{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "6eUXGz8G94ZQ"
   },
   "source": [
    "# How to estimate a star's mass and radius using asteroseismology"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "CqMHYBsI96w6"
   },
   "source": [
    "## Learning Goals\n",
    "\n",
    "In this tutorial you will learn:\n",
    "\n",
    "- What the periodogram of a star with solar-like oscillations looks like.\n",
    "- How the oscillations can be characterized by two key metrics ($\\nu_{\\rm max}$ and $\\Delta\\nu$). \n",
    "- How these metrics can be used to estimate a star's mass, radius, and surface gravity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "xsLsB9PV-IdJ"
   },
   "source": [
    "## Introduction\n",
    "\n",
    "Stars of all shapes and sizes oscillate. In many cases, these oscillations are created by standing waves formed inside of the star, which disturb the stellar surface. The study of these types of internal oscillations is called *asteroseismology*.\n",
    "\n",
    "This tutorial focuses on a very common type of oscillating star: *solar-like oscillators*. This type includes main sequence stars like the Sun as well as many red giant stars. Stars of this type experience convection in the outer layers of their atmospheres. As material moves up and down in these layers, the turbulent motion forms damped standing waves throughout the stellar interior. Because these waves probe the full stellar interior, we can estimate fundamental properties of a star by studying how these waves disturb the surface of the star. Properties which can be inferred in this way include mass, radius, surface gravity, and even age for the most advanced studies.\n",
    "\n",
    "In this tutorial we will explain two key metrics asteroseismologists use to characterize the oscillations of a Sun-like star: the average frequency spacing $\\Delta\\nu$, and the frequency of maximum oscillation amplitude $\\nu_{\\rm max}$. We will also demonstrate how these metrics can be used to estimate the mass, radius, and surface gravity of a star."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "_-ldXN0k-DaL"
   },
   "source": [
    "## Imports\n",
    "\n",
    "This tutorial requires **[Lightkurve](https://docs.lightkurve.org)** (for its features to handle *Kepler* data) and **[NumPy](https://numpy.org/)** (to help plot some additional details on figures).  We will use **[Matplotlib](https://matplotlib.org/)** for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:44.665634Z",
     "iopub.status.busy": "2023-11-03T14:23:44.665128Z",
     "iopub.status.idle": "2023-11-03T14:23:45.913960Z",
     "shell.execute_reply": "2023-11-03T14:23:45.913649Z"
    },
    "id": "9vxrKDrS-FjI"
   },
   "outputs": [],
   "source": [
    "import lightkurve as lk\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ahkq0CCwrokE"
   },
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "szMCbZPa-YI5"
   },
   "source": [
    "## 1. Plotting the Frequency Spectrum of a Sun-Like Star"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Zq1yZeY2-aJi"
   },
   "source": [
    "The frequency spectrum (also known as periodogram) of a solar-like oscillator like the Sun shows a rich spectrum of modes of oscillation, equally spaced in frequency, colloquially referred to as a \"comb.\"\n",
    "\n",
    "We will investigate this spectrum using the Sun-like star KIC 10963065 as an example. This star is also colloquially known as \"Rudy\" (cf. [Lund et al. 2016](https://arxiv.org/pdf/1612.00436.pdf)). In order to get a good resolution in the frequency domain, we start by downloading and combining four quarters of Short Cadence *Kepler* data as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:45.916102Z",
     "iopub.status.busy": "2023-11-03T14:23:45.915947Z",
     "iopub.status.idle": "2023-11-03T14:23:47.787837Z",
     "shell.execute_reply": "2023-11-03T14:23:47.787471Z"
    },
    "id": "_MqdHCoz-bSg"
   },
   "outputs": [],
   "source": [
    "search_result = lk.search_lightcurve('KIC 10963065',\n",
    "                                     cadence='short', \n",
    "                                     author='Kepler',\n",
    "                                     quarter=(2,5,6,7))\n",
    "lc = search_result.download_all().stitch()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "83w84X7O-cFt"
   },
   "source": [
    "In one of the companion tutorials, we already identified the location of the modes of oscillation, so we'll zoom in on that region right away when creating the periodogram. We also set the [`normalization='psd'`](https://docs.lightkurve.org/reference/api/lightkurve.periodogram.LombScarglePeriodogram.html#lightkurve.periodogram.LombScarglePeriodogram.from_lightcurve) keyword argument, to match the common conventions in asteroseismology of solar-like oscillators."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 411
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:47.789883Z",
     "iopub.status.busy": "2023-11-03T14:23:47.789757Z",
     "iopub.status.idle": "2023-11-03T14:23:48.671621Z",
     "shell.execute_reply": "2023-11-03T14:23:48.671234Z"
    },
    "executionInfo": {
     "elapsed": 3856,
     "status": "ok",
     "timestamp": 1600230552390,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
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     "user_tz": 420
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    "id": "YdQYN0b-iL1e",
    "outputId": "eb3d43a1-499c-421e-808f-43713a602df4"
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 848.5x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pg = lc.to_periodogram(normalization='psd',\n",
