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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "430cdb67",
+   "metadata": {},
+   "source": [
+    "(Root_tutorial)=\n",
+    "\n",
+    "# Symbolic Root Finding\n",
+    ":::{post} June 12, 2025 \n",
+    ":tags: optimization, root finding, worked examples, tutorial\n",
+    ":category: beginner, explanation \n",
+    ":author: Jesse Grabowski\n",
+    ":::\n",
+    "\n",
+    "\n",
+    "When faced with problems involving systems of nonlinear equations, it is rare to actually have access to analytic solutions for the zeros of the system. Nevertheless, these zeros are often important to downstream tasks. A common application is in perturbation theory, where we seek to linearize a nonlinear system around the fixed points of that system.\n",
+    "\n",
+    "To find such fixed points, numerical algorithms such as Newton-Raphson and Broyden's Method are typically utilized. Once you have written down your system symbolically in Pytensor, it is always possible to compile the function (and, if desired, the jacobian of the system), then pass these compiled functions to a numerical solver of your choice.\n",
+    "\n",
+    "This solution can be incomplete, however, in cases where one is interested in using the roots as an intermediate computation in a larger graph. Compiling the function breaks the graph, causing:\n",
+    "\n",
+    "1. Pytensor to not see optimizations, such as re-use of computation, between the two halves, and;\n",
+    "2. We cannot get end-to-end gradients, because the optimization step happens outside of pytensor.\n",
+    "\n",
+    "To address these limitations, pytensor offers *symbolic* root finding via the `pytensor.tensor.optimize.root` function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "d746079b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pytensor\n",
+    "import pytensor.tensor as pt\n",
+    "\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "037051ac",
+   "metadata": {},
+   "source": [
+    "## Basic Usage\n",
+    "\n",
+    "To use `tensor.optimize.root`, first set up a system of equations. The first test function we will look at is:\n",
+    "\n",
+    "$$ \n",
+    "\\begin{align}\n",
+    "x^2 - y - 1 &= 0 \\\\\n",
+    "x - y^2 + 1 &= 0 \n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "This system is analytically tractible. Two roots are immediately visible by simple inspection (aka experience-based guess-and-check): $x=0, y=-1$, and by symmetry, $x=-1, y=0$. \n",
+    "\n",
+    "Remaining roots can be found by solving the first equation for y and plugging in the result to the second:\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "y &= x^2 - 1 \\\\\n",
+    "x - (x^2 - 1)^2 +1 &= 0 \\\\\n",
+    "x -x^4 + 2x^2 -1 + 1 &= 0 \\\\\n",
+    "x^4 - 2x^2 - x &= 0 \\\\\n",
+    "x (x^3 - 2x - x) &= 0\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "As already noted, $x = 0$ is a root, and we see it here. We also can see from inspecting $x^3 - 2x - x$ that $x=-1$ is also a root. Remove the root $x = -1$ from the cubic expression by dividing it by $x+1$ to reduce it to a quadratic factor:\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "\\frac{x^3 - 2x - x}{x + 1} = x^2 - x - 1\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "Which leads to two roots:\n",
+    "\n",
+    "$$x = -\\frac{-1 \\pm \\sqrt{5}}{2}$$\n",
+    "\n",
+    "Plugging this expression back into equation 1:\n",
+    "\n",
+    "$$ \\begin{align}\n",
+    "y &= \\left ( \\frac{-1 \\pm \\sqrt{5}}{2} \\right)^2 - 1 \\\\\n",
+    "y &= \\begin{cases} -\\left ( \\frac{-1 + \\sqrt{5}}{2} \\right)^2 - 1 &  =  -\\frac{-1 + \\sqrt{5}}{2} \\\\\n",
+    "                   - \\left ( \\frac{-1 - \\sqrt{5}}{2} \\right)^2 - 1 & = -\\frac{-1 - \\sqrt{5}}{2}\n",
+    "    \\end{cases}\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "Whichever branch we choose, the value for $x$ and $y$ are the same. So the four roots are:\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "x &= 0, & y &=-1 \\\\\n",
+    "x &= -1, & y&= 0 \\\\\n",
+    "x &= -\\frac{-1 - \\sqrt{5}}{2}, & y&= -\\frac{-1 - \\sqrt{5}}{2} \\\\\n",
+    "x &= -\\frac{-1 + \\sqrt{5}}{2}, & y&= -\\frac{-1 + \\sqrt{5}}{2}\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "In the next cell, we plot this system of equations, and mark the four roots."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e9b609af",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1078x462 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(subplot_kw={'aspect':'equal'}, dpi=77, figsize=(14, 6))\n",
+    "\n",
+    "x_plot = np.linspace(-2, 2, 1000)\n",
+    "ax.plot(x_plot, x_plot ** 2 - 1, color='tab:blue', lw=2, label=r'$y = x^2 - 1$')\n",
+    "\n",
+    "with np.errstate(all='ignore'):\n",
+    "    ax.plot(x_plot, np.sqrt(x_plot + 1), color='tab:orange', lw=2, label=r'$y = \\pm \\sqrt{x + 1}$')\n",
+    "    ax.plot(x_plot, -np.sqrt(x_plot + 1), color='tab:orange', lw=2)\n",
+    "    \n",
+    "ax.axhline(0, ls='--', c='k', lw=0.5)\n",
+    "ax.axvline(0, ls='--', c='k', lw=0.5)\n",
+    "\n",
+    "quad_root_1 = -(-1 + np.sqrt(5)) / 2\n",
+    "quad_root_2 = -(-1 - np.sqrt(5)) / 2\n",
+    "\n",
+    "for x, y in [(0, -1), (-1, 0), (quad_root_1, quad_root_1), (quad_root_2, quad_root_2)]:\n",
+    "    ax.scatter(x, y, color='tab:red', marker='*', zorder=100, s=150)\n",
+    "\n",
+    "ax.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "adcfacb9",
+   "metadata": {},
+   "source": [
+    "To find roots of our system using pytensor, we first have to symbolically set it up. \n",
+    "\n",
+    "Currently, all variables need to be provided in a single vector. So we first make a vector (called `variables`) of length 2, then unpack it into `x` and `y`. I use fancy python double-assignment to do this.\n",
+    "\n",
+    "`x` and `y` are then used to type in our equations. Like scipy, we need to rewrite the system so that the right-hand size is always zero. In this case we already had that, but in general you will need to keep this in mind."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4ad8a428",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x, y = variables = pt.tensor('variables', shape=(2, ))\n",
+    "\n",
+    "eq_1 = x ** 2 - y - 1\n",
+    "eq_2 = x - y ** 2 + 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1dcba2cf",
+   "metadata": {},
+   "source": [
+    "To make a compute graph with a root finder, use `pt.optimize.root`. The function expects:\n",
+    "\n",
+    "- A vector of equations to solve, `equations`\n",
+    "- A vector of variables with respect to which the equations will be solved, `variables`\n",
+    "- Configuration arguments, like `method`, `jac` and `optimizer_kwargs`, which are forwarded to `scipy.optimize.root`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c992e50d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solution, success = pt.optimize.root(equations=pt.stack([eq_1, eq_2]), \n",
+    "                       variables=variables,\n",
+    "                       method='hybr',\n",
+    "                       optimizer_kwargs={'tol':1e-8})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1ecf771b",
+   "metadata": {},
+   "source": [
+    "Looking at the graph for the `solution`, we can see that the outer function takes `variables` as input and returns the first output of `RootOp` (the solution).\n",
+    "\n",
+    "It also has an inner graph with two outputs. The first is a `MakeVector` (this is `pt.stack`), combining `eq1` and `eq2`. So the first inner graph simply computes the equations we provided. The second graph is a `Scan` -- this is the $2\\times2$ Jacobian matrix of the system of the system:\n",
+    "\n",
+    "$$ \n",
+    "J = \\begin{bmatrix} \\frac{\\partial f_1(x,y)}{\\partial x} & \\frac{\\partial f_1(x,y)}{\\partial y} \\\\\n",
+    "                        \\frac{\\partial f_2(x,y)}{\\partial x} & \\frac{\\partial f_2(x,y)}{\\partial y} \n",
+    "    \\end{bmatrix} \n",
+    "$$\n",
+    "\n",
+    "Pytensor happens to compute this matrix using a `Scan`, so that's why one appears here.\n",
+    "\n",
+    "So notice that we don't have to compute the Jacobian for this ourselves -- it's automatically by pytensor! Also pytensor can see all these inner functions and optimize across them. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "61498784",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RootOp(method=hybr, jac=True).0 [id A]\n",
+      " └─ variables [id B]\n",
+      "\n",
+      "Inner graphs:\n",
+      "\n",
+      "RootOp(method=hybr, jac=True) [id A]\n",
+      " ← MakeVector{dtype='float64'} [id C]\n",
+      "    ├─ Sub [id D]\n",
+      "    │  ├─ Sub [id E]\n",
+      "    │  │  ├─ Pow [id F]\n",
+      "    │  │  │  ├─ Subtensor{i} [id G]\n",
+      "    │  │  │  │  ├─ variables [id H]\n",
+      "    │  │  │  │  └─ 0 [id I]\n",
+      "    │  │  │  └─ 2 [id J]\n",
+      "    │  │  └─ Subtensor{i} [id K]\n",
+      "    │  │     ├─ variables [id H]\n",
+      "    │  │     └─ 1 [id L]\n",
+      "    │  └─ 1 [id M]\n",
+      "    └─ Add [id N]\n",
+      "       ├─ Sub [id O]\n",
+      "       │  ├─ Subtensor{i} [id G]\n",
+      "       │  │  └─ ···\n",
+      "       │  └─ Pow [id P]\n",
+      "       │     ├─ Subtensor{i} [id K]\n",
+      "       │     │  └─ ···\n",
+      "       │     └─ 2 [id Q]\n",
+      "       └─ 1 [id R]\n",
+      " ← Scan{scan_fn, while_loop=False, inplace=none} [id S]\n",
+      "    ├─ Subtensor{i} [id T]\n",
+      "    │  ├─ Shape [id U]\n",
+      "    │  │  └─ Subtensor{start:} [id V]\n",
+      "    │  │     ├─ ARange{dtype='int64'} [id W]\n",
+      "    │  │     │  ├─ 0 [id X]\n",
+      "    │  │     │  ├─ Subtensor{i} [id Y]\n",
+      "    │  │     │  │  ├─ Shape [id Z]\n",
+      "    │  │     │  │  │  └─ MakeVector{dtype='float64'} [id C]\n",
+      "    │  │     │  │  │     └─ ···\n",
+      "    │  │     │  │  └─ 0 [id BA]\n",
+      "    │  │     │  └─ 1 [id BB]\n",
+      "    │  │     └─ 0 [id BC]\n",
+      "    │  └─ 0 [id BD]\n",
+      "    ├─ Subtensor{:stop} [id BE]\n",
+      "    │  ├─ Subtensor{start:} [id V]\n",
+      "    │  │  └─ ···\n",
+      "    │  └─ ScalarFromTensor [id BF]\n",
+      "    │     └─ Subtensor{i} [id T]\n",
+      "    │        └─ ···\n",
+      "    ├─ Subtensor{i} [id T]\n",
+      "    │  └─ ···\n",
+      "    ├─ MakeVector{dtype='float64'} [id C]\n",
