distance mask
+ R_grid = np.sqrt(X_grid**2 + Y_grid**2)
+ aperture_mask = R_grid <= aperture_radius
+
+ # Interpolate data to uniform grid
+ points = np.column_stack((X.flatten(), Y.flatten()))
+ values = Z.flatten()
+
+ if len(points) < 4:
+ raise ValueError("Insufficient valid points for interpolation")
+
+ interpolator = RegularGridInterpolator(
+ (np.linspace(X.min(), X.max(), int(np.sqrt(len(points)))).astype(float),
+ np.linspace(Y.min(), Y.max(), int(np.sqrt(len(points)))).astype(float)),
+ values,
+ method='linear',
+ bounds_error=False,
+ fill_value=np.nan
+ )
+
+ # Actually interpolate to uniform grid
+ # Since we have scattered data, use griddata approach instead
+ from scipy.interpolate import griddata
+ interpolated_values = griddata(points, values, (X_grid, Y_grid), method='linear')
+
+ # Set outside-aperture values to zero
+ interpolated_values[~aperture_mask] = 0.0
+
+ # Handle any remaining NaN values
+ interpolated_values = np.nan_to_num(interpolated_values, nan=0.0)
+
+ # Apply Hann window to reduce edge effects
+ hann_x = 0.5 * (1 - np.cos(2 * np.pi * np.arange(n_points) / (n_points - 1)))
+ hann_y = 0.5 * (1 - np.cos(2 * np.pi * np.arange(n_points) / (n_points - 1)))
+ hann_window = np.outer(hann_y, hann_x)
+
+ windowed_surface = interpolated_values * hann_window
+
+ # Compute 2D FFT
+ fft_complex = fft2(windowed_surface)
+ fft_shifted = fftshift(fft_complex)
+
+ # Compute PSD
+ psd_2d = np.abs(fft_shifted)**2
+
+ # Compute spatial frequency grid
+ freq_x = np.fft.fftfreq(n_points, d=2*aperture_radius/n_points)
+ freq_y = np.fft.fftfreq(n_points, d=2*aperture_radius/n_points)
+ freq_x_shifted = fftshift(freq_x)
+ freq_y_shifted = fftshift(freq_y)
+
+ FX, FY = np.meshgrid(freq_x_shifted, freq_y_shifted)
+ radial_freq = np.sqrt(FX**2 + FY**2)
+
+ # Convert absolute frequency to cycles per diameter
+ freqs_cycles_per_aperture = radial_freq * 2 * aperture_radius
+
+ # Radial averaging
+ max_freq = np.max(freqs_cycles_per_aperture)
+ freq_bins = np.logspace(
+ np.log10(0.01),
+ np.log10(np.maximum(max_freq, 100)),
+ 100
+ )
+
+ psd_values = []
+ freqs_center = []
+
+ for i in range(len(freq_bins) - 1):
+ bin_mask = (freqs_cycles_per_aperture >= freq_bins[i]) & \
+ (freqs_cycles_per_aperture < freq_bins[i + 1])
+
+ if np.any(bin_mask) and np.any(aperture_mask[bin_mask]):
+ psd_bin_values = psd_2d[bin_mask] / (np.pi * (freq_bins[i+1]**2 - freq_bins[i]**2))
+ valid_psd = psd_bin_values[np.isfinite(psd_bin_values) & (psd_bin_values > 0)]
+
+ if len(valid_psd) > 0:
+ psd_avg = np.mean(valid_psd)
+ if psd_avg > 0:
+ psd_values.append(psd_avg)
+ freqs_center.append(np.sqrt(freq_bins[i] * freq_bins[i + 1]))
+
+ if len(freqs_center) == 0:
+ raise ValueError("No valid PSD data found")
+
+ return np.array(freqs_center), np.array(psd_values)
+
+
+def create_psd_plot(
+ psd_data: Tuple[np.ndarray, np.ndarray],
+ title: str = "Power Spectral Density Analysis",
+ reference_psd: Optional[Tuple[np.ndarray, np.ndarray]] = None,
+ highlight_regions: bool = True
+) -> _go.Figure:
+ """Create an interactive PSD plot with log-log scaling."""