    "                       minimum_frequency=1500,\n",
    "                       maximum_frequency=2700)\n",
    "ax = pg.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "wrAT_dq2iYDK"
   },
   "source": [
    "In this spectrum we can see that the modes of oscillation rise up from the noise, reach a peak, and then decrease in power. This region, where the modes are visible, is commonly referred to as the *mode envelope*. The peak of this envelope is what we call the *frequency of maximum oscillation amplitude*, or $\\nu_{\\rm max}$ (colloquially called \"numax\").\n",
    "\n",
    "An approximation of the shape of the envelope (roughly a Gaussian function) is shown as the dashed line in the figure below. We also overlay a smoothed version of the power spectrum, and annotate the location of the oscillation modes with arrows. Making this figure is an optional step, but it helps to visualize the oscillation features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 411
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:48.673608Z",
     "iopub.status.busy": "2023-11-03T14:23:48.673406Z",
     "iopub.status.idle": "2023-11-03T14:23:48.980087Z",
     "shell.execute_reply": "2023-11-03T14:23:48.979784Z"
    },
    "executionInfo": {
     "elapsed": 1366,
     "status": "ok",
     "timestamp": 1600230592217,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "dfp4Nbck-iyP",
    "outputId": "e824f004-0249-40c0-e25d-d94773df4878"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 848.5x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a smoothed version of the power spectrum on top in green\n",
    "ax = pg.plot(label='Original spectrum')\n",
    "pg.smooth(filter_width=1).plot(ax=ax,\n",
    "                               color='green',\n",
    "                               label='Smoothed spectrum')\n",
    "\n",
    "# Highlight the \"mode envelope\" using a Gaussian curve\n",
    "f = pg.frequency.value\n",
    "ax.plot(f, 5e-11*np.exp(-(f-2100)**2/(2*230**2)),\n",
    "        lw=5, ls='--', zorder=0,\n",
    "        color='blue', label='Mode envelope');\n",
    "\n",
    "# Annotate the modes using red arrows\n",
    "for i in range(6):\n",
    "  ax.annotate('',\n",
    "              xy=(1831.66+i*103.8, 5.2e-11),\n",
    "              xytext=(1831.66+i*103.8, 7e-11), \n",
    "              arrowprops=dict(arrowstyle='->',\n",
    "              color='red',\n",
    "              linewidth=1.5))\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "KsnuTxCl-jjB"
   },
   "source": [
    "A distinctive feature in the spectrum is the equal spacing of the modes of oscillation. The spacing between two consecutive overtones of the same radial order (for example, radial oscillations, dipole oscillations, etc.) is what we call the *average large frequency spacing*, or $\\Delta\\nu$ (colloquially called \"deltanu\"). In the figure above, the arrows point to dipole modes of oscillation (hemispheres expanding and contracting alternately), and are all evenly spaced.\n",
    "\n",
    "Both of these metrics, $\\nu_{\\rm max}$ and $\\Delta\\nu$, are very useful because they are related to the mass, radius, and temperature of the star. The next step in our tutorial is to estimate the values of these metrics, using Lightkurve's tools."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "9jWfV4ik-lB4"
   },
   "source": [
    "## 2. Estimating the Frequency of Maximum Amplitude $\\nu_{\\rm max}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "GF3kZ0uI-mi_"
   },
   "source": [
    "The frequency of maximum amplitude can be estimated in a number of ways. An obvious estimate would be to take the frequency that corresponds to the maximum amplitude in the power spectrum. This would not be a robust estimate however, because the maximum peak is very sensitive to noise and sampling effects. \n",
    "\n",
    "Instead, one of the most commonly used methods to estimate $\\nu_{\\rm max}$ is the 2D autocorrelation function (ACF) method. Literature publications using this method include, for example, [Huber et al. (2009)](https://arxiv.org/abs/0910.2764) and [Viani et al. (2019)](https://arxiv.org/abs/1905.08333). A version of this method is provided by the Lightkurve package.\n",
    "\n",
    "Before diving into Lightkurve's tools, we will need to prepare our [Periodogram](https://docs.lightkurve.org/reference/api/lightkurve.periodogram.Periodogram.html?highlight=periodogram#lightkurve.periodogram.Periodogram) object. We do this by first removing background noise using the [flatten()](https://docs.lightkurve.org/reference/api/lightkurve.periodogram.Periodogram.flatten.html?highlight=flatten#lightkurve.periodogram.Periodogram.flatten) method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 393
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:48.981877Z",
     "iopub.status.busy": "2023-11-03T14:23:48.981767Z",
     "iopub.status.idle": "2023-11-03T14:23:49.221048Z",
     "shell.execute_reply": "2023-11-03T14:23:49.220682Z"
    },
    "executionInfo": {
     "elapsed": 1689,
     "status": "ok",
     "timestamp": 1600231082818,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "dn-BeCwc-oI0",
    "outputId": "98013e74-345f-4f97-a2c9-d0f44b721e59"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 848.5x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snr = pg.flatten()\n",
    "ax = snr.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "gVPXkoUEmeF7"
   },
   "source": [
    "Next, we need to convert the periodogram to a [Seismology](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.html?highlight=seismology) object, which hosts Lightkurve's asteroseismology tools:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:49.223027Z",