+      "    │  └─ ···\n",
+      "    └─ variables [id H]\n",
+      "\n",
+      "Scan{scan_fn, while_loop=False, inplace=none} [id S]\n",
+      " ← Add [id BG]\n",
+      "    ├─ IncSubtensor{i} [id BH]\n",
+      "    │  ├─ Second [id BI]\n",
+      "    │  │  ├─ *2-<Vector(float64, shape=(2,))> [id BJ] -> [id H]\n",
+      "    │  │  └─ ExpandDims{axis=0} [id BK]\n",
+      "    │  │     └─ 0.0 [id BL]\n",
+      "    │  ├─ Add [id BM]\n",
+      "    │  │  ├─ Mul [id BN]\n",
+      "    │  │  │  ├─ Mul [id BO]\n",
+      "    │  │  │  │  ├─ Subtensor{i} [id BP]\n",
+      "    │  │  │  │  │  ├─ IncSubtensor{i} [id BQ]\n",
+      "    │  │  │  │  │  │  ├─ Second [id BR]\n",
+      "    │  │  │  │  │  │  │  ├─ *1-<Vector(float64, shape=(2,))> [id BS] -> [id C]\n",
+      "    │  │  │  │  │  │  │  └─ ExpandDims{axis=0} [id BT]\n",
+      "    │  │  │  │  │  │  │     └─ 0.0 [id BU]\n",
+      "    │  │  │  │  │  │  ├─ Second [id BV]\n",
+      "    │  │  │  │  │  │  │  ├─ Subtensor{i} [id BW]\n",
+      "    │  │  │  │  │  │  │  │  ├─ *1-<Vector(float64, shape=(2,))> [id BS] -> [id C]\n",
+      "    │  │  │  │  │  │  │  │  └─ ScalarFromTensor [id BX]\n",
+      "    │  │  │  │  │  │  │  │     └─ *0-<Scalar(int64, shape=())> [id BY] -> [id BE]\n",
+      "    │  │  │  │  │  │  │  └─ 1.0 [id BZ]\n",
+      "    │  │  │  │  │  │  └─ ScalarFromTensor [id BX]\n",
+      "    │  │  │  │  │  │     └─ ···\n",
+      "    │  │  │  │  │  └─ 0 [id CA]\n",
+      "    │  │  │  │  └─ 2 [id J]\n",
+      "    │  │  │  └─ Pow [id CB]\n",
+      "    │  │  │     ├─ Subtensor{i} [id CC]\n",
+      "    │  │  │     │  ├─ *2-<Vector(float64, shape=(2,))> [id BJ] -> [id H]\n",
+      "    │  │  │     │  └─ 0 [id I]\n",
+      "    │  │  │     └─ Sub [id CD]\n",
+      "    │  │  │        ├─ 2 [id J]\n",
+      "    │  │  │        └─ DimShuffle{order=[]} [id CE]\n",
+      "    │  │  │           └─ 1 [id CF]\n",
+      "    │  │  └─ Subtensor{i} [id CG]\n",
+      "    │  │     ├─ IncSubtensor{i} [id BQ]\n",
+      "    │  │     │  └─ ···\n",
+      "    │  │     └─ 1 [id CH]\n",
+      "    │  └─ 0 [id I]\n",
+      "    └─ IncSubtensor{i} [id CI]\n",
+      "       ├─ Second [id CJ]\n",
+      "       │  ├─ *2-<Vector(float64, shape=(2,))> [id BJ] -> [id H]\n",
+      "       │  └─ ExpandDims{axis=0} [id CK]\n",
+      "       │     └─ 0.0 [id CL]\n",
+      "       ├─ Add [id CM]\n",
+      "       │  ├─ Neg [id CN]\n",
+      "       │  │  └─ Subtensor{i} [id BP]\n",
+      "       │  │     └─ ···\n",
+      "       │  └─ Mul [id CO]\n",
+      "       │     ├─ Mul [id CP]\n",
+      "       │     │  ├─ Neg [id CQ]\n",
+      "       │     │  │  └─ Subtensor{i} [id CG]\n",
+      "       │     │  │     └─ ···\n",
+      "       │     │  └─ 2 [id Q]\n",
+      "       │     └─ Pow [id CR]\n",
+      "       │        ├─ Subtensor{i} [id CS]\n",
+      "       │        │  ├─ *2-<Vector(float64, shape=(2,))> [id BJ] -> [id H]\n",
+      "       │        │  └─ 1 [id L]\n",
+      "       │        └─ Sub [id CT]\n",
+      "       │           ├─ 2 [id Q]\n",
+      "       │           └─ DimShuffle{order=[]} [id CU]\n",
+      "       │              └─ 1 [id CV]\n",
+      "       └─ 1 [id L]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<ipykernel.iostream.OutStream at 0x10673b550>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "solution.dprint()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4fedca48",
+   "metadata": {},
+   "source": [
+    "Since we're not doing anything with the outputs, we're ready to compile a function. We don't have any parameters, so we just pass in the variables -- which are treated as the inital values -- and pass back the solution and success flag. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7d770466",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fn = pytensor.function([variables],\n",
+    "                       [solution, success])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aa89c9e5",
+   "metadata": {},
+   "source": [
+    "Looking at the final graph, we see how both outputs -- the system of equations and the jacobian -- become simplified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "3adc6558",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RootOp(method=hybr, jac=True).0 [id A] 0\n",
+      " └─ variables [id B]\n",
+      "RootOp(method=hybr, jac=True).1 [id A] 'success' 0\n",
+      " └─ ···\n",
+      "\n",
+      "Inner graphs:\n",
+      "\n",
+      "RootOp(method=hybr, jac=True) [id A]\n",
+      " ← MakeVector{dtype='float64'} [id C]\n",
+      "    ├─ Composite{((-1.0 + sqr(i0)) - i1)} [id D]\n",
+      "    │  ├─ Subtensor{i} [id E]\n",
+      "    │  │  ├─ variables [id F]\n",
+      "    │  │  └─ 0 [id G]\n",
+      "    │  └─ Subtensor{i} [id H]\n",
+      "    │     ├─ variables [id F]\n",
+      "    │     └─ 1 [id I]\n",
+      "    └─ Composite{((1.0 + i1) - sqr(i0))} [id J]\n",
+      "       ├─ Subtensor{i} [id H]\n",
+      "       │  └─ ···\n",
+      "       └─ Subtensor{i} [id E]\n",
+      "          └─ ···\n",
+      " ← Scan{scan_fn, while_loop=False, inplace=none} [id K]\n",
+      "    ├─ 2 [id L]\n",
+      "    ├─ [0 1] [id M]\n",
+      "    ├─ 2 [id L]\n",
+      "    ├─ MakeVector{dtype='float64'} [id C]\n",
+      "    │  └─ ···\n",
+      "    ├─ Subtensor{i} [id H]\n",
+      "    │  └─ ···\n",
+      "    └─ Subtensor{i} [id E]\n",
+      "       └─ ···\n",
+      "\n",
+      "Composite{((-1.0 + sqr(i0)) - i1)} [id D]\n",
+      " ← sub [id N] 'o0'\n",
+      "    ├─ add [id O]\n",
+      "    │  ├─ -1.0 [id P]\n",
+      "    │  └─ sqr [id Q]\n",
+      "    │     └─ i0 [id R]\n",
+      "    └─ i1 [id S]\n",
+      "\n",
+      "Composite{((1.0 + i1) - sqr(i0))} [id J]\n",
+      " ← sub [id T] 'o0'\n",
+      "    ├─ add [id U]\n",
+      "    │  ├─ 1.0 [id V]\n",
+      "    │  └─ i1 [id W]\n",
+      "    └─ sqr [id X]\n",
+      "       └─ i0 [id Y]\n",
+      "\n",
+      "Scan{scan_fn, while_loop=False, inplace=none} [id K]\n",
+      " ← IncSubtensor{i} [id Z]\n",
+      "    ├─ SetSubtensor{i} [id BA]\n",
+      "    │  ├─ [0. 0.] [id BB]\n",
+      "    │  ├─ Composite{((2.0 * i0 * i1) + i2)} [id BC]\n",
+      "    │  │  ├─ Subtensor{i} [id BD]\n",
+      "    │  │  │  ├─ SetSubtensor{i} [id BE]\n",
+      "    │  │  │  │  ├─ [0. 0.] [id BB]\n",
+      "    │  │  │  │  ├─ 1.0 [id BF]\n",
+      "    │  │  │  │  └─ ScalarFromTensor [id BG]\n",
+      "    │  │  │  │     └─ *0-<Scalar(int64, shape=())> [id BH] -> [id M]\n",
+      "    │  │  │  └─ 0 [id BI]\n",
+      "    │  │  ├─ *3-<Scalar(float64, shape=())> [id BJ] -> [id E]\n",
+      "    │  │  └─ Subtensor{i} [id BK]\n",
+      "    │  │     ├─ SetSubtensor{i} [id BE]\n",
+      "    │  │     │  └─ ···\n",
+      "    │  │     └─ 1 [id BL]\n",
+      "    │  └─ 0 [id BI]\n",
+      "    ├─ Composite{((-2.0 * i0 * i1) - i2)} [id BM]\n",
+      "    │  ├─ Subtensor{i} [id BK]\n",
+      "    │  │  └─ ···\n",
+      "    │  ├─ *2-<Scalar(float64, shape=())> [id BN] -> [id H]\n",
+      "    │  └─ Subtensor{i} [id BD]\n",
+      "    │     └─ ···\n",
+      "    └─ 1 [id BL]\n",
+      "\n",
+      "Composite{((2.0 * i0 * i1) + i2)} [id BC]\n",
+      " ← add [id BO] 'o0'\n",
+      "    ├─ mul [id BP]\n",
+      "    │  ├─ 2.0 [id BQ]\n",
+      "    │  ├─ i0 [id BR]\n",
+      "    │  └─ i1 [id BS]\n",
+      "    └─ i2 [id BT]\n",
+      "\n",
+      "Composite{((-2.0 * i0 * i1) - i2)} [id BM]\n",
+      " ← sub [id BU] 'o0'\n",
+      "    ├─ mul [id BV]\n",
+      "    │  ├─ -2.0 [id BW]\n",
+      "    │  ├─ i0 [id BX]\n",
+      "    │  └─ i1 [id BY]\n",
+      "    └─ i2 [id BZ]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<ipykernel.iostream.OutStream at 0x10673b550>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fn.dprint()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "feab3dd9",
+   "metadata": {},
+   "source": [
+    "Checking some points. We see that starting at $0, 0$, we converge to $x, y = \\frac{-1 - \\sqrt{5}}{2} \\approx -0.618$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "1b4b47e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[array([-0.61803399, -0.61803399]), np.True_]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fn([0., 0.])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aa1df7d0",
+   "metadata": {},
+   "source": [
+    "Starting at $1,1$, we converge to $x, y = \\frac{-1 + \\sqrt{5}}{2} \\approx 1.618$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "aff1d6e4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[array([1.61803399, 1.61803399]), np.True_]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fn([1., 1.])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7ebde90a",
+   "metadata": {},
+   "source": [
+    "Starting at $-1, 1$, we converge to $x=-1, y=0$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "f50a5ff0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[array([-1.00000000e+00, -1.26919661e-12]), np.True_]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fn([-1, 1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ae7a4b57",
+   "metadata": {},
+   "source": [
+    "And starting at $1, -1$, we converge to $x=0, y=-1$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "48b0142d",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[array([-1.2693654e-12, -1.0000000e+00]), np.True_]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fn([1, -1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eb9cbae7",
+   "metadata": {},
+   "source": [
+    "## Graph manipulation\n",
+    "\n",
+    "Since the `root` Op is fully symbolic, we can manipulate its graph as much as we like. \n",
+    "\n",
+    "For example, we can vectorize it. This will allow us to test many points at the same time. To do this, we create a new variable with a batch dimension, then rewrite the graph to work out the resulting dimensions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "1cfebb4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pytensor.graph.replace import vectorize_graph\n",
+    "\n",
+    "variables_grid = pt.tensor('x', shape=(None, 2))\n",
+    "grid_of_solutions = vectorize_graph([solution, success], \n",
+    "                                    {variables:variables_grid})\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bc21773a",
+   "metadata": {},
+   "source": [
