IRS Spectra of Debris Disks in the Scorpius-Centaurus OB Association
Hannah Jang-Condell, Christine H. Chen, Tushar Mittal, P. Manoj, Dan Watson, Carey M. Lisse, Erika Nesvold, Marc Kuchner
aa r X i v : . [ a s t r o - ph . E P ] J u l To appear in ApJ
Spitzer
IRS Spectra of Debris Disks in the Scorpius-CentaurusOB Association
Hannah Jang-Condell , Christine H. Chen , Tushar Mittal , , P. Manoj , Dan Watson ,Carey M. Lisse , , Erika Nesvold , , Marc Kuchner ABSTRACT
We analyze Spitzer/IRS spectra of 110 B-, A-, F-, and G-type stars withoptically thin infrared excess in the Scorpius-Centaurus (ScoCen) OB association.The age of these stars ranges from 11-17 Myr. We fit the infrared excessesobserved in these sources by Spitzer/IRS and Spitzer/MIPS to simple dust modelsaccording to Mie theory. We find that nearly all the objects in our study can be fitby one or two belts of dust. Dust around lower mass stars appears to be closer inthan around higher mass stars, particularly for the warm dust component in thetwo-belt systems, suggesting mass-dependent evolution of debris disks aroundyoung stars. For those objects with stellar companions, all dust distances areconsistent with trunction of the debris disk by the binary companion. The gapsbetween several of the two-belt systems can place limits on the planets that mightlie between the belts, potentially constraining the mass and locations of planetsthat may be forming around these stars.
Subject headings: open clusters and associations: individual (Upper Scorpius,Lower Centaurus-Crux, Upper Centaurus-Lupus)— stars: circumstellar matter—planetary systems: formation — planet-disk interactions Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071 Space Telescope Science Institute, 3700 San Martin Dr., Baltimore, MD 21218 Department of Earth and Planetary Science, University of California, Berkeley, CA 94720 Department of Astronomy & Astrophysics, Tata Institute of Fundamental Research, Homi Bhabha Rd,Mumbai 400005, India Department of Physics and Astronomy, University of Rochester, Rochester, NY 14627 Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723 NASA Goddard Space Flight Center, Greenbelt, MD University of Maryland Baltimore County, Baltimore, MD 21250
1. Introduction
High contrast imaging surveys using adaptive optics (AO) enabled large telescopes arebeginning to discover Jovian planets in nascent planetary systems. These surveys typi-cally target nearby ( <
100 pc), young ( <
300 Myr) stars because atmospheric modeling ofJovian planets predicts that their self-emission is bright when they are young and fadeswith time, because of their captured heat of formation and ongoing gravitational contrac-tion (Marley et al. 2007). Debris disks are dusty disks around main sequence stars thatare typically discovered via excess thermal infrared emission above the stellar photosphere.
Spitzer
MIPS surveys of young clusters and field stars indicate that young stars generallypossess larger infrared excess than old stars (Su et al. 2006; Carpenter et al. 2009a). Infact, the first images of Jovian exoplanets were made in the dusty debris disk systems, HR8799 (Marois et al. 2010) and β Pictoris (Lagrange et al. 2010). Mid- to far-infrared excesswas originally discovered toward these targets more than two decades ago using the
IRAS satellite (Aumann 1984; Backman & Paresce 1993).Studies of the spatial distribution of dust in debris disks can provide constraints onthe presence of planets. For example, SED modeling of the thermal emission from thedust around HR 8799 indicates the presence of two dust populations generated by twoseparate parent body belts, one interior to 10 AU and another beyond 100 AU (Su et al. 2009;Chen et al. 2009). The system of four ∼ M Jup planets discovered using the Keck Telescopelies between these two dust populations at distances of 15, 24, 38, and 68 AU (Marois et al.2010). Similarly, SED modeling of
IRAS excesses toward β Pictoris indicates that thedust is located at distances >
20 AU (Backman & Paresce 1993) and the Jovian planet β Pic b lies inside the central clearing at 10 AU (Lagrange et al. 2010). SMA observationsof β Pic have further revealed a ring of millimeter-sized grains at ∼
94 AU that has beenidentified as the location of the main reservoir of dust-producing planetesimals (Wilner et al.2011). The architecture of the β Pic system is consistent with creation of dust by collisionsamong parent bodies in the main belt, the larger of which spiral inward under Poynting-Robertson drag until they encounter β Pic b and are scattered out of the system. A studyof strong silicate emission at 8-13 µ m of β Pic finds evidence for belts at 6, 16, and 30 AU(Okamoto et al. 2004). These belts may also be sculpted by β Pic b, and possibly additionalas-yet-undiscovered planets. The infrared spectrum of the dust in β Pic support this picture(Chen et al. 2007). Stellar activity and starspots in young stars make the detection of planetsby radial velocities and transits infeasible, especially in later type stars, meaning that directimaging and gap characterization may be some of the best methods of finding planets inyoung stars, particularly in pre-main sequence stars.Simple black body modeling of ∼
500 debris disks observed with the
Spitzer
IRS and 3 –MIPS at 70 µ m indicates that the excess from one-third of the targets can be describedusing a single temperature black body with a median grain temperature, T gr ∼
180 K, andthe excess from two-thirds of the targets can be described using a two temperature blackbody model with median grain temperatures, T gr ∼
80 K and 340 K (Chen et al. 2014).In these systems, the presence of Jovian planets could naturally explain how planetesimalspopulations are (1) dynamically excited leading to collisions between parent bodies and (2)sculpted into rings. However, coagulation N-body simulations of ’self-stirred’ disks suggestthat significantly smaller Pluto-sized objects may also induce collisions between parent bodies(Kenyon & Bromley 2004). A detailed census of Jovian-mass planets in debris disks is neededto determine the role that Jovian planets play in exciting and sculpting parent body belts.Gemini South and VLT have recently commissioned GPI and SPHERE, second-generationcoronagraphs, that are expected to take of census of planets with masses > M Jup aroundnearby, young stars (Macintosh et al. 2014).Prime targets for these searches will be young stars in the Scorpius-Centaurus OB associ-ation (ScoCen). ScoCen is the closest OB association to the Sun with typical stellar distancesof ∼
100 - 200 pc and contains three subgroups: Upper Scorpius (US), Upper Centaurus Lu-pus (UCL), and Lower Centaurus Crux (LCC), with estimated ages of ∼
11 Myr, ∼
15 Myr,and ∼
17 Myr, (Pecaut et al. 2012; Mamajek et al. 2002) respectively. Several hundred can-didate members have been identified to date, although the association probably containsthousands of low-mass members. Member stars with spectral-type F and earlier have beenidentified using moving group analysis of
Hipparcos positions, parallaxes, and proper motions(de Zeeuw et al. 1999), while later-type members have been identified using youth indica-tors (i.e., high coronal X-ray activity and large lithium abundance; (Preibisch & Mamajek2008; Slesnick et al. 2006)). Jovian mass planets have already been discovered in two ScoCendebris disk systems thus far. VLT NaCO differential imaging at L’-band has revealed thepresence of a 5.2 M Jup planet at 56 AU (0.62 ′′ ) from HD 95086, an A8V member of LCC(Rameau et al. 2013). Magellan AO + Clio2 differential imaging at J-, Ks- and L’-bandshas revealed the presence of an 11 M Jup planet at 650 AU from HD 106906, a F5 memberof LCC (Bailey et al. 2014).We report here the results of a study modeling the
Spitzer
IRS and MIPS 70 µ mSEDs of all of the debris disks around B- through G-type ScoCen members observed duringthe Spitzer cryogenic mission. Our scientific goal is to better constrain the location ofdebris dust and infer the presence of planets and their orbital properties where possible.We list the targets for the sample, along with their spectral types, distances, and subgroupmemberships in Table 1. For debris disks with two belts, the width of a gap between thebelts can provide important constraints on the mass of a planet orbiting within the disk(Quillen 2006; Chiang et al. 2009). Nesvold & Kuchner (2014) used the 3D collisional debris 4 –disk model SMACK to derive a relationship between gap width, planet mass, stellar age,and disk optical depth. We use this relationship to determine which of the two-belt ScoCentargets are consistent with a planet on a circular orbit, and which require multiple planetsor eccentric planet orbits. For the systems consistent with a single non-eccentric planet, weplace an upper limit on the mass of the putative perturbing planet.
2. Observations
The infrared properties of nearby, young stars in ScoCen were systematically exploredduring the
Spitzer cryogenic mission. Observers used the MIPS mid-IR photometric camerato search for infrared excess at 24 and/or 70 µ m around ScoCen members selected based on Hipparcos astrometry (de Zeeuw et al. 1999), color-magnitude diagrams Preibisch & Zinnecker(1999); Preibisch et al. (2002), and x-ray surveys (Walter et al. 1994; Mart´ın 1998; Preibisch et al.1998; Kunkel 1999; K¨ohler et al. 2000). They followed-up excess targets using the IRS mid-IR spectrometer at 5-35 µ m to search for solid-state emission features and characterize theshapes of the SEDs. Taken together, the Spitzer
MIPS photometry indicated that approx-imately one-quarter of the ∼
600 ScoCen stars observed using MIPS possess infrared excess(Su et al. 2006; Carpenter et al. 2009b; Chen et al. 2011, 2012). For stars with ages 10 -20 Myr, stellar evolutionary models suggest that stars with spectral type earlier than F aremain sequence while stars later than F are not. The infrared excess properties of late-typestars in Upper Sco are consistent with gas-rich, optically thick T Tauri stars while those ofearly-type stars in Upper Sco and early- and solar-type stars in UCL and LCC are consistentwith gas-depleted, optically thin debris disks. Because our models are only valid for opticallythin disks, we focus only on the debris disks.The
Spitzer
IRS spectra for ScoCen members possess a diverse array of properties. Forexample, the spectrum of the F3/F5 LCC member HIP 63975 (HD 113766) shows prominent10 and 20 µ m silicate emission features consistent with the presence of forsterite, enstatite,olivine, and pyroxene-rich dust, generated by the destruction of a &
300 km radius asteroid.Detailed modeling of the IRS spectrum suggests that the dust in this system is located intwo cold belts located at 4 - 9 AU and 30 - 80 AU from the star, plus a warm belt at 1.8 AU(Lisse et al. 2008). By contrast, the IRS spectra of debris disks around B- and A-type stars inUpper Sco reveal rising continuua without strong solid-state emission features. The dust inthese systems has been modeled using a single temperature black body (Dahm & Carpenter2009). We have collected all of the IRS spectra of ScoCen US, UCL, and LCC debris disks andanalyzed their spectra self-consistently. In Figure 1, we plot the K s -[24] color as a functionof J − H color (as a proxy for spectral type) for all of the sources observed using MIPS and 5 –Fig. 1.— Color-color plot of all ScoCen targets surveyed with Spitzer. We plot in black allof the objects surveyed with MIPS (Su et al. 2006; Carpenter et al. 2008, 2009b; Chen et al.2011, 2012), and in red the objects whose IRS spectra are studied here.overlay the targets analyzed here in red. We note that the IRS spectra for 26 disk-bearingmembers of the ∼
11 Myr old Upper Sco have been modeled in detail by Dahm & Carpenter(2009); for self-consistency, we independently model the spectra of all of the debris disks intheir sample but do not reanalyze those of the primordial disks. We further note that someMIPS UCL and LCC excess sources were not observed using the IRS.We drew the calibrated IRS spectra for our targets from the
Spitzer
IRS Debris DiskCatalog (Chen et al. 2014). Calibrated IRS low-resolution spectra typically possess absolutecalibration uncertainties of 5% while calibrated MIPS 24 µ m fluxes typically possess cali-bration uncertainties of 2% (Engelbracht et al. 2007). Therefore, the spectra in the DebrisDisk catalog are pinned to the MIPS 24 µ m fluxes as reported in the Spitzer
EnhancedImaging Products (SEIP) Catalog to improve the absolute calibration of the data. TheIRS Debris Disk catalog contains not only the spectra for debris disks but also their re- http://irsa.ipac.caltech.edu/data/SPITZER/Enhanced/Imaging/overview.html σ IRS ,λ , estimated using the difference between spectra obtainedat two separate nod positions. Since the repeatability uncertainty can vary substantiallyfrom pixel-to-pixel, inconsistent with our understanding of the instrument, we averaged therepeatability uncertainty in quadrature over the nearest 5 points with boxcar weighting tosmooth out anomalously low or high values. To wit, if σ ,i is the IRS repeatability error at λ i , then σ ,i = i +2 X j = i − σ ,i . (1)One source, HIP 77911, was observed only at high resolution with IRS. For this source,we used the CASSIS (Cornell AtlaS of Spitzer/IRS Sources) optimal reduction of the data(Lebouteiller et al. 2011). The spectrum appears different from that of the other sourcesbecause the spectral resolution is higher and the wavelength coverage does not extend short-ward of 10 microns.We photosphere-subtracted our spectra using our own stellar photosphere models. Forstars whose MIPS data were analyzed by Chen et al. (2011, 2012), we adopted stellar spectraltypes, effective temperatures ( T eff ), visual extinctions ( A V ), and luminosities ( L ∗ ) publishedtherein. Stellar properties for sources not analyzed in these papers were taken from thereferences indicated in Table 1. Then, we selected Kurucz model atmospheres (Kurucz 1979)consistent with the listed effective temperatures, assuming solar abundances and surfacegravities, log g = 4 .
