There are compelling reasons to search for companions to nearby stars. In particular, the properties of binary systems provide important clues to their formation processes. Any successful model of star formation must be able to account for both the frequency of multiple star systems and their properties (separation, eccentricity and so forth) – as well as variations in those properties as a function of system mass. In addition, the orbits of binary systems provide us with the means to directly measure the mass of each component in the system. This is fundamental to the calibration of the mass-luminosity relation (MLR: Henry & McCarthy 1993; Henry et al. 1999; Ségransan et al. 2000).
The stellar multiplicity fraction appears to decrease with decreasing primary mass (eg. Siegler et al. 2005). Around 57% of solar-type stars (F7–G9) have known stellar companions (Abt & Levy, 1976; Duquennoy & Mayor, 1991), while imaging and radial velocity surveys of early M dwarfs suggest that between 25% & 42% have companions (Henry & McCarthy, 1990; Fischer & Marcy, 1992; Leinert et al., 1997; Reid & Gizis, 1997). Later spectral types have been studied primarily with high resolution adaptive optics imaging: Close et al. 2003 and Siegler et al. 2005 find binary fractions of around 10–20% for primary spectral types in the range M6–L1. Bouy et al. 2003 and Gizis et al. 2003 find that 10–15% of L dwarfs have companions, and Burgasser et al. 2003 find that 10% of T dwarfs have binaries. These very low mass (VLM) M, L and T systems appear to have a tighter and closer distribution of orbital separations, peaking at around 4 AU compared to 30 AU for G dwarfs (Close et al., 2003).
However, each of these surveys have inevitably different (and hard to quantify) sensitivities, the effect of which is especially evident in the large spread in the derived multiplicity of early M-dwarfs. In particular, high-resolution imaging surveys are sensitive only to companions wider than ~0.1” while radial velocity surveys are much more sensitive to closer (shorter period) companions. Maxted & Jeffries (2005), by examining a small sample of radial velocity measurements, estimate that accounting for systems with orbital radius <3 AU could increase the overall observed VLM star/BD binary frequency to 32–45%. Basri & Reiners (2006) also find that taking into account spectroscopic binaries doubles the binary fraction (in a more heterogenous sample of VLM stars and brown dwarfs).
The orbital radius distribution of VLM binary systems is also quite uncertain (figure 6.1). A well-constrained peak is found at around 4 AU, but several systems have been found at much wider radii. It is important to enlarge the sample of VLM binaries to ascertain how common these wide systems are, and whether they form a separate population of large-radius systems or are simply the tail of the distribution which peaks at 4 AU.
For these reasons, we decided to use LuckyCam to target several well-understood samples of low-mass and very low mass stars. The surveys have the aim of both increasing the known number of VLM binary systems (and finding more exotic systems such as triples and substellar companions), and constraining the binary statistics in a number of different samples.
In this thesis, I define VLM stars to have a V-K colour of >6 (M5 and later, Leggett (1992)) and therefore a mass of < 0.11M⊙, following the stellar models described in Baraffe et al. (1998) for ages >2 Gyr. The distinction between VLM and low mass stars is somewhat arbitrary, and some authors (eg. Burgasser et al. (2006)) would place the cut-off at the slightly lower primary mass of 0.10M⊙ .
VLM binary stars are an excellent example of a science programme which cannot be performed with seeing-limited instruments. Figure 6.1 shows the distribution of the orbital radii of known VLM binaries as of 2005 (prior to the LuckyCam survey). Only 45 VLM binaries were known (the figure at the time of writing is only on the order of 80, spanning a wide range of system total mass, mass ratios and separations). Almost all are at smaller orbital radii than 10AU.
|
|
Generating a larger sample of VLM binaries for statistical studies of the nature of these systems, the aim of the LuckyCam survey and others like it, requires including target stars up to a sufficiently large distance from the Sun that a large number of M-dwarfs are within the survey volume. As figure 6.1 shows, at 10pc distance almost all VLM binaries have separations smaller than 1.0 arcsec, and 60% are at separations smaller than 0.5 arcsec. Essentially all the stars within 10pc have been surveyed for close companions; significantly extending the VLM binary sample thus requires observations with consistently better than 0.5 arcsec resolution if any large number of new systems are to be resolved. Detailed studies of the nature of the systems and the measurement of accurate astrometry requires still higher resolution. A high-resolution imaging system, capable of around 0.1 arcsec resolution, is thus required.