     "iopub.status.busy": "2023-11-03T14:23:49.222815Z",
     "iopub.status.idle": "2023-11-03T14:23:49.484647Z",
     "shell.execute_reply": "2023-11-03T14:23:49.484322Z"
    },
    "id": "LTDbIca--pFo"
   },
   "outputs": [],
   "source": [
    "seismology = snr.to_seismology()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "PyeuroRa-qW9"
   },
   "source": [
    "Lightkurve's estimation method uses the autocorrelation function (ACF). Autocorrelation values are the result of calculating the correlation of the data with itself as it is gradually shifted over itself. One way to imagine how the ACF method works is by holding your hands up side by side and slowly shifting them past one another. Where your fingers overlap, the ACF will be high, and vice versa."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "3krZClnz2DnB"
   },
   "source": [
    "\n",
    "The [Seismology](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.html?highlight=seismology) object provides both `estimate` and `diagnose` methods. The former estimates the value, and the latter shows us how it was calculated. First, let's call [estimate_numax()](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.estimate_numax.html?highlight=estimate_numax):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:49.486772Z",
     "iopub.status.busy": "2023-11-03T14:23:49.486499Z",
     "iopub.status.idle": "2023-11-03T14:23:54.364016Z",
     "shell.execute_reply": "2023-11-03T14:23:54.363573Z"
    },
    "executionInfo": {
     "elapsed": 3952,
     "status": "ok",
     "timestamp": 1600231089673,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "Poi4Tpcd-rnO",
    "outputId": "7c4d9aaa-17ee-4aed-c5a3-ddcc3ccafa83"
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "numax: $2145.00$ $\\mathrm{\\mu Hz}$ (method: ACF2D)"
      ],
      "text/plain": [
       "numax: 2145.00 uHz (method: ACF2D)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seismology.estimate_numax()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "hN0wCxri-shH"
   },
   "source": [
    "Here, the [estimate_numax()](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.estimate_numax.html?highlight=estimate_numax)) function has measured a value for $\\nu_{\\rm max}$ from our `SNRPeriodogram`, and has stored it as a property of the [Seismology](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.html?highlight=seismology) object. We can access the value as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:54.365722Z",
     "iopub.status.busy": "2023-11-03T14:23:54.365604Z",
     "iopub.status.idle": "2023-11-03T14:23:54.367717Z",
     "shell.execute_reply": "2023-11-03T14:23:54.367467Z"
    },
    "executionInfo": {
     "elapsed": 271,
     "status": "ok",
     "timestamp": 1600231089674,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "i8H9eO15_ar9",
    "outputId": "d30f4b65-0400-4693-c37f-1bcbfe59119a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2145.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seismology.numax.value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "_QbB-JH7_bdp"
   },
   "source": [
    "Before moving on, let's have a look at exactly how $\\nu_{\\rm max}$ was measured, using the [`diagnose_numax()`](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.diagnose_numax.html?highlight=diagnose_numax) function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 997
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:54.369331Z",
     "iopub.status.busy": "2023-11-03T14:23:54.369221Z",
     "iopub.status.idle": "2023-11-03T14:23:55.164439Z",
     "shell.execute_reply": "2023-11-03T14:23:55.164140Z"
    },
    "executionInfo": {
     "elapsed": 80156,
     "status": "ok",
     "timestamp": 1600130326019,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "VQ1cEi6-_dVg",
    "outputId": "6e1b3605-c763-4193-dbff-16863554e510"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 848.5x1200 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "seismology.diagnose_numax();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "r_q9oK3R_eJC"
   },
   "source": [
    "The figure above shows three plots, so let's break them down, one by one:\n",
    "\n",
    "1. The top panel shows the original periodogram. \n",
    "2. The middle panel shows an image representing the ACF values calculated for different parts of the power spectrum. In this case, each segment used to calculate the ACF is $250\\, \\mu\\rm{Hz}$ wide, which you can see on the y-axis. The x-axis is the central frequency of each segment, and the z-axis (the color) shows the strength of the autocorrelation function. As we get closer to the frequency of maximum oscillation, the colors get darker, and so the ACF is increasing.\n",
    "3. The bottom panel shows the same autocorrelation values as the middle panel, but collapsed (that is, summed) along the y-axis. The integrated value of the ACF is strongest closest to the frequency of maximum oscillation. The blue line over the top is a smoothed version of the collapsed ACF. Lightkurve estimates  $\\nu_{\\rm max}$ by computing the maximum of the smoothed blue line. The resulting estimate is marked across all three panels using the vertical red line.\n",
    "\n",
    "Now that we have estimated a value for $\\nu_{\\rm{max}}$, calculating $\\Delta\\nu$ becomes faster. We can observe the features of $\\Delta\\nu$ in the middle panel above: there are repeating peaks in the ACF, corresponding to repeating features overlapping, just like the fingers on your hand. The spacing between these repeating peaks will be used to estimate $\\Delta\\nu$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "KPM8SPqu_hzA"