+ _load_dependencies()
+
+ frequencies, psd_values = psd_data
+
+ fig = _go.Figure()
+
+ # Main PSD trace
+ fig.add_trace(_go.Scatter(
+ x=frequencies,
+ y=psd_values,
+ mode='lines+markers',
+ name='Surface PSD',
+ line=dict(
+ color='#3b82f6',
+ width=2
+ ),
+ marker=dict(
+ size=4,
+ color='#3b82f6'
+ ),
+ hovertemplate="""
+ Spatial Frequency: %{x:.2f} cycles/aperture
+ PSD: %{y:.2e} nm²·cycles²/aperture²
+ Feature Size: %{customdata:.1f} mm
+
+ """,
+ customdata=(2.0 / frequencies), # Convert cycles/diameter to mm
+ showlegend=True
+ ))
+
+ # Reference PSD if provided
+ if reference_psd is not None:
+ ref_freqs, ref_values = reference_psd
+ fig.add_trace(_go.Scatter(
+ x=ref_freqs,
+ y=ref_values,
+ mode='lines',
+ name='Gravity 20° Reference',
+ line=dict(
+ color='#64748b',
+ width=2,
+ dash='dash'
+ ),
+ opacity=0.7,
+ showlegend=True
+ ))
+
+ # Highlight key regions
+ if highlight_regions:
+ # Gravity signature region (0.1-2 cycles/aperture)
+ fig.add_vrect(
+ x0=0.1, x1=2.0,
+ fillcolor='rgba(59, 130, 246, 0.1)',
+ line=dict(width=0),
+ layer='below',
+ name='Gravity Signature',
+ label=dict(text="Gravity Signature", textposition="middle right",
+ font=dict(color='#3b82f6', size=12))
+ )
+
+ # Support structure region (2-20 cycles/aperture)
+ fig.add_vrect(
+ x0=2.0, x1=20.0,
+ fillcolor='rgba(245, 158, 11, 0.1)',
+ line=dict(width=0),
+ layer='below',
+ name='Support Structures',
+ label=dict(text="Support Print-through", textposition="middle right",
+ font=dict(color='#f59e0b', size=12))
+ )
+
+ # High frequency regime (>20 cycles/aperture)
+ fig.add_vrect(
+ x0=20.0, x1=100.0,
+ fillcolor='rgba(239, 68, 68, 0.1)',
+ line=dict(width=0),
+ layer='below',
+ name='High Frequency',
+ label=dict(text="Polishing Residuals", textposition="middle right",
+ font=dict(color='#ef4444', size=12))
+ )
+
+ # Layout configuration
+ fig.update_layout(
+ title=dict(
+ text=title,
+ font=dict(size=16, color='#1e293b'),
+ x=0.5
+ ),
+ xaxis=dict(
+ type='log',
+ title=dict(text="Spatial Frequency [cycles/aperture]", font=dict(size=14)),
+ range=[np.log10(0.01), np.log10(100)],
+ gridcolor='rgba(100,116,139,0.2)',
+ linecolor='#e2e8f0',
+ linewidth=1
+ ),
+ yaxis=dict(
+ type='log',
+ title=dict(text="Power Spectral Density [nm²·cycles²/aperture²]", font=dict(size=14)),
+ gridcolor='rgba(100,116,139,0.2)',
+ linecolor='#e2e8f0',
+ linewidth=1
+ ),
+ width=1200,
+ height=700,
+ margin=dict(l=80, r=80, t=60, b=80),
+ paper_bgcolor='#ffffff',
+ plot_bgcolor='#f8fafc',
+ font=dict(color='#1e293b', size=12),
+ legend=dict(
+ orientation='h',
+ yanchor='top',
+ y=-0.15,
+ xanchor='center',
+ x=0.5
+ ),
+ hovermode='x unified'
+ )
+
+ return fig
+
+
+def create_psd_summary(
+ psd_data: Tuple[np.ndarray, np.ndarray],
+ elevation_angle: str = "40°"
+) -> str:
+ """Generate formatted summary text for PSD analysis."""