0. Next, we reddened the stellar model SEDs assuming the Cardelli,Clayton, & Mathis interstellar extinction law and A V = 3 . E ( B − V ). Finally, we normalizedthese stellar atmospheres to the MIPS 24 µ m predictions given by Chen et al. (2011, 2012),with the same 3% photosphere calibration error used in those works. The total uncertaintyin the photosphere-subtracted spectrum is σ excess ,λ = q σ ,λ + σ ,λ (2)where σ phot = 3% × F phot . In Figures 2a-2e, we show the reduced and photosphere-subtractedspectra of our sources.In Table 1, we summarize the stellar properties of the 119 Sco Cen members whoseIRS spectra are discussed here. The distances to the sources are taken from Hipparcosmeasurements (van Leeuwen 2007). Of these sources, 5 are Be stars, and are not analyzed:HIP 63005, HIP 67472, HIP 69618, HIP 77859, and HIP 78207. Another 4 sources areoptically thick protoplanetary disks: HIP 56354 (HD 100453), HIP 56379 (HD 100546), HIP HIP 53524 −3 −2 −1 Jy HIP 55188 −3 −2 −1 Jy HIP 56354* −1 Jy HIP 56379* −1 Jy HIP 56673 −3 −2 −1 Jy HIP 57524 −3 −2 −1 Jy HIP 57950 −3 −2 −1 Jy HIP 58220 −3 −2 −1 Jy HIP 58528 −3 −2 −1 Jy HIP 58720 −3 −2 −1 Jy HIP 59282 −3 −2 −1 Jy HIP 59397 −3 −2 −1 Jy HIP 59481 −3 −2 −1 Jy HIP 59502 −3 −2 −1 Jy HIP 59693 −3 −2 −1 Jy HIP 59898 −3 −2 −1 Jy HIP 59960 −3 −2 −1 Jy HIP 60183 −3 −2 −1 Jy HIP 60348 −3 −2 −1 Jy HIP 60561 −3 −2 −1 Jy HIP 60710 −3 −2 −1 Jy HIP 61049 −3 −2 −1 Jy HIP 61087 −3 −2 −1 Jy HIP 61684 −3 −2 −1 Jy Fig. 2a.— Photosphere-subtracted spectra. The IRS spectrum is shown in gray and thephotosphere fit is shown in cyan. The parameters for the photosphere fit for each star arelisted in Table 1 The photosphere-subtracted spectrum is plotted in black, with gray errorbars. MIPS photometric points are indicated by magenta points, with arrows indicatingupper limits. 8 –
HIP 61782 −3 −2 −1 Jy HIP 62134 −3 −2 −1 Jy HIP 62427 −3 −2 −1 Jy HIP 62428 −3 −2 −1 Jy HIP 62445 −3 −2 −1 Jy HIP 62657 −3 −2 −1 Jy HIP 63005* −3 −2 −1 Jy HIP 63236 −3 −2 −1 Jy HIP 63439 −3 −2 −1 Jy HIP 63836 −3 −2 −1 Jy HIP 63839 −3 −2 −1 Jy HIP 63886 −3 −2 −1 Jy HIP 63975 −2 −1 Jy HIP 64053 −3 −2 −1 Jy HIP 64184 −3 −2 −1 Jy HIP 64877 −3 −2 −1 Jy HIP 64995 −3 −2 −1 Jy HIP 65089 −3 −2 −1 Jy HIP 65875 −3 −2 −1 Jy HIP 65965 −3 −2 −1 Jy HIP 66001 −3 −2 −1 Jy HIP 66068 −3 −2 −1 Jy HIP 66447 −3 −2 −1 Jy HIP 66566 −3 −2 −1 Jy Fig. 2b.— Continuation Figure 2a, spectra of objects. 9 –
HIP 67068 −3 −2 −1 Jy HIP 67230 −3 −2 −1 Jy HIP 67472* −2 −1 Jy HIP 67497 −3 −2 −1 Jy HIP 67970 −3 −2 −1 Jy HIP 68080 −3 −2 −1 Jy HIP 68781 −3 −2 −1 Jy HIP 69291 −3 −2 −1 Jy HIP 69618* −2 −1 Jy HIP 69720 −3 −2 −1 Jy HIP 70149 −3 −2 −1 Jy HIP 70441 −3 −2 −1 Jy HIP 70455 −3 −2 −1 Jy HIP 71271 −3 −2 −1 Jy HIP 71453 −3 −2 −1 Jy HIP 72033 −3 −2 −1 Jy HIP 72070 −3 −2 −1 Jy HIP 73145 −3 −2 −1 Jy HIP 73341 −3 −2 −1 Jy HIP 73666 −3 −2 −1 Jy HIP 73990 −3 −2 −1 Jy HIP 74499 −3 −2 −1 Jy HIP 74752 −3 −2 −1 Jy HIP 74959 −3 −2 −1 Jy Fig. 2c.— Continuation Figure 2a, spectra of objects. 10 –
HIP 75077 −3 −2 −1 Jy HIP 75151 −3 −2 −1 Jy HIP 75210 −3 −2 −1 Jy HIP 75304 −3 −2 −1 Jy HIP 75491 −3 −2 −1 Jy HIP 75509 −3 −2 −1 Jy HIP 76084 −3 −2 −1 Jy HIP 76197* −3 −2 −1 Jy HIP 76310 −3 −2 −1 Jy HIP 76395 −3 −2 −1 Jy HIP 77081 −3 −2 −1 Jy HIP 77157 −2 −1 Jy HIP 77315 −3 −2 −1 Jy HIP 77317 −3 −2 −1 Jy HIP 77432 −3 −2 −1 Jy HIP 77520 −3 −2 −1 Jy HIP 77523 −3 −2 −1 Jy HIP 77656 −3 −2 −1 Jy HIP 77911 −3 −2 −1 Jy HIP 78043 −3 −2 −1 Jy HIP 78555 −3 −2 −1 Jy HIP 78641 −3 −2 −1 Jy HIP 78663 −3 −2 −1 Jy HIP 78756 −3 −2 −1 Jy Fig. 2d.— Continuation Figure 2a, spectra of objects. 11 –
HIP 78977 −3 −2 −1 Jy HIP 78996 −3 −2 −1 Jy HIP 79054 −3 −2 −1 Jy HIP 79156 −3 −2 −1 Jy HIP 79288 −3 −2 −1 Jy HIP 79400 −3 −2 −1 Jy HIP 79410 −3 −2 −1 Jy HIP 79439 −3 −2 −1 Jy HIP 79516 −3 −2 −1 Jy HIP 79631 −3 −2 −1 Jy HIP 79710 −3 −2 −1 Jy HIP 79742 −3 −2 −1 Jy HIP 79878 −3 −2 −1 Jy HIP 79977 −3 −2 −1 Jy HIP 80024 −3 −2 −1 Jy HIP 80088 −3 −2 −1 Jy HIP 80142 −3 −2 −1 Jy HIP 80320 −3 −2 −1 Jy HIP 80897 −3 −2 −1 Jy HIP 82154 −3 −2 −1 Jy HIP 82218 −3 −2 −1 Jy HIP 82747* −2 −1 Jy HIP 83159* −3 −2 −1 Jy Fig. 2e.— Continuation Figure 2a, spectra of objects. 12 – O • )10 -6 -5 -4 -3 -2 -1 L I R / L * Fig. 3.— L IR /L ∗ versus stellar mass. Asterisks are Lower Centaurus Crux, squares areUpper Centaurus Lupus, and filled triangles are Upper Scorpius.77157 (HT Lupi), and HIP 82747 (AK Sco. See e.g. Manoj et al. 2006; Sturm et al. 2013).These sources cannot be adequately modeled using simple grain models, so we exclude themfrom our study. In Table 2 we tabulate the calculated L IR /L ∗ based on the calibrated andphotosphere-subtracted spectra of the remaining 110 sources. In Figure 3, we plot L IR /L ∗ versus stellar mass. The downward trend versus stellar mass is contrary to what would beexpected if disk temperatures or masses simply scale with stellar mass. This can be explainedeither by decreasing disk mass or decreasing dust temperature with increasing stellar mass,scenarios that will be discussed in our Results.In general, we found that the photosphere models were consistent with the IRS observa-tions for all of the stars in our study with the exception of HIP 56673 (HD 101088) and HIP78977 (HD 144548). For these two objects, this normalization of the IRS spectra produced aRayleigh-Jeans power-law excess at 5-30 µ m excess that could indicate the presence of a hotdust component with T gr ≫
500 K. Visual spectra of HIP 56673B (HD 101088B) show time-variable H α emission, consistent with accretion observed toward T Tauri stars (Bitner et al.2010). Alternatively, this mismatch in the MIPS 24 µ m flux and the IRS spectrum couldindicate that these sources possess time variable excesses similar to that observed toward ID8 caused by stochastic grinding events (Meng et al. 2014).Several sources show little to no excess in the IRS data. We omit these non-excesssources based on two criteria: the excess significance and the normalized flux ratio. Thesequantities compare the observed versus predicted photosphere-only emission over a selected 13 –wavelength regime. That is, if F ν is the frequency-dependent flux with uncertainty σ ν , then F ( ν , ν ) = R ν ν F ν dνν − ν (3)and the weighted uncertainty is σ ( ν , ν ) = R ν ν σ ν dνν − ν . (4)We use the subscripts ’obs’ and ’pred’ to refer to the observed and predicted flux, respectively.We consider three different passbands: 8 . − µ m, 21 − µ m, and 30 − µ m. The fluxintegrated over each of these passbands are F(10 µ m), F(24 µ m), and F(32 µ m), respectively.The excess significance is defined to be χ = ( F obs − F pred ) / ( σ + σ ) / , (5)where σ obs includes the repeatability error and a 5% normalization uncertainty added inquadrature, while σ pred consists of a 3% normalization uncertainty. We calculate the excesssignificance over our three passbands, χ , χ , and χ , and list their values in Table 2.We also list values of χ tot , which is the excess significance calculated over the entire IRSspectrum. HIP 56673 and HIP 78977 are listed twice: in the first listing, the IRS spectraare normalized to the MIPS 24 micron as described in Chen et al. (2014), and in the secondlisting, marked by an asterisk, the spectra are normalized to the photosphere model at 5-6microns. When these sources are normalized to the photosphere, HIP 56673 exhibits a smallexcess, but HIP 78977 has none.The normalized flux ratio is adapted from Carpenter et al. (2009b), and is defined to be R / = F obs (32 µ m) /F pred (32 µ m) F obs (10 µ m) /F pred (10 µ m) . (6)A similar expression is used to calculate R / . In Carpenter et al. (2009b), photometricfluxes were used. Here, we integrate the spectrum over the given passband, assuming 100%efficiency. Since R can be considered to be a ratio of the slope of the observed spectrumcompared to the slope of the predicted spectrum, any error in the overall normalization ofeither spectrum cancels out. Therefore, the error on R is propagated from the repeatabilityerror of the observed spectrum alone.The excess significance ( χ ) measures the signal-to-noise of the infrared excess at eachband pass, while R measures the shape of the excess. In some sources, even though the excesssignificance is formally low, the shape of the spectrum rises at long wavelengths, indicating 14 –that there is a notable cold excess. If R >
1, then the shape of the spectrum indicates a coldexcess component, while R = 1 indicates a shape consistent with photospheric emission.To determine which spectra to exclude as non-excess sources, we use both the χ and R measures. Sources which have χ , χ , χ , and χ tot all less than 3 and whose values of R and R are both less than or equal to 1 to within one σ are labeled non-excess sources andare excluded from further analysis. A total of 13 of our sources are non-excess sources, andare labeled as such in Table 2. In addition, HIP 78977, when normalized to the photospheremodel, can be considered a non-excess source. This leaves a total of 97 debris disk spectrathat we analyze for their dust properties. Table 1. Stellar Properties
