Identifying Candidate Variables with Phoenix

Stellar jitter is well known to increase with stellar rotation. As well as having faster rotation than older stars of similar spectral type, young stars show significant stellar jitter due to increased chromospheric activity (Campbell et al. 1991; Bailey et al. 2012). By comparing the standard deviation of the epoch RV for each star with the measured vsini values, we can produce an empirical estimate of the expected activity induced variability. We note that there is no standard prescription for identifying companion-induced RV variation for young stars. As such, we investigate the average standard deviation versus vsini, and the statistical P-χ2 _{test to identify RV variables. Objects that show a higher than average}

standard deviation for a given vsini may have an additional component to their variability, such as the reflex motion from a companion. In Figure 2.6 we show the standard deviation in the epoch RVs for young stars in the Phoenix sample. There are four young stars in our sample with modestvsini values (4 - 12 km/s) that have RV standard deviations above 200 km/s (TWA 13A - 209 m/s; ScoPMS 13 - 353 m/s; RXJ 1557.8-2305 - 201 m/s; SZ 96 - 359 m/s). However, the majority of young stars (15) show similar RV dispersion (_.100 m/s) independent of vsini over a range of vsini values (0.3 - 15 km/s). Of the latter group, the average standard deviation for young stars is 63 m/s with a standard deviation of that average of 25 m/s. In Figure 2.6, we see four stars that lie 5σ above the average standard deviation. These include TWA 13A, SZ96, RXJ 1557.8-2305, and ScoPMS 13. TWA 13A which had been previously identified as a candidate RV variable (Bailey et al. 2012) and was targeted for additional follow-up in our CRIRES observations (see Section 2.2). The average

SNR for young stars in this sample is 82, and in the case of SZ 96 and RXJ 1557.8-2305, lower SNR spectra (SNRSZ96=52-63; SNRRXJ1557.8−2305=55-76) is the likely explanation as to their

elevation above the average standard deviation. ScoPMS 13, with a higher than average SNR (SNR=75-99), needs further investigation into the cause of the its higher than average RV standard deviation. In addition to these four stars, RXJ1204.6-7731 has a standard deviation more than 2 orders of magnitude above the average standard deviation (σ=8,825 m/s), and we identify this as a spectroscopic binary and discuss it further in Section 2.1.5.2.

Figure 2.6 Here we plot the standard deviation of the epoch RVs (m/s) versusvsinifor each star with multiple epoch observations. The error bars are the averageσObsA andσObsB values for each star. Excluding the stars with average standard deviations greater than 200 m/s, we calculated the average of the standard deviations for young stars in the sample (solid line) to be 63 m/s with standard deviation in the average of 25 m/s. This gives a empirical estimate for the stellar jitter for these young stars. We plot 3σ and 5σ (dotted lines) lines above the average standard deviation for a given vsini. 4 stars (SZ 96, ScoPMS 13, RXJ 1557.8-2305, and TWA 13A) show significant RV variability (>5σ), but only ScoPMS 13 has errors that do not cross below the 5σ line.

Although identifying stars with a higher than average standard deviation is a good first order indication of variability, high standard deviations can also be caused by low signal- to-noise particularly with a small number of observations. To quantitatively assess RV variability, given the short temporal baseline, we used a P-χ2 _{test to independently identify}

RV variability. A P-χ2 test shows how significant a set of observations deviates from a χ2

distribution (Carney et al. 2003). In calculating the p-values from the P-χ2 _{test, we use the}

epoch RV and the associated σAB. A p-value of .01 would indicate a 99% confidence that a star has significant RV variability over the observational run. Our histogram of p-values from our P-χ2 _{test is plotted in Figure 2.7 for the stars observed with more than 1 epoch}

of data from Gemini South Phoenix. The distribution shows a strong cluster near 1. As we expect the distribution of p-values to be uniform, this suggests our uncertainties in the RV error are being overestimated. By reducing our errors by 50%, we were able to achieve a flat P-χ2 distribution. This gives a good estimate as to how overestimated our RV errors are. Nevertheless, we adopt the more conservative values. Despite this, two stars showed significant p-values: the spectroscopic binary RXJ1204.6-7731 with a p-value <0.0001 and ScoPMS 13 with a p-value of 0.024. None of the remaining candidate variables (SZ 96, TWA 13A, and RXJ 1557.8-2305) were identified by the P-χ2 _{test. P-values are listed in}

