diff --git a/docs/tutorials.rst b/docs/tutorials.rst
index 7f437b59..c4f5d08e 100644
--- a/docs/tutorials.rst
+++ b/docs/tutorials.rst
@@ -29,6 +29,7 @@ A more in-depth look into how LSDB works
     Topic: Manual catalog verification <tutorials/manual_verification>
     Topic: Accessing Remote Data <tutorials/remote_data>
     Topic: Margins <tutorials/margins>
+    Topic: Index Tables <tutorials/index_table>
     Topic: Performance Testing <tutorials/performance>
 
 Example Science Use Cases
diff --git a/docs/tutorials/pre_executed/index_table.ipynb b/docs/tutorials/pre_executed/index_table.ipynb
new file mode 100644
index 00000000..20d3ccf0
--- /dev/null
+++ b/docs/tutorials/pre_executed/index_table.ipynb
@@ -0,0 +1,531 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f7e5b09e",
+   "metadata": {},
+   "source": [
+    "# Using Index Tables\n",
+    "\n",
+    "HATS catalogs are partitioned spatially, typically on right ascension and declination. This makes finding objects in a particular area of the sky very straightforward. However, you may occassionally only know the object by the survey-assigned identifier.\n",
+    "\n",
+    "HATS supports creating additional secondary index tables, stored separately from the HATS catalog. You can find more information about creating these index tables in the [hats-import documentation](https://hats-import.readthedocs.io/en/latest/guide/index_table.html), or request that your archive provider create an index table for your use.\n",
+    "\n",
+    "In this notebook, we explore using index tables to find GAIA objects, if you know their designation.\n",
+    "\n",
+    "First, let's create some list of designations that we're interested in. The ones here have no special signficance."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "7a0b32db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ids = [\n",
+    "    6350084614282952448,\n",
+    "    4684296460655809408,\n",
+    "    4684296460655681280,\n",
+    "    6350084408124522368,\n",
+    "    6379030430412267264,\n",
+    "    6397962092201358080,\n",
+    "    999999988604363776,\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "66d623ad",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Norder: uint8\n",
+       "Dir: uint64\n",
+       "Npix: uint64\n",
+       "source_id: int64\n",
+       "-- schema metadata --\n",
+       "pandas: '{\"index_columns\": [\"source_id\"], \"column_indexes\": [{\"name\": nul' + 641"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import hats\n",
+    "\n",
+    "catalog_index = hats.read_hats(\"/data3/epyc/data3/hats/catalogs/gaia_dr3/gaia_source_id_index/\")\n",
+    "catalog_index.schema"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e1f7a9d3",
+   "metadata": {},
+   "source": [
+    "This small set of GAIA designations are in just a handful of partitions. Let's check the index catalog, and see if we can reduce this list of IDs into just those pixels of interest. \n",
+    "\n",
+    "We're still only using the HATS api, so the reading is single-threaded."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a2d945d7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2min 51s, sys: 1min 41s, total: 4min 32s\n",
+      "Wall time: 33.2 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([Order: 3, Pixel: 111, Order: 5, Pixel: 8320, Order: 3, Pixel: 705,\n",
+       "       Order: 3, Pixel: 708], dtype=object)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "partitions = catalog_index.loc_partitions(ids)\n",
+    "partitions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d8691bc1",
+   "metadata": {},
+   "source": [
+    "## Faster selection with LSDB\n",
+    "\n",
+    "Now let's try the search and selection with LSDB. This will use dask to fetch the full rows of these objects."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "4df5b899",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 769 ms, sys: 54.8 ms, total: 824 ms\n",
+      "Wall time: 1 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "import lsdb\n",
+    "\n",
+    "gaia = lsdb.read_hats(\"/data3/epyc/data3/hats/catalogs/gaia_dr3/gaia\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fd65ce14",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2min 53s, sys: 1min 58s, total: 4min 51s\n",
+      "Wall time: 24.5 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>solution_id</th>\n",
+       "      <th>designation</th>\n",
+       "      <th>source_id</th>\n",
+       "      <th>random_index</th>\n",
+       "      <th>ref_epoch</th>\n",
+       "      <th>ra</th>\n",
+       "      <th>ra_error</th>\n",
+       "      <th>dec</th>\n",
+       "      <th>dec_error</th>\n",
+       "      <th>parallax</th>\n",
+       "      <th>...</th>\n",
+       "      <th>ag_gspphot</th>\n",
+       "      <th>ag_gspphot_lower</th>\n",
+       "      <th>ag_gspphot_upper</th>\n",
+       "      <th>ebpminrp_gspphot</th>\n",
+       "      <th>ebpminrp_gspphot_lower</th>\n",
+       "      <th>ebpminrp_gspphot_upper</th>\n",
+       "      <th>libname_gspphot</th>\n",
+       "      <th>Norder</th>\n",
+       "      <th>Dir</th>\n",