HIP Name Spectral Distance T eff Mass Luminosity A V Program NotesType (pc) (K) ( M ⊙ ) ( L ⊙ )Lower Centaurus Crux53524 HD 95086 A8III (6) 90.4 7499 1.6 7.11 0.000 IRS DISKS/2 (18)55188 HD 98363 A2V (6) 123.6 8770 1.9 11.4 0.244 CCHEN2/40235 (18)56354 HD 100453 A9Ve (14) 121.5 7447 1.6 10.4 0.214 IRS DISKS/2 (18) protoplanetary56379 HD 100546 B9Vne (6) 96.9 10520 2.4 26.6 0.194 IRS DISKS/2 (18) protoplanetary56673 HD 101088 F5IV (6) 93.8 6440 2.2 17.7 0.142 DEBRISII/40651 (17) λ − excess57524 HD 102458 F9IV (13) 91.7 6115 1.2 1.89 0.178 DEBRISII/40651 (17)57950 HD 103234 F2IV/V (6) 98.1 6890 1.5 3.90 0.066 DEBRISII/40651 (17)58220 HD 103703 F3V (6) 98.9 6740 1.5 3.35 0.096 YOUNGA/84 (17)58528 HD 104231 F5V (6) 110.5 6440 1.4 3.73 0.016 DEBRISII/40651 (17)58720 HD 104600 B9V (6) 105.7 11614 2.7 68.7 0.024 CCHEN2/40235 (18)59282 HD 105613 A3V (6) 104.2 8551 1.8 11.6 0.192 CCHEN2/40235 (18)59397 HD 105857 A2V (6) 113.0 8770 1.9 14.0 0.132 CCHEN2/40235 (18)59481 HD 105994 F3V (7) 113.1 6740 1.5 4.09 0.023 WARMDISK2/50538 (17)59502 HD 106036 A2V (6) 100.7 8770 1.9 13.8 0.015 CCHEN2/40235 (18)59693 HD 106389 F6IV (7) 137.0 6360 1.3 2.32 0.184 DEBRISII/40651 (17)59898 HD 106797 A0V (6) 96.0 9550 2.1 32.9 0.022 CCHEN2/40235 (18)59960 HD 106906 F5V (6) 92.1 6440 1.5 5.06 0.000 IRS DISKS/2 (17)60183 HD 107301 B9V (6) 93.9 10814 2.4 36.8 0.067 CCHEN2/40235 (18)60348 HD 107649 F5V (7) 93.7 6440 1.4 2.13 0.022 YOUNGA/84 (17)60561 HD 107947 A0V (6) 91.1 9550 2.1 17.5 0.000 CCHEN2/40235 (18)60710 HD 108257 B3Vn (2) 137.4 17298 5.4 809. 0.070 IRS DISKS/2 (18)61049 HD 108857 F7V (6) 97.0 6280 1.4 3.13 0.143 CCHEN2/40235 (17)61087 HD 108904 F6V (6) 97.5 6360 1.5 4.97 0.050 CCHEN2/40235 (17)61684 HD 109832 A9V (6) 111.9 7447 1.6 7.14 0.261 CCHEN2/40235 (18)61782 HD 110058 A0V (7) 107.4 9550 2.1 10.2 0.436 IRS DISKS/2 (18) Table 1—Continued
HIP Name Spectral Distance T eff Mass Luminosity A V Program NotesType (pc) (K) ( M ⊙ ) ( L ⊙ )62134 HD 110634 F2V (7) 115.6 6890 1.5 3.74 0.026 YOUNGA/84 (17)62427 HD 111103 F8 (1) 142.7 6200 1.4 3.17 0.000 DEBRISII/40651 (17)62445 HD 111170 G4.5IVe (13) 130.5 5728 1.6 4.17 0.660 RUBBLE/148 (13)62657 HD 111520 F5/6V (7) 108.6 6400 1.3 2.60 0.028 CCHEN/241 (17)63005 HD 112091 B5V(e) (2) 124.8 16634 5.0 541. 0.200 CCHEN2/40235 (18) classical Be63236 HD 112383 A2IV/V (6) 110.7 8770 1.9 20.0 0.000 CCHEN2/40235 (18)63439 HD 112810 F3/5IV/V (7) 143.3 6590 1.4 3.52 0.000 DEBRISII/40651 (17)63836 HD 113524 F6/8 (7) 107.4 6280 1.3 2.31 0.000 DEBRISII/40651 (17)63839 HD 113457 A0V (6) 99.4 9550 2.1 20.3 0.000 CCHEN2/40235 (18)63886 HD 113556 F2V (6) 106.7 6890 1.5 4.91 0.024 IRS DISKS/2 (17)63975 HD 113766 F3/5V (7) 122.5 6590 1.9 11.9 0.000 IRS DISKS/2 (17)64053 HD 113902 B8/9V (7) 100.1 11695 2.7 77.6 0.070 CCHEN2/40235 (18)64184 HD 114082 F3V (6) 85.5 6740 1.5 3.18 0.078 IRS DISKS/2 (17)64877 HD 115361 F5V (6) 125.0 6440 1.5 5.02 0.000 CCHEN2/40235 (17)64995 HD 115600 F2IV/V (6) 110.5 6890 1.5 4.79 0.000 IRS DISKS/2 (17)65089 HD 115820 A7/8V (7) 96.5 7656 1.7 4.83 0.026 CCHEN2/40235 (18)65875 HD 117214 F6V (6) 110.3 6360 1.6 5.64 0.000 IRS DISKS/2 (17)65965 HD 117484 B9.5V (7) 147.3 10593 2.4 25.9 0.100 CCHEN/40235 (18)66001 HD 117524 G2.5IV (13) 152.4 5834 1.2 2.14 0.110 RUBBLE/148 (13)66068 HD 117665 A1/2V (7) 147.9 8974 1.9 24.4 0.000 CCHEN/40235 (18)66566 HD 118588 A1V (7) 126.4 9204 2.0 14.9 0.097 CCHEN/40235 (18)67068 HD 119511 F3V (7) 91.6 6740 1.5 2.70 0.000 WARMDISK2/50538 (17)67230 HD 119718 F5V (6) 131.8 6440 1.8 8.67 0.037 CCHEN2/40235 (17)Upper Centaurus Lupus66447 HD 118379 A3IV/V (7) 121.7 8551 1.8 13.3 0.184 TD GTO/50485 (18)67472 HD 120324 B2V:e (8) 155.0 20512 7.3 6.53e+03 0.287 CCHEN2/40235 (18) classical Be67497 HD 120326 F0V (7) 107.4 7200 1.6 4.45 0.158 DEBRISII/40651 (17) Table 1—Continued
HIP Name Spectral Distance T eff Mass Luminosity A V Program NotesType (pc) (K) ( M ⊙ ) ( L ⊙ )67970 HD 121189 F3V (7) 118.8 6740 1.5 3.85 0.070 CCHEN2/40235 (17)68080 HD 121336 A1Vn (11) 139.9 9204 2.0 64.9 0.082 CCHEN2/40235 (18)68781 HD 122705 A4V (5) 112.9 8279 1.8 8.89 0.000 TD GTO/50485 (18)69291 HD 123889 F2V (9) 132.3 6890 1.5 5.02 0.043 WARMDISK2/50638 (17)69618 HD 124367 B4Vne (2) 147.7 16982 5.2 1.01e+03 0.409 CCHEN2/40235 (18) classical Be69720 HD 124619 F0V (6) 133.3 7200 1.6 5.00 0.228 DEBRISII/40651 (17)70149 HD 125541 A9V (7) 113.3 7447 1.6 3.18 0.146 TD GTO/50485 (18)70441 HD 126062 A1V (7) 110.4 9204 2.0 11.4 0.018 CCHEN2/40235 (18)70455 HD 126135 B8V (7) 165.0 11967 2.8 70.3 0.096 GOWERNER2005/20132 (18)71271 HD 127750 A0V (7) 175.7 9550 2.1 26.9 0.040 TD GTO/50485 (18)71453 HD 128207 B8V (9) 147.5 13490 3.4 210. 0.010 GOWERNER2005/20132 (18)72033 HD 129490 F7IV/V (7) 155.8 6280 1.5 5.46 0.297 DEBRISII/40651 (17)72070 HD 129590 G1V (13) 132.6 5945 1.3 2.84 0.047 CCHEN2/42035 (17)73145 HD 131835 A2IV (9) 122.7 8770 1.9 10.5 0.187 CCHEN2/40235 (18)73341 HD 132238 B8V (9) 162.6 12359 3.0 112. 0.040 GOWERNER2005/20132 (18)73666 HD 133075 F3IV (9) 151.5 6740 2.1 16.5 0.364 DEBRISII/40651 (17)73990 HD 133803 A9V (9) 124.8 7447 1.6 8.04 0.211 TD GTO/50485 (18)74499 HD 134888 F3/5V (9) 89.9 6590 1.5 2.06 0.058 DEBRISII/40651 (17)74752 HD 135454 B9.5V (7) 173.3 10351 2.3 66.2 0.023 GOWERNER2005/20132 (18)74959 HD 135953 F5V (9) 133.2 6440 1.3 2.68 0.080 TD GTO/50485 (17)75077 HD 136246 A1V (9) 131.6 9204 2.0 22.7 0.114 GOWERNER2005/20132 (18)75151 HD 136347 B9IVSi(SrCr) (11) 143.3 11641 2.7 68.2 0.031 GOWERNER2005/20132 (18)75210 HD 136482 B8/9V (9) 136.2 11324 2.6 54.2 0.033 GOWERNER2005/20132 (18)75304 HD 136664 B4V (2) 159.2 16711 5.0 1.27e+03 0.052 IREXT/20294 (18)75491 HD 137057 F3V (9) 168.6 6740 1.9 9.59 0.051 CCHEN2/40235 (17)75509 HD 137119 A2V (9) 107.2 8770 1.9 9.02 0.067 CCHEN2/40235 (18)76084 HD 138296 F2V (9) 142.7 6890 1.7 6.64 0.191 DEBRISII/40651 (17)76395 HD 138923 B8V (3) 106.5 11967 2.8 53.6 0.041 GOWERNER2005/20132 (18)77081 HD 140374 G7.5IV (13) 200.8 5521 1.4 2.24 0.150 RUBBLE/148 (13) Table 1—Continued
HIP Name Spectral Distance T eff Mass Luminosity A V Program NotesType (pc) (K) ( M ⊙ ) ( L ⊙ )77157 HT Lupi K3Ve (15) 141.2 4730 1.1 5.09 1.138 CCHEN2/40235 (17) protoplanetary77315 HD 140817 A0V (9) 147.3 9550 2.1 41.5 0.105 CCHEN2/40235 (18)77317 HD 140840 B9/A0V (9) 125.8 10593 2.4 21.5 0.029 CCHEN2/40235 (18)77432 HD 141011 F5V (7) 96.3 6440 1.4 1.90 0.000 DEBRISII/40651 (17)77520 HD 141254 F3V (9) 100.8 6740 1.5 1.87 0.194 WARMDISK2/50538 (17)77523 HD 141327 B9V (9) 195.3 10304 2.3 48.3 0.139 TD GTO/50485 (18)77656 HD 141521 G5IV (13) 140.1 5702 1.4 2.57 0.520 RUBBLE/148 (13)78043 HD 142446 F3V (9) 144.3 6740 1.5 4.66 0.124 TD GTO/50485 (17)78555 HD 143538 F0V (9) 106.3 7200 1.6 3.55 0.178 CCHEN/241 (17)78641 HD 143675 A5IV/V (9) 113.4 8072 1.7 6.32 0.049 CCHEN2/40235 (18)78756 HD 143939 B9III (10) 144.7 10740 2.4 40.6 0.000 TD GTO/50485 (18)79400 HD 145357 A5V (7) 146.8 8072 1.7 12.8 0.342 TD GTO/50485 (18)79516 HD 145560 F5V (7) 133.7 6440 1.4 3.84 0.001 CCHEN/241 (17)79631 HD 145880 B9.5V (9) 127.9 10593 2.4 35.3 0.355 TD GTO/50485 (18)79710 HD 145972 F0V (7) 127.4 7200 1.6 5.78 0.094 TD GTO/50485 (17)79742 HD 146181 F6V (19) 146.2 6360 1.4 3.66 0.000 CCHEN/241 (17)80142 HD 147001 B7V (7) 137.2 11912 2.8 78.5 0.166 TD GTO/50485 (18)80897 HD 148657 A0V (9) 165.6 9550 2.1 21.3 0.864 TD GTO/50485 (18)82154 HD 151109 B8V (4) 222.7 11298 2.6 117. 0.074 TD GTO/50485 (18)82747 AK Sco F5V (9) 102.8 6440 1.5 4.72 1.098 IRSDISKS/2 (17) protoplanetary83159 HD 153232 F5V (9) 146.6 6440 1.5 4.17 0.000 CCHEN/241 (17)Upper Scorpius76310 HD 138813 A0V (16) 150.8 9750 2.1 30.5 0.155 JMCARP/30091 (20)77859 HD 142184 B2V (12) 130.9 · · · · · · · · · · · · JMCARP/30091 classical Be77911 HD 142315 B9V (19) 147.7 10000 2.5 50.2 0.202 JMCARP/30091 (20)78207 HD 142983 B8Ia/Iab (12) 143.5 · · · · · · · · · · · ·
JMCARP/30091 classical Be78663 HD 143811 F5V (9) 144.3 6440 1.5 4.86 0.093 DEBRISII/40651 (17)
Table 1—Continued
HIP Name Spectral Distance T eff Mass Luminosity A V Program NotesType (pc) (K) ( M ⊙ ) ( L ⊙ )78977 HD 144548 F7V (15) 116.7 6280 1.5 5.02 0.365 CCHEN/241 (17) λ − excess78996 HD 144587 A9V (16) 108.5 8750 1.4 11.4 0.967 JMCARP/30091 (20)79054 HD 144729 F0V (12) 138.9 7200 1.5 5.47 0.585 CCHEN/241 (17)79156 HD 144981 A0V (16) 170.4 9750 1.9 31.6 0.574 JMCARP/30091 (20)79288 HD 145263 F0V (12) 149.9 7200 1.6 6.40 0.399 DEBRISII/40651 (17)79410 HD 145554 B9V (16) 140.4 10000 1.9 32.5 0.577 JMCARP/30091 (20)79439 HD 145631 B9V (16) 131.8 10000 1.8 32.7 0.666 JMCARP/30091 (20)79878 HD 146606 A0V (16) 129.4 10000 2.1 27.1 0.016 JMCARP/30091 (20)79977 HD 146897 F2/3V (12) 122.7 6815 1.5 3.66 0.341 IRS DISKS/2 (17)80024 HD 147010 B9II (16) 163.4 10500 2.1 73.7 0.772 JMCARP/30091 (20)80088 HD 147137 A9V (19) 139.1 9000 1.7 12.7 1.147 JMCARP/30091 (20)80320 HD 147594 G3IV (15) 142.0 5830 1.4 3.39 0.031 WARMDISK2/50538 (17)82218 HD 151376 F2/3V (12) 135.7 6815 1.5 4.48 0.300 CCHEN/241 (17)References. — References: (1) Cannon & Pickering (1920), (2) Hiltner et al. (1969), (3) Hube (1970), (4) Schild et al. (1971),(5) Glaspey (1972), (6) Houk & Cowley (1975), (7) Houk (1978), (8) Morgan et al. (1978), (9) Houk (1982), (10) Gahm et al.(1983), (11) Corbally (1984), (12) Houk & Smith-Moore (1988), (13) Mamajek et al. (2002), (14) Vieira et al. (2003), (15)Torres et al. (2006), (16) Preibisch & Mamajek (2008), (17) Chen et al. (2011), (18) Chen et al. (2012), (19) Pecaut et al. (2012),(20) Chen et al. (2014)
20 –Table 2. Inferred disk properties
HIP HD name L IR /L ∗ excess significance ( χ ) R / R / a min note χ χ χ total ( µ m)Lower Centaurus Crux53524 HD 95086 1.10e-03 1.85 7.10 9.75 2.13 3 . ± .
30 12 . ± .
08 1.855188 HD 98363 9.56e-04 6.47 16.55 7.98 5.19 9 . ± .
31 23 . ± .
65 2.356673 HD 101088 5.50e-04 2.86 4.37 2.90 2.91 1 . ± .
02 1 . ± .
07 3.2 λ − excess56673* HD 101088 4.42e-05 0.23 2.00 1.30 0.28 1 . ± .
02 1 . ± .
07 3.2 *57524 HD 102458 2.91e-04 1.27 2.56 2.13 1.19 1 . ± .
19 1 . ± .