Table 2.5. The following subsections discuss the candidate variable ScoPMS 13 and the new spectroscopic binary RXJ1204.6-7731.

Table 2.5: Gemini South Phoenix P-χ Values Star P-χ2 Value GJ 628 0.688535 GJ 752A 0.987186 HD155555C 0.986277 HIP107345 0.970670 HIP23309 0.907517 HIP29964 0.773007 V721Cra 0.882744 RecX 10 0.736741 RecX 12 0.811978 RecX 4 0.864611 RXJ 1005.3-7749 0.987853 RXJ 1204.6-7731 0.000000 RXJ 1219.7-7403 0.979684 RXJ 1534.3-3300 0.920422 RXJ 1557.8-2305 0.551008 ScoPMS 13 0.003198 SZ 78 0.917578 SZ 96 0.434182 TWA 10 0.956949 TWA 13A 0.206557 TWA 13B 0.928382 TWA 7 0.886298

Figure 2.7 A histogram of the p-values from our P-χ2 _{test on the Phoenix sample are shown.}

The two objects with p-values <0.1 show significant deviation from theχ2 _{distribution and}

indicates RV variability. The large cluster of objects with p-values near 1 show that our errors are slightly overestimated.

2.1.5.1 ScoPMS 13

ScoPMS 13 is a young M1.5 spectral type star in the Scorpius-Centaurus region (K¨ohler et al. 2000). After our program began, a companion with a separation of 0.14600 and likely with

a comparable brightness (∆K=0.10) was identified using adaptive optics (AO) observations (Lafreni`ere et al. 2014). At a distance of ∼145 pc for Sco-Cen (de Zeeuw et al. 1999), this would correspond to a projected separation of ∼21 AU.

We show the RV curve for ScoPMS 13 in Figure 2.8. Our results show ∼+380 m/s and ∼ −310 m/s deviation from the mean RV over the observation time frame (3 days). Given the 21 AU separation of the known companion, we would not expect to see a RV variation of this amplitude caused by th companion. We, therefore, classify ScoPMS 13 as a candidate RV variable, that requires more observations to determine if the variations are caused by stellar jitter, a close companion, or possible contamination of the spectrum by its spatially unresolved companion. We caution that while ScoPMS 13 is identified as a candidate variable, we note that this is based on only 3 epochs. Additionally, ScoPMS 13 was observed in the Kepler 2 EPIC dataset and was not flagged as an object of interest.

ScoPMS 13

Figure 2.8 The RV curve for candidate variable ScoPMS 13 is plotted with epoch errors for each observing day.

2.1.5.2 RXJ 1204.6-7731

RXJ1204.6-7731 is a M2 spectral type young star in the Chamaeleon star forming region (Covino et al. 1997). It was observed by an AO-aided speckle companion search by Brice˜no & Tokovinin (2017) and found to be single within their spatial detection limits of 0.0400 and maximum detectable magnitude difference of ∆m(0.1500)=2.3 and ∆m(100)=4.5. RXJ

1204.6-7731 was identified as a SB2 during the initial observing run, so two spectra were obtained on the last night separated by ∼7 hours. As noted in Section 2.1.2, two additional observations were obtained 46 days later, providing a total of 7 RV values.