+    "Compile the new, vectorized function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "bdc1182f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fn_vec = pytensor.function([variables_grid],\n",
+    "                        grid_of_solutions)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f7d3e24",
+   "metadata": {},
+   "source": [
+    "Now that we're vectorized, the input will be a 2d array of values, with the first column representing `x`, and the second column `y`. \n",
+    "\n",
+    "To quickly get a bunch of pairs of values, we can use `np.meshgrid`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "51f7145c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_values = np.linspace(-2, 2, 30)\n",
+    "xx, yy = np.meshgrid(x_values, x_values)\n",
+    "grid_values = np.c_[xx.ravel(), yy.ravel()]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "3eac6e42",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solution_grid, success_grid = fn_vec(grid_values)\n",
+    "\n",
+    "unique_solutions = np.unique(np.round(solution_grid, 3), axis=0)\n",
+    "solution_ids = {tuple(v.tolist()): k for k, v in enumerate(unique_solutions)}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "024ed40e",
+   "metadata": {},
+   "source": [
+    "Across all the solution, we found only the four roots we expected, which is great!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "d6434b1d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-1.   , -0.   ],\n",
+       "       [-0.618, -0.618],\n",
+       "       [ 0.   , -1.   ],\n",
+       "       [ 1.618,  1.618]])"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "unique_solutions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b856dcb",
+   "metadata": {},
+   "source": [
+    "We can make a nice plot to see that roots roughly correspond to the four graph quadrents. But there are some exceptions, especially near the origin. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "4d2e5d20",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(subplot_kw={'aspect':'equal'}, figsize=(14, 6))\n",
+    "\n",
+    "x_plot = np.linspace(-2, 2, 1000)\n",
+    "ax.plot(x_plot, x_plot ** 2 - 1, color='tab:blue', lw=2)\n",
+    "\n",
+    "with np.errstate(all='ignore'):\n",
+    "    ax.plot(x_plot, np.sqrt(x_plot + 1), color='tab:orange', lw=2)\n",
+    "    ax.plot(x_plot, -np.sqrt(x_plot + 1), color='tab:orange', lw=2)\n",
+    "    \n",
+    "ax.axhline(0, ls='--', c='k', lw=0.5)\n",
+    "ax.axvline(0, ls='--', c='k', lw=0.5)\n",
+    "\n",
+    "colors = ['tab:blue', 'tab:orange', 'tab:green', 'tab:purple']\n",
+    "\n",
+    "rounded_solutions = np.round(solution_grid, 3)\n",
+    "\n",
+    "for root, color in zip(unique_solutions, colors):\n",
+    "    subset_idx = (rounded_solutions == root).all(axis=1)\n",
+    "    subset = grid_values[subset_idx]\n",
+    "    ax.scatter(*subset.T, facecolor=color, edgecolor='none', alpha=0.25, label=fr'$({root[0]}, {root[1]})$')\n",
+    "    ax.scatter(*root, color='tab:red', zorder=1000)\n",
+    "    for x0 in subset:\n",
+    "        ax.annotate(xy=root, xytext=x0, text='', arrowprops={'arrowstyle':'->', 'linewidth':0.5, 'alpha':0.5})\n",
+    "\n",
+    "fig.legend(ncol=1, bbox_to_anchor=(0.65, 0.5), loc='center left')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "26e65d23",
+   "metadata": {},
+   "source": [
+    "## A function with parameters\n",
+    "\n",
+    "Our first function was really simple. More commonly, a function of interest will have both variables and parameters. \n",
+    "\n",
+    "To keep things simple, we can add a coefficent in front of every term in our system of two equations:\n",
+    "\n",
+    "$$ \n",
+    "\\begin{align}\n",
+    "ax^2 + by + c &= 0 \\\\\n",
+    "dx + ey^2 + f &= 0 \n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "Although this still looks quite simple, we no longer have a general analytic solution! If we are faced with a parameterized function like like \"in the wild\", we have no choice but to resort to numerical methods.\n",
+    "\n",
+    "\n",
+    "To get back to what we've been looking at, we can set:  $a=1$, $b=-1$, $c=-1$, $d=1$, $e=-1$, $f=1$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "fe60c766",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x, y = variables = pt.tensor('variables', shape=(2, ))\n",
+    "a, b, c, d, e, f = pt.scalars('a b c d e f'.split())\n",
+    "\n",
+    "eq_1 = a * x ** 2 + b * y + c\n",
+    "eq_2 = d * x + e * y ** 2 + f"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "074a63db",
+   "metadata": {},
+   "source": [
+    "Notice that we don't change the call to `optimize.root` at all!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "48e9291e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "solution, success = pt.optimize.root(equations=pt.stack([eq_1, eq_2]), \n",
+    "                       variables=variables,\n",
+    "                       method='hybr',\n",
+    "                       optimizer_kwargs={'tol':1e-8})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97064e08",
+   "metadata": {},
+   "source": [
+    "Unlike `scipy.optimize.root`, pytensor is going to automatically figure out what additional arguments are required. By knowing `equations` and `variables`, pytensor analyses the implied subgraph, and collects all other unknowns as `args`.\n",
+    "\n",
+    "We can see now that the inputs to the `RootOp` are `variables`, then all the parameters. Otherwise, the graph is unchanged. As a user, though, you will never interact with this inner function! You just pass the parameter values and pytensor will figure out the rest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "5a900fdc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RootOp(method=hybr, jac=True).0 [id A]\n",
+      " ├─ variables [id B]\n",
+      " ├─ f [id C]\n",
+      " ├─ e [id D]\n",
+      " ├─ d [id E]\n",
+      " ├─ c [id F]\n",
+      " ├─ b [id G]\n",
+      " └─ a [id H]\n",
+      "\n",
+      "Inner graphs:\n",
+      "\n",
+      "RootOp(method=hybr, jac=True) [id A]\n",
+      " ← MakeVector{dtype='float64'} [id I]\n",
+      "    ├─ Add [id J]\n",
+      "    │  ├─ Add [id K]\n",
+      "    │  │  ├─ Mul [id L]\n",
+      "    │  │  │  ├─ a [id M]\n",
+      "    │  │  │  └─ Pow [id N]\n",
+      "    │  │  │     ├─ Subtensor{i} [id O]\n",
+      "    │  │  │     │  ├─ variables [id P]\n",
+      "    │  │  │     │  └─ 0 [id Q]\n",
+      "    │  │  │     └─ 2 [id R]\n",
+      "    │  │  └─ Mul [id S]\n",
+      "    │  │     ├─ b [id T]\n",
+      "    │  │     └─ Subtensor{i} [id U]\n",
+      "    │  │        ├─ variables [id P]\n",
+      "    │  │        └─ 1 [id V]\n",
+      "    │  └─ c [id W]\n",
+      "    └─ Add [id X]\n",
+      "       ├─ Add [id Y]\n",
+      "       │  ├─ Mul [id Z]\n",
+      "       │  │  ├─ d [id BA]\n",
+      "       │  │  └─ Subtensor{i} [id O]\n",
+      "       │  │     └─ ···\n",
+      "       │  └─ Mul [id BB]\n",
+      "       │     ├─ e [id BC]\n",
+      "       │     └─ Pow [id BD]\n",
+      "       │        ├─ Subtensor{i} [id U]\n",
+      "       │        │  └─ ···\n",
+      "       │        └─ 2 [id BE]\n",
+      "       └─ f [id BF]\n",
+      " ← Scan{scan_fn, while_loop=False, inplace=none} [id BG]\n",
+      "    ├─ Subtensor{i} [id BH]\n",
+      "    │  ├─ Shape [id BI]\n",
+      "    │  │  └─ Subtensor{start:} [id BJ]\n",
+      "    │  │     ├─ ARange{dtype='int64'} [id BK]\n",
+      "    │  │     │  ├─ 0 [id BL]\n",
+      "    │  │     │  ├─ Subtensor{i} [id BM]\n",
+      "    │  │     │  │  ├─ Shape [id BN]\n",
+      "    │  │     │  │  │  └─ MakeVector{dtype='float64'} [id I]\n",
+      "    │  │     │  │  │     └─ ···\n",
+      "    │  │     │  │  └─ 0 [id BO]\n",
+      "    │  │     │  └─ 1 [id BP]\n",
+      "    │  │     └─ 0 [id BQ]\n",
+      "    │  └─ 0 [id BR]\n",
+      "    ├─ Subtensor{:stop} [id BS]\n",
+      "    │  ├─ Subtensor{start:} [id BJ]\n",
+      "    │  │  └─ ···\n",
+      "    │  └─ ScalarFromTensor [id BT]\n",
+      "    │     └─ Subtensor{i} [id BH]\n",
+      "    │        └─ ···\n",
+      "    ├─ Subtensor{i} [id BH]\n",
+      "    │  └─ ···\n",
+      "    ├─ MakeVector{dtype='float64'} [id I]\n",
+      "    │  └─ ···\n",
+      "    ├─ variables [id P]\n",
+      "    ├─ a [id M]\n",
+      "    ├─ d [id BA]\n",
+      "    ├─ b [id T]\n",
+      "    └─ e [id BC]\n",
+      "\n",
+      "Scan{scan_fn, while_loop=False, inplace=none} [id BG]\n",
+      " ← Add [id BU]\n",
+      "    ├─ IncSubtensor{i} [id BV]\n",
+      "    │  ├─ Second [id BW]\n",
+      "    │  │  ├─ *2-<Vector(float64, shape=(2,))> [id BX] -> [id P]\n",
+      "    │  │  └─ ExpandDims{axis=0} [id BY]\n",
+      "    │  │     └─ 0.0 [id BZ]\n",
+      "    │  ├─ Add [id CA]\n",
+      "    │  │  ├─ Mul [id CB]\n",
+      "    │  │  │  ├─ Mul [id CC]\n",
+      "    │  │  │  │  ├─ Mul [id CD]\n",
+      "    │  │  │  │  │  ├─ Subtensor{i} [id CE]\n",
+      "    │  │  │  │  │  │  ├─ IncSubtensor{i} [id CF]\n",
+      "    │  │  │  │  │  │  │  ├─ Second [id CG]\n",
+      "    │  │  │  │  │  │  │  │  ├─ *1-<Vector(float64, shape=(2,))> [id CH] -> [id I]\n",
+      "    │  │  │  │  │  │  │  │  └─ ExpandDims{axis=0} [id CI]\n",
+      "    │  │  │  │  │  │  │  │     └─ 0.0 [id CJ]\n",
+      "    │  │  │  │  │  │  │  ├─ Second [id CK]\n",
+      "    │  │  │  │  │  │  │  │  ├─ Subtensor{i} [id CL]\n",
+      "    │  │  │  │  │  │  │  │  │  ├─ *1-<Vector(float64, shape=(2,))> [id CH] -> [id I]\n",
+      "    │  │  │  │  │  │  │  │  │  └─ ScalarFromTensor [id CM]\n",
+      "    │  │  │  │  │  │  │  │  │     └─ *0-<Scalar(int64, shape=())> [id CN] -> [id BS]\n",
+      "    │  │  │  │  │  │  │  │  └─ 1.0 [id CO]\n",
+      "    │  │  │  │  │  │  │  └─ ScalarFromTensor [id CM]\n",
+      "    │  │  │  │  │  │  │     └─ ···\n",
+      "    │  │  │  │  │  │  └─ 0 [id CP]\n",
+      "    │  │  │  │  │  └─ *3-<Scalar(float64, shape=())> [id CQ] -> [id M]\n",
+      "    │  │  │  │  └─ 2 [id R]\n",
+      "    │  │  │  └─ Pow [id CR]\n",
+      "    │  │  │     ├─ Subtensor{i} [id CS]\n",
+      "    │  │  │     │  ├─ *2-<Vector(float64, shape=(2,))> [id BX] -> [id P]\n",
+      "    │  │  │     │  └─ 0 [id Q]\n",
+      "    │  │  │     └─ Sub [id CT]\n",
+      "    │  │  │        ├─ 2 [id R]\n",
+      "    │  │  │        └─ DimShuffle{order=[]} [id CU]\n",
+      "    │  │  │           └─ 1 [id CV]\n",
+      "    │  │  └─ Mul [id CW]\n",