   },
   "source": [
    "## 3. Estimating the Frequency Spacing $\\Delta\\nu$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "35CWZ61_hkFC"
   },
   "source": [
    "In order to estimate $\\Delta\\nu$ efficiently, we can use the fact that we only need to investigate the ACF in the region surrounding $\\nu_{\\rm max}$. In this region, peaks in the ACF will show up corresponding to the repeating comb structure overlapping with itself.\n",
    "\n",
    "Having an estimate of $\\nu_{\\rm max}$ also makes measuring $\\Delta\\nu$ possible in a second way. Using well-established empirical relations which have been published in the literature, we can infer the Full Width Half Maximum (FWHM) of the mode envelope based on the value of $\\nu_{\\rm max}$. This helps us further narrow down the region in which to calculate the ACF.  Lightkurve uses the relationships published by [Mosser et al. 2010](https://arxiv.org/abs/1004.0449) and [Lund et al. 2017](https://arxiv.org/abs/1612.00436), which are:\n",
    "\n",
    "$$\n",
    "\\textrm{FWHM} \\approx 0.25 \\times \\nu_{\\rm max}\\, \\text{for main sequence stars, and}$$\n",
    "\n",
    "$$\\textrm{FWHM} \\approx 0.66 \\times \\nu_{\\rm max}^{0.88}\\, \\text{for red giants.}$$\n",
    "\n",
    "We can also use $\\nu_{\\rm max}$ to make a rough estimate of $\\Delta\\nu$ to guide our search for the true $\\Delta\\nu$. This is roughly\n",
    "\n",
    "$$\\Delta\\nu \\approx 0.294 \\times \\nu_{\\rm max}^{0772}\\, ,$$\n",
    "\n",
    "which we assume to be the same for all solar-like oscillators ([Stello et al. 2009](https://arxiv.org/abs/0909.5193))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "CnsZRghQhijU"
   },
   "source": [
    "To understand how this works in practice, let's first [estimate_deltanu()](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.estimate_deltanu.html?highlight=estimate_deltanu), and then [diagnose_deltanu()](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.diagnose_deltanu.html?highlight=diagnose_deltanu)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:55.166732Z",
     "iopub.status.busy": "2023-11-03T14:23:55.166609Z",
     "iopub.status.idle": "2023-11-03T14:23:56.137038Z",
     "shell.execute_reply": "2023-11-03T14:23:56.136745Z"
    },
    "executionInfo": {
     "elapsed": 978,
     "status": "ok",
     "timestamp": 1600234078400,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "esMnrljZ_jz0",
    "outputId": "52761a54-a149-4519-fb6f-ca96029b693a"
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "deltanu: $103.11$ $\\mathrm{\\mu Hz}$ (method: ACF2D)"
      ],
      "text/plain": [
       "deltanu: 103.11 uHz (method: ACF2D)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seismology.estimate_deltanu()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "qRfsq3Sl34UZ"
   },
   "source": [
    "Now let's see how this $\\Delta\\nu$ value was obtained."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 697
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:56.138833Z",
     "iopub.status.busy": "2023-11-03T14:23:56.138714Z",
     "iopub.status.idle": "2023-11-03T14:23:56.721066Z",
     "shell.execute_reply": "2023-11-03T14:23:56.720779Z"
    },
    "executionInfo": {
     "elapsed": 2432,
     "status": "ok",
     "timestamp": 1600234081641,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "AYkaOm8g37vX",
    "outputId": "597b209d-5dc2-488a-9985-5a27f55e916f"
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'NoneType' object has no attribute '_get_renderer'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
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      "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/lightkurve-hY241qo1-py3.9/lib/python3.9/site-packages/IPython/core/pylabtools.py:152\u001b[0m, in \u001b[0;36mprint_figure\u001b[0;34m(fig, fmt, bbox_inches, base64, **kwargs)\u001b[0m\n\u001b[1;32m    149\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend_bases\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m FigureCanvasBase\n\u001b[1;32m    150\u001b[0m     FigureCanvasBase(fig)\n\u001b[0;32m--> 152\u001b[0m \u001b[43mfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcanvas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprint_figure\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbytes_io\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkw\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    153\u001b[0m data \u001b[38;5;241m=\u001b[39m bytes_io\u001b[38;5;241m.\u001b[39mgetvalue()\n\u001b[1;32m    154\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m fmt \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msvg\u001b[39m\u001b[38;5;124m'\u001b[39m:\n",
