{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "![HELP-Logo](https://avatars1.githubusercontent.com/u/7880370?s=200&v=4)\n", "\n", "# Exploring $z\\sim5$ Lyman Break Galaxies in the HELP Virtual Observatory\n", "\n", "In this notebook we use the HELP VO system to explore the properties of a sample of $z\\sim5$ ($r$-dropouts) in the ELAIS-N1 data. Using the VO we search for $r$-dropout sources in the HyperSuprimeCam (HSC) data following the selection criteria applied by [Ono et al. (2017)](https://arxiv.org/abs/1704.06004).\n", "\n", "For this sample of $z\\sim5$ candidates we then explore their properties in the far-infrared using the HELP XID+ deconfused photometry measurements and make use of the HELP photometric redshift posteriors to construct a cleaner sample if IR-luminous LBG candidates.\n", "\n", "This notebook assumes you have PyVO installed and working, if this is your first experience with using the HELP VO service you may consider starting with the other example notebooks to familiarise yourself with the steps.\n", "\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import h5py\n", "import pyvo as vo\n", "from IPython import display" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we define our main query, selecting all our columns of interest and joining the main datatable with the depth maps so that we only include sources from within the HSC optical footprint:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "base_query=\"\"\"\n", "SELECT top 1000000\n", " t.help_id, t.hp_idx, t.ra, t.dec, t.redshift, t.zspec,\n", " t.m_ap_suprime_g, t.m_ap_suprime_r, t.m_ap_suprime_i, t.m_ap_suprime_z, t.m_ap_suprime_y,\n", " t.merr_ap_suprime_g, t.merr_ap_suprime_r, t.merr_ap_suprime_i, t.merr_ap_suprime_z, t.merr_ap_suprime_y,\n", " t.m_ap_irac_i1, t.merr_ap_irac_i1, t.m_ap_irac_i2, t.merr_ap_irac_i2,\n", " t.f_spire_250, t.f_spire_350, t.f_spire_500, \n", " t.ferr_spire_250, t.ferr_spire_350, t.ferr_spire_500, \n", " t.field, \n", " t.cigale_sfr, t.cigale_dustlumin, t.cigale_mstar,\n", " t.cigale_sfr_err, t.cigale_dustlumin_err, t.cigale_mstar_err,\n", " c.ferr_suprime_z_mean, c.ferr_irac_i2_mean\n", "FROM herschelhelp.main AS t\n", "JOIN depth.main AS c\n", "ON (t.field = 'ELAIS-N1') and t.hp_idx = c.hp_idx_o_13 and c.ferr_suprime_i_mean is NOT NULL\n", "\"\"\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we define the additional colour criteria that will be added to select the dropout candidates (`dropout_criteria`) or a small subset of the full catalog (`background_criteria`):" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "dropout_criteria = \"\"\"\n", "WHERE\n", " ((t.m_ap_suprime_r - t.m_ap_suprime_i) > 1.2) AND \n", " ((t.m_ap_suprime_i - t.m_ap_suprime_z) < 0.7) AND \n", " ((t.m_ap_suprime_r - t.m_ap_suprime_i) > (1.5*(t.m_ap_suprime_i - t.m_ap_suprime_z) + 1.1)) AND\n", " (abs(t.f_ap_suprime_g/t.ferr_ap_suprime_g) < 2) AND\n", " (abs(t.f_ap_suprime_z/t.ferr_ap_suprime_z) > 5) AND\n", " (abs(t.f_ap_suprime_y/t.ferr_ap_suprime_y) > 4) \n", "\"\"\"\n", "\n", "background_criteria=\"\"\"\n", "WHERE\n", " t.hp_idx BETWEEN 188733368 AND 188763368\n", "\"\"\"\n", "\n", "# ((abs(t.f_spire_250/t.ferr_spire_250) > 2) OR (abs(t.f_spire_350/t.ferr_spire_350) > 2) OR (abs(t.f_spire_500/t.ferr_spire_500) > 2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Executing the queries and loading into astropy tables..." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: W27: None:2:2435: W27: COOSYS deprecated in VOTable 1.2 [astropy.io.votable.tree]\n", "WARNING: W06: None:2:4118: W06: Invalid UCD 'src.redsfhit': Unknown word 'src.redsfhit' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:7526: W06: Invalid UCD 'phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:7799: W06: Invalid UCD 'phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:8072: W06: Invalid UCD 'phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:8343: W06: Invalid UCD 'stat.error;phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:8528: W06: Invalid UCD 'stat.error;phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:8713: W06: Invalid UCD 'stat.error;phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:9230: W06: Invalid UCD 'phys.dust;phys.luminosity': Unknown word 