+      "    │  │     ├─ Subtensor{i} [id CX]\n",
+      "    │  │     │  ├─ IncSubtensor{i} [id CF]\n",
+      "    │  │     │  │  └─ ···\n",
+      "    │  │     │  └─ 1 [id CY]\n",
+      "    │  │     └─ *4-<Scalar(float64, shape=())> [id CZ] -> [id BA]\n",
+      "    │  └─ 0 [id Q]\n",
+      "    └─ IncSubtensor{i} [id DA]\n",
+      "       ├─ Second [id DB]\n",
+      "       │  ├─ *2-<Vector(float64, shape=(2,))> [id BX] -> [id P]\n",
+      "       │  └─ ExpandDims{axis=0} [id DC]\n",
+      "       │     └─ 0.0 [id DD]\n",
+      "       ├─ Add [id DE]\n",
+      "       │  ├─ Mul [id DF]\n",
+      "       │  │  ├─ Subtensor{i} [id CE]\n",
+      "       │  │  │  └─ ···\n",
+      "       │  │  └─ *5-<Scalar(float64, shape=())> [id DG] -> [id T]\n",
+      "       │  └─ Mul [id DH]\n",
+      "       │     ├─ Mul [id DI]\n",
+      "       │     │  ├─ Mul [id DJ]\n",
+      "       │     │  │  ├─ Subtensor{i} [id CX]\n",
+      "       │     │  │  │  └─ ···\n",
+      "       │     │  │  └─ *6-<Scalar(float64, shape=())> [id DK] -> [id BC]\n",
+      "       │     │  └─ 2 [id BE]\n",
+      "       │     └─ Pow [id DL]\n",
+      "       │        ├─ Subtensor{i} [id DM]\n",
+      "       │        │  ├─ *2-<Vector(float64, shape=(2,))> [id BX] -> [id P]\n",
+      "       │        │  └─ 1 [id V]\n",
+      "       │        └─ Sub [id DN]\n",
+      "       │           ├─ 2 [id BE]\n",
+      "       │           └─ DimShuffle{order=[]} [id DO]\n",
+      "       │              └─ 1 [id DP]\n",
+      "       └─ 1 [id V]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<ipykernel.iostream.OutStream at 0x10673b550>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "solution.dprint()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "877783c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fn = pytensor.function([variables, a, b, c, d, e, f],\n",
+    "                       [solution, success])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "aa07dee7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "arg_inputs = {'a': 1, 'b': -1, 'c': -1, 'd': 1, 'e': -1, 'f': 1}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c72129d4",
+   "metadata": {},
+   "source": [
+    "We can double-check that we still get the same answers:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "5a653a4a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[array([-0.61803399, -0.61803399]), np.True_]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fn([0., 0.], **arg_inputs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "7a345308",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[array([1.61803399, 1.61803399]), np.True_]"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fn([1., 1.], **arg_inputs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96f86022",
+   "metadata": {},
+   "source": [
+    "## Gradients\n",
+    "\n",
+    "Since `root` is symbolic `Op`, we can backprop through it. To do this, we use the implicit value theorem. We have a function $f(x, \\theta)$, where $x$ are the variables, and $\\theta$ are the parameters. There's some optimal $x^\\star$ that depends on $\\theta$ such, such that $f(x^\\star(\\theta), \\theta) = 0$ \n",
+    "\n",
+    "If we take $\\frac{\\partial}{\\partial \\theta} f(x^\\star(\\theta), \\theta)$ and use the chain rule, we get:\n",
+    "\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "\\frac{\\partial}{\\partial \\theta} f(x^\\star(\\theta), \\theta) &= \\frac{\\partial f \\left ( x^\\star(\\theta), \\theta \\right )}{\\partial x^\\star} \\frac{x^\\star(\\theta)}{\\partial \\theta} + \\frac{\\partial f(x^\\star(\\theta), \\theta)}{\\partial \\theta} \\Rightarrow \\\\\n",
+    "0 &= \\left. \\frac{\\partial f \\left ( x, \\theta \\right )}{\\partial x} \\right|_{x = x^\\star} \\frac{\\partial x^\\star(\\theta)}{\\partial \\theta} + \\left. \\frac{\\partial f(x, \\theta)}{\\partial \\theta} \\right |_{x = x^\\star}\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "The zero arises because, by definition, $f(x^\\star(\\theta), \\theta) = 0$. All three of the terms in this expression are matrices, and we know 2 of them. As a result, we can directly solve for the unknown quantity of interest, $\\frac{\\partial x^\\star(\\theta)}{\\partial \\theta}$:\n",
+    "\n",
+    "$$\n",
+    "\\frac{\\partial x^\\star(\\theta)}{\\partial \\theta} = - \\left(\\left. \\frac{\\partial f \\left ( x, \\theta \\right )}{\\partial x} \\right|_{x = x^\\star}\\right)^{-1} \\left. \\frac{\\partial f(x, \\theta)}{\\partial \\theta} \\right |_{x = x^\\star}\n",
+    "$$\n",
+    "\n",
+    "So we just need the jacobian of the objective function with respect to the variables $x$ and parameters $\\theta$, all evaluated at the optimal point $x^\\star$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "90a3a4f2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dx_dtheta = pt.grad(solution[0], [a, b, c, d, e, f])\n",
+    "dy_dtheta = pt.grad(solution[1], [a, b, c, d, e, f])\n",
+    "\n",
+    "d_theta_vec = pt.stack([dx_dtheta, dy_dtheta], axis=-1)\n",
+    "\n",
+    "f_d_theta = pytensor.function([variables, a, b, c, d, e, f], d_theta_vec)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01d4fc9a",
+   "metadata": {},
+   "source": [
+    "These values show, evidently, the effect of a nudge to one of the 6 parameteres (on the rows) on the value of the variables $x$ and $y$ (on the columns). "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "725c23f9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.89442719, -0.7236068 ],\n",
+       "       [-1.4472136 ,  1.17082039],\n",
+       "       [ 2.34164079, -1.89442719],\n",
+       "       [-1.17082039,  1.4472136 ],\n",
+       "       [ 0.7236068 , -0.89442719],\n",
+       "       [ 1.89442719, -2.34164079]])"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f_d_theta([0., 0.], **arg_inputs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5851e416",
+   "metadata": {},
+   "source": [
+    "Note that this is unique to the root associated with the $(0, 0)$ point. If we shift the point $(0, 0)$ slightly, but still in a zone that converges to the $(-0.618, -0.618)$ root, we will get the same gradients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "4f35bcbe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.89442719, -0.7236068 ],\n",
+       "       [-1.4472136 ,  1.17082039],\n",
+       "       [ 2.34164079, -1.89442719],\n",
+       "       [-1.17082039,  1.4472136 ],\n",
+       "       [ 0.7236068 , -0.89442719],\n",
+       "       [ 1.89442719, -2.34164079]])"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f_d_theta([-1.0, -1.0], **arg_inputs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cce26caf",
+   "metadata": {},
+   "source": [
+    "On the other hand, if we evaluate at a different root, for example the $(1.618, 1.618)$ root, we will have different gradients."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "9737f793",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-0.89442719, -0.2763932 ],\n",
+       "       [-0.5527864 , -0.17082039],\n",
+       "       [-0.34164079, -0.10557281],\n",
+       "       [ 0.17082039,  0.5527864 ],\n",
+       "       [ 0.2763932 ,  0.89442719],\n",
+       "       [ 0.10557281,  0.34164079]])"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f_d_theta([0.8, 0.8], **arg_inputs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5803a46f",
+   "metadata": {},
+   "source": [
+    "## Using roots for downstream computation\n",
+    "\n",
+    "Often, there are quantities of interest downstream of an optimization problem that researchers are interested in studying.\n",
+    "\n",
+    "One such example comes from labor economics. The [McCall Search Model](https://python.quantecon.org/mccall_model.html) is a relatively simple model of how people look for jobs. Every day, an unemployed worker wakes up and gets a job offer. The wage of the job on offer that day (at time $t$) is drawn from a known distribution $w_t \\sim Q(\\cdot)$. Offers are IID across time.\n",
+    "\n",
+    "The workers can either:\n",
+    "\n",
+    "1. Accept the job and work it for the rest of his life, earning $w_t$ forever, or;\n",
+    "2. Reject the job, and wait for another one to come along. In this case, he earns unemployment benefits $c$, and gets to see another offer tomorrow.\n",
+    "\n",
+    "The agent's objective is to maxmize expected discounted utility over his lifetime. We assume he discounts at rate $\\beta$, such that:\n",
+    "\n",
+    "$$ U_t = \\mathbb E_t \\left [\\sum_{s=0}^\\infty \\beta^s y_{t+s} \\right ] $$\n",
+    "\n",
+    "Where $y_t$ is the the income the worker will earn at period $t$, either $c$ or $w_\\tau$, depending on his choices up to that point ($\\tau$ is the period in which he accepted the wage, if he did).\n",
+    "\n",
+    "Interested readers can check the quantecon link for details. For our purposes here, it suffices to say that this is a dynamic program involving a search for an optimal **value function**. A value function maps states of the world to expected utility, allowing an agent to evaluate actions. With some manipulation, it can be shown that the worker in this model has the following value function:\n",
+    "\n",
+    "$$ v^\\star(w)\n",
+    "= \\max \\left\\{\n",
+    "        \\frac{w}{1 - \\beta}, \\, c + \\beta\n",
+    "        \\sum_{w' \\in \\mathbb{W}} v^\\star(w') q (w')\n",
+    "    \\right\\}\n",
+    "$$\n",
+    "\n",
+    "Where $w$ is a vector of all known wages (or at least some kind of sampling over the support of the wage distribution, $\\mathbb{W}$). So $v$, $w$ and $q(w)$ are all vectors. By $v^\\star(w)$, we mean the value of a wage offer $w$ under the optimal value function, $v^\\star$.\n",
+    "\n",
+    "Because of the special properties of this value function, it can be shown that it defines a **fixed-point operator** $T$. Starting an arbitrary vector $v_0$, iteratively applying the following function:\n",
+    "\n",
+    "$$\n",
+    "Tv_i\n",
+    "= \\max \\left\\{\n",
+    "        \\frac{w_i}{1 - \\beta}, \\, c + \\beta \\sum_{1 \\leq j \\leq n}\n",
+    "            v(j) q (j)\n",
+    "    \\right\\}\n",
+    "\\quad\n",
+    "\\text{for } i = 1, \\ldots, n\n",
+    "$$\n",
+    "\n",
+    "Will eventaully converge to the optimal value function, no matter what $v_0$ is chosen."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "941cf87e",