      "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/lightkurve-hY241qo1-py3.9/lib/python3.9/site-packages/matplotlib/backend_bases.py:2353\u001b[0m, in \u001b[0;36mFigureCanvasBase.print_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)\u001b[0m\n\u001b[1;32m   2350\u001b[0m         bbox_inches \u001b[38;5;241m=\u001b[39m bbox_inches\u001b[38;5;241m.\u001b[39mpadded(pad_inches)\n\u001b[1;32m   2352\u001b[0m     \u001b[38;5;66;03m# call adjust_bbox to save only the given area\u001b[39;00m\n\u001b[0;32m-> 2353\u001b[0m     restore_bbox \u001b[38;5;241m=\u001b[39m \u001b[43m_tight_bbox\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madjust_bbox\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   2354\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbbox_inches\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcanvas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfixed_dpi\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2356\u001b[0m     _bbox_inches_restore \u001b[38;5;241m=\u001b[39m (bbox_inches, restore_bbox)\n\u001b[1;32m   2357\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/lightkurve-hY241qo1-py3.9/lib/python3.9/site-packages/matplotlib/_tight_bbox.py:28\u001b[0m, in \u001b[0;36madjust_bbox\u001b[0;34m(fig, bbox_inches, fixed_dpi)\u001b[0m\n\u001b[1;32m     26\u001b[0m locator \u001b[38;5;241m=\u001b[39m ax\u001b[38;5;241m.\u001b[39mget_axes_locator()\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m locator \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 28\u001b[0m     ax\u001b[38;5;241m.\u001b[39mapply_aspect(\u001b[43mlocator\u001b[49m\u001b[43m(\u001b[49m\u001b[43max\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m)\n\u001b[1;32m     29\u001b[0m locator_list\u001b[38;5;241m.\u001b[39mappend(locator)\n\u001b[1;32m     30\u001b[0m current_pos \u001b[38;5;241m=\u001b[39m ax\u001b[38;5;241m.\u001b[39mget_position(original\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\u001b[38;5;241m.\u001b[39mfrozen()\n",
      "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/lightkurve-hY241qo1-py3.9/lib/python3.9/site-packages/mpl_toolkits/axes_grid1/inset_locator.py:73\u001b[0m, in \u001b[0;36mAnchoredLocatorBase.__call__\u001b[0;34m(self, ax, renderer)\u001b[0m\n\u001b[1;32m     71\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, ax, renderer):\n\u001b[1;32m     72\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxes \u001b[38;5;241m=\u001b[39m ax\n\u001b[0;32m---> 73\u001b[0m     bbox \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_window_extent\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m     px, py \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_offset(bbox\u001b[38;5;241m.\u001b[39mwidth, bbox\u001b[38;5;241m.\u001b[39mheight, \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m, renderer)\n\u001b[1;32m     75\u001b[0m     bbox_canvas \u001b[38;5;241m=\u001b[39m Bbox\u001b[38;5;241m.\u001b[39mfrom_bounds(px, py, bbox\u001b[38;5;241m.\u001b[39mwidth, bbox\u001b[38;5;241m.\u001b[39mheight)\n",
      "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/lightkurve-hY241qo1-py3.9/lib/python3.9/site-packages/matplotlib/offsetbox.py:399\u001b[0m, in \u001b[0;36mOffsetBox.get_window_extent\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m    396\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_window_extent\u001b[39m(\u001b[38;5;28mself\u001b[39m, renderer\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m    397\u001b[0m     \u001b[38;5;66;03m# docstring inherited\u001b[39;00m\n\u001b[1;32m    398\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m renderer \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 399\u001b[0m         renderer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_renderer\u001b[49m()\n\u001b[1;32m    400\u001b[0m     bbox \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_bbox(renderer)\n\u001b[1;32m    401\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:  \u001b[38;5;66;03m# Some subclasses redefine get_offset to take no args.\u001b[39;00m\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute '_get_renderer'"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 848.5x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "seismology.diagnose_deltanu();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "LdLbip5W4ICX"
   },
   "source": [
    "In the top panel we see the region in the frequency spectrum for which the ACF is evaluated, which is one FWHM on either side of $\\nu_{\\rm max}$. This region encompasses the strongest modes of oscillation.\n",
    "\n",
    "In the bottom panel we can see the ACF, that is, the result of calculating the correlation of the data with itself as it is shifted over itself. Where modes of oscillation overlap with one another, there will be a spike in the ACF. Because the modes are regularly spaced, these spikes will also be regularly spaced, and will reflect the spacing between modes of oscillation.\n",
    "\n",
    "The inset on the upper right hand corner shows a region around the *empirically* estimated $\\Delta\\nu$, which is based on the literature equations shown above. Using the [Scipy](https://www.scipy.org/) find_peaks() function, Lightkurve finds the tip of the ACF peak nearest to this estimate, and reports this as the *measured* $\\Delta\\nu$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "dLhEAvv3_j6F"
   },
   "source": [
    "## 4. Estimating Stellar Mass, Radius, and Surface Gravity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Cr3Gu2P8_j_1"
   },
   "source": [
    "Having obtained estimates for $\\Delta\\nu$ and $\\nu_\\rm{max}$, we can now estimate the star's mass ($M$), radius ($R$), and surface gravity ($g$) given an estimate for the star's effective temperature ($T_\\rm{eff}$). Asteroseismologists have established three *scaling relations* between these properties. These scaling relations read as follows:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "JCXPHZcO_lr8"
   },
   "source": [
    "$$\\frac{M}{M_\\odot} \\simeq \\left(\\frac{\\nu_\\rm{max}}{\\nu_\\rm{max,\\odot}}\\right)^3 \\left(\\frac{\\Delta\\nu}{\\Delta\\nu_{\\odot}}\\right)^{-4}\\left(\\frac{T_{\\rm eff}}{T_{\\rm eff,\\odot}}\\right)^{3/2}\\, ,$$\n",
    "\n",
    "$$\n",