'phys.dust' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:9820: W06: Invalid UCD 'stat.error;phys.dust;phys.luminosity': Unknown word 'phys.dust' [astropy.io.votable.tree]\n", "WARNING: W27: None:2:2080: W27: COOSYS deprecated in VOTable 1.2 [astropy.io.votable.tree]\n", "WARNING: W06: None:2:3763: W06: Invalid UCD 'src.redsfhit': Unknown word 'src.redsfhit' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:7171: W06: Invalid UCD 'phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:7444: W06: Invalid UCD 'phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:7717: W06: Invalid UCD 'phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:7988: W06: Invalid UCD 'stat.error;phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:8173: W06: Invalid UCD 'stat.error;phot.flux;em.IR.750-1500GHz': Unknown word 'em.IR.750-1500GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:8358: W06: Invalid UCD 'stat.error;phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:8875: W06: Invalid UCD 'phys.dust;phys.luminosity': Unknown word 'phys.dust' [astropy.io.votable.tree]\n", "WARNING: W06: None:2:9465: W06: Invalid UCD 'stat.error;phys.dust;phys.luminosity': Unknown word 'phys.dust' [astropy.io.votable.tree]\n" ] } ], "source": [ "#Then we execute the query\n", "service = vo.dal.TAPService(\"https://herschel-vos.phys.sussex.ac.uk/__system__/tap/run/tap\")\n", "result_set = service.search(base_query + dropout_criteria)\n", "reference_set = service.search(base_query + background_criteria)\n", "\n", "hsc_r_drops = result_set.to_table()\n", "hsc_background = reference_set.to_table()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The forced photometry of XID+ may return many measurements that are consistent with zero, so we'll set our threshold for FIR detection as $2\\sigma$ or more in at least two of the SPIRE bands." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/numpy/ma/core.py:852: RuntimeWarning: invalid value encountered in absolute\n", " return umath.absolute(a) * self.tolerance >= umath.absolute(b)\n", "/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/numpy/ma/core.py:852: RuntimeWarning: invalid value encountered in greater_equal\n", " return umath.absolute(a) * self.tolerance >= umath.absolute(b)\n", "/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/astropy/table/column.py:965: RuntimeWarning: invalid value encountered in greater\n", " return getattr(self.data, op)(other)\n" ] } ], "source": [ "fir_det = (((hsc_r_drops['f_spire_250']/hsc_r_drops['ferr_spire_250'] > 2.).astype('int') + \n", " (hsc_r_drops['f_spire_350']/hsc_r_drops['ferr_spire_350'] > 2.).astype('int') +\n", " (hsc_r_drops['f_spire_500']/hsc_r_drops['ferr_spire_500'] > 2.).astype('int')) >= 2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## $r$-dropouts in ELAIS N1\n", "\n", "Lets plots the candidates in the $r$-dropout colour space alongside our background subset of all galaxies to illustrate where everything lies." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(-1, 4)" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Fig, Ax = plt.subplots(1,1, figsize=(5,5))\n", "\n", "Ax.plot(hsc_background['m_ap_suprime_i']-hsc_background['m_ap_suprime_z'], \n", " hsc_background['m_ap_suprime_r']-hsc_background['m_ap_suprime_i'], ',', alpha=0.1, label='All HSC')\n", "\n", "Ax.plot(hsc_r_drops['m_ap_suprime_i']-hsc_r_drops['m_ap_suprime_z'], \n", " hsc_r_drops['m_ap_suprime_r']-hsc_r_drops['m_ap_suprime_i'], \n", " 'o', ms=4, color='indianred', alpha=0.2, label=r'All $r$-drops')\n", "\n", "Ax.plot((hsc_r_drops['m_ap_suprime_i']-hsc_r_drops['m_ap_suprime_z'])[fir_det], \n", " (hsc_r_drops['m_ap_suprime_r']-hsc_r_drops['m_ap_suprime_i'])[fir_det], \n", " 'o', ms=8, color='firebrick', label=r'FIR Detected $r$-drops')\n", "\n", "Leg = Ax.legend(loc='lower right')\n", "\n", "Ax.set_xlabel(r'$i_{\\rm{HSC}} - z_{\\rm{HSC}}$', size=12)\n", "Ax.set_ylabel(r'$r_{\\rm{HSC}} - i_{\\rm{HSC}}$', size=12)\n", "Ax.set_xlim([-0.5, 2])\n", "Ax.set_ylim([-1, 4])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What do the photometric redshift posteriors of our candidates look like?\n", "\n", "Now we load the [HELP photo-$z$](https://github.com/H-E-L-P/dmu_products/tree/master/dmu24) posteriors to see the estimated redshifts for these candidates taking into account all of the available photometry (including additional near- and mid-infrared where available).