+   "metadata": {},
+   "source": [
+    "### Where's the root?\n",
+    "\n",
+    "What quantecon presents is **value function iteration**. We can, however, just jump to the end by interpreting the definition of the fixed-point operator $Tv$ as a system of non-linear equations. In particular, we just require some vector $v$ such that:\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "Tv - v &= 0 && \\Rightarrow  \\\\\n",
+    "\\max \\left\\{\n",
+    "        \\frac{w}{1 - \\beta}, \\, c + \\beta \\sum_{1 \\leq j \\leq n}\n",
+    "            v(j) q (j)\n",
+    "    \\right\\} - v &= 0 &&\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "Such a vector will contain all the **roots** of this equation. We can find the answer directly, without using value-function iteration."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "89b8f8d8",
+   "metadata": {},
+   "source": [
+    "### Where do wages come from?\n",
+    "\n",
+    "This is a free choice in the model. Following QuantEcon, we will assume they follow a *Beta-Binomial Distribution*. Pytensor implements this random variable and can draw samples from it, but it doesn't give us the PMF out of the box. We have to write it ourselves, using the definition from [Wikipedia](https://en.wikipedia.org/wiki/Beta-binomial_distribution):\n",
+    "\n",
+    "$$\n",
+    "f(x\\mid n,\\alpha,\\beta)\n",
+    "= \\begin{pmatrix} n \\\\ k \\end{pmatrix} \\frac{B(x + \\alpha, n - x + \\beta)}{B(\\alpha, \\beta)}\n",
+    "$$\n",
+    "\n",
+    "Where $B(x, y)$ is the Beta function.\n",
+    "\n",
+    "For numerical stability, we will actually compute the logpmf, then exp it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "f065a891",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pytensor.tensor.special import betaln\n",
+    "\n",
+    "n, a, b = pt.scalars('n a b'.split())\n",
+    "w_min, w_max = pt.scalars('w_min w_max'.split())\n",
+    "\n",
+    "w_support = pt.linspace(w_min, w_max, n+1)\n",
+    "\n",
+    "k = pt.floor(w_support)\n",
+    "ln_n_choose_k = -pt.log(n + 1) - betaln(n - k + 1, k + 1)\n",
+    "q_probs = pt.exp(ln_n_choose_k + betaln(k + a, n - k + b) - betaln(a, b))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "543052e6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dist_args = [n, a, b, w_min, w_max]\n",
+    "f = pytensor.function(dist_args, [w_support, q_probs])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "b90d037a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dist_params = {'n':50, 'a':200, 'b':100, 'w_min':10, 'w_max':60}\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(14, 4))\n",
+    "ax.bar(*f(**dist_params))\n",
+    "ax.set(title='Wage Distribution', xlabel='Wage', ylabel='P(Wage)')\n",
+    "ax.grid(ls='--', lw=0.5)\n",
+    "[spine.set_visible(False) for spine in ax.spines.values()]\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a4e368ba",
+   "metadata": {},
+   "source": [
+    "### Setting up the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "ed92df70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c = pt.dscalar('c') # Unemployment benefit\n",
+    "β = pt.dscalar('β') # Discount rate\n",
+    "\n",
+    "# initial value function guess\n",
+    "v0 = pt.dvector('v0') \n",
+    "\n",
+    "# Fixed-point operator\n",
+    "T = pt.maximum(w_support / (1 - β), c + β * pt.dot(v0, q_probs))\n",
+    "\n",
+    "v_star, success = pt.optimize.root(equations=T - v0,\n",
+    "                                   variables=v0,\n",
+    "                                   method='hybr')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "fdc49be0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fn = pytensor.function([v0, c, β, *dist_args],\n",
+    "                       [w_support, v_star, success])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e6e77f4",
+   "metadata": {},
+   "source": [
+    "### Solving for the value function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "e70e2bae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c_value = 25\n",
+    "beta_value = 0.99\n",
+    "v0_value = np.zeros(dist_params['n'] + 1)\n",
+    "\n",
+    "w_values, v_star_val, success_flag = fn(v0_value, c_value, beta_value, **dist_params)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "22af8580",
+   "metadata": {},
+   "source": [
+    "This plot shows the optimal value function. Below the reservation wage (which appears to be around 38), the worker will not accept a job, and gets constant utility from being on unemployment. After the reservation wage, his lifetime utility is increasing linearly in his wage level. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "29760ad2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2016x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(14, 4), dpi=144)\n",
+    "ax.plot(w_values, v_star_val)\n",
+    "ax.set(title='Lifetime Value of Wages', xlabel='Wage', ylabel='Value Function')\n",
+    "ax.grid(ls='--', lw=0.5)\n",
+    "[spine.set_visible(False) for spine in ax.spines.values()]\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "792a3381",
+   "metadata": {},
+   "source": [
+    "### Studying the reservation wage"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eb63e54a",
+   "metadata": {},
+   "source": [
+    "While the shape of the value function is interesting per se, it is not the primary object of interest in this study. Instead, we are interested in the reservation wage -- the minimum wage at which the worker will willingly choose to exit unemployment and join the workforce.\n",
+    "\n",
+    "This wage can be computed as:\n",
+    "\n",
+    "$$\n",
+    "\\bar w := (1 - \\beta) \\left\\{ c + \\beta \\sum_{w'} v^*(w') q (w') \\right\\}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "b318e23c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "w_bar = (1 - β) * (c + β * pt.dot(v_star, q_probs))\n",
+    "\n",
+    "# We want to study the impact of change in unemployment and patience on the reserve wage \n",
+    "w_grads = pt.grad(w_bar, [c, β])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "a77aa3d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fn_2 = pytensor.function([v0, c, β, *dist_args],\n",
+    "                         [success, w_bar, *w_grads],\n",
+    "                         on_unused_input='ignore')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "fa568587",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reservation wage at c=25, β=0.99: 38.13336026307221\n",
+      "Change in reservation wage given unit change in c: 0.12353985797683031\n",
+      "Change in reservation wage given 1% change in β: 1.638882284503543\n"
+     ]
+    }
+   ],
+   "source": [
+    "success_flag, reservation_wage, dw_dc, dw_dβ = fn_2(v0_value, c_value, beta_value, **dist_params)\n",
+    "print(f'Reservation wage at c={c_value}, β={beta_value}: {reservation_wage.item()}')\n",
+    "print(f'Change in reservation wage given unit change in c: {dw_dc}')\n",
+    "print(f'Change in reservation wage given 1% change in β: {dw_dβ / 100}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "86110c8c",
+   "metadata": {},
+   "source": [
+    "We likely want to study the effect of many pairs of c and $\\beta$, so we vectorize the function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "798abcb6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c_grid = pt.dmatrix('c_grid')\n",
+    "β_grid = pt.dmatrix('β_grid')\n",
+    "\n",
+    "w_bar_grid, *w_grad_grid = vectorize_graph([w_bar, *w_grads], {β:β_grid, c:c_grid})\n",
+    "\n",
+    "fn_grid = pytensor.function([v0, c_grid, β_grid, *dist_args],\n",
+    "                            [w_bar_grid, *w_grad_grid],\n",
+    "                            on_unused_input='ignore')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "c9dc5bb7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c_values = np.linspace(10, 50, 30)\n",
+    "β_values = np.linspace(0.1, 0.99, 30)\n",
+    "\n",
+    "cc, bb = np.meshgrid(c_values, β_values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "46c5a937",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Use the answer we already found as starting value to try to speed up convergence\n",
+    "\n",
+    "w_bar_grid_vals, *w_grad_grid_vals = fn_grid(v_star_val, cc, bb,\n",
+    "                                             **dist_params)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b2010d3f",
+   "metadata": {},
+   "source": [
+    "This next cell reproduces the final plot of the quantecon lecture"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "a5434ef6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(8, 5))\n",
+    "cs1 = ax.contourf(cc, bb, w_bar_grid_vals, alpha=0.75)\n",
+    "ctr1 = ax.contour(cc, bb, w_bar_grid_vals, colors='k', linestyles='dashed', )\n",
+    "\n",
+    "ax.clabel(ctr1, inline=1, fontsize=13, colors='k')\n",
+    "plt.colorbar(cs1, ax=ax)\n",
+    "\n",
+    "ax.set_title(\"reservation wage\")\n",
+    "ax.set_xlabel(\"$c$\", fontsize=16)\n",
+    "ax.set_ylabel(\"$β$\", fontsize=16)\n",
+    "\n",
+    "ax.ticklabel_format(useOffset=False)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9c3bab4b",
+   "metadata": {},
+   "source": [
+    "Since we have the gradients, we can also show a vector field of how the reservation wage changes at each point.\n",
+    "\n",
+    "From this perspective, we see that the reservation wage increases more when $c$ is increased by \\\\$1 than when $\\beta$ is increased by 1\\%. The gradients primarily point in the $c$ direction, except when $c < 20$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "1d2d756c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(8, 5))\n",
+    "cc_grad, bb_grad = w_grad_grid_vals\n",
+    "\n",
+    "cs1 = ax.contourf(cc, bb, w_bar_grid_vals, alpha=0.75)\n",
+    "ax.quiver(cc, bb, cc_grad, bb_grad / 100)\n",
+    "\n",
+    "plt.colorbar(cs1, ax=ax)\n",
+    "\n",
+    "ax.set_title(\"reservation wage\")\n",
+    "ax.set_xlabel(\"$c$\", fontsize=16)\n",
+    "ax.set_ylabel(\"$β$\", fontsize=16)\n",
+    "\n",
+    "ax.ticklabel_format(useOffset=False)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "564a8ea4",
+   "metadata": {},
+   "source": [
+    "### Effect of the wage distribution"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2feee726",
+   "metadata": {},
+   "source": [