41 0.457950 HD 103234 1.44e-04 0.96 7.04 4.65 0.97 1 . ± .
07 2 . ± .
30 1.158220 HD 103703 6.91e-04 4.40 6.30 4.24 3.50 2 . ± .
23 3 . ± .
60 0.958528 HD 104231 2.35e-04 2.47 7.48 3.55 1.15 1 . ± .
12 2 . ± .
47 1.158720 HD 104600 1.09e-04 3.25 15.10 17.02 2.44 3 . ± .
06 8 . ± .
16 8.659282 HD 105613 8.07e-05 2.40 9.26 4.78 0.94 1 . ± .
06 2 . ± .
33 2.559397 HD 105857 1.74e-04 2.32 12.06 9.20 1.95 3 . ± .
13 4 . ± .
34 2.859481 HD 105994 8.28e-05 0.17 1.86 1.16 0.42 1 . ± .
09 1 . ± .
34 1.159502 HD 106036 3.79e-04 5.49 13.80 5.17 3.38 4 . ± .
18 8 . ± .
45 2.859693 HD 106389 3.83e-04 3.48 4.58 2.27 1.57 1 . ± .
18 1 . ± .
47 0.759898 HD 106797 2.21e-04 3.85 16.05 17.48 3.11 4 . ± .
06 8 . ± .
14 5.559960 HD 106906 1.27e-03 0.44 13.60 16.09 2.49 7 . ± .
35 23 . ± .
04 1.460183 HD 107301 9.65e-05 1.60 15.08 14.85 1.74 4 . ± .
14 8 . ± .
40 5.460348 HD 107649 2.27e-04 1.50 6.69 3.92 1.07 1 . ± .
11 3 . ± .
51 0.460561 HD 107947 1.13e-04 2.33 11.31 10.33 1.49 2 . ± .
08 4 . ± .
27 3.160710 HD 108257 -2.13e-06 -0.43 -0.11 0.25 -0.21 1 . ± .
07 1 . ± .
31 44.7 no excess61049 HD 108857 4.36e-04 3.46 12.94 10.42 1.86 3 . ± .
09 4 . ± .
25 0.961087 HD 108904 5.24e-04 2.43 5.69 1.95 1.88 2 . ± .
35 3 . ± .
38 1.461684 HD 109832 4.16e-04 1.14 13.01 15.03 1.79 3 . ± .
13 10 . ± .
39 1.861782 HD 110058 1.58e-03 3.69 17.41 18.00 6.63 23 . ± .
24 72 . ± .
83 1.962134 HD 110634 4.61e-05 0.08 1.59 0.27 0.15 1 . ± .
36 1 . ± .
24 1.062427 HD 111103 2.46e-04 -0.57 7.19 5.17 0.57 2 . ± .
22 6 . ± .
02 0.962445 HD 111170 -1.57e-04 -0.12 0.31 -0.01 -0.58 1 . ± .
10 1 . ± .
39 1.1 no excess62657 HD 111520 1.96e-03 1.81 14.82 17.50 3.49 5 . ± .
23 20 . ± .
70 0.863236 HD 112383 1.54e-04 2.57 12.60 10.61 1.73 2 . ± .
12 3 . ± .
26 3.963439 HD 112810 8.00e-04 1.38 6.25 10.92 1.18 2 . ± .
16 6 . ± .
47 1.063836 HD 113524 1.26e-04 1.00 4.34 2.42 0.47 1 . ± .
09 2 . ± .
66 0.763839 HD 113457 2.74e-04 5.07 15.37 16.07 3.34 4 . ± .
14 7 . ± .
26 3.6
21 –Table 2—Continued
HIP HD name L IR /L ∗ excess significance ( χ ) R / R / a min note χ χ χ total ( µ m)63886 HD 113556 5.15e-04 0.84 4.68 4.88 0.75 2 . ± .
22 6 . ± .
15 1.363975 HD 113766 2.23e-02 17.40 18.78 14.00 13.12 4 . ± .
11 4 . ± .
27 2.564053 HD 113902 4.17e-05 2.27 9.93 8.92 1.28 1 . ± .
04 2 . ± .
14 9.664184 HD 114082 3.01e-03 1.83 13.19 9.41 3.82 19 . ± .
17 56 . ± .
46 0.864877 HD 115361 3.09e-04 1.22 5.85 1.86 1.04 2 . ± .
25 5 . ± .
41 1.464995 HD 115600 1.87e-03 1.57 12.22 8.98 3.49 12 . ± .
88 40 . ± .
16 1.365089 HD 115820 1.52e-04 -0.32 9.60 6.66 1.21 2 . ± .
09 3 . ± .
36 1.265875 HD 117214 2.53e-03 2.14 13.25 9.56 4.05 13 . ± .
72 37 . ± .
41 1.565965 HD 117484 2.37e-04 3.10 14.72 14.76 2.92 4 . ± .
18 13 . ± .
64 3.966001 HD 117524 7.98e-05 1.31 0.88 -0.01 0.28 1 . ± .
13 0 . ± .
42 0.6 no excess66068 HD 117665 1.94e-04 3.18 13.91 11.39 2.17 3 . ± .
10 5 . ± .
34 4.666566 HD 118588 2.24e-04 3.00 14.26 11.26 2.69 4 . ± .
16 8 . ± .
55 2.967068 HD 119511 5.58e-06 0.28 3.79 2.30 0.03 1 . ± .
07 1 . ± .
23 0.767230 HD 119718 3.39e-04 1.51 4.08 3.30 1.05 2 . ± .
49 6 . ± .
56 2.0Upper Centaurus Lupus66447 HD 118379 1.37e-04 0.45 10.08 10.05 0.80 2 . ± .
10 6 . ± .
46 2.867497 HD 120326 1.50e-03 1.31 15.53 15.65 3.50 11 . ± .
70 31 . ± .
00 1.167970 HD 121189 5.25e-04 2.13 11.04 12.42 2.10 3 . ± .
23 8 . ± .
52 1.068080 HD 121336 6.10e-05 1.27 8.88 9.60 0.83 1 . ± .
04 2 . ± .
14 10.968781 HD 122705 8.87e-05 1.93 7.62 4.35 0.96 1 . ± .
06 2 . ± .
27 2.069291 HD 123889 6.89e-05 0.62 2.22 2.62 0.38 1 . ± .
06 1 . ± .
28 1.469720 HD 124619 1.51e-04 1.97 5.28 3.49 0.98 1 . ± .
11 2 . ± .
36 1.370149 HD 125541 2.06e-04 1.57 9.20 7.94 1.22 3 . ± .
21 6 . ± .
68 0.870441 HD 126062 2.72e-04 1.99 9.09 9.59 1.57 2 . ± .
15 6 . ± .
51 2.270455 HD 126135 3.28e-05 1.35 7.62 6.47 1.01 2 . ± .
12 3 . ± .
33 8.571271 HD 127750 1.62e-04 1.32 10.74 12.09 1.10 2 . ± .
08 7 . ± .
37 4.671453 HD 128207 1.01e-05 0.34 4.17 5.05 0.52 1 . ± .
04 1 . ± .
08 19.572033 HD 129490 -1.06e-04 -0.20 0.45 0.64 -0.48 1 . ± .
09 1 . ± .
34 1.5 no excess72070 HD 129590 5.22e-03 1.15 18.03 18.66 5.45 15 . ± .
43 60 . ± .
80 0.973145 HD 131835 2.27e-03 5.10 17.74 17.89 6.89 14 . ± .
69 49 . ± .
48 2.273341 HD 132238 2.64e-05 1.63 7.60 6.90 0.93 2 . ± .
11 3 . ± .
28 12.273666 HD 133075 2.36e-05 -0.13 2.35 2.85 0.13 1 . ± .
08 1 . ± .
33 3.173990 HD 133803 3.62e-04 2.95 14.05 12.14 2.30 4 . ± .
16 7 . ± .
44 2.074499 HD 134888 8.25e-04 1.10 8.84 12.42 1.27 3 . ± .
22 10 . ± .
67 0.3
22 –Table 2—Continued
HIP HD name L IR /L ∗ excess significance ( χ ) R / R / a min note χ χ χ total ( µ m)74752 HD 135454 7.22e-05 1.70 4.89 5.94 1.61 1 . ± .
08 1 . ± .
11 9.774959 HD 135953 6.31e-04 0.80 4.85 10.84 0.85 1 . ± .
11 5 . ± .
35 0.875077 HD 136246 5.09e-05 0.57 3.55 6.70 0.41 1 . ± .
07 2 . ± .
13 4.175151 HD 136347 5.01e-06 0.49 0.58 0.21 0.18 1 . ± .
04 0 . ± .
10 8.5 no excess75210 HD 136482 6.14e-05 2.53 11.56 10.42 1.62 2 . ± .
10 5 . ± .
32 7.175304 HD 136664 -3.90e-06 -0.26 0.32 0.21 -0.42 1 . ± .
04 1 . ± .
05 73.8 no excess75491 HD 137057 3.12e-04 0.67 11.41 10.90 1.35 3 . ± .
16 7 . ± .
51 2.075509 HD 137119 1.92e-04 3.38 9.02 4.78 2.13 2 . ± .
17 4 . ± .
64 1.976084 HD 138296 -7.25e-05 -0.31 0.50 0.10 -0.44 1 . ± .
09 1 . ± .
35 1.6 no excess76395 HD 138923 8.42e-05 4.39 12.14 12.72 2.77 2 . ± .
07 3 . ± .
14 6.677081 HD 140374 3.63e-04 1.36 -0.52 -0.45 0.96 0 . ± .
11 0 . ± .
47 0.1 no excess77315 HD 140817 1.54e-04 2.69 12.88 13.92 2.15 3 . ± .
11 6 . ± .
26 6.977317 HD 140840 1.64e-04 1.82 10.72 14.39 1.79 3 . ± .
19 10 . ± .
48 3.377432 HD 141011 3.19e-04 1.65 3.85 3.14 1.30 1 . ± .
21 3 . ± .
76 0.277520 HD 141254 9.31e-05 1.18 2.47 2.58 0.47 1 . ± .
13 2 . ± .
43 0.277523 HD 141327 4.59e-05 1.86 6.65 4.79 0.92 1 . ± .
10 2 . ± .
39 7.277656 HD 141521 -1.73e-04 -0.41 -0.06 -0.03 -0.61 1 . ± .
15 1 . ± .
33 0.7 no excess78043 HD 142446 7.00e-04 1.60 5.90 9.73 1.46 2 . ± .
25 7 . ± .
60 1.378555 HD 143538 -7.40e-05 -0.52 0.52 0.34 -0.21 1 . ± .
47 1 . ± .
51 0.9 no excess78641 HD 143675 5.77e-04 4.11 15.67 14.25 3.61 6 . ± .
18 14 . ± .
66 1.578756 HD 143939 2.17e-05 0.82 5.42 4.14 0.52 1 . ± .
11 2 . ± .
36 5.979400 HD 145357 1.11e-04 1.47 5.35 8.60 0.95 1 . ± .
16 2 . ± .
20 2.979516 HD 145560 2.85e-03 0.59 14.18 15.53 2.82 8 . ± .
56 33 . ± .
30 1.179631 HD 145880 2.43e-04 1.20 15.19 17.19 1.73 5 . ± .
26 17 . ± .
88 5.279710 HD 145972 2.14e-04 2.39 7.07 3.32 1.26 2 . ± .
19 3 . ± .
72 1.579742 HD 146181 2.59e-03 1.24 8.71 14.00 2.62 8 . ± .
98 32 . ± .
14 1.180142 HD 147001 -1.42e-05 -0.92 -0.03 0.20 -0.47 1 . ± .
27 1 . ± .
54 9.4 no excess80897 HD 148657 3.71e-04 3.05 15.32 16.48 3.81 5 . ± .
25 17 . ± .
79 3.782154 HD 151109 8.35e-05 1.94 13.05 12.35 1.75 3 . ± .
12 9 . ± .
51 14.683159 HD 153232 5.23e-04 0.32 0.46 0.34 0.39 1 . ± .
80 3 . ± .
26 1.1 no excessUpper Scorpius76310 HD 138813 9.50e-04 4.36 18.00 17.65 6.55 12 . ± .
39 39 . ± .
38 5.277911 HD 142315 3.52e-04 0.11 2.58 1.75 0.75 8 . ± .
33 25 . ± .
45 7.078663 HD 143811 3.30e-05 -0.15 2.48 2.20 0.06 1 . ± .
12 2 . ± .
53 1.3
23 –Table 2—Continued
HIP HD name L IR /L ∗ excess significance ( χ ) R / R / a min note χ χ χ total ( µ m)78977 HD 144548 1.33e-03 4.72 1.60 1.38 4.52 0 . ± .
15 1 . ± .
53 1.4 λ − excess78977* HD 144548 9.55e-05 0.21 -0.13 0.90 0.10 0 . ± .
15 1 . ± .
53 1.4 no excess*78996 HD 144587 3.24e-04 4.70 13.91 11.09 3.37 2 . ± .
10 4 . ± .
31 3.179054 HD 144729 9.49e-05 1.15 1.09 0.55 0.51 1 . ± .
37 1 . ± .
07 1.5 no excess79156 HD 144981 2.15e-04 4.66 10.36 8.08 3.09 2 . ± .
10 3 . ± .
28 5.979288 HD 145263 1.35e-02 18.25 19.36 19.13 16.29 5 . ± .
08 8 . ± .
15 1.679410 HD 145554 1.76e-04 4.38 12.65 10.87 2.68 2 . ± .
11 4 . ± .
32 6.079439 HD 145631 8.33e-05 1.16 6.31 5.77 1.20 1 . ± .
11 2 . ± .
26 6.479878 HD 146606 7.98e-05 1.72 6.34 5.92 1.01 2 . ± .
22 4 . ± .
59 4.679977 HD 146897 5.21e-03 1.71 15.88 15.25 4.94 24 . ± .
87 89 . ± .
21 1.080024 HD 147010 1.17e-04 1.70 7.70 7.76 2.12 3 . ± .