\n", "\n", "The posterior files are large but as they are HDF5 files, they do not need to be loaded into memory. Here we assume that the relevant file has been downloaded from [HeDAM](http://hedam.lam.fr/HELP/dataproducts/dmu24/) and is stored locally. We load in the posteriors for only our $z\\sim5$ candidate sources." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "pz_hdf = h5py.File('/Users/ken/pz_hb_en1.hdf', 'r') # Update to relevant local path\n", "pz_help_id = pz_hdf['help_id'].value\n", "\n", "matches = list(np.array([np.where(idx == pz_help_id) for idx in hsc_r_drops['help_id']]).squeeze())\n", "hsc_r_drops_pz = np.array([pz_hdf['pz'][idx] for idx in matches])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For illustrative purposes, lets stack the posteriors (and re-normalise) for our different subsamples to see the overall redshift distributions." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "pz_all = np.nansum(hsc_r_drops_pz, 0) # Sum all posteriors\n", "pz_all /= np.trapz(pz_all, pz_hdf['zgrid']) # Re-normalise\n", "\n", "pz_fir = np.nansum(hsc_r_drops_pz[fir_det], 0) # Sum SPIRE detected posteriors\n", "pz_fir /= np.trapz(pz_fir, pz_hdf['zgrid']) # Re-normalise" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'$P(z)$')" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Fig, Ax = plt.subplots(1, 1, figsize=(6,4))\n", "Ax.plot(pz_hdf['zgrid'], pz_all, lw=3, label=r'All $r$-drops')\n", "Ax.plot(pz_hdf['zgrid'], pz_fir, lw=3, label=r'FIR Detected $r$-drops')\n", "\n", "Leg = Ax.legend(loc='upper right')\n", "Ax.set_xlim([0, 7])\n", "Ax.set_title(r'ELAIS-N1 HSC $r$-dropouts - Stacked $P(z)$')\n", "Ax.set_xlabel('z', size=12)\n", "Ax.set_ylabel(r'$P(z)$', size=12)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we can above, only approximately $\\sim50\\%$ of the sources are predicted to be at high redshift. This is consistent with the contamination estimates presented in [Ono et al. (2017)](https://arxiv.org/abs/1704.06004). As expected, the high redshift peak is centred at $z\\sim5$ but has a very broad distribution.\n", "\n", "The posterior distribution for the FIR detected sources is clearly different, with the majority being consistent with low redshift galaxies (i.e. mis-identification of the Balmer/Lyman break). There is still however clearly some candidates that are consistent with being at high redshift. Lets find out how many of the dropout sources have redshift posteriors consistent with the source being at $z > 3$" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/ipykernel_launcher.py:1: RuntimeWarning: invalid value encountered in greater\n", " \"\"\"Entry point for launching an IPython kernel.\n" ] } ], "source": [ "pz_gtr3 = (np.trapz(hsc_r_drops_pz[:,462:], pz_hdf['zgrid'][462:], axis=1) > 0.95)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How many SPIRE detected sources remain after enforcing a stricter photo-$z$ requirement?" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(pz_gtr3 * fir_det).sum()" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'$P(z)$')" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pz_stack_gtr3 = np.nansum(hsc_r_drops_pz[pz_gtr3], 0) # Sum all posteriors\n", "pz_stack_gtr3 /= np.trapz(pz_stack_gtr3, pz_hdf['zgrid']) # Re-normalise\n", "\n", "pz_fir_gtr3 = np.nansum(hsc_r_drops_pz[fir_det*pz_gtr3], 0) # Sum SPIRE detected posteriors\n", "pz_fir_gtr3 /= np.trapz(pz_fir_gtr3, pz_hdf['zgrid']) # Re-normalise\n", "\n", "Fig, Ax = plt.subplots(1, 1, figsize=(6,4))\n", "Ax.plot(pz_hdf['zgrid'], pz_stack_gtr3, lw=3, label=r'$z > 3$ $r$-drops')\n", "Ax.plot(pz_hdf['zgrid'], pz_fir_gtr3, lw=3, label=r'FIR Detected $z > 3 r$-drops')\n", "\n", "Leg = Ax.legend(loc='upper left')\n", "Ax.set_xlim([0, 7])\n", "Ax.set_title(r'ELAIS-N1 HSC $r$-dropouts - Stacked $P(z)$')\n", "Ax.set_xlabel('z', size=12)\n", "Ax.set_ylabel(r'$P(z)$', size=12)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Visual Inspection\n" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table masked=True length=4\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