VLM binary surveys have been pursued using HST (eg. Bouy et al. (2003); Gizis et al. (2003)) and AO (eg. Close et al. (2003); Siegler et al. (2005)) systems. Obtaining time for an extensive survey using HST is difficult, given the popularity of the telescope. Adaptive optics surveys can be very time intensive, as each of the tens-to-hundreds of targets requires a separate re-lock of the AO systems. For example, the NAOS-CONICA AO system on the VLT requires 5-10 minutes for AO acquisition per target before data can be taken (VLT NAOS-CONICA User Manual* , 2006). Furthermore, the M-dwarfs in question are very red objects, and are thus faint in the visible wavelengths used by most AO systems for wavefront sensing (NAOS-CONICA has both visible and infrared WFSs).
LuckyCam offers capabilities that make it an excellent instrument for VLM binary surveys. It is a completely passive system, so data is taken as soon as the telescope is pointed. A complete observation of a candidate VLM binary target usually takes 6-7 minutes, including telescope pointing, target finding and 100 second integrations in two filters. The faint guide star capabilities of LuckyCam also allow observations of M-dwarfs that are fainter than most AO systems can use (apart from those with infrared wavefront sensors, as these objects are very red). For example, the binaries newly discovered with LuckyCam in chapter 7 are all fainter than the previously known ones in the same sample of targets.
In this chapter I present results from a 32-star VLM binary sample, completed in only 5 hours of on-sky time. I present five new VLM binaries and evaluate the utility of LuckyCam for programmes of this type, including the use of calibrated high-spatial resolution photometry.
|
|
![]() |
We selected a distance, flux and colour limited sample of stars from the LSPM-North Catalogue (Lépine & Shara, 2005), which is the result of a systematic search for stars with declination > 0 and proper motion > 0.15”/year in the Digitized Sky Surveys. Most stars in the catalogue have 2MASS IR photometry as well as V-band magnitudes estimated from the photographic BJ and RF bands.
The selection of high-proper-motion stars ensures that the stars are nearby. Historically, the vast majority of stars now known to be in the solar neighbourhood were first identified as high-proper-motion stars (Lépine, 2005). However, stars with motion vectors pointing towards or away from the sun are not detected, and some distant stars can have large proper motions if their relative velocity is also large, such as stars on Galactic halo orbits (Lépine, 2005). For this reason, to construct a well-defined sample, I use colour, magnitude and photometric distance cuts to narrow down the parameter space of the targets. Giant stars are excluded by the proper motion and magnitude cut, because even halo stars, with velocities typically 2-5× larger than disk objects, are only likely to be 2-5× more distant than the rest of the candidates (Lépine & Shara, 2005).
Lépine (2005) finds that the census of nuclear-burning stars within 33pc is ~68% complete in the LSPM (and 82% complete within 25pc), where the main source of incompleteness is the lower proper motion limit. High-velocity stars (halo, old disk) tend to be selected from a larger distance, and may thus bias the sample (Lépine & Shara, 2005). However, in both the survey presented in this chapter and that in chapter 7 we select stars which are significantly brighter than the V=+19.0m 90% completeness limit of the LSPM North survey (figure 6.2), excluding the more distant population of high-velocity stars.
The properties of the selected stars are detailed below:
The remaining sample consists of 91 stars in the R.A. and declination range that was accessible during the survey period (June 2005). 32 were selected for these observations (picking the brightest targets first, as well as those close to the zenith during the observations), and are detailed in table 6.1. The region of colour-magnitude space in which they are found is shown in figure 6.2; the distributions of magnitudes and colours are detailed in figure 6.3.
The V-band LSPM photometry has been estimated from observations in the photographic BJ and RF bands (as detailed in Lépine & Shara 2005), and its use therefore requires some caution. To test its utility for late M-dwarf target selection I have confirmed that a sample of spectroscopically confirmed late M-dwarfs (Cruz et al., 2003) is fully recovered by the V-K selection (figure 6.2). In addition, LuckyCam resolved SDSS i’ and z’ photometry gives confirmation of estimated spectral type for the objects in the full survey. In all checked cases the spectral type and distance estimated from LSPM-North V-K photometry matches that derived from LuckyCam SDSS i’ and z’ photometry. The LSPM V & K photometry is used extensively in the survey described in chapter 7, where more detailed checks on its accuracy are made.