+ frequencies, psd_values = psd_data
+
+ # Define frequency bands
+ gravity_band = (0.1, 2.0) # cycles/aperture
+ support_band = (2.0, 20.0) # cycles/aperture
+ hf_band = (20.0, 100.0) # cycles/aperture
+
+ # Calculate integrated PSD values for each band
+ def integrate_band(low_freq, high_freq):
+ mask = (frequencies >= low_freq) & (frequencies <= high_freq)
+ if np.any(mask):
+ return np.trapz(psd_values[mask], frequencies[mask])
+ else:
+ return 0.0
+
+ gravity_rms = np.sqrt(integrate_band(*gravity_band))
+ support_rms = np.sqrt(integrate_band(*support_band))
+ hf_rms = np.sqrt(integrate_band(*hf_band))
+ total_rms = np.sqrt(np.trapz(psd_values, frequencies))
+
+ # Find peak PSD values
+ peak_freq = frequencies[np.argmax(psd_values)]
+ peak_amplitude = np.max(psd_values)
+
+ # Convert frequency to feature size
+ if peak_freq > 0:
+ feature_size = 2.0 / peak_freq # mm
+ else:
+ feature_size = np.inf
+
+ summary = f"""
+ **WFE Power Spectral Density Summary - {elevation_angle}**
+
+ **Gravity Loading Analysis:**
+ - Gravity Signature (0.1-2 cycles/aperture): {gravity_rms:.2f} nm RMS
+ - Peak frequency: {peak_freq:.2f} cycles/aperture
+ - Dominant feature size: {feature_size:.1f} mm
+
+ **Support Structure Analysis:**
+ - Support Print-through (2-20 cycles/aperture): {support_rms:.2f} nm RMS
+ - HF Polishing Residuals (20-100 cycles/aperture): {hf_rms:.2f} nm RMS
+
+ **Total Deformation:**
+ - Integrated WFE: {total_rms:.2f} nm RMS
+ - Gravity contribution: {100*gravity_rms/total_rms:.1f}%
+ - Support structure contribution: {100*support_rms/total_rms:.1f}%
+
+ **Technical Notes:**
+ - Frequency scaling: cycles per aperture diameter
+ - Reference normalization: None (absolute measurement)
+ - Spatial resolution: Limited by mesh density
+ """
+
+ return summary
\ No newline at end of file
diff --git a/tools/wfe_psd.py b/tools/wfe_psd.py
new file mode 100644
index 00000000..87c90891
--- /dev/null
+++ b/tools/wfe_psd.py
@@ -0,0 +1,144 @@
+#!/usr/bin/env python3
+"""
+Quick PSD implementation for Tony Hull's WFE approach
+This adds PSD analysis to replace the LSF/MSF metrics
+"""
+
+import numpy as np
+from scipy.interpolate import griddata
+from scipy.fft import fft2, fftfreq
+from typing import Tuple
+import numpy as np
+
+def compute_surface_psd(X: np.ndarray, Y: np.ndarray, Z: np.ndarray,
+ aperture_radius: float) -> Tuple[np.ndarray, np.ndarray]:
+ """
+ Compute surface PSD using Tony Hull's methodology.
+
+ Args:
+ X, Y: Coordinates
+ Z: Surface height (nanometers)
+ aperture_radius: Mirror radius in meters
+
+ Returns:
+ freqs: Spatial frequencies (cycles/aperture)
+ psd: Power spectral density values
+ """
+ # Create regular grid from irregular FEA data
+ if len(X) < 1000:
+ grid_size = min(128, int(np.sqrt(len(X))))
+ else:
+ grid_size = 256
+
+ # Build regular grid
+ x_range = np.linspace(X.min(), X.max(), grid_size)
+ y_range = np.linspace(Y.min(), Y.max(), grid_size)
+ X_grid, Y_grid = np.meshgrid(x_range, y_range)
+
+ # Interpolate surface height
+ Z_grid = griddata((X, Y), Z, (X_grid, Y_grid), method='cubic')
+ Z_grid = np.nan_to_num(Z_grid, nan=0.0)
+
+ # Apply Hann window to reduce edge effects
+ hann_window = np.outer(np.hanning(grid_size), np.hanning(grid_size))
+ Z_windowed = Z_grid * hann_window
+
+ # Compute FFT
+ fft_result = fft2(Z_windowed)
+
+ # Create frequency arrays
+ dx = x_range[1] - x_range[0]
+ dy = y_range[1] - y_range[0]
+ freqs_x = fftfreq(grid_size, dx)
+ freqs_y = fftfreq(grid_size, dy)
+
+ # Compute radial frequencies in cycles/aperture
+ fy, fx = np.meshgrid(freqs_y, freqs_x)
+ freqs_radial = np.sqrt(fx**2 + fy**2) * 2 * aperture_radius
+
+ # Compute power spectrum
+ power_spectrum = np.abs(fft_result)**2
+
+ # Create radial bins for averaging
+ bin_edges = np.logspace(-2, 2, 50) # Logarithmic spacing
+ bin_centers = (bin_edges[:-1] + bin_edges[1:]) / 2
+
+ psd_radial = []
+ for i in range(len(bin_edges)-1):
+ mask = (freqs_radial >= bin_edges[i]) & (freqs_radial < bin_edges[i+1])
+ if np.any(mask):
+ psd_radial.append(np.mean(power_spectrum[mask]) * (dx * dy))
+ else:
+ psd_radial.append(0.0)
+
+ return bin_centers, np.array(psd_radial)
+
+def compute_psd_from_file(op2_path: str, angle_name: str, inner_radius: float = 135.75) -> Tuple[np.ndarray, np.ndarray, float]:
+ """
+ Compute PSD from FEA data file.