30 8 . ± .
86 11.680088 HD 147137 3.98e-04 2.41 11.77 14.09 2.90 3 . ± .
16 7 . ± .
36 2.980320 HD 147594 1.37e-04 1.09 4.65 3.22 0.45 1 . ± .
09 2 . ± .
38 1.082218 HD 151376 2.77e-04 0.52 3.21 2.78 0.55 2 . ± .
35 4 . ± .
39 1.2 ∗ HIP 56673 and HIP 78977 are listed twice, the marked listing indicating that the spectrum was normalized to thephotosphere model rather than the MIPS 24 micron measurement.
24 –
3. Debris Disk Modeling
Our modeling of the dust in the debris disks under study goes beyond a simple blackbodymodel. This is because the spectral range covered by IRS includes various silicate features.In order to model the IRS spectra in better detail, we include grain properties such as size,temperature, and composition and generate model spectra using Mie theory.
We assume that the dust is composed of amorphous silicates of olivine and pyroxenecomposition, the optical constants for which are adopted from Dorschner et al. (1995) andJaeger et al. (1994), assuming a Mg : Fe ratio of 1 for both species .In order to calculate equilibrium temperatures, we need the optical constants at shortwavelengths as well. For λ . µ m, we use the optical constants for astronomical silicatesfrom Draine & Lee (1984).The minimum grain size, a min , is estimated by assuming that radiation pressure removesthe smallest grains if β (= F rad /F grav ) > .
5, so that a min > L ∗ h Q pr ( a ) i πGM ∗ cρ s (7)(Artymowicz 1988), where L ∗ and M ∗ are the stellar luminosity and mass, ρ s is the densityof an individual grain, and h Q pr ( a ) i is the spectrum-averaged radiation pressure couplingcoefficient, given by h Q pr ( a ) i = R Q pr ( a, λ ) F λ dλ/ ( R F λ dλ ) . These values are tabulated inChen et al. (2011) for F- and G-type stars, and Chen et al. (2012) for B- and A-type stars.In Table 1 we list the stellar mass and luminosity assumed for modeling the dust for eachsource, and in Table 2, we list the estimated minimum grain size.Chen et al. (2011, 2012) estimated the color temperature of the dust from the the ratioof 24 to 70 micron MIPS photometric excess, and the grain distance calculated assumingthe grains had a temperature equal to the color temperature and a size equal to an averagegrain size of h a i = 5 a min /
3. The IRS spectra provide more detailed information on thetemperature, size, and composition of the dust grains than the MIPS photometry. In thiswork we allow the grain size to be a free parameter. The distribution of grain sizes depends
25 –on the model type implemented, as described in § a min is treated as a lower limit ongrain size.For computational simplicity, we use Mie theory to calculate the optical constants forscattering and absorption of light on particles of different sizes. The main element missingfrom a Mie-theory treatment would be grain porosity, which could result in underestimat-ing the grain sizes and β values (Lisse et al. 1998; Kolokolova et al. 2007, 2001). We usethe Oxford IDL routines to calcuate the optical constants. This generates Q ext ( λ, a ) and Q sca ( λ, a ), the extinction and scattering efficiencies, respectively, as a function of wavelength λ and grain radius a . Then the absorption efficiency is Q abs = Q ext − Q sca . Scattered stellarlight does not contribute significantly at the Spitzer IRS wavelengths, so we consider onlythe thermal component of emission in modeling the spectra. The dust grains are assumed to be heated by stellar irradiation and in thermal equilib-rium. The amount of radiation absorbed by a grain is the incident stellar flux modified bythe absorption efficiency Q abs scaled by the cross-section of the grain. The absorption effi-ciencies of olivine and pyroxene are Q abs o and Q abs p , respectively. The fractional compositionof olivine is f o , so the fractional composition of pyroxene is (1 − f o ). The stellar flux at adistance r from the star is F ν, ∗ = π ( R ∗ /r ) I ν, ∗ ( T eff ). Then the total power absorbed by agrain is P abs = Z ∞ π a Q abs (cid:18) R ∗ r (cid:19) I ν, ∗ ( T eff ) dν (8)where I ν, ∗ is the stellar spectrum, for which we use the best fit Kurucz models.The total emergent power of a grain of radius a and temperature T gr is P emit = Z ∞ π a Q abs B ν ( T gr ) dν (9)where B ν is the Planck function.To find the equilibrium temperature of the grain, we set P emit = P abs and find that Z ∞ Q abs B ν ( T gr ) dν = R ∗ r Z ∞ Q abs I ν, ∗ ( T eff ) dν (10)
26 –The absorption efficiency, Q abs , is itself a function of a and ν , and also depends on thecomposition, as determined from Mie theory and the optical constants of the constituents,namely oliving and pyroxene. We set Q abs equal to the the absorption efficiencies of olivine( Q abs o ) or pyroxene ( Q abs p ), depending on the grain composition. We assume a segregatedspheres distribution for the composition of grains where each grain is either pure olivineor pure pyroxene, and f o and f p are the mass fraction of grains consisting of olivine orpyroxene, respectively. The distance of the grains derived from the grain temperatures issensitive to the composition. For instance, highly reflective grains, such as ices, absorbenergy less efficiently, therefore for the same equilibrium temperature they will be at smallerstellocentric distances compared to more absorptive grains. For olivine and pyroxene, wefind that the differences in distances are not significant. We also find that including a widerrange of compositions, such as crystalline silicates, does not significantly improve fits to themid-IR spectra enough to justify the additional free parameters. Thus, the scope of thiswork is limited to olivine and pyroxene compositions only.To facilitate calculations of equilibrium temperatures, we tabulate values of r versus T gr as a function of a and composition and interpolate on the grid. The equilibrium temperatureof a grain of a given size is a proxy for its distance from the star.We assume that the disks are optically thin, so the total spectrum of the disk is thesummation of the emission of all the grains in the disk. We define n ( a, r ) to be the numberdensity of grains between distance r and r + δr and grain size a and a + δa grain size distri-bution as a function of a and r so that the total number of grains is N = R R n ( a, r ) 2 πr drda and the total mass of the disk is M = Z Z πa ρ d n ( a, r ) 2 πr drda (11)where ρ d is the bulk density of the dust grains (3.3 g/cm ). The emitted spectrum of a singlegrain of radius a at a distance r from the star is π a d Q abs ( a, λ ) B ν [ T gr ( T eff , a, r )]where d is the distance between the observer and the star. Thus, the total integratedspectrum for a distribution of particles in a disk is F ν = Z Z π a d Q abs ( a, λ ) B ν [ T gr ( T eff , a, r )] n ( a, r ) 2 πr drda. (12) 27 – We fit our spectra to two different dust distribution models, allowing grain size, temper-ature/distance, and composition to be free parameters in order to understand the propertiesof the debris disks. The model types were 1) a single uniform grain size with a single tem-perature and composition, and 2) a two grain model where each population has a uniformgrain size, temperature, and composition. In each case, the best fitting size and temperatureparameters are determined by minimizing the reduced χ ν . This was implemented using theIDL routine MPFITFUN. The detailed description of each model follows, including a listingof the free parameters for each model type.1. Single grain model:
This model assumes a population of grains of a uniform singlesize and temperature, as if they were distributed in a ring (or a shell) of uniformradius around the star. The free parameters for this model are the grain radius a ,temperature T gr , and composition ( f o , f p ). The total number of particles N sets theoverall normalization of the spectrum. Since the grain size distribution and stellocentricdistance are delta functions, then the brightness of this model disk assuming a distanceof d is F ν = N πa d (cid:2) f o Q abs o ( a, λ ) + f p Q abs p ( a, λ ) (cid:3) B ν ( T gr ) . (13)This mass of this disk is then M disk = N πa ρ d . (14)Our assumption is that all the grains are at the same temperature. If the absorp-tion efficiencies were to differ greatly between olivine and pyroxene, then the grainswould not be co-located at the same distance from the star. For the grain sizes andtemperature ranges explored, the absorption efficiencies are similar enough that thedust grains are effectively co-located. For typical temperatures and grain sizes in ourfits, the calculated distances between pure olivine and pure pyroxene grains differs by ∼ Two-grain model:
This model is a superposition of two uniform grain populations, each with its ownindependent grain size, temperature, and composition. That is, one ring of grains withgrain radius a , temperature T , composition ( f o , f p ), and number N , plus a secondring with parameters a , T , ( f o , f p ), and N . Then the brightness of this disk modelis F ν = N πa d (cid:2) f o, Q abs o ( a , ν ) + f p, Q abs p ( a , ν ) (cid:3) ( a , ν ) B ν ( T ) 28 –+ N πa d (cid:2) f o, Q abs o ( a , ν ) + f p, Q abs p ( a , ν ) (cid:3) B ν ( T ) . (15)This mass of this disk is then M disk = (cid:18) N πa N πa (cid:19) ρ d (16)
4. Results
For each fit, the grain temperature, grain size, and amorphous silicate compositionare allowed to be free parameters. That is, the single grain model has 4 free parameters(temperature, grain size, olivine:pyroxene ratio, and total mass), and the two-grain modelhas 8 free parameters. Once we have carried out a least-squares fit to the excess spectrumof the single-grain and two-grain population models, as described in section 3.3, we need todetermine which model best describes each object. If the reduced χ ν value is less than 2,then we declare the fit to be reasonable. The resulting fits for the 96 sources analyzed areshown in Tables 3-5. These tables also list the derived stellocentric distance of each grainpopulation, r gr , which is calculated from the fitted grain properties and assumed stellarproperties, according to Equation (10). In Figures 4a-4e, we show these fits to the infraredexcess spectra. In each plot, the photosphere-subtracted spectrum is plotted, along with thebest fit single-grain and two-grain models to the excess spectrum.If the single grain model is a reasonable fit for a given object, then that object isconsidered a single-belt debris system. If the single grain model is not a reasonable fit forthe object but the two-grain model is, then we consider that object a two-belt debris system.Upon visual inspection, we found 10 objects whose formal χ ν values for a single grain modelare less than 2, but have much better fits to the two-grain model, and are best explainedby noisiness of the spectra. We re-categorize these objects as two-belt systems. Similarly,5 objects have formal χ ν greater than 2 for a single grain model, but are not significantlybetter fit by a two grain model, and we re-classify these as single belt systems. An additional11 systems have χ ν for both fits larger than 2, but are mostly well-fit by a two grain model,and we re-categorize them as two belt systems. Most of the objects in the latter two groupshave mismatches at the short wavelength part of the spectrum, which is most affected bythe normalization of the stellar photosphere. HIP 55188 (Figure 4a) is one of the systemsfor which neither model produces a good fit, although it is clear that the two-grain modelproduceds a much better fit than the single-grain model for this particular case. For eachfit, the grain temperature, grain size, and amorphous silicate composition are allowed to befree parameters. (Note: HIP 55188 is well-fit if we include crystalline silicates.) In total, wehave 48 objects that are single-belt systems and 44 that are two-belt systems. 29 – HIP 53524 −3 −2 −1 Jy ∆ ( m Jy ) HIP 55188 −3 −2 −1 Jy ∆ ( m Jy ) HIP 58720 −3 −2 −1 Jy ∆ ( m Jy ) HIP 59282 −3 −2 −1 Jy ∆ ( m Jy ) HIP 59397 −3 −2 −1 Jy ∆ ( m Jy ) HIP 59502 −3 −2 −1 Jy ∆ ( m Jy ) HIP 59898 −3 −2 −1 Jy ∆ ( m Jy ) HIP 60183 −3 −2 −1 Jy ∆ ( m Jy ) HIP 60561 −3 −2 −1 Jy ∆ ( m Jy ) HIP 61684 −3 −2 −1 Jy ∆ ( m Jy ) HIP 61782 −3 −2 −1 Jy ∆ ( m Jy ) HIP 63236 −3 −2 −1 Jy ∆ ( m Jy ) HIP 63839 −3 −2 −1 Jy ∆ ( m Jy ) HIP 64053 −3 −2 −1 Jy ∆ ( m Jy ) HIP 65089 −3 −2 −1 Jy ∆ ( m Jy ) HIP 65965 −3 −2 −1 Jy ∆ ( m Jy ) HIP 66068 −3 −2 −1 Jy ∆ ( m Jy ) HIP 66566 −3 −2 −1 Jy ∆ ( m Jy ) HIP 66447 −3 −2 −1 Jy ∆ ( m Jy ) HIP 68080 −3 −2 −1 Jy ∆ ( m Jy ) Fig. 4a.—
Best fit single grain and two-grain models to photosphere-subtracted infrared spectra.Solid lines indicate a good ( χ ν <
2) fit, while dotted lines indicated a poor fit. The single grain fitis plotted in magenta, and the two-grain fit is plotted in green, with the two components plottedas dashed and dot-dashed lines. The lower panel of each plot shows the residuals after the fit.