We performed observations with the Cambridge Lucky Imaging system, LuckyCam, on the 2.56m Nordic Optical Telescope in June 2005, during 5 hours of on-sky time spread over 4 night observing run. Each target was observed for 100 seconds in each of the SDSS i’ and z’ filters. SDSS standard stars (Smith et al. 2002) were observed for photometric calibration; globular clusters and similar fields were imaged for astrometric calibration. The seeing measured by the Isaac Newton Group RoboDIMM at the observatory site varied between 0.5” and 1.0” during the observations, with a median of ~ 0.8”.
Each target observation was completed in an average of 10 minutes including telescope pointing, 100 seconds of integration in each filter, the observation of one standard star for every three targets, and all other overheads.
|
For this survey we operated LuckyCam at 30 frames per second, with each frame being 552x360 pixels. The image scale was 0.04~/pixel, giving a field of view of 22×14.4 arcseconds2. The observations totalled approximately 100GB. The dataset was reduced with the standard Lucky Imaging pipeline (chapter 3).
Obvious binaries with a low contrast ratio and/or > 0.5” separation were detected by eye in reduced images including <= 10% of frames. I limited the companion detection radius to 1.5”, allowing use of the remainder of the 20”x14” fields as control areas. Because the chance probability of an object falling within the small detection radius is very low, any detections are likely to be physically associated with the target star.
In order to detect fainter companions I fit and subtract a model Moffat profile point spread function (see chapters 4 and 5) to each target, using 50% of the recorded frames to increase the SNR of faint companions at the expense of some resolution. Candidate companions were detected using a sliding-box method, with custom software implementing the detection criteria.
We stipulated the detection of a faint companion to require a 10σ deviation above the background noise, which is due to both photon and speckle noise and varies with distance from the primary star. The background noise at each radius was specified to be the upper 1σ excursion from the average RMS noise at several azimuthal positions.
In addition, I implemented the following criteria to confirm the detection of faint companions:
I measured resolved flux measurements and errors for binaries wider than 0.4” with simple aperture photometry. However, at closer radii more sophisticated strategies were required, especially since four of the five detected binaries had primaries fainter than i’=15m. As detailed in chapter 5, if a Lucky Imaging guide star is faint, its PSF is altered by frame selection proceeding partially on the basis of high excursions of photon-shot-noise. Since the companion and primary now have different PSFs, point spread function subtraction is difficult (although possible with sufficiently similar calibrator binary observations). The closest binary detected in these observations was sufficiently bright to avoid these problems, however.
Extensive experimentation confirmed that simple aperture photometry also provides accurate flux measurements at close radii for Lucky Imaging PSFs, provided that care is taken in the choice of foreground and background aperture sizes. The contrast ratios of the two close binaries with relatively faint primaries were reduced in this manner. The accuracy and precision of the derived contrast ratios was measured by repetition over several different frame selection fractions (and thus several different PSFs). The accuracy of the algorithms was also checked against simulated binary images. Note that these reductions were performed before the development of the more sophisticated PSF fitting routines described in chapter 5 and used in chapter 7.
|
|
|
|
|
|
For this survey, I measured photometry in the SDSS system from the total integrated flux in a 3” radius aperture, calibrated against SDSS standards (Smith et al. 2002, figure 6.4). I then used the measured contrast ratios to derive resolved photometry. In each observation the L3CCD gain is calibrated as described in chapter 2. The calibrated magnitudes are then calculated as:
![]() | (6.1) |
where the raw photometry is given in data numbers (DN) per second, gain is measured in photons per DN, and ZP is the photometric zero point of the system. Airmass corrections are not calculated because all observations were performed within 30o of the zenith; the approximately 10% uncertainty in the L3CCD gain calibration dominated the remaining errors.
Beyond 1.0” radius from the primary detection sensitivity is primarily limited by the sky background; at smaller radii both azimuthal variations in the target star’s PSF and its photon shot noise limit the detection sensitivity. The SDSS i’ detection contrast ratios for two typical stars are shown in figure 6.5 and example faint companion simulated PSFs are shown in figure 6.6.
The survey is sensitive to the detection of brown dwarf companions around all the surveyed stars. For example, around a star with mi ≤ 14, the survey is sensitive to