diff --git a/CITATIONS.md b/CITATIONS.md
index 3c42e40e6..e5d881cc2 100644
--- a/CITATIONS.md
+++ b/CITATIONS.md
@@ -11,6 +11,6 @@ our GitHub page!
 **PyAutoGalaxy** is published in the [Journal of Open Source Software](https://joss.theoj.org/papers/10.21105/joss.02825#) and its
 entry in the above .bib file is under the citation key `pyautogalaxy`.
 
-You should also specify the non-linear search(es) you use in your analysis (e.g. Dynesty, Emcee, PySwarms, etc) in
+You should also specify the non-linear search(es) you use in your analysis (e.g. Nautilus, Dynesty, Emcee, Zeus, etc) in
 the main body of text, and delete as appropriate any packages your analysis did not use. The citations.bib file includes
 the citation key for all of these projects.
diff --git a/docs/general/citations.md b/docs/general/citations.md
index b8c644b6e..19c77d31a 100644
--- a/docs/general/citations.md
+++ b/docs/general/citations.md
@@ -13,7 +13,7 @@ entry in the above .bib file is under the citation key `pyautogalaxy`.
 As shown in the examples, we would greatly appreciate it if you mention **PyAutoGalaxy** by name and include a link to
 our GitHub page!
 
-You should also specify the non-linear search(es) you use in your analysis (e.g. Dynesty, Emcee, PySwarms, etc) in
+You should also specify the non-linear search(es) you use in your analysis (e.g. Nautilus, Dynesty, Emcee, Zeus, etc) in
 the main body of text, and delete as appropriate any packages your analysis did not use. The citations.bib file includes
 the citation key for all of these projects.
 
diff --git a/docs/index.md b/docs/index.md
index 52d04d391..6f9a99b3b 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -144,7 +144,7 @@ galaxies_plotter.figures_2d(image=True)
 To perform model-fitting, `PyAutoGalaxy` adopts the probabilistic programming
 language `PyAutoFit` (<https://github.com/PyAutoLabs/PyAutoFit>). `PyAutoFit` allows users to compose a
 model from `LightProfile` and `Galaxy` objects, customize the model parameterization and fit it to data via a
-non-linear search (e.g., `dynesty` [@dynesty], `emcee` [@emcee], `PySwarms` [@pyswarms]). By composing a model with
+non-linear search (e.g., `Nautilus` [@nautilus], `dynesty` [@dynesty], `emcee` [@emcee]). By composing a model with
 `Pixelization` objects, the galaxy's light is reconstructed using a non-parametric rectangular
 grid or Voronoi mesh that accounts for irregular galaxy morphologies.
 
diff --git a/docs/installation/overview.md b/docs/installation/overview.md
index c1eeffde3..f3746b46e 100644
--- a/docs/installation/overview.md
+++ b/docs/installation/overview.md
@@ -32,8 +32,6 @@ our [building from source installation guide](https://pyautogalaxy.readthedocs.i
 
 **emcee** <https://github.com/dfm/emcee>
 
-**PySwarms** <https://github.com/ljvmiranda921/pyswarms>
-
 **colossus**: <https://bdiemer.bitbucket.io/colossus/>
 
 **astropy** <https://www.astropy.org/>
diff --git a/docs/research/nfw_ludlow16_jax_assessment.md b/docs/research/nfw_ludlow16_jax_assessment.md
index b69d697ab..7c3f70e5f 100644
--- a/docs/research/nfw_ludlow16_jax_assessment.md
+++ b/docs/research/nfw_ludlow16_jax_assessment.md
@@ -233,7 +233,7 @@ top.
 
 The `kappa_s` discrepancy (1 × 10⁻³ relative, 0.1%) is one bit-flip in a
 typical 10-bit posterior coverage on `kappa_s` — invisible in any plausible
-HMC / Nautilus / MultiNest run on real data.
+HMC / Nautilus / Dynesty run on real data.
 
 ### Verdict on science fidelity