+       "      <th>Npix</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>_healpix_29</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>500000002326108747</th>\n",
+       "      <td>1636148068921376768</td>\n",
+       "      <td>Gaia DR3 999999988604363776</td>\n",
+       "      <td>999999988604363776</td>\n",
+       "      <td>1146519553</td>\n",
+       "      <td>2016.0</td>\n",
+       "      <td>104.910499</td>\n",
+       "      <td>0.416448</td>\n",
+       "      <td>55.969686</td>\n",
+       "      <td>0.392039</td>\n",
+       "      <td>1.501113</td>\n",
+       "      <td>...</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2342148232994970763</th>\n",
+       "      <td>1636148068921376768</td>\n",
+       "      <td>Gaia DR3 4684296460655681280</td>\n",
+       "      <td>4684296460655681280</td>\n",
+       "      <td>935088391</td>\n",
+       "      <td>2016.0</td>\n",
+       "      <td>7.756788</td>\n",
+       "      <td>0.075319</td>\n",
+       "      <td>-75.621828</td>\n",
+       "      <td>0.069098</td>\n",
+       "      <td>0.249487</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.013</td>\n",
+       "      <td>0.0027</td>\n",
+       "      <td>0.0005</td>\n",
+       "      <td>0.0071</td>\n",
+       "      <td>MARCS</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8320</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2342148241066740563</th>\n",
+       "      <td>1636148068921376768</td>\n",
+       "      <td>Gaia DR3 4684296460655809408</td>\n",
+       "      <td>4684296460655809408</td>\n",
+       "      <td>930596526</td>\n",
+       "      <td>2016.0</td>\n",
+       "      <td>7.74122</td>\n",
+       "      <td>3.736654</td>\n",
+       "      <td>-75.619753</td>\n",
+       "      <td>3.646013</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>...</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8320</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3175042221187998424</th>\n",
+       "      <td>1636148068921376768</td>\n",
+       "      <td>Gaia DR3 6350084408124522368</td>\n",
+       "      <td>6350084408124522368</td>\n",
+       "      <td>64296681</td>\n",
+       "      <td>2016.0</td>\n",
+       "      <td>359.838284</td>\n",
+       "      <td>0.249825</td>\n",
+       "      <td>-83.92197</td>\n",
+       "      <td>0.239047</td>\n",
+       "      <td>0.656007</td>\n",
+       "      <td>...</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>705</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3175042313799520523</th>\n",
+       "      <td>1636148068921376768</td>\n",
+       "      <td>Gaia DR3 6350084614282952448</td>\n",
+       "      <td>6350084614282952448</td>\n",
+       "      <td>1750910513</td>\n",
+       "      <td>2016.0</td>\n",
+       "      <td>359.435728</td>\n",
+       "      <td>0.510138</td>\n",
+       "      <td>-83.921882</td>\n",
+       "      <td>0.492162</td>\n",
+       "      <td>-0.272154</td>\n",
+       "      <td>...</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>705</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3189515220382416186</th>\n",
+       "      <td>1636148068921376768</td>\n",
+       "      <td>Gaia DR3 6379030430412267264</td>\n",
+       "      <td>6379030430412267264</td>\n",
+       "      <td>1257926240</td>\n",
+       "      <td>2016.0</td>\n",
+       "      <td>348.261377</td>\n",
+       "      <td>0.101749</td>\n",
+       "      <td>-73.622147</td>\n",
+       "      <td>0.093109</td>\n",
+       "      <td>0.199036</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.0012</td>\n",
+       "      <td>0.0129</td>\n",
+       "      <td>0.0027</td>\n",
+       "      <td>0.0006</td>\n",
+       "      <td>0.007</td>\n",
+       "      <td>MARCS</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>708</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3192976252233877374</th>\n",
+       "      <td>1636148068921376768</td>\n",
+       "      <td>Gaia DR3 6397962092201358080</td>\n",
+       "      <td>6397962092201358080</td>\n",
+       "      <td>150735067</td>\n",
+       "      <td>2016.0</td>\n",
+       "      <td>336.476393</td>\n",
+       "      <td>0.079348</td>\n",
+       "      <td>-67.482415</td>\n",
+       "      <td>0.09224</td>\n",
+       "      <td>0.239489</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0021</td>\n",
+       "      <td>0.0004</td>\n",
+       "      <td>0.0073</td>\n",
+       "      <td>0.0011</td>\n",
+       "      <td>0.0002</td>\n",
+       "      <td>0.0039</td>\n",
+       "      <td>MARCS</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>708</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7 rows × 155 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             solution_id                   designation  \\\n",
+       "_healpix_29                                                              \n",
+       "500000002326108747   1636148068921376768   Gaia DR3 999999988604363776   \n",
+       "2342148232994970763  1636148068921376768  Gaia DR3 4684296460655681280   \n",
+       "2342148241066740563  1636148068921376768  Gaia DR3 4684296460655809408   \n",
