diff --git a/docs/examples/transmon.ipynb b/docs/examples/transmon.ipynb
index b067b29..f6b225c 100644
--- a/docs/examples/transmon.ipynb
+++ b/docs/examples/transmon.ipynb
@@ -7,9 +7,13 @@
     "collapsed": false
    },
    "source": [
-    "# Transmon Floquet analysis\n",
+    "# Floquet analysis\n",
     "\n",
-    "Here we perform a Floquet simulation of a transmon subject to off-resonant drives. We extract as a function of drive strength and drive frequency the probability of ionization for the two qubit states. We then compare the 2D plots (with the x and y axes drive frequency and induced ac stark shift on the qubit, respectively and the z axis ionization probability) with Blais-style branch crossing plots, which identify the states the qubit states leak to."
+    "In this demo we perform four separate simulations to demonstrate the wide applicability of this package. In each case we extract as a function of drive strength and drive frequency the probability of ionization. We then compare these simulations to Blais-style branch crossing plots, which identify the states the qubit states leak to. The four separate simulations are\n",
+    "1. The most typical analysis of a transmon with a readout resonator whose frequency is above the transmon, sweeping the resonator frequency\n",
+    "2. Fixing the resonator frequency, but sweeping a transmon parameter (in this case transmon `EJ`)\n",
+    "3. Parametric pumping of a transmon below its resonance frequency\n",
+    "4. Finally, applying the same analysis as in case 1 to fluxonium"
    ]
   },
   {
@@ -39,12 +43,12 @@
    "id": "f5c02996",
    "metadata": {},
    "source": [
-    "## Define simulation parameters"
+    "## Transmon with readout resonator above the qubit frequency"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 41,
    "id": "fde5cfeb",
    "metadata": {},
    "outputs": [],
@@ -53,6 +57,7 @@
     "\n",
     "# Transmon parameters\n",
     "num_states = 20\n",
+    "# These parameters give a transmon with E10 = 5.45 GHz, alpha = -219 MHz\n",
     "qubit_params = {\"EJ\": 20.0, \"EC\": 0.2, \"ng\": 0.25, \"ncut\": 41}\n",
     "tmon = scq.Transmon(**qubit_params, truncated_dim=num_states)\n",
     "state_indices = [0, 1]  # get data for ground and first excited states\n",
diff --git a/docs/index.md b/docs/index.md
index 3b9e709..c2b7950 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -51,7 +51,7 @@ options = ft.Options(num_cpus=6)
 floquet_analysis = ft.FloquetAnalysis(model, state_indices=state_indices, options=options)
 data_vals = floquet_analysis.run()
 ```
-`data_vals` is a dictionary containing all quantities computed during the call to `run()`. This includes the overlap with the "ideal" displaced state, which can be plotted to reveal "scars" in the drive frequency and amplitude space where resonances occur. This part of the analysis is based on [Xiao, Venkatraman et al, arXiv (2023)](https://arxiv.org/abs/2304.13656), see Appendices I and J. Additionally we perform a so-called branch analysis to understand which states are responsible for ionization, based on [Dumas et al, arXiv 2024](https://arxiv.org/abs/2402.06615). See the transmon tutorial notebook under Examples on the left for more details on the analysis and how to plot and visualize the computed quantities.  
+`data_vals` is a dictionary containing all quantities computed during the call to `run()`. This includes the overlap with the "ideal" displaced state, which can be plotted to reveal "scars" in the drive frequency and amplitude space where resonances occur. This part of the analysis is based on [Xiao, Venkatraman et al, arXiv (2023)](https://arxiv.org/abs/2304.13656), see Appendices I and J. Additionally we perform a so-called branch analysis to understand which states are responsible for ionization, based on [Dumas et al, arXiv 2024](https://arxiv.org/abs/2402.06615). See the tutorial notebook under Examples on the left for more details on the analysis and how to plot and visualize the computed quantities.  
 
 ## Citation