+    "Since our entire problem is symbolic -- including the distribution over wage offers -- we can also study the effect of a shift in the wage distribution. To do this, we fix $\\beta = 0.99$ and $c=25$, and instead vectorize $\\alpha$, $\\beta$, and $n$. \n",
+    "\n",
+    "We are interested in the effect of shifts in the moments of the distribution. For a Beta-Binominal, the first two raw moments are:\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "\\mu &= np \\\\\n",
+    "\\sigma^2 &= np(1 - p)[1 + (n-1)\\rho ]\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "Where $p = \\frac{\\alpha}{\\alpha + \\beta}$ and $\\rho = \\frac{1}{\\alpha + \\beta + 1}$\n",
+    "\n",
+    "For this analysis, it's not helpful to have the problem written in terms of $\\alpha$ and $\\beta$ -- we'd like to ask questions like \"what happens if the mean or variance of the wage distribution changes\"? \n",
+    "\n",
+    "To do this, we can reparameterize the wage distribution in terms of $\\mu$ and $\\sigma$. Given a fixed $n$, we simply solve the two equations above for $\\alpha$ and $\\beta$:\n",
+    "\n",
+    "$$\n",
+    "\\begin{align}\n",
+    "\\alpha &= \\frac{\\mu (\\mu^2 - n \\mu + \\sigma ^2 )}{-\\mu^2 + n \\mu - n \\sigma^2} \\\\\n",
+    "\\beta &= \\frac{(\\mu - n) (\\mu^2 - n \\mu + \\sigma^2 )}{\\mu^2 - n \\mu + n \\sigma^2}\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "We will re-use the graphs we've been using so far, merely replacing $\\alpha$ and $\\beta$ by these functions of $\\mu$ and $\\sigma$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "c8ac0c84",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mu, sigma = pt.scalars('mu sigma'.split())\n",
+    "a_fn = mu * (mu ** 2 - mu * n + sigma ** 2) / (-mu ** 2 + mu * n - n * sigma ** 2)\n",
+    "b_fn = (mu - n) * (mu ** 2 - mu * n + sigma ** 2) / (mu ** 2 - mu * n + n * sigma ** 2)\n",
+    "\n",
+    "w_bar_2 = pytensor.graph_replace(w_bar, {a: a_fn, b:b_fn})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5355af67",
+   "metadata": {},
+   "source": [
+    "To drive home what we've just done, we can look at what input values `w_bar_2` expects. Note that `a` and `b` no longer appear! Instead, it looks for `mu` and `sigma`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "826df86b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[β, c, v0, n, w_min, w_max, mu, sigma]"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pytensor.graph.basic import explicit_graph_inputs\n",
+    "list(explicit_graph_inputs(w_bar_2))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8ef7370b",
+   "metadata": {},
+   "source": [
+    "We can check that our formulas are right by checking that we can make a \"round trip\" from the original parameterization of $a=200$, $b=100$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "0991edad",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mu = 33.333\n",
+      "sigma = 3.594\n"
+     ]
+    }
+   ],
+   "source": [
+    "p = a / (a + b)\n",
+    "rho = 1 / (1 + a + b)\n",
+    "\n",
+    "mu_val = (p * n).eval({a:200, b:100, n:50})\n",
+    "sigma_val = pt.sqrt(n * p * (1 - p) * (1 + (n - 1) * rho)).eval({a:200, b:100, n:50})\n",
+    "\n",
+    "print(f'mu = {mu_val.item():0.3f}')\n",
+    "print(f'sigma = {sigma_val.item():0.3f}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "448604df",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "a = 200.00\n",
+      "b = 100.00\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f'a = {a_fn.eval({mu:mu_val, sigma:sigma_val, n:50}):0.2f}')\n",
+    "print(f'b = {b_fn.eval({mu:mu_val, sigma:sigma_val, n:50}):0.2f}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63ac410c",
+   "metadata": {},
+   "source": [
+    "We can also plot the distributions we get for different values of $\\mu$ and $\\sigma$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "ac2faccc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dist_args = [n, mu, sigma, w_min, w_max]\n",
+    "f = pytensor.function(dist_args, [w_support, \n",
+    "                                  pytensor.graph_replace(q_probs, {a:a_fn, b:b_fn})])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "5fe29a45",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dist_params = {'n':50, 'mu':33.333, 'sigma':3.594, 'w_min':10, 'w_max':60}\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(14, 4))\n",
+    "\n",
+    "ax.bar(*f(**dist_params), alpha=0.75, label='μ=33.3, σ=3.594')\n",
+    "ax.bar(*f(**dist_params | {'mu':40}), alpha=0.75, label='μ=40.0, σ=3.594')\n",
+    "ax.bar(*f(**dist_params | {'sigma': 5.0}), alpha=0.75, label='μ=33.3, σ=5.0')\n",
+    "\n",
+    "ax.set(title='Wage Distribution', xlabel='Wage', ylabel='P(Wage)')\n",
+    "ax.legend()\n",
+    "\n",
+    "ax.grid(ls='--', lw=0.5)\n",
+    "[spine.set_visible(False) for spine in ax.spines.values()]\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b2b9f287",
+   "metadata": {},
+   "source": [
+    "Nice! Now let's vectorize w_bar over $\\mu$ and $\\sigma^2$, and make a contour plot with vector field"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "ba6f5ed5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mu_grid, sigma_grid = pt.dmatrices('mu_grid', 'sigma_grid')\n",
+    "w_bar_dist_grads = pt.grad(w_bar_2, [mu, sigma])\n",
+    "\n",
+    "w_bar_grid, *w_grad_grid = vectorize_graph([w_bar_2, *w_bar_dist_grads], {mu:mu_grid, sigma:sigma_grid})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "ac4b9228",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fn_w_bar_dist = pytensor.function([v0, c, β, mu_grid, sigma_grid, n, w_min, w_max],\n",
+    "                                  [w_bar_grid, *w_grad_grid])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "27ce3b7a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mu_values = np.linspace(15, 35, 30)\n",
+    "sigma_values = np.linspace(2.5, 10, 30)\n",
+    "\n",
+    "mm, ss = np.meshgrid(mu_values, sigma_values)\n",
+    "\n",
+    "w_bars, mu_grads, sigma_grads = fn_w_bar_dist(v0_value, c=25, β=0.99, mu_grid=mm, sigma_grid=ss,\n",
+    "                                              n=50, w_min=10, w_max=60)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6e9f168c",
+   "metadata": {},
+   "source": [
+    "From this last plot, we can see the effects of varying the mean (x-axis) and standard deviation (y-axis) of the wage distribution. Since we have access to the gradients, we can also see how the reservation wage changes at each grid point.\n",
+    "\n",
+    "Perhaps unsurprisingly, as the mean wage increases, the reservation wage increases. The effect of variance, on the other hand, is revealed to be more complex. When the mean is low, the reservation wage is strictly decreasing in variance. But as the mean increases, there are \"sweet spots\" in variance, above and below which the reservation wage decreases."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "1066aff6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(8, 5))\n",
+    "\n",
+    "cs1 = ax.contourf(mm, ss, w_bars, alpha=0.75)\n",
+    "ax.quiver(mm, ss, mu_grads, sigma_grads)\n",
+    "\n",
+    "plt.colorbar(cs1, ax=ax)\n",
+    "\n",
+    "ax.set_title(\"reservation wage\")\n",
+    "ax.set_xlabel(r\"$\\mu$\", fontsize=16)\n",
+    "ax.set_ylabel(r\"$\\sigma^2$\", fontsize=16)\n",
+    "\n",
+    "ax.ticklabel_format(useOffset=False)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9495f353",
+   "metadata": {},
+   "source": [
+    "## Conclusion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "61be28c4",
+   "metadata": {},
+   "source": [
+    "Anyway, the key point is not the result of the analysis. Instead, we see how we can leverage the power of pytensor's symbolic graph manipulation to:\n",
+    "\n",
+    "- Solve a root-finding problem\n",
+    "- Compute quantities of interest that depend on the solution\n",
+    "- Use graph transformations, including `graph_replace`, `vectorize_graph`, and `grad`, to push the analysis even further"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "071fee51",
+   "metadata": {},
+   "source": [
+    "## Authors\n",
+    "\n",
+    "- Authored by Jesse Grabowski in June 2025"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d08d2548",
+   "metadata": {},
+   "source": [
+    "## References\n",
+    "\n",
+    ":::{bibliography} :filter: docname in docnames"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17360af5",
+   "metadata": {},
+   "source": [
+    "## Watermark "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "d22c2ef1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Last updated: Thu Jun 12 2025\n",
+      "\n",
+      "Python implementation: CPython\n",
+      "Python version       : 3.12.9\n",
+      "IPython version      : 9.1.0\n",
+      "\n",
+      "pytensor: 2.31.3+9.g0b1cddc3c.dirty\n",
+      "\n",
+      "matplotlib: 3.10.3\n",
+      "numpy     : 2.2.4\n",
+      "pytensor  : 2.31.3+9.g0b1cddc3c.dirty\n",
+      "\n",
+      "Watermark: 2.5.0\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "%load_ext watermark\n",
+    "%watermark -n -u -v -iv -w -p pytensor"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/doc/library/tensor/index.rst b/doc/library/tensor/index.rst
index 519d49293c..23f0698e50 100644
--- a/doc/library/tensor/index.rst
+++ b/doc/library/tensor/index.rst
@@ -31,3 +31,4 @@ symbolic expressions using calls that look just like numpy calls, such as
     math_opt
     basic_opt
     functional
+    optimize
diff --git a/doc/library/tensor/optimize.rst b/doc/library/tensor/optimize.rst
new file mode 100644
index 0000000000..b09b1fc32b
--- /dev/null
+++ b/doc/library/tensor/optimize.rst
@@ -0,0 +1,11 @@
+========================================================
+:mod:`tensor.optimize` -- Symbolic Optimization Routines
+========================================================
+
+.. module:: tensor.conv
+   :platform: Unix, Windows
+   :synopsis: Symbolic Optimization Routines
+.. moduleauthor:: LISA, PyMC Developers, PyTensor Developers
+
+.. automodule:: pytensor.tensor.optimize
+    :members:
diff --git a/pytensor/tensor/__init__.py b/pytensor/tensor/__init__.py
index ce590f8228..afcc08a612 100644
--- a/pytensor/tensor/__init__.py
+++ b/pytensor/tensor/__init__.py
@@ -118,6 +118,7 @@ def _get_vector_length_Constant(op: Op | Variable, var: Constant) -> int:
 from pytensor.tensor import linalg
 from pytensor.tensor import special
 from pytensor.tensor import signal
+from pytensor.tensor import optimize
 
