From 7f837f7b9969a0f6d5eac864efbc1bd6c6fdeeab Mon Sep 17 00:00:00 2001 From: jrob93 Date: Wed, 15 Nov 2023 15:19:45 +0000 Subject: [PATCH] update text, add mean --- .../SSO_alerts_per_night.pdf | Bin 35180 -> 35180 bytes .../SSO_alerts_per_visit.pdf | Bin 36394 -> 36470 bytes .../SSO_alerts_per_visit.png | Bin 46370 -> 49349 bytes .../SSO_alerts_per_visit_hist.pdf | Bin 13252 -> 13772 bytes .../SSO_alerts_per_visit_hist.png | Bin 18262 -> 22302 bytes .../alerts_per_night.ipynb | 40 ++++++++++++------ 6 files changed, 28 insertions(+), 12 deletions(-) diff --git a/notebooks/SSO_alerts_per_visit/SSO_alerts_per_night.pdf b/notebooks/SSO_alerts_per_visit/SSO_alerts_per_night.pdf index c8721bb5334a94e08089a54d116ae487447e7ab2..add7dd01ecf79b53bc01b9af59a40e3348dd7ec7 100644 GIT binary patch delta 23 dcmaDeiRsNGrVS5UISfsK(89=Y^UKy|W&nCb30?pI delta 23 fcmaDeiRsNGrVS5UISecfjZ92U%{RYnZDs}ldW8vR diff --git a/notebooks/SSO_alerts_per_visit/SSO_alerts_per_visit.pdf 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zG}JU-gMCba`_c@^mgEB0*?!I#rLcPhKhAcsEyY5c)pnifCYOwiRd9MmwP;qWtq1u% z4D{RfA4WGp##y)EH*s{A1th?yGXRJ#IrC*RnF;#PRM{T;dKEyU_~3dHmOFMSYp#chhLXv)p5Fogc2E8A9bA;Czqp%8ib-Ai4&*M zxCm!kHS9hSNUQNM#`&{Ody9{Jgxi<~heFISt!)EiB$+leQJ%2 zm&H&B76qele)we$1A#J`hUH9fUSyXldfqBAhlmnlOlUf~kz-$m;I>Mi3BF(SecQ<yJ{3sI4N4 z{Jv!P" ] @@ -771,15 +773,17 @@ "\n", "ax1.plot(all_centres,alerts_visit)\n", "\n", - "x = np.nanmedian(alerts_visit)\n", - "ax1.axhline(x,c=\"r\",label = \"median = {:.0f}\".format(x))\n", + "med = np.nanmedian(alerts_visit)\n", + "ax1.axhline(med,c=\"r\",label = \"median = {:.0f}\".format(med))\n", + "mean = np.nanmean(alerts_visit)\n", + "ax1.axhline(mean,c=\"r\", ls = \":\", label = \"mean = {:.0f}\".format(mean))\n", "\n", "ax1.set_xlabel(\"night\")\n", "ax1.set_ylabel(\"mean SSO alerts per visit (per night)\")\n", "ax1.legend()\n", "\n", - "# fname = \"SSO_alerts_per_visit.pdf\"\n", - "fname = \"SSO_alerts_per_visit.png\"\n", + "fname = \"SSO_alerts_per_visit.pdf\"\n", + "# fname = \"SSO_alerts_per_visit.png\"\n", "plt.savefig(fname, facecolor=\"w\", transparent=True, bbox_inches=\"tight\")\n", "\n", "plt.show()" @@ -793,7 +797,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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    " ] @@ -810,15 +814,17 @@ "\n", "ax1.hist(alerts_visit,bins = 50, histtype = \"step\")\n", "\n", - "x = np.nanmedian(alerts_visit)\n", - "ax1.axvline(x,c=\"r\",label = \"median = {:.0f}\".format(x))\n", + "med = np.nanmedian(alerts_visit)\n", + "ax1.axvline(med,c=\"r\",label = \"median = {:.0f}\".format(med))\n", + "mean = np.nanmean(alerts_visit)\n", + "ax1.axvline(mean,c=\"r\", ls = \":\", label = \"mean = {:.0f}\".format(mean))\n", "\n", "ax1.set_ylabel(\"number\")\n", "ax1.set_xlabel(\"mean SSO alerts per visit (per night)\")\n", "ax1.legend()\n", "\n", - "# fname = \"SSO_alerts_per_visit_hist.pdf\"\n", - "fname = \"SSO_alerts_per_visit_hist.png\"\n", + "fname = \"SSO_alerts_per_visit_hist.pdf\"\n", + "# fname = \"SSO_alerts_per_visit_hist.png\"\n", "plt.savefig(fname, facecolor=\"w\", transparent=True, bbox_inches=\"tight\")\n", "\n", "plt.show()" @@ -829,12 +835,22 @@ "id": "3986b935", "metadata": {}, "source": [ - "From this analysis we can expect ~300 SSO alerts per visit for typical LSST visits. Note that this number is an order of magnitude lower than the predicted ~3000 SSO alerts per visit in DMTN-102. In section 2.2 of that document it has been assumed that all main belt asteroids are evenly spread across the sky and it would appear they have assumed they would all be visible. DP0.3 takes into account the distribution of small bodies across the sky and their brightness relative the the LSST detection limit. Therefore our value of ~300 alerts per visit is more accurate.\n", + "From this analysis we can expect ~300 SSO alerts per visit for typical LSST visits (median value). Note that this number is an order of magnitude lower than the predicted ~3000 SSO alerts per visit in DMTN-102. In section 2.2 of that document it has been assumed that all main belt asteroids are evenly spread across the sky and they have assumed that all asteroids in the field of view of a visit would be detectable by LSST:\n", + "\n", + "N_survey = 5.5e6 asteroids in LSST survey \n", + "A_survey = 1.8e4 square degrees of LSST survey footprint \n", + "A_visit = 9.6 square degrees footprint for a single visit\n", + "\n", + "The estimated number of asteroids per visit is therefore:\n", + "\n", + "N_visit = (N_survey/A_survey) * A_visit ~ 3000 asteroids per visit\n", + "\n", + "This estimate does not take into account the effects of changing heliocentric/geocentric distance, or phase angle effects, on the brightness of an asteroid in the field of view of a visit. DP0.3 takes into account the distribution of small bodies across the sky and has calculated their ephemerides in order to obtain a predicted brightness at the time of each visit. Furthermore the predicted brightness for each asteroid has been calculated in different filters by using the surface colour which was assigned when the population was generated. We would therefore expect that only a fraction of asteroids in the field of view would be above the LSST detection limit (in that filter). Therefore the lower value of ~300 alerts per visit is a more accurate estimate of number of SSO alerts per visit during the survey.\n", "\n", "In comparison to the number of other transients alerts in DP0.3, SSO alerts are not expected to dominate the total number of alerts:\n", "- Variable Stars: ~7200 alerts per visit\n", "- Supernovae: ~200 alerts per visit\n", - "- Active Galactic Nuclei: ~70 alerts per visit\n" + "- Active Galactic Nuclei: ~70 alerts per visit" ] }, {