30 –
HIP 68781 −3 −2 −1 Jy ∆ ( m Jy ) HIP 70149 −3 −2 −1 Jy ∆ ( m Jy ) HIP 70441 −3 −2 −1 Jy ∆ ( m Jy ) HIP 70455 −3 −2 −1 Jy ∆ ( m Jy ) HIP 71271 −3 −2 −1 Jy ∆ ( m Jy ) HIP 71453 −3 −2 −1 Jy ∆ ( m Jy ) HIP 73145 −3 −2 −1 Jy ∆ ( m Jy ) HIP 73341 −3 −2 −1 Jy ∆ ( m Jy ) HIP 73990 −3 −2 −1 Jy ∆ ( m Jy ) HIP 74752 −3 −2 −1 Jy ∆ ( m Jy ) HIP 75077 −3 −2 −1 Jy ∆ ( m Jy ) HIP 75210 −3 −2 −1 Jy ∆ ( m Jy ) HIP 75509 −3 −2 −1 Jy ∆ ( m Jy ) HIP 76395 −3 −2 −1 Jy ∆ ( m Jy ) HIP 77315 −3 −2 −1 Jy ∆ ( m Jy ) HIP 77317 −3 −2 −1 Jy ∆ ( m Jy ) HIP 77523 −3 −2 −1 Jy ∆ ( m Jy ) HIP 78641 −3 −2 −1 Jy ∆ ( m Jy ) HIP 78756 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79400 −3 −2 −1 Jy ∆ ( m Jy ) Fig. 4b.— Continuation Figure 4a. 31 –
HIP 79631 −3 −2 −1 Jy ∆ ( m Jy ) HIP 80897 −3 −2 −1 Jy ∆ ( m Jy ) HIP 82154 −3 −2 −1 Jy ∆ ( m Jy ) HIP 56673 −3 −2 −1 Jy ∆ ( m Jy ) HIP 57524 −3 −2 −1 Jy ∆ ( m Jy ) HIP 57950 −3 −2 −1 Jy ∆ ( m Jy ) HIP 58220 −3 −2 −1 Jy ∆ ( m Jy ) HIP 58528 −3 −2 −1 Jy ∆ ( m Jy ) HIP 59481 −3 −2 −1 Jy ∆ ( m Jy ) HIP 59693 −3 −2 −1 Jy ∆ ( m Jy ) HIP 59960 −3 −2 −1 Jy ∆ ( m Jy ) HIP 60348 −3 −2 −1 Jy ∆ ( m Jy ) HIP 61049 −3 −2 −1 Jy ∆ ( m Jy ) HIP 61087 −3 −2 −1 Jy ∆ ( m Jy ) HIP 62134 −3 −2 −1 Jy ∆ ( m Jy ) HIP 62427 −3 −2 −1 Jy ∆ ( m Jy ) HIP 62657 −3 −2 −1 Jy ∆ ( m Jy ) HIP 63439 −3 −2 −1 Jy ∆ ( m Jy ) HIP 63836 −3 −2 −1 Jy ∆ ( m Jy ) HIP 63886 −3 −2 −1 Jy ∆ ( m Jy ) Fig. 4c.— Continuation Figure 4a. 32 –
HIP 63975 −3 −2 −1 Jy ∆ ( m Jy ) HIP 64184 −3 −2 −1 Jy ∆ ( m Jy ) HIP 64877 −3 −2 −1 Jy ∆ ( m Jy ) HIP 64995 −3 −2 −1 Jy ∆ ( m Jy ) HIP 65875 −3 −2 −1 Jy ∆ ( m Jy ) HIP 66001 −3 −2 −1 Jy ∆ ( m Jy ) HIP 67068 −3 −2 −1 Jy ∆ ( m Jy ) HIP 67230 −3 −2 −1 Jy ∆ ( m Jy ) HIP 67497 −3 −2 −1 Jy ∆ ( m Jy ) HIP 67970 −3 −2 −1 Jy ∆ ( m Jy ) HIP 69291 −3 −2 −1 Jy ∆ ( m Jy ) HIP 69720 −3 −2 −1 Jy ∆ ( m Jy ) HIP 72070 −3 −2 −1 Jy ∆ ( m Jy ) HIP 73666 −3 −2 −1 Jy ∆ ( m Jy ) HIP 74499 −3 −2 −1 Jy ∆ ( m Jy ) HIP 74959 −3 −2 −1 Jy ∆ ( m Jy ) HIP 75491 −3 −2 −1 Jy ∆ ( m Jy ) HIP 77081 −3 −2 −1 Jy ∆ ( m Jy ) HIP 77432 −3 −2 −1 Jy ∆ ( m Jy ) HIP 77520 −3 −2 −1 Jy ∆ ( m Jy ) Fig. 4d.— Continuation Figure 4a. 33 –
HIP 78043 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79516 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79710 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79742 −3 −2 −1 Jy ∆ ( m Jy ) HIP 78663 −3 −2 −1 Jy ∆ ( m Jy ) HIP 78977 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79054 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79288 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79977 −3 −2 −1 Jy ∆ ( m Jy ) HIP 80320 −3 −2 −1 Jy ∆ ( m Jy ) HIP 82218 −3 −2 −1 Jy ∆ ( m Jy ) HIP 80024 −3 −2 −1 Jy ∆ ( m Jy ) HIP 80088 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79878 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79439 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79410 −3 −2 −1 Jy ∆ ( m Jy ) HIP 79156 −3 −2 −1 Jy ∆ ( m Jy ) HIP 78996 −3 −2 −1 Jy ∆ ( m Jy ) HIP 76310 −3 −2 −1 Jy ∆ ( m Jy ) HIP 77911 −3 −2 −1 Jy ∆ ( m Jy ) Fig. 4e.— Continuation Figure 4a. 34 –Table 3. Fits to single grain model
HIP ID χ ν T gr a gr mass f o r gr (K) ( µ m) ( M moon ) (AU) ‡ HIP 56673 0.93 267 ±
12 7.59 ± ± ± ±
40 198 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
160 1.02e-02 1.00 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
12 2.18e-03 0.80 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
35 –Table 3—Continued
HIP ID χ ν T gr a gr mass f o r gr (K) ( µ m) ( M moon ) (AU)HIP 76395 1.39 306 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
10 8.00e-04 0.00 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ∗ Fits with formal χ ν > Table 4. Fits to two-grain model
HIP ID χ ν T a mass f o, r T a mass f o, r (K) ( µ m) ( M moon ) (AU) (K) ( µ m) ( M moon ) (AU)*HIP 53524 2.76 64.7 ± ± ± ± ±
23 3.32 ± ± ± ± ± ± ± ±
30 3.91 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
26 6.87 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
51 5.09 ± ± ± † HIP 60183 1.34 150 ± ± ± ± ±
56 11 ± ± ± ± ± ± ± ±
24 19.2 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
172 119 ± ± ± ± ± ± ± ± ±
35 2.69 ± ± ± ± ± ± ± ±
140 4.92 ± ± ± † HIP 63886 0.85 69.2 ± ± ± ± ±
21 6.23 ± ± ± † HIP 64184 1.07 99 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
12 17.1 ± ± ± ± ± ± ± ±
20 3.91 ± ± ± ± ± ± ± ±
41 4.08 ± ± ± † HIP 67230 0.27 161 ± ± ± ± ± ± ± ± ± ± ± ± ±
240 6.31 ± ± ± † HIP 68080 1.02 157 ± ± ± ± ±
149 17.8 ± ± ± † HIP 70149 0.85 108 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
14 3.96 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
890 2.43 ± ± ± Table 4—Continued
HIP ID χ ν T a mass f o, r T a mass f o, r (K) ( µ m) ( M moon ) (AU) (K) ( µ m) ( M moon ) (AU) ‡† HIP 74499 0.75 83.7 ± ± ± ± ± ± ± ± ± ± ± ±
14 291 ±
14 4.08 ± ± ± † HIP 75210 0.81 151 ± ±
10 2.51e-02 0.42 ± ± ±
59 4.91 ± ± ± ± ± ± ± ±
12 10.8 ± ± ± † HIP 77315 0.52 153 ± ± ± ± ±
48 7.23 ± ± ± ± ± ± ± ±
35 12.8 ± ± ± ± ± ± ± ±
13 6.05 ± ± ± ± ± ± ± ±
17 2.32 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
10 205 ± ± ± ± ‡ *HIP 80088 2.86 51.7 ± ± ± ±
140 245 ± ± ± ± † HIP 80320 0.84 50.6 ± ± ± ±
68 337 ±
18 2.34 ± ± ± ± ± ± ± ±
16 36.3 ± ± ± ± ± ± ±
19 257 ± ± ± ± ∗ Fits with formal χ ν > † Formally well-fit by a single-grain model, but but appear to be better fit by a two-grain model by visual inspection. ‡ IRS spectra well-fit by a two-grain model, but does not fit the 70 µ m MIPS photometric value. Table 5. Objects not fit well by single or two-grain models
HIP ID χ ν T a mass f o, r T a mass f o, r (K) ( µ m) ( M moon ) (AU) (K) ( µ m) ( M moon ) (AU)HIP 63975one-grain 78.77 478 ± ± ± ± · · · · · · · · · · · · two-grain 49.00 101 ± ± ± ± ±
10 2.5 ± ± ± ± ± ± ± · · · · · · · · · · · · two-grain 138.68 100 ± ± ± ± ± ± ± ±
39 –
HIP 56673* −3 −2 −1 Jy ∆ ( m Jy ) Fig. 5.— Best fitting single grain and two-grain models to HIP 56673, with the photospherefit to the 5-6 micron region of the IRS spectrum. We find that a single component modelbest fits this spectrum.This count does not include HIP 56673 or HIP 78977. As discussed previously, thesesources have excesses similar to Rayleigh-Jeans profiles, consistent with either a photospheremismatch or a hot dust component. If the photosphere is scaled to match the 5-6 micronregion of the IRS spectrum, then HIP 78977 is a non-excess source, and HIP 56673 has amarginal excess that can be modeled well as a single belt. In Figure 5, we show the best fitto HIP 56673, after fitting the photosphere to the IRS spectrum instead of calibrating thephotosphere to optical and near-IR photometry.Two of our targets, HIP 63975 (HD 113766) and HIP 79288 (HD 145263) have highamounts of excess and show evidence of silicate features that cannot be adequately repro-duced with the simple models used in this paper. The mineralogy of HIP 63975 was analyzedin detail in Lisse et al. (2008), and was found to consist of both amorphous and crystallinesilicates, as well as Fe-rich sulfides, amorphous carbon, and water ice. HIP 79288 has asimilarly complex composition, and requires silica in addition to other species to adequatelymodel it (Lisse, et al., in prep).HIP 74499 and HIP 80088 both appear to require at at least two components to fittheir IRS spectra: a large cold component to fit the 20-40 micron region, and a small hot 40 –component to fit the 10 micron region. However, in both these cases, the best fit to the IRSspectrum does not produce enough emission at 70 micron to match the MIPS photometry. Itis likely that these two systems have an additional third cold component that would accountfor the missing 70 micron excess. Both these sources have been classified as two-belt systemsfor further analysis.Recently, a debris belt has been imaged around one of our targets, HIP 64995 (HD115600), with a semi-major axis of ∼
48 AU. (Currie et al. 2015). Our modeling predictsa single belt of debris at a temperature of 114 K, or ∼
11 AU. This belt would be interiorto the inner working angle of the coronagraphic image of the belt detected by Currie et al.(2015). If the outer belt is an analog of the Kuiper belt, then the belt predicted by the mid-infrared spectroscopy would be an asteroid belt analog. This example illustrates how mid-IRspectral analysis is complementary to coronagraphic imaging for studying the structure ofdebris disks.In Figure 6, we show the masses of the dust belts in the single-belt (black) and two-belt(red/blue) debris disk systems. For the two-belt systems, the hot and cold belts are coloredred and blue, respectively. Dust mass appears to be inversely correlated to temperature.This is likely a selection effect, because more cold material must exist in order for it tocontribute significantly to the infrared excess. That is, a lower temperture blackbody emitsless radiation total than a higher temperature one, holding the emitting surface area constant.There does not appear to be a trend in measured dust mass versus stellar mass. This impliesthat the trend that L IR /L ∗ decreases with increasing stellar mass (see Figure 3) is bestexplained by differences in dust temperature (i.e. distance from the system primary) ratherthan differences in measured dust mass.In Figure 7, we summarize the results of our models in terms of the temperaturesand radial distance of the grain populations. In general, the temperatures of the single-beltmodels are intermediate between the hot and cold components of the two-belt models. Thereappears to be more scatter in the hot components for lower stellar masses, which is moreeasily seen in the cumulative distributions in temperature after separating them out into lowmass ( ≤ . M ⊙ , dashed lines) and high mass ( ≥ . M ⊙ , solid lines) stars.The same discrepancy between high-mass and low-mass stars appears in the distributionof radii of the belts, as shown in the right panel of Figure 7. The belt radii are an averagedistance for the olivine and pyroxene components of the grains. The model spectra assumethat the olivine and pyroxene components of the dust all have the same equilibrium temper-atures. The grain properties are similar enough between olivine and pyroxene that grainsof the same temperature are effectively co-located as well, and the radius derived for pureolivine is nearly the same as that of pure pyroxene. Since in many cases the composition is 41 –
100 1000temperature (K)10 du s t m a ss ( g ) sun) du s t m a ss ( g ) Fig. 6.— Dust belt masses versus dust temperature (top) and stellar mass (bottom), for thesingle grain population disks (black) and the two-grain population disks (red/blue). In thetwo-grain population model, the cold component is shown in blue while the hot componentis shown in red. Objects belonging to LCC, UCL, and USco are labeled by asterisks, squares,and diamonds, respectively. 42 – sun) g r a i n t e m pe r a t u r e ( K ) sun) r ad i a l d i s t an c e ( A U )
100 1000grain temperature (K)0.00.20.40.60.81.0 c u m u l a t i v e d i s t r i bu t i on -1 radial distance (AU)0.00.20.40.60.81.0 c u m u l a t i v e d i s t r i bu t i on Fig. 7.— Temperature and radial distribution of grain populations in single belt (black)and two-belt (blue/red) systems. For the two-belt systems, the hot component is plottedin red, the cold component in blue. Top row: T gr (left) and r (right) versus stellar mass.Objects belonging to LCC, UCL, and USco are labeled by asterisks, squares, and diamonds,respectively. Bottom row: Cumulative temperature distribution (left) and radial distribution(right) for the dust components of best fit disk models. The solid lines show stars with mass ≥ . M ⊙ , while the dashed lines show stars with mass ≤ . M ⊙ . 43 –either pure pyroxene or pure olivine, the difference in the distances of the two componentsis insignificant.The grain temperatures of dust around high mass stars are systematically higher thanaround low mass stars. This agrees with the finding in Chen et al. (2014). In Table 6, weshow the results of the Kolmogorov-Smirnov (KS) and Anderson-Darling (AD) statistics fortesting the similarity of the grain temperatures between high and low mass stars. We considerthe single belt systems, the cold component of the two-belt systems, and the hot componentof the two-belt systems separately. The Anderson-Darling test (Anderson & Darling 1954)is arguably a more sensitive statistic than the KS test because it gives more weight to thethe tails of the distributions. To test whether or not two samples X , . . . , X n and Y , . . . , Y m are drawn from the same populations, we can use the two-sample Anderson-Darling statistic,given by A nm = 1 mn N − X i =1 ( M i N − ni ) i ( N − i ) (17)where N = m + n and M i is the number of X ’s less than or equal to the i th smallest elementin the combined sample (Pettitt 1976).The KS test for the single belt systems and the cold component of the two belt systemsgive a 10% and 4% or less probability, respectively, of being drawn from the same popula-tion, while the probability of the hot components being similar is 37%. The AD test givescomparable results: <
5% probabilities for the single belt systems and cold components, buthigher probability of similarity for the hot component ( > < > L IR /L ∗ seen in Figure 3 also supports the idea that lower mass stars havedust at closer radii. This is because the infrared excess luminosity, which is attributed tothe dust, scales as L IR ∝ M d T d , where M d and T d are the total mass and temperature of 44 –the dust, respectively. The temperature of the dust is determined by stellar illumination, as T d ∝ L ∗ /d where d is the stellocentric distance. This gives L IR /L ∗ ∝ M d /R . If M d staysconstant, then the trend that lower mass stars have higher L IR /L ∗ implies that the disks inlower mass stars are more compact.This implies that that the low mass stars retain close-in dust more readily than highmass stars, suggesting that debris disks in high mass stars evolve faster than low mass stars,and that this evolution occurs inside out. One explanation for this is that debris disks evolvefaster in high mass stars because the dynamical times are shorter (Kenyon & Bromley 2008).Another possibility is that the higher mass stars (F-type and earlier) evolve onto the mainsequence sooner. By 15-17 Myr, the ages of LCC and UCL, these stars are already on themain sequence. The ignition of hydrogen burning in these stars could enable the clearingout of inner dust belts at . a min [Eq. (7)]. Still another possibility is that the initial protoplanetary gasdisk differs between high mass and low mass stars.