 # For backward compatibility
 from pytensor.tensor import nlinalg
diff --git a/pytensor/tensor/optimize.py b/pytensor/tensor/optimize.py
index 09a11563bb..99a3d8b444 100644
--- a/pytensor/tensor/optimize.py
+++ b/pytensor/tensor/optimize.py
@@ -4,17 +4,14 @@
 from typing import cast
 
 import numpy as np
-from scipy.optimize import minimize as scipy_minimize
-from scipy.optimize import minimize_scalar as scipy_minimize_scalar
-from scipy.optimize import root as scipy_root
-from scipy.optimize import root_scalar as scipy_root_scalar
 
 import pytensor.scalar as ps
-from pytensor import Variable, function, graph_replace
+from pytensor.compile.function import function
 from pytensor.gradient import grad, hessian, jacobian
 from pytensor.graph import Apply, Constant, FunctionGraph
 from pytensor.graph.basic import ancestors, truncated_graph_inputs
 from pytensor.graph.op import ComputeMapType, HasInnerGraph, Op, StorageMapType
+from pytensor.graph.replace import graph_replace
 from pytensor.tensor.basic import (
     atleast_2d,
     concatenate,
@@ -24,7 +21,12 @@
 )
 from pytensor.tensor.math import dot
 from pytensor.tensor.slinalg import solve
-from pytensor.tensor.variable import TensorVariable
+from pytensor.tensor.variable import TensorVariable, Variable
+
+
+# scipy.optimize can be slow to import, and will not be used by most users
+# We import scipy.optimize lazily inside optimization perform methods to avoid this.
+optimize = None
 