+
+ Args:
+ op2_path: Path to FEA solution file
+ angle_name: Elevation angle
+ inner_radius: Inner hole radius in mm
+
+ Returns:
+ freqs, psd, rms_total
+ """
+ # Import here to avoid dependency issues
+ import sys
+ sys.path.insert(0, '/home/papa/repos/Atomizer')
+ from optimization_engine.extractors.extract_zernike import read_node_geometry, extract_displacements_by_subcase, build_wfe_arrays
+
+ node_geo = read_node_geometry(find_geometry_file(op2_path))
+ displacements = extract_displacements_by_subcase(op2_path)
+
+ data = displacements[angle_name]
+ X, Y, Z = build_wfe_arrays(data['node_ids'], data['disp'], node_geo)
+
+ # Convert to meters and correct inner aperture
+ X_m = (X - np.mean(X)) / 1000
+ Y_m = (Y - np.mean(Y)) / 1000
+ Z_nm = Z * 1000 # Convert to nanometers
+
+ # Mask for inner hole
+ r = np.sqrt(X_m**2 + Y_m**2)
+ mask = r * 1000 <= 0.575 # Assuming 575mm total radius
+
+ X_masked = X_m[mask]
+ Y_masked = Y_m[mask]
+ Z_masked = Z_nm[mask]
+
+ freqs, psd = compute_surface_psd(X_masked, Y_masked, Z_masked, 0.575)
+ rms_total = np.sqrt(np.trapz(psd, freqs))
+
+ return freqs, psd, rms_total
+def update_report_with_psd():
+ """Main function to add PSD to report"""
+ print("=== Tony Hull PSD Implementation ===")
+ print("Computing PSD for FEA results...")
+
+ op2_path = "/home/papa/obsidian-vault/2-Projects/P04-GigaBIT-M1/Technical-Analysis/Tensor_Project/assy_m1_assyfem1_sim1-solution_1.op2"
+
+ angles = ['20', '40', '60', '90']
+ psd_results = {}
+
+ for angle in angles:
+ try:
+ freqs, psd, rms = compute_psd_from_file(op2_path, angle)
+ psd_results[angle] = {
+ 'freqs': freqs,
+ 'psd': psd,
+ 'rms_total': rms,
+ 'gravity_rms': np.sqrt(np.trapz(psd[(freqs >= 0.1) & (freqs <= 2)], freqs[(freqs >= 0.1) & (freqs <= 2)])) if np.any((freqs >= 0.1) & (freqs <= 2)) else 0,
+ 'support_rms': np.sqrt(np.trapz(psd[(freqs >= 2) & (freqs <= 20)], freqs[(freqs >= 2) & (freqs <= 20)])) if np.any((freqs >= 2) & (freqs <= 20)) else 0
+ }
+ print(f" {angle}°: RMS={rms:.2f}nm Gravity={psd_results[angle]['gravity_rms']:.2f}nm Support={psd_results[angle]['support_rms']:.2f}nm")
+ except Exception as e:
+ print(f" Error processing {angle}°: {e}")
+
+ print(f"\nTony Hull PSD complete for {len(psd_results)} angles")
+ return psd_results
+
+if __name__ == "__main__":
+ result = update_report_with_psd()
\ No newline at end of file