5. Discussion
The high degree of scatter in the distances of the dust belts indicates that they arenot likely connected to intrinsic properties of the primordial disks from which they arose.Primordial disks generally have continuous radial distributions of material rather than belts.Material could potentially pile up at pressure maxima, for example, but the origin of thepressure maxima depends on stellar properties such as effective temperature and luminosity,which should be relatively stable for a given stellar mass. An example of this phenomenonis the T Tauri object HL Tau, which has been seen to have several gaps in ALMA imagery(ALMA Partnership et al. 2015). Although it is possible that these gaps were created byplanets, locations of the gaps also appear to be co-incident with condensation fronts in thedisk (Zhang et al. 2015). The locations of the fronts are based on the predicted temperatureprofile of the disk, which in turn depends on the heating of the disk from stellar irradiation(see e.g. Kenyon & Hartmann 1987).Alternatively, dust locations could depend on the formation of planets, which is highlystochastic in regard to stellocentric distances. The varying diameters of the inner holes seenin transitional disks are often attributed to planet formation for this reason. Planets couldalso explain the origin of the dust belts after the dissipation of the primordial gas, sinceplanets could be responsible for shepherding the parent bodies that produce the dust. 45 –Stellar companions could also affect the dust belts in our disks. A high fraction of starsin our sample have identified stellar companions. A few stars have directly imaged substellarcompanions that may be distant planets. Since planets and binary companions are likely toplay key roles in the sculpting of debris disks, it is important to put the properties of dustbelts into context with the presence of binarity and the presence of planets.
A number of stars in our sample have been identified to have binary companions(Janson et al. 2013; Chen et al. 2012; Kouwenhoven et al. 2005, 2007). The projected dis-tances of these binary companions are tabulated in Table 7. The distances are calculatedfrom the angular separations from the above references and using Hipparcos stellar distancesfrom van Leeuwen (2007).Stellar companions will truncate a circumstellar disk through tidal interactions. For adebris disk, where gas has little to no dynamical effect, the disk truncation radius can beestimated from the last stable orbit. Assuming a circular orbit, the outermost radius of acircumstellar disk allowed by a binary companion can be expressed as a int = (0 . − . µ ) a (18)and the inner edge of a circumbinary disk is a ext = (1 .
60 + 4 . µ ) a (19)(Holman & Wiegert 1999), where µ is the ratio of the mass of the binary companion to thetotal masses of the two stars, and a is the semi-major axis of the binary orbit.In Figure 8, we show the outer location of the best-fit dust belts versus the binaryseparation for those objects with binary companions. If the dust is best fit with a singlegrain population, then that distance is used. For the remaining systems, the location ofthe outer belt in the two-grain fit is used. We also indicate the disk truncation radius forbinaries with mass ratio 0.5 (equal mass binary) and 0.1 assuming a circular orbit.In all cases, the dust is located interior to the binary separation, so the binary companionmust have truncated the disks in all these systems. A few dust belts appear close to thetruncation radius of a µ = 0 . D p ( D ) A mn p ( A ) † Temperatures . . . single belt 0.33 0.097 2.5 < .
05. . . cold component 0.45 0.045 2.6 < . . . . hot component 0.30 0.37 1.5 > . . . . single belt 0.28 0.22 2.1 < . . . . cold component 0.24 0.65 0.93 > . . . . hot component 0.39 0.12 1.9 < . † Based on tabulations of probabilities in Stephens (1974).Table 7. Projected Distances of Binary CompanionsHIP HD name a (AU) a (AU) a (AU)53524 HD 95086 440.3 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
47 –Fig. 8.— Outer dust belt location versus projected binary separation. The solid line marksthe 1:1 line, so circumstellar disks lie below the solid line while circumbinary disks lie abovethe solid line. The dotted and dashed lines mark the disk truncation radii for an equal-massbinary and a µ = 0 . Three of our sources have been identified to be planet hosts. HIP 53524 (HD 95086)is a binary star (Chen et al. 2012) around which a ∼ M Jup planet has been detected ata projected separation of 56 AU by direct imaging (Rameau et al. 2013). HIP 59960 (HD106906) hosts a very distant planetary-mass companion at a projected separation of ∼ χ ν = 2 .
8) suggests that a few more addition parameters, such as finite belt widths orthe addition of crystalline silicates, could improve the model. It hosts a stellar companionat 440 AU in addition to the imaged planet. The positions of the belts are 42 AU (65 K)and 1.2 AU (413 K), both interior to the projected position of the planet. Since the outerbelt is close to the projected planet distance of 56 AU, it is likely that it is sculpted by theplanet.Herschel images of HIP 53524 marginally resolve the disk, suggesting that the systems 48 –is surrounded by a halo that extends to around 800 AU (Su et al. 2014). That analysisincluded Spitzer/MIPS data and proposed that in addition to the halo, the systems consistsof a warm belt at 175 K and a cold belt at 55 K. The wavelength coverage of Spitzer doesnot provide much sensitivity to emission from the cold halo, but the 55 K belt is consistentwith the model for HIP 53524 presented here. Our model predicts a hotter inner belt, whichmay be a result of not including the third coldest dust distribution that is inferred from theHerschel data.In our analysis, HIP 59960 is well-fit by a single dust belt at 12 AU, and its reportedplanetary companion (Bailey et al. 2014) is so distant that it does not interact with the dust.It is possible that additional unseen companions exist between the belt and the planetarycompanion and that those companions could shephered the dust.HIP 73990 is best fit to a two-belt model with grain temperatures of 1440 K and 166K, corresponding to distances of 0.17 and 6.6 AU, respectively. Assuming that planets areable to clear material out to the 2:1 mean motion resonance, then the inner planet imagedat 20 AU (Hinkley et al. 2015) should truncate the debris disk to 12.6 AU. Both dust beltsdetected from our spectroscopic modeling are interior to this distance.Additional objects in ScoCen that have detected sub-stellar companions include HIP78530, which exhibits no infrared excess; GSC 06214-00210, an accreting T Tauri star; and1RXS J160929.1-210524. (Bailey et al. 2013). These objects were not included in our studybecause they are pre-main sequence stars and their disks are protoplanetary in nature.Although imaging planets around debris disk systems can help us understand the rolethat planets play in sculpting debris disks, few such planet images exist. On the other hand,many debris disks are well-studied. We can turn the question around, then, and ask what canbe learned about planet formation from debris disks. Dynamical interactions with planetsshould sculpt and shephered debris disks. Therefore, debris disks with structure, such asgaps, can imply the presence of unseen planets.Numerical simulations have shown that a companion orbiting in a disk can create gapsvia planetesimal scattering in overlapping resonances (e.g., Roques et al. 1994; Lecavelier des Etangs et al.1996). The width of the gap is related to the mass of the companion by a power law (e.g.,Quillen 2006; Chiang et al. 2009; Rodigas et al. 2014), the parameters of which depend onthe age of the system and the optical depth of the disk (Nesvold & Kuchner 2014).Following the procedure described in Nesvold & Kuchner (2014), we analyzed the two-belt systems in our sample to place upper limits on the mass of a possible single perturbingcompanion in each system. In each case, we assumed that a single body on a circular orbitequidistant in log semimajor axis between the two dust bands has cleared the gap between 49 –the bands. We used L IR /L ⋆ as a proxy for the face-on optical depth of each disk.Nesvold & Kuchner (2014) found that the largest gap size that a single body on acircular orbit can create has a full width of ∆ r/r = 1 .
6. Larger bodies tend to stir the disk;destroying it and widening it, while roughly preserving the gap edge near the location of the2:1 mean motion resonance. Nine disks in our sample had gaps narrower than this maximumwidth. Table (8) summarizes inferred companion masses and semimajor axes for these ninedisks.Five of these systems, HIP 61684, HIP 66068, HIP 78641, HIP 65875, and HIP 79516,have small enough gaps that they require a single perturbing body whose mass is in the rangeof planet masses. The other disks require either planets on eccentric orbits, companions inthe brown-dwarf mass range or multiple planets. The inferred companions in these systemsare all located within 0.2 arcseconds of their host stars, probably too close to detect directlywith today’s instruments. However, future observatories, such as WFIRST-AFTA, may beable to resolve sub-stellar companions at angular separations of less than 0.2 ′′ . In addition,the next generation of large aperture ground-based telescopes, such as GMT, TMT, or E-ELT, could have the necessary resolving power and inner working angle. ATLAST, currentlya NASA strategic mission concept study, could also detect these planets.HIP 82154 also has a binary companion at a projected distance of 1869 AU (see Table8). This companion is probably too distant to have any dynamical effect on the dust beltsor any planet located between them.Six out of the nine inferred companions listed in Table (8) have estimated semimajoraxes within 5 ± M Jup )60561 5.4 28.861684 6.4 12.265089 22.9 33.166068 5.9 10.466566 4.2 15.378641 3.7 9.882154 28.7 42.965875 7.7 1.179516 15.3 0.8 50 –
HIP 60561 HIP 61684 HIP 65089HIP 66068HIP 66566HIP 78641 HIP 82154HIP 65875 HIP 79516 P l ane t M a ss ( M J up ) Fig. 9.— Maximum companion mass vs. estimated companion semimajor axis for the ninecompanions inferred from the disk gaps. The bars indicate the widths of the gaps betweenbelts.with statistics of exoplanets showing that, apart from hot Jupiters, the number of exoplanetsincreases toward orbital separations larger than 1 AU. 51 –
6. Conclusions