 
 _log = logging.getLogger(__name__)
@@ -352,8 +354,6 @@ def implict_optimization_grads(
 
 
 class MinimizeScalarOp(ScipyScalarWrapperOp):
-    __props__ = ("method",)
-
     def __init__(
         self,
         x: Variable,
@@ -377,7 +377,14 @@ def __init__(
         self._fn = None
         self._fn_wrapped = None
 
+    def __str__(self):
+        return f"{self.__class__.__name__}(method={self.method})"
+
     def perform(self, node, inputs, outputs):
+        global optimize
+        if optimize is None:
+            import scipy.optimize as optimize
+
         f = self.fn_wrapped
         f.clear_cache()
 
@@ -385,7 +392,7 @@ def perform(self, node, inputs, outputs):
         # the args of the objective function), but it is not used in the optimization.
         x0, *args = inputs
 
-        res = scipy_minimize_scalar(
+        res = optimize.minimize_scalar(
             fun=f.value,
             args=tuple(args),
             method=self.method,
@@ -426,6 +433,27 @@ def minimize_scalar(
 ):
     """
     Minimize a scalar objective function using scipy.optimize.minimize_scalar.
+
+    Parameters
+    ----------
+    objective : TensorVariable
+        The objective function to minimize. This should be a PyTensor variable representing a scalar value.
+    x : TensorVariable
+        The variable with respect to which the objective function is minimized. It must be a scalar and an
+        input to the computational graph of `objective`.
+    method : str, optional
+        The optimization method to use. Default is "brent". See `scipy.optimize.minimize_scalar` for other options.
+    optimizer_kwargs : dict, optional
+        Additional keyword arguments to pass to `scipy.optimize.minimize_scalar`.
+
+    Returns
+    -------
+    solution: TensorVariable
+        Value of `x` that minimizes `objective(x, *args)`. If the success flag is False, this will be the
+        final state returned by the minimization routine, not necessarily a minimum.
+    success : TensorVariable
+        Symbolic boolean flag indicating whether the minimization routine reported convergence to a minimum
+        value, based on the requested convergence criteria.
     """
 
     args = _find_optimization_parameters(objective, x)
@@ -438,12 +466,14 @@ def minimize_scalar(
         optimizer_kwargs=optimizer_kwargs,
     )
 
-    return minimize_scalar_op(x, *args)
+    solution, success = cast(
+        tuple[TensorVariable, TensorVariable], minimize_scalar_op(x, *args)
+    )
 
+    return solution, success
 
-class MinimizeOp(ScipyWrapperOp):
-    __props__ = ("method", "jac", "hess", "hessp")
 
+class MinimizeOp(ScipyWrapperOp):
     def __init__(
         self,
         x: Variable,
@@ -487,11 +517,24 @@ def __init__(
         self._fn = None
         self._fn_wrapped = None
 
+    def __str__(self):
+        str_args = ", ".join(
+            [
+                f"{arg}={getattr(self, arg)}"
+                for arg in ["method", "jac", "hess", "hessp"]
+            ]
+        )
+        return f"{self.__class__.__name__}({str_args})"
+
     def perform(self, node, inputs, outputs):
+        global optimize
+        if optimize is None:
+            import scipy.optimize as optimize
+
         f = self.fn_wrapped
         x0, *args = inputs
 
-        res = scipy_minimize(
+        res = optimize.minimize(
             fun=f.value_and_grad if self.jac else f.value,
             jac=self.jac,
             x0=x0,
@@ -538,7 +581,7 @@ def minimize(
     jac: bool = True,
     hess: bool = False,
     optimizer_kwargs: dict | None = None,
-):
+) -> tuple[TensorVariable, TensorVariable]:
     """
     Minimize a scalar objective function using scipy.optimize.minimize.
 
@@ -563,9 +606,13 @@ def minimize(
 
     Returns
     -------
-    TensorVariable
-        The optimized value of x that minimizes the objective function.
+    solution: TensorVariable
+        The optimized value of the vector of inputs `x` that minimizes `objective(x, *args)`. If the success flag
+        is False, this will be the final state of the minimization routine, but not necessarily a minimum.
 
+    success: TensorVariable
+        Symbolic boolean flag indicating whether the minimization routine reported convergence to a minimum
+        value, based on the requested convergence criteria.
     """
     args = _find_optimization_parameters(objective, x)
 
@@ -579,12 +626,14 @@ def minimize(
         optimizer_kwargs=optimizer_kwargs,
     )
 
-    return minimize_op(x, *args)
+    solution, success = cast(
+        tuple[TensorVariable, TensorVariable], minimize_op(x, *args)
+    )
+
+    return solution, success
 
 
 class RootScalarOp(ScipyScalarWrapperOp):
-    __props__ = ("method", "jac", "hess")
-
     def __init__(
         self,
         variables,
@@ -633,14 +682,24 @@ def __init__(
         self._fn = None
         self._fn_wrapped = None
 
+    def __str__(self):
+        str_args = ", ".join(
+            [f"{arg}={getattr(self, arg)}" for arg in ["method", "jac", "hess"]]
+        )
+        return f"{self.__class__.__name__}({str_args})"
+
     def perform(self, node, inputs, outputs):
+        global optimize
+        if optimize is None:
+            import scipy.optimize as optimize
+
         f = self.fn_wrapped
         f.clear_cache()
         # f.copy_x = True
 
         variables, *args = inputs
 
-        res = scipy_root_scalar(
+        res = optimize.root_scalar(
             f=f.value,
             fprime=f.grad if self.jac else None,
             fprime2=f.hess if self.hess else None,
@@ -676,19 +735,48 @@ def L_op(self, inputs, outputs, output_grads):
 
 def root_scalar(
     equation: TensorVariable,
-    variables: TensorVariable,
+    variable: TensorVariable,
     method: str = "secant",
     jac: bool = False,
     hess: bool = False,
     optimizer_kwargs: dict | None = None,
-):
+) -> tuple[TensorVariable, TensorVariable]:
     """
     Find roots of a scalar equation using scipy.optimize.root_scalar.
+
+    Parameters
+    ----------
+    equation : TensorVariable
+        The equation for which to find roots. This should be a PyTensor variable representing a single equation in one
+        variable. The function will find `variables` such that `equation(variables, *args) = 0`.
+    variable : TensorVariable
+        The variable with respect to which the equation is solved. It must be a scalar and an input to the
+        computational graph of `equation`.
+    method : str, optional
+        The root-finding method to use. Default is "secant". See `scipy.optimize.root_scalar` for other options.
+    jac : bool, optional
+        Whether to compute and use the first derivative of the equation with respect to `variables`.
+        Default is False. Some methods require this.
+    hess : bool, optional
+        Whether to compute and use the second derivative of the equation with respect to `variables`.
+        Default is False. Some methods require this.
+    optimizer_kwargs : dict, optional
+        Additional keyword arguments to pass to `scipy.optimize.root_scalar`.
+
+    Returns
+    -------
+    solution: TensorVariable
+        The final state of the root-finding routine. When `success` is True, this is the value of `variables` that
+        causes `equation` to evaluate to zero. Otherwise it is the final state returned by the root-finding
+        routine, but not necessarily a root.
+
+    success: TensorVariable
+        Boolean indicating whether the root-finding was successful. If True, the solution is a root of the equation
     """
-    args = _find_optimization_parameters(equation, variables)
+    args = _find_optimization_parameters(equation, variable)
 
     root_scalar_op = RootScalarOp(
-        variables,
+        variable,
         *args,
         equation=equation,
         method=method,
@@ -697,7 +785,11 @@ def root_scalar(
         optimizer_kwargs=optimizer_kwargs,
     )
 
-    return root_scalar_op(variables, *args)
+    solution, success = cast(
+        tuple[TensorVariable, TensorVariable], root_scalar_op(variable, *args)
+    )
+
+    return solution, success
 
 
 class RootOp(ScipyWrapperOp):
@@ -734,6 +826,12 @@ def __init__(
         self._fn = None
         self._fn_wrapped = None
 
+    def __str__(self):
+        str_args = ", ".join(
+            [f"{arg}={getattr(self, arg)}" for arg in ["method", "jac"]]
+        )
+        return f"{self.__class__.__name__}({str_args})"
+
     def build_fn(self):
         outputs = self.inner_outputs
         variables, *args = self.inner_inputs
@@ -761,13 +859,17 @@ def build_fn(self):
         self._fn_wrapped = LRUCache1(fn)
 
     def perform(self, node, inputs, outputs):
+        global optimize
+        if optimize is None:
+            import scipy.optimize as optimize
+
         f = self.fn_wrapped
         f.clear_cache()
         f.copy_x = True
 
         variables, *args = inputs
 
-        res = scipy_root(
+        res = optimize.root(
             fun=f,
             jac=self.jac,
             x0=variables,
@@ -815,8 +917,36 @@ def root(
     method: str = "hybr",
     jac: bool = True,
     optimizer_kwargs: dict | None = None,
-):
-    """Find roots of a system of equations using scipy.optimize.root."""
+) -> tuple[TensorVariable, TensorVariable]:
+    """
+    Find roots of a system of equations using scipy.optimize.root.
+
+    Parameters
+    ----------
+    equations : TensorVariable
+        The system of equations for which to find roots. This should be a PyTensor variable representing a
+        vector (or scalar) value. The function will find `variables` such that `equations(variables, *args) = 0`.
+    variables : TensorVariable
+        The variable(s) with respect to which the system of equations is solved. It must be an input to the
+        computational graph of `equations` and have the same number of dimensions as `equations`.
+    method : str, optional
+        The root-finding method to use. Default is "hybr". See `scipy.optimize.root` for other options.
+    jac : bool, optional
+        Whether to compute and use the Jacobian of the `equations` with respect to `variables`.
+        Default is True. Most methods require this.
+    optimizer_kwargs : dict, optional
+        Additional keyword arguments to pass to `scipy.optimize.root`.
+
+    Returns
+    -------
+    solution: TensorVariable
+        The final state of the root-finding routine. When `success` is True, this is the value of `variables` that
+        causes all `equations` to evaluate to zero. Otherwise it is the final state returned by the root-finding
+        routine, but not necessarily a root.
+
+    success: TensorVariable
+        Boolean indicating whether the root-finding was successful. If True, the solution is a root of the equation
+    """
 
     args = _find_optimization_parameters(equations, variables)
 
@@ -829,7 +959,11 @@ def root(
         optimizer_kwargs=optimizer_kwargs,
     )
 
-    return root_op(variables, *args)
+    solution, success = cast(
+        tuple[TensorVariable, TensorVariable], root_op(variables, *args)
+    )
+
+    return solution, success
 
 
 __all__ = ["minimize_scalar", "minimize", "root_scalar", "root"]
diff --git a/scripts/generate_gallery.py b/scripts/generate_gallery.py
index 5cd78d8494..15e94ca7f4 100644
--- a/scripts/generate_gallery.py
+++ b/scripts/generate_gallery.py
@@ -58,6 +58,7 @@
     "introduction": "Introduction",
     "rewrites": "Graph Rewriting",
     "scan": "Looping in Pytensor",
+    "optimize": "Optimization in Pytensor",
 }