help_idhp_idxradecredshiftzspecm_ap_suprime_gm_ap_suprime_rm_ap_suprime_im_ap_suprime_zm_ap_suprime_ymerr_ap_suprime_gmerr_ap_suprime_rmerr_ap_suprime_imerr_ap_suprime_zmerr_ap_suprime_ym_ap_irac_i1merr_ap_irac_i1m_ap_irac_i2merr_ap_irac_i2f_spire_250f_spire_350f_spire_500ferr_spire_250ferr_spire_350ferr_spire_500fieldcigale_sfrcigale_dustlumincigale_mstarcigale_sfr_errcigale_dustlumin_errcigale_mstar_errferr_suprime_z_meanferr_irac_i2_mean
degdegmagmagmagmagmagmagmagmagmagmagmagmagmagmaguJyuJyuJyuJyuJyuJyMsun / yrWMsunMsun / yrWMsunuJyuJy
objectint64float64float64float32float32float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64objectfloat64float64float64float64float64float64float64float64
HELP_J161743.484+543902.987166309753244.43118355805754.6508297664992994.6686001--29.11485000000000124.7693322.85369899999999922.43782399999999922.0359882.11956240.0721940799999999940.0182673299999999980.0218822769999999990.03569076599999999920.2678516605103990.02640669655562620.4064536441216010.0460905237101969039921.381999999999610215.8045362.30659999999991805.2592175.9242765.2613999999999ELAIS-N11430.38475443247993.9800921350160101e+39330903037993.5180190.7021391056478022.0752333104221501e+3845033175967.1080020.135851980000000012.4308661417322801
HELP_J161847.732+554248.369166422561244.6988833190569955.71343596149935.6430998--26.90151600000000141.94673999999999822.262121.63765321.1034580.99654790000000004550775.250.021454080.0311169120.03582094200000000119.5074594131718020.015958327419017119.7691423623431990.02248351526219239913674.58499999999915308.7900000000016072.76249999999984283.26100000000044449.30199999999974991.5995000000003ELAIS-N12689.48290335079995.7566311626709399e+39481898491732.29498230.0181425534435.1331593416800703e+3858188517943.9094010.681248960000000011.3140993788819899
HELP_J161843.759+554214.534166411615244.68232740605755.7040372544992985.7767--38.31674999999999938.79377000000000221.88874821.65575400000000221.34927636696.68800000000230187.1110000000010.0149825750.0309085199999999980.04298509300000000219.7202174688959990.020568438106316220.1159573155302990.03127772088484959812646.1188568.045000000000110819.8700000000012909.15700000000023262.48999999999984924.4179999999997ELAIS-N12601.97599007006016.4843754998497703e+39689985684819.448225.645353551587993.7573670763251099e+38107116115219.9670.24127441.15818181818182
HELP_J160634.608+544111.999166382126241.6442005550570154.6866662924992974.3558002--28.71017525.98756824.36956424.24266400000000124.0400871.28039290000000010.20706690.0540991050000000010.106603950.2111106000000000122.9719909307264980.1857876828534900122.8984408759731010.22799633773409311643.51399999999915613.21314544.671776.64799999999991212.2080000000001700.64900000000102ELAIS-N11320.912245578982.5473743349500602e+3936784715156.15219970.6404480060591031.44994532155387e+387406474085.89908030.1191665160.76026626032448996
" ], "text/plain": [ "\n", " help_id hp_idx ... ferr_irac_i2_mean \n", " ... uJy \n", " object int64 ... float64 \n", "--------------------------- --------- ... -------------------\n", "HELP_J161743.484+543902.987 166309753 ... 2.4308661417322801\n", "HELP_J161847.732+554248.369 166422561 ... 1.3140993788819899\n", "HELP_J161843.759+554214.534 166411615 ... 1.15818181818182\n", "HELP_J160634.608+544111.999 166382126 ... 0.76026626032448996" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hsc_r_drops[fir_det*pz_gtr3]" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "url = 'https://hsc-release.mtk.nao.ac.jp/hscMap2'\n", "iframe = ''\n", "display.HTML(iframe)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " ![HELP LOGO](https://avatars1.githubusercontent.com/u/7880370?s=75&v=4)\n", " \n", "**Author**: [Kenneth Duncan](http://dunkenj.github.io)\n", "\n", "The Herschel Extragalactic Legacy Project, ([HELP](http://herschel.sussex.ac.uk/)), is a [European Commission Research Executive Agency](https://ec.europa.eu/info/departments/research-executive-agency_en)\n", "funded project under the SP1-Cooperation, Collaborative project, Small or medium-scale focused research project, FP7-SPACE-2013-1 scheme, Grant Agreement\n", "Number 607254.\n", "\n", "[Acknowledgements](http://herschel.sussex.ac.uk/acknowledgements)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python (herschelhelp_internal)", "language": "python", "name": "helpint" } }, "nbformat": 4, "nbformat_minor": 2 }