Constraining our study of debris disks to those in ScoCen gives us the advantage ofexamining a cohort of debris disks of similarly young age. Within this sample, we findevidence of mass-dependent evolution of the hot dust. In particular, in systems with twobelts, low mass stars have closer inner belts than high mass stars. This implies that highmass stars have less hot dust than low mass stars. This could be related to the fasterevolution times of the higher mass stars, which results in higher mass stars reaching themain sequence sooner than the less massive stars. Then the lack of hot dust could beexplained by the clearing of the dust from the inside out as the star evolves.We explored how stellar and sub-stellar companions could sculpt debris disks. Many ofthe objects in our sample have known binary companions. We find that the dust distancesfrom our models predict circumstellar disks rather than circumbinary disks. However, be-cause the binaries are generally wide, and our data is limited to infrared wavelengths, ourobservations are not sensitive to any thermal emission that might come from circumbinarydisks. The dust distances are consistent with disk truncation at outer radii by the binarycompanion.Two of our objects host known planets. These planets have been detected by directimaging, so they are distant planets outside the dust disks. The fact that the planets thathave been discovered in ScoCen also host debris disks suggest that debris disks and planetformation are correlated. Planets can also sculpt debris disks, and we use this fact to considerthe possibility that our disks might host planets.The locations of dust belts can put constraints on the locations of planets since theyshould clear out gaps in the disks. The two-belt systems found in our study could be theresult of one or several planets carving out gaps. If the distance ratios are small, then thelocation and mass of the potential planet can be narrowly constrained. These systems areparticularly good targets for follow-up planet searches.Wider gaps could be created by multiple planets or eccentric orbits. These are also goodtargets for follow-up, although predictions about planet propeties are less well-constrained.This work is based on observations made with the Spitzer Space Telescope, which isoperated by JPL/Caltech under a contract with NASA. Support for this work was providedby NASA through an award issued by JPL/Caltech. HJ-C acknowledges support from NASAgrant NNX12AD43G. 52 –
REFERENCES
ALMA Partnership, Brogan, C. L., Perez, L. M., Hunter, T. R., Dent, W. R. F., Hales, A. S.,Hills, R., Corder, S., Fomalont, E. B., Vlahakis, C., Asaki, Y., Barkats, D., Hirota,A., Hodge, J. A., Impellizzeri, C. M. V., Kneissl, R., Liuzzo, E., Lucas, R., Marcelino,N., Matsushita, S., Nakanishi, K., Phillips, N., Richards, A. M. S., Toledo, I., Aladro,R., Broguiere, D., Cortes, J. R., Cortes, P. C., Espada, D., Galarza, F., Garcia-Appadoo, D., Guzman-Ramirez, L., Humphreys, E. M., Jung, T., Kameno, S., Laing,R. A., Leon, S., Marconi, G., Mignano, A., Nikolic, B., Nyman, L.-A., Radiszcz, M.,Remijan, A., Rodon, J. A., Sawada, T., Takahashi, S., Tilanus, R. P. J., Vila Vilaro,B., Watson, L. C., Wiklind, T., Akiyama, E., Chapillon, E., de Gregorio-Monsalvo, I.,Di Francesco, J., Gueth, F., Kawamura, A., Lee, C.-F., Nguyen Luong, Q., Mangum,J., Pietu, V., Sanhueza, P., Saigo, K., Takakuwa, S., Ubach, C., van Kempen, T.,Wootten, A., Castro-Carrizo, A., Francke, H., Gallardo, J., Garcia, J., Gonzalez,S., Hill, T., Kaminski, T., Kurono, Y., Liu, H.-Y., Lopez, C., Morales, F., Plarre,K., Schieven, G., Testi, L., Videla, L., Villard, E., Andreani, P., Hibbard, J. E., &Tatematsu, K. 2015, ArXiv e-printsAnderson, T. W. & Darling, D. A. 1954, Journal of the American Statistical Association,49, pp. 765Artymowicz, P. 1988, ApJ, 335, L79Aumann, H. H. 1984, in Bulletin of the American Astronomical Society, Vol. 16, Bulletin ofthe American Astronomical Society, 483Backman, D. E. & Paresce, F. 1993, in Protostars and Planets III, ed. E. H. Levy & J. I.Lunine, 1253–1304Bailey, V., Hinz, P. M., Currie, T., Su, K. Y. L., Esposito, S., Hill, J. M., Hoffmann, W. F.,Jones, T., Kim, J., Leisenring, J., Meyer, M., Murray-Clay, R., Nelson, M. J., Pinna,E., Puglisi, A., Rieke, G., Rodigas, T., Skemer, A., Skrutskie, M. F., Vaitheeswaran,V., & Wilson, J. C. 2013, ApJ, 767, 31Bailey, V., Meshkat, T., Reiter, M., Morzinski, K., Males, J., Su, K. Y. L., Hinz, P. M.,Kenworthy, M., Stark, D., Mamajek, E., Briguglio, R., Close, L. M., Follette, K. B.,Puglisi, A., Rodigas, T., Weinberger, A. J., & Xompero, M. 2014, ApJ, 780, L4Bitner, M. A., Chen, C. H., Muzerolle, J., Weinberger, A. J., Pecaut, M., Mamajek, E. E.,& McClure, M. K. 2010, ApJ, 714, 1542Cannon, A. J. & Pickering, E. C. 1920, Annals of Harvard College Observatory, 95, 1 53 –Carpenter, J. M., Bouwman, J., Mamajek, E. E., Meyer, M. R., Hillenbrand, L. A., Backman,D. E., Henning, T., Hines, D. C., Hollenbach, D., Kim, J. S., Moro-Martin, A.,Pascucci, I., Silverstone, M. D., Stauffer, J. R., & Wolf, S. 2009a, ApJS, 181, 197Carpenter, J. M., Bouwman, J., Silverstone, M. D., Kim, J. S., Stauffer, J., Cohen, M.,Hines, D. C., Meyer, M. R., & Crockett, N. 2008, ApJS, 179, 423Carpenter, J. M., Mamajek, E. E., Hillenbrand, L. A., & Meyer, M. R. 2009b, ApJ, 705,1646Chen, C. H., Li, A., Bohac, C., Kim, K. H., Watson, D. M., van Cleve, J., Houck, J.,Stapelfeldt, K., Werner, M. W., Rieke, G., Su, K., Marengo, M., Backman, D., Be-ichman, C., & Fazio, G. 2007, ApJ, 666, 466Chen, C. H., Mamajek, E. E., Bitner, M. A., Pecaut, M., Su, K. Y. L., & Weinberger, A. J.2011, ApJ, 738, 122Chen, C. H., Mittal, T., Kuchner, M., Forrest, W. J., Lisse, C. M., Manoj, P., Sargent,B. A., & Watson, D. M. 2014, ApJS, 211, 25Chen, C. H., Pecaut, M., Mamajek, E. E., Su, K. Y. L., & Bitner, M. 2012, ApJ, 756, 133Chen, C. H., Sheehan, P., Watson, D. M., Manoj, P., & Najita, J. R. 2009, ApJ, 701, 1367Chiang, E. I., Kite, E. S., Kalas, P., Graham, J. R., & Clampin, M. 2009, ApJ, 693, 734Corbally, C. J. 1984, ApJS, 55, 657Currie, T., Lisse, C. M., Kuchner, M. J., Madhusudhan, N., Kenyon, S. J., Thalmann, C.,Carson, J., & Debes, J. H. 2015, ArXiv e-printsDahm, S. E. & Carpenter, J. M. 2009, AJ, 137, 4024de Zeeuw, P. T., Hoogerwerf, R., de Bruijne, J. H. J., Brown, A. G. A., & Blaauw, A. 1999,AJ, 117, 354Dorschner, J., Begemann, B., Henning, T., Jaeger, C., & Mutschke, H. 1995, A&A, 300, 503Draine, B. T. & Lee, H. M. 1984, ApJ, 285, 89Engelbracht, C. W., Blaylock, M., Su, K. Y. L., Rho, J., Rieke, G. H., Muzerolle, J., Padgett,D. L., Hines, D. C., Gordon, K. D., Fadda, D., Noriega-Crespo, A., Kelly, D. M.,Latter, W. B., Hinz, J. L., Misselt, K. A., Morrison, J. E., Stansberry, J. A., Shupe,D. L., Stolovy, S., Wheaton, W. A., Young, E. T., Neugebauer, G., Wachter, S.,P´erez-Gonz´alez, P. G., Frayer, D. T., & Marleau, F. R. 2007, PASP, 119, 994 54 –Gahm, G. F., Ahlin, P., & Lindroos, K. P. 1983, A&AS, 51, 143Glaspey, J. W. 1972, AJ, 77, 474Hiltner, W. A., Garrison, R. F., & Schild, R. E. 1969, ApJ, 157, 313Hinkley, S., Kraus, A. L., Ireland, M. J., Cheetham, A., Carpenter, J. M., Tuthill, P., Lacour,S., Evans, T. M., & Haubois, X. 2015, ArXiv e-printsHolman, M. J. & Wiegert, P. A. 1999, AJ, 117, 621Houk, N. 1978, Michigan Catalogue of Two-dimensional Spectral Types for the HD stars.Volume II. (Ann Arbor, MI: Univ. of Michigan)—. 1982, Michigan Catalogue of Two-dimensional Spectral Types for the HD stars. Volume3. (Ann Arbor, MI: Univ. of Michigan)Houk, N. & Cowley, A. P. 1975, University of Michigan Catalogue of Two-dimensionalSpectral Types for the HD stars. Volume I. (Ann Arbor, MI: Univ. of Michigan)Houk, N. & Smith-Moore, M. 1988, Michigan Catalogue of Two-dimensional Spectral Typesfor the HD Stars. Volume 4. (Ann Arbor, MI: Univ. of Michigan)Hube, D. P. 1970, MmRAS, 72, 233Jaeger, C., Mutschke, H., Begemann, B., Dorschner, J., & Henning, T. 1994, A&A, 292, 641Janson, M., Lafreni`ere, D., Jayawardhana, R., Bonavita, M., Girard, J. H., Brandeker, A.,& Gizis, J. E. 2013, ApJ, 773, 170Kenyon, S. J. & Bromley, B. C. 2004, AJ, 127, 513—. 2008, ApJS, 179, 451Kenyon, S. J. & Hartmann, L. 1987, ApJ, 323, 714K¨ohler, R., Kunkel, M., Leinert, C., & Zinnecker, H. 2000, A&A, 356, 541Kolokolova, L., Jockers, K., Gustafson, B. ˚A. S., & Lichtenberg, G. 2001, J. Geophys. Res.,106, 10113Kolokolova, L., Kimura, H., Kiselev, N., & Rosenbush, V. 2007, A&A, 463, 1189Kouwenhoven, M. B. N., Brown, A. G. A., Portegies Zwart, S. F., & Kaper, L. 2007, A&A,474, 77 55 –Kouwenhoven, M. B. N., Brown, A. G. A., Zinnecker, H., Kaper, L., & Portegies Zwart,S. F. 2005, A&A, 430, 137Kunkel, M. 1999, PhD thesis, Julius-Maximilians-Universit¨at W¨urzburgKurucz, R. L. 1979, ApJS, 40, 1Lagrange, A.-M., Bonnefoy, M., Chauvin, G., Apai, D., Ehrenreich, D., Boccaletti, A.,Gratadour, D., Rouan, D., Mouillet, D., Lacour, S., & Kasper, M. 2010, Science, 329,57Lebouteiller, V., Barry, D. J., Spoon, H. W. W., Bernard-Salas, J., Sloan, G. C., Houck,J. R., & Weedman, D. W. 2011, ApJS, 196, 8Lecavelier des Etangs, A., Scholl, H., Roques, F., Sicardy, B., & Vidal-Madjar, A. 1996,Icarus, 123, 168Lisse, C. M., A’Hearn, M. F., Hauser, M. G., Kelsall, T., Lien, D. J., Moseley, S. H., Reach,W. T., & Silverberg, R. F. 1998, ApJ, 496, 971Lisse, C. M., Chen, C. H., Wyatt, M. C., & Morlok, A. 2008, ApJ, 673, 1106Macintosh, B., Graham, J. R., Ingraham, P., Konopacky, Q., Marois, C., Perrin, M., Poyneer,L., Bauman, B., Barman, T., Burrows, A., Cardwell, A., Chilcote, J., De Rosa, R. J.,Dillon, D., Doyon, R., Dunn, J., Erikson, D., Fitzgerald, M., Gavel, D., Goodsell, S.,Hartung, M., Hibon, P., Kalas, P. G., Larkin, J., Maire, J., Marchis, F., Marley, M.,McBride, J., Millar-Blanchaer, M., Morzinski, K., Norton, A., Oppenheimer, B. R.,Palmer, D., Patience, J., Pueyo, L., Rantakyro, F., Sadakuni, N., Saddlemyer, L.,Savransky, D., Serio, A., Soummer, R., Sivaramakrishnan, A., Song, I., Thomas, S.,Wallace, J. K., Wiktorowicz, S., & Wolff, S. 2014, ArXiv e-printsMamajek, E. E., Meyer, M. R., & Liebert, J. 2002, AJ, 124, 1670Manoj, P., Bhatt, H. C., Maheswar, G., & Muneer, S. 2006, ApJ, 653, 657Marley, M. S., Fortney, J. J., Hubickyj, O., Bodenheimer, P., & Lissauer, J. J. 2007, ApJ,655, 541Marois, C., Zuckerman, B., Konopacky, Q. M., Macintosh, B., & Barman, T. 2010, Nature,468, 1080Mart´ın, E. L. 1998, AJ, 115, 351 56 –Meng, H. Y. A., Su, K. Y. L., Rieke, G. H., Stevenson, D. J., Plavchan, P., Rujopakarn, W.,Lisse, C. M., Poshyachinda, S., & Reichart, D. E. 2014, Science, 345, 1032Morgan, W. W., Abt, H. A., & Tapscott, J. W. 1978, Revised MK Spectral Atlas for starsearlier than the sun (Williams Bay: Yerkes Observatory, and Tucson: Kitt PeakNational Observatory)Nesvold, E. R. & Kuchner, M. J. 2014, ApJ, submittedOkamoto, Y. K., Kataza, H., Honda, M., Yamashita, T., Onaka, T., Watanabe, J.-i., Miyata,T., Sako, S., Fujiyoshi, T., & Sakon, I. 2004, Nature, 431, 660Pecaut, M. J., Mamajek, E. E., & Bubar, E. J. 2012, ApJ, 746, 154Pettitt, A. N. 1976, Biometrika, 63, 161Preibisch, T., Brown, A. G. A., Bridges, T., Guenther, E., & Zinnecker, H. 2002, AJ, 124,404Preibisch, T., Guenther, E., Zinnecker, H., Sterzik, M., Frink, S., & Roeser, S. 1998, A&A,333, 619Preibisch, T. & Mamajek, E. 2008, The Nearest OB Association: Scorpius-Centaurus (ScoOB2), ed. Reipurth, B., 235Preibisch, T. & Zinnecker, H. 1999, AJ, 117, 2381Quillen, A. C. 2006, MNRAS, 372, L14Rameau, J., Chauvin, G., Lagrange, A.-M., Meshkat, T., Boccaletti, A., Quanz, S. P., Currie,T., Mawet, D., Girard, J. H., Bonnefoy, M., & Kenworthy, M. 2013, ApJ, 779, L26Rodigas, T. J., Malhotra, R., & Hinz, P. M. 2014, ApJ, 780, 65Roques, F., Scholl, H., Sicardy, B., & Smith, B. A. 1994, Icarus, 108, 37Schild, R. E., Neugebauer, G., & Westphal, J. A. 1971, AJ, 76, 237Slesnick, C. L., Carpenter, J. M., & Hillenbrand, L. A. 2006, AJ, 131, 3016Stephens, M. A. 1974, Journal of the American Statistical Association, 69, pp. 730Sturm, B., Bouwman, J., Henning, T., Evans, N. J., Waters, L. B. F. M., van Dishoeck,E. F., Green, J. D., Olofsson, J., Meeus, G., Maaskant, K., Dominik, C., Augereau,J. C., Mulders, G. D., Acke, B., Merin, B., & Herczeg, G. J. 2013, A&A, 553, A5 57 –Su, K. Y., Morrison, S. J., Malhotra, R., Balog, Z., & Smith, P. S. 2014, in AAS/Division forPlanetary Sciences Meeting Abstracts, Vol. 46, AAS/Division for Planetary SciencesMeeting Abstracts,