    "\\frac{R}{R_\\odot} \\simeq \\left(\\frac{\\nu_\\rm{max}}{\\nu_\\rm{max,\\odot}}\\right) \\left(\\frac{\\Delta\\nu}{\\Delta\\nu_{\\odot}}\\right)^{-2}\\left(\\frac{T_{\\rm eff}}{T_{\\rm eff,\\odot}}\\right)^{1/2}\\, \\text{and}\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\frac{g}{g_\\odot} \\simeq \\left(\\frac{\\nu_\\rm{max}}{\\nu_\\rm{max,\\odot}}\\right) \\left(\\frac{T_{\\rm eff}}{T_{\\rm eff,\\odot}}\\right)^{1/2}\\,\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "jG2kIGb_m79_"
   },
   "source": [
    "where the $\\odot$ symbol represents the Sun. In Lightkurve, the solar values used are $\\nu_{\\rm max, \\odot} = 3090\\, \\mu\\rm{Hz}$, $\\Delta\\nu_\\odot = 135.1\\, \\mu{\\rm Hz}$ ([Huber et al. 2010](https://arxiv.org/abs/1010.4566)) and $T_{\\rm eff, \\odot} = 5777.2\\, \\rm{K}$ ([Prša et al. 2016](https://arxiv.org/abs/1605.09788))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "jbMU6Ka8n5qx"
   },
   "source": [
    "These scaling relations are built into Lightkurve. We can call them as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:56.723049Z",
     "iopub.status.busy": "2023-11-03T14:23:56.722937Z",
     "iopub.status.idle": "2023-11-03T14:23:56.725334Z",
     "shell.execute_reply": "2023-11-03T14:23:56.725045Z"
    },
    "executionInfo": {
     "elapsed": 1003,
     "status": "ok",
     "timestamp": 1600234086297,
     "user": {
      "displayName": "Geert Barentsen",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
      "userId": "05704237875861987058"
     },
     "user_tz": 420
    },
    "id": "66QlH667oCBJ",
    "outputId": "d7e3cabf-7b77-4307-cb1d-78ba16ea9542"
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "mass: $1.08$ $\\mathrm{M_{\\odot}}$ (method: Uncorrected Scaling Relations)"
      ],
      "text/plain": [
       "mass: 1.08 solMass (method: Uncorrected Scaling Relations)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seismology.estimate_mass()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "execution": {
     "iopub.execute_input": "2023-11-03T14:23:56.726872Z",
     "iopub.status.busy": "2023-11-03T14:23:56.726762Z",
     "iopub.status.idle": "2023-11-03T14:23:56.728955Z",
     "shell.execute_reply": "2023-11-03T14:23:56.728713Z"
    },
    "executionInfo": {
     "elapsed": 444,
     "status": "ok",
     "timestamp": 1600234091530,
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       "radius: $1.23$ $\\mathrm{R_{\\odot}}$ (method: Uncorrected Scaling Relations)"
      ],
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       "radius: 1.23 solRad (method: Uncorrected Scaling Relations)"
      ]
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       "logg: $4.29$ $\\mathrm{dex}$ (method: Uncorrected Scaling Relations)"
      ],
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       "logg: 4.29 dex (method: Uncorrected Scaling Relations)"
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    "For the last one, surface gravity ($g$) is expressed in log space (that is, $\\log g$), which is the convention in stellar physics. If we look at our  [Seismology](https://docs.lightkurve.org/reference/api/lightkurve.seismology.Seismology.html?highlight=seismology) object now, we'll see that it has stored all of these variables in one place."
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      "text/plain": [
       "Seismology(ID: KIC 10963065) - computed values:\n",
       " * numax: 2145.00 uHz (method: ACF2D)\n",
       " * deltanu: 103.11 uHz (method: ACF2D)\n",
       " * mass: 1.08 solMass (method: Uncorrected Scaling Relations)\n",
       " * radius: 1.23 solRad (method: Uncorrected Scaling Relations)\n",
       " * logg: 4.29 dex (method: Uncorrected Scaling Relations)"
      ]
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   ],
   "source": [
    "seismology"
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   "source": [
    "## 5. Closing Remarks\n",
    "\n",
    "In this tutorial, we have seen how Lightkurve's tools can be used to estimate the mass, radius, and surface gravity of a solar-like oscillator. We did this by first estimating the seismic observables $\\nu_{\\rm max}$ and $\\Delta\\nu$. \n",
    "It is important to remember, however, that these are *estimates*, and that the method built into Lightkurve is an adaptation of established 2D ACF methods designed to provide first look estimates of stellar properties. Lightkurve's implementation has not been tested thoroughly in the literature yet, and it does not provide uncertainties yet.\n",
    "\n",
    "If you're interested in learning more about asteroseismology, we recommend the following review papers:\n",
    "\n",
    "- [Chaplin & Miglio (2013)](https://arxiv.org/pdf/1303.1957.pdf) provides a review on asteroseismology of solar-like oscillators with *Kepler*, including an explanation of the seismic scaling relations.\n",
    "- [Aerts (2019)](https://arxiv.org/pdf/1912.12300.pdf) provides a comprehensive review that covers asteroseismology of a wide range of oscillating stars, including solar-like oscillators.\n",
    "\n",
    "Or even better, get in contact and collaborate with an asteroseismologist!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "eTCiB1-J_olM"
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   "source": [
    "## About this Notebook\n",
    "\n",
    "**Authors**: Oliver Hall (oliver.hall@esa.int), Geert Barentsen\n",
    "\n",
    "**Updated On**: 2020-09-29"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
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   "source": [
    "## Citing Lightkurve and Astropy\n",
    "\n",
    "If you use `lightkurve` or `astropy` for published research, please cite the authors. Click the buttons below to copy BibTeX entries to your clipboard."
