diff --git a/experiment/figures/52/three_separations.png b/experiment/figures/52/three_separations.png
index 04076830b..0e9122e0b 100644
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diff --git a/experiment/figures/52/toy_centroid_residual.png b/experiment/figures/52/toy_centroid_residual.png
index a7a02b99d..d3c28fe9f 100644
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diff --git a/experiment/figures/52/toy_detection_prob.png b/experiment/figures/52/toy_detection_prob.png
index 5654c67fa..f3d09a6b4 100644
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diff --git a/experiment/figures/52/toy_residuals.png b/experiment/figures/52/toy_residuals.png
index 8399d49c5..9b553114b 100644
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diff --git a/experiment/scripts/figures/toy_figures.py b/experiment/scripts/figures/toy_figures.py
index 0023af2e8..34e1a2e69 100644
--- a/experiment/scripts/figures/toy_figures.py
+++ b/experiment/scripts/figures/toy_figures.py
@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
+import pytorch_lightning as pl
 import torch
 from einops import rearrange
 from matplotlib.figure import Figure
@@ -69,6 +70,9 @@ def separations_to_plot(self) -> list[int]:
         return [5, 10, 15]
 
     def compute_data(self, detection: DetectionEncoder, deblender: GalaxyEncoder):
+        # match previous noise realization that used a different seed
+        pl.seed_everything(43)
+
         # first, decide image size
         slen = 55
         bp = detection.bp
@@ -165,7 +169,7 @@ def compute_data(self, detection: DetectionEncoder, deblender: GalaxyEncoder):
         assert recon_ptiles.shape[-1] == recon_ptiles.shape[-2] == ptile_slen
         recon = reconstruct_image_from_ptiles(recon_ptiles, tile_slen)
         recon = recon.detach().cpu()
-        residuals = (recon - images) / torch.sqrt(bg)
+        residuals = (recon - images) / np.sqrt(bg)
 
         # now we need to obtain pred. plocs, prob. of detection in tile and std. of plocs
         # for each source