+       "3175042221187998424  1636148068921376768  Gaia DR3 6350084408124522368   \n",
+       "3175042313799520523  1636148068921376768  Gaia DR3 6350084614282952448   \n",
+       "3189515220382416186  1636148068921376768  Gaia DR3 6379030430412267264   \n",
+       "3192976252233877374  1636148068921376768  Gaia DR3 6397962092201358080   \n",
+       "\n",
+       "                               source_id  random_index  ref_epoch          ra  \\\n",
+       "_healpix_29                                                                     \n",
+       "500000002326108747    999999988604363776    1146519553     2016.0  104.910499   \n",
+       "2342148232994970763  4684296460655681280     935088391     2016.0    7.756788   \n",
+       "2342148241066740563  4684296460655809408     930596526     2016.0     7.74122   \n",
+       "3175042221187998424  6350084408124522368      64296681     2016.0  359.838284   \n",
+       "3175042313799520523  6350084614282952448    1750910513     2016.0  359.435728   \n",
+       "3189515220382416186  6379030430412267264    1257926240     2016.0  348.261377   \n",
+       "3192976252233877374  6397962092201358080     150735067     2016.0  336.476393   \n",
+       "\n",
+       "                     ra_error        dec  dec_error  parallax  ...  \\\n",
+       "_healpix_29                                                    ...   \n",
+       "500000002326108747   0.416448  55.969686   0.392039  1.501113  ...   \n",
+       "2342148232994970763  0.075319 -75.621828   0.069098  0.249487  ...   \n",
+       "2342148241066740563  3.736654 -75.619753   3.646013      <NA>  ...   \n",
+       "3175042221187998424  0.249825  -83.92197   0.239047  0.656007  ...   \n",
+       "3175042313799520523  0.510138 -83.921882   0.492162 -0.272154  ...   \n",
+       "3189515220382416186  0.101749 -73.622147   0.093109  0.199036  ...   \n",
+       "3192976252233877374  0.079348 -67.482415    0.09224  0.239489  ...   \n",
+       "\n",
+       "                     ag_gspphot  ag_gspphot_lower  ag_gspphot_upper  \\\n",
+       "_healpix_29                                                           \n",
+       "500000002326108747         <NA>              <NA>              <NA>   \n",
+       "2342148232994970763       0.005             0.001             0.013   \n",
+       "2342148241066740563        <NA>              <NA>              <NA>   \n",
+       "3175042221187998424        <NA>              <NA>              <NA>   \n",
+       "3175042313799520523        <NA>              <NA>              <NA>   \n",
+       "3189515220382416186       0.005            0.0012            0.0129   \n",
+       "3192976252233877374      0.0021            0.0004            0.0073   \n",
+       "\n",
+       "                     ebpminrp_gspphot  ebpminrp_gspphot_lower  \\\n",
+       "_healpix_29                                                     \n",
+       "500000002326108747               <NA>                    <NA>   \n",
+       "2342148232994970763            0.0027                  0.0005   \n",
+       "2342148241066740563              <NA>                    <NA>   \n",
+       "3175042221187998424              <NA>                    <NA>   \n",
+       "3175042313799520523              <NA>                    <NA>   \n",
+       "3189515220382416186            0.0027                  0.0006   \n",
+       "3192976252233877374            0.0011                  0.0002   \n",
+       "\n",
+       "                     ebpminrp_gspphot_upper  libname_gspphot  Norder  Dir  \\\n",
+       "_healpix_29                                                                 \n",
+       "500000002326108747                     <NA>             <NA>       3    0   \n",
+       "2342148232994970763                  0.0071            MARCS       5    0   \n",
+       "2342148241066740563                    <NA>             <NA>       5    0   \n",
+       "3175042221187998424                    <NA>             <NA>       3    0   \n",
+       "3175042313799520523                    <NA>             <NA>       3    0   \n",
+       "3189515220382416186                   0.007            MARCS       3    0   \n",
+       "3192976252233877374                  0.0039            MARCS       3    0   \n",
+       "\n",
+       "                     Npix  \n",
+       "_healpix_29                \n",
+       "500000002326108747    111  \n",
+       "2342148232994970763  8320  \n",
+       "2342148241066740563  8320  \n",
+       "3175042221187998424   705  \n",
+       "3175042313799520523   705  \n",
+       "3189515220382416186   708  \n",
+       "3192976252233877374   708  \n",
+       "\n",
+       "[7 rows x 155 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "gaia.index_search(ids, catalog_index).compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "1f09fbf3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_ = gaia.index_search(ids, catalog_index).plot_pixels(plot_title=\"Pixels containing objects of interest\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5c309ca9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Melissa HATS",
+   "language": "python",
+   "name": "hatsenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}