   ]
  },
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       "                {Hedges}, C. and {Gully-Santiago}, M. and {Saunders}, N. and\n",
       "                {Cody}, A.~M. and {Barclay}, T. and {Hall}, O. and\n",
       "                {Sagear}, S. and {Turtelboom}, E. and {Zhang}, J. and\n",
       "                {Tzanidakis}, A. and {Mighell}, K. and {Coughlin}, J. and\n",
       "                {Bell}, K. and {Berta-Thompson}, Z. and {Williams}, P. and\n",
       "                {Dotson}, J. and {Barentsen}, G.},\n",
       "    title = \"{Lightkurve: Kepler and TESS time series analysis in Python}\",\n",
       "    keywords = {Software, NASA},\n",
       "howpublished = {Astrophysics Source Code Library},\n",
       "        year = 2018,\n",
       "    month = dec,\n",
       "archivePrefix = \"ascl\",\n",
       "    eprint = {1812.013},\n",
       "    adsurl = {http://adsabs.harvard.edu/abs/2018ascl.soft12013L},\n",
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       "@ARTICLE{astropy:2022,\n",
       "       author = {{Astropy Collaboration} and {Price-Whelan}, Adrian M. and {Lim}, Pey\n",
       "       Lian and {Earl}, Nicholas and {Starkman}, Nathaniel and {Bradley}, Larry and\n",
       "       {Shupe}, David L. and {Patil}, Aarya A. and {Corrales}, Lia and {Brasseur}, C.~E.\n",
       "       and {N{\\\"o}the}, Maximilian and {Donath}, Axel and {Tollerud}, Erik and {Morris},\n",
       "       Brett M. and {Ginsburg}, Adam and {Vaher}, Eero and {Weaver}, Benjamin A. and\n",
       "       {Tocknell}, James and {Jamieson}, William and {van Kerkwijk}, Marten H. and\n",
       "       {Robitaille}, Thomas P. and {Merry}, Bruce and {Bachetti}, Matteo and\n",
       "       {G{\\\"u}nther}, H. Moritz and {Aldcroft}, Thomas L. and {Alvarado-Montes}, Jaime\n",
       "       A. and {Archibald}, Anne M. and {B{\\'o}di}, Attila and {Bapat}, Shreyas and\n",
       "       {Barentsen}, Geert and {Baz{\\'a}n}, Juanjo and {Biswas}, Manish and {Boquien},\n",
       "       M{\\'e}d{\\'e}ric and {Burke}, D.~J. and {Cara}, Daria and {Cara}, Mihai and\n",
       "       {Conroy}, Kyle E. and {Conseil}, Simon and {Craig}, Matthew W. and {Cross},\n",
       "       Robert M. and {Cruz}, Kelle L. and {D'Eugenio}, Francesco and {Dencheva}, Nadia\n",
       "       and {Devillepoix}, Hadrien A.~R. and {Dietrich}, J{\\\"o}rg P. and {Eigenbrot},\n",
       "       Arthur Davis and {Erben}, Thomas and {Ferreira}, Leonardo and {Foreman-Mackey},\n",
       "       Daniel and {Fox}, Ryan and {Freij}, Nabil and {Garg}, Suyog and {Geda}, Robel and\n",
       "       {Glattly}, Lauren and {Gondhalekar}, Yash and {Gordon}, Karl D. and {Grant},\n",
       "       David and {Greenfield}, Perry and {Groener}, Austen M. and {Guest}, Steve and\n",
       "       {Gurovich}, Sebastian and {Handberg}, Rasmus and {Hart}, Akeem and\n",
       "       {Hatfield-Dodds}, Zac and {Homeier}, Derek and {Hosseinzadeh}, Griffin and\n",
       "       {Jenness}, Tim and {Jones}, Craig K. and {Joseph}, Prajwel and {Kalmbach}, J.\n",
       "       Bryce and {Karamehmetoglu}, Emir and {Ka{\\l}uszy{\\'n}ski}, Miko{\\l}aj and\n",
       "       {Kelley}, Michael S.~P. and {Kern}, Nicholas and {Kerzendorf}, Wolfgang E. and\n",
       "       {Koch}, Eric W. and {Kulumani}, Shankar and {Lee}, Antony and {Ly}, Chun and\n",
       "       {Ma}, Zhiyuan and {MacBride}, Conor and {Maljaars}, Jakob M. and {Muna}, Demitri\n",
       "       and {Murphy}, N.~A. and {Norman}, Henrik and {O'Steen}, Richard and {Oman}, Kyle\n",
       "       A. and {Pacifici}, Camilla and {Pascual}, Sergio and {Pascual-Granado}, J. and\n",
       "       {Patil}, Rohit R. and {Perren}, Gabriel I. and {Pickering}, Timothy E. and\n",
       "       {Rastogi}, Tanuj and {Roulston}, Benjamin R. and {Ryan}, Daniel F. and {Rykoff},\n",