Our RV code identified it as having large (∼20 km/s) amplitude RV change over a short time period, and the appearance of a companion spectrum in residuals of our fits, indicate that RXJ1204.6-7731 is an SB2. Since our code is not designed to model a composite spectrum, we used an IDL adaptation of TODCOR1 originally described by Zucker & Mazeh (1994), a two-dimensional correlation algorithm, to determine the RVs of both components. TODCOR determines the RV of both components of a SB2 by correlating two template spectra with an observed spectrum by Doppler shifting the template spectra. As our code was able to fit the telluric features of this star, we used the output wavelength calibrated spectrum fitted with our code to input into TODCOR. We then subtracted the telluric lines from our spectra using the same telluric template used in our fitting. These telluric-removed composite spectra were then fit with TODCOR using a template spectra with Tef f and logg from Table 2.4. Using the same Tef f and logg for both components, the template spectral intensities for the secondary were scaled to be 50% of the primary to obtain this fit. This choice of 50% was a ”χ-by-eye” selection. The individual RVs are listed in Table 2.6, and the first 5 epochs are shown in Figure 2.9. As there is no standard method for determining the error in the RVs obtained from TODCOR, we adopt the average difference in the RVs between the A and B nod for each component (346 m/s for RXJ 1204.6-7731A and 43 m/s for RXJ 1204.6-7731B with a standard deviation of 589 m/s and 106 m/s, respectively).

With the resulting RV’s from TODCOR, we fit Keplerian orbits to each component separately utilizing a Markov Chain Monte Carlo (MCMC) algorithm described in Quinn et al. (2015). We use the component RVs from TODCOR, the estimated error, and the estimated stellar jitter (see Chapter 4) to fit for orbital period (P), time of periastron passage (T0), radial velocity semi-amplitude (K), center-of-mass velocity (γ), eccentricity (e) and the

argument of periastron (ω). Quinn et al. (2015) describe this method as assigning best-fit parameters from the mode of each distribution which they identify from the peak of the probability density function (PDF). The errors are assigned from the region that encloses 1σ of the PDF. The best fit for each component is listed in Table 2.7, and the orbital fits are shown in Figure 2.10. Although we do not fit components simultaneously, we note the agreement in period and T0 shows self-consistent results. While the best orbital fit is

preliminary, we report the system to be a 5.6 day SB2 component RV amplitudes of RXJ 1204.6-7731A (10.8 km/s) and RXJ 1204.6-7731B (29.6 km/s) corresponding to a mass ratio of KA/KB= 0.37.

Table 2.6: RXJ1204.6-7731 Individual Radial Velocities

MJD RVComponent1 RVComponent2 (m/s) (m/s) 53489.2 7087.6 −5174.5 53490.1 14842.1 −23314.1 53491.1 7473.4 −3256.0 53492.0 −3153.9 24318.5 53492.3 −5244.3 30159.3

Figure 2.9 RV’s of RXJ1204.6-7731A (filled circles) and RXJ1204.6-7731B (open circles) in km/s over the initial 5 observations with Gemini Phoenix.

Table 2.6: RXJ1204.6-7731 Individual Radial Velocities MJD RVComponent1 RVComponent2

(m/s) (m/s)

53538.2 3009.2 34718.3 53544.1 7945.5 35769.7

The error in the RV is estimated to be 346 m/s for RXJ 1204.6-7731A and 43 m/s for RXJ 1204.6-7731B. See the discussion in Section 2.1.5.2

Table 2.7: Orbital Parameters of RXJ 1204.6-7731 Parameter RXJ 1204.6-7731A RXJ 1204.6-7731B P 5.48±0.001 days 5.69±0.002 days T0 53491.40±0.01 53491.43±0.003 K 10793.1±74.9 m/s −29550.2±70.7 m/s γ 3222.6±65.1 m/s 8366.4±57.8 m/s e 0.1001±0.008 0.078±0.002 ω 29.51±3.31 18.01±2.10

Figure 2.10 Best fit orbit for RXJ1204.6-7731A (left) and RXJ1204.6-7731B (right).