       "       Eli S. and {Sabater}, Jose and {Sakurikar}, Parikshit and {Salgado}, Jes{\\'u}s\n",
       "       and {Sanghi}, Aniket and {Saunders}, Nicholas and {Savchenko}, Volodymyr and\n",
       "       {Schwardt}, Ludwig and {Seifert-Eckert}, Michael and {Shih}, Albert Y. and\n",
       "       {Jain}, Anany Shrey and {Shukla}, Gyanendra and {Sick}, Jonathan and {Simpson},\n",
       "       Chris and {Singanamalla}, Sudheesh and {Singer}, Leo P. and {Singhal}, Jaladh and\n",
       "       {Sinha}, Manodeep and {Sip{\\H{o}}cz}, Brigitta M. and {Spitler}, Lee R. and\n",
       "       {Stansby}, David and {Streicher}, Ole and {{\\v{S}}umak}, Jani and {Swinbank},\n",
       "       John D. and {Taranu}, Dan S. and {Tewary}, Nikita and {Tremblay}, Grant R. and\n",
       "       {Val-Borro}, Miguel de and {Van Kooten}, Samuel J. and {Vasovi{\\'c}}, Zlatan and\n",
       "       {Verma}, Shresth and {de Miranda Cardoso}, Jos{\\'e} Vin{\\'\\i}cius and {Williams},\n",
       "       Peter K.~G. and {Wilson}, Tom J. and {Winkel}, Benjamin and {Wood-Vasey}, W.~M.\n",
       "       and {Xue}, Rui and {Yoachim}, Peter and {Zhang}, Chen and {Zonca}, Andrea and\n",
       "       {Astropy Project Contributors}}, title = \"{The Astropy Project: Sustaining and\n",
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       "\t{Cowperthwaite}, P.~S. and {Craig}, M.~W. and {Deil}, C. and\n",
       "\t{Guillochon}, J. and {Guzman}, G. and {Liedtke}, S. and {Lian Lim}, P. and\n",
       "\t{Lockhart}, K.~E. and {Mommert}, M. and {Morris}, B.~M. and\n",
       "\t{Norman}, H. and {Parikh}, M. and {Persson}, M.~V. and {Robitaille}, T.~P. and\n",
       "\t{Segovia}, J.-C. and {Singer}, L.~P. and {Tollerud}, E.~J. and\n",
       "\t{de Val-Borro}, M. and {Valtchanov}, I. and {Woillez}, J. and\n",
       "\t{The Astroquery collaboration} and {a subset of the astropy collaboration}\n",
       "\t},\n",
       "    title = \"{astroquery: An Astronomical Web-querying Package in Python}\",\n",
       "  journal = {\\aj},\n",
       "archivePrefix = \"arXiv\",\n",
       "   eprint = {1901.04520},\n",
       " primaryClass = \"astro-ph.IM\",\n",
       " keywords = {astronomical databases: miscellaneous, virtual observatory tools},\n",
       "     year = 2019,\n",
       "    month = mar,\n",
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       "          {Mullally}, S.~E. and {White}, Richard L.},\n",
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       "\n",
       "    <p>\n",
       "        When using Lightkurve, we kindly request that you cite the following packages:\n",
       "        <ul>\n",
       "            <li>\n",
       "                <a href=\"https://docs.lightkurve.org\">lightkurve</a>\n",
       "                <button onclick=\"copyBibtex('lightkurve')\"><i class=\"fas fa-clipboard\"></i> Copy BibTeX</button>\n",
       "            </li>\n",
       "            <li>\n",
       "                <a href=\"https://astropy.org\">astropy</a>\n",
       "                <button onclick=\"copyBibtex('astropy')\"><i class=\"fas fa-clipboard\"></i> Copy BibTeX</button>\n",
       "            </li>\n",
       "            <li>\n",
       "                <a href=\"https://astroquery.readthedocs.io\">astroquery</a>\n",
       "                <button onclick=\"copyBibtex('astroquery')\"><i class=\"fas fa-clipboard\"></i> Copy BibTeX</button>\n",
       "                —  if you are using <i>search_lightcurve()</i> or <i>search_targetpixelfile()</i>.\n",
       "            </li>\n",
       "            <li>\n",
       "                <a href=\"https://mast.stsci.edu/tesscut/\">tesscut</a>\n",
       "                <button onclick=\"copyBibtex('tesscut')\"><i class=\"fas fa-clipboard\"></i> Copy BibTeX</button>\n",
       "                — if you are using <i>search_tesscut()</i>.\n",
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