Free Access
Issue
A&A
Volume 590, June 2016
Article Number A116
Number of page(s) 36
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/201527242
Published online 25 May 2016

© ESO, 2016

1. Introduction

A chemically peculiar (CP) star can be distinguished from a chemically normal star by its spectrum, where anomalies can be seen on a visual inspection of low-dispersion spectra. The optical spectra of the CP stars exhibit normal hydrogen lines combined with enhanced silicon, metal, and or rare-earth lines and weak calcium lines. The chemical peculiarities in these stars result from the diffusion process (Michaud 1970; Michaud et al. 1981; Babel 1992; Richer et al. 2000). Chemical elements with many lines near flux maximum, such as iron peak and rare earth elements, are brought up to the surface by the dominance of radiation pressure over gravity in the radiative envelopes of these stars, causing an apparent overabundance of such elements. The elements with few lines near the flux maximum settle gravitationally and appear to be underabundant. Slow rotation is thus a basic condition to operate the diffusion process in CP stars. The CP stars are found on the main-sequence between spectral types B2 and F5, from the zero-age main-sequence (ZAMS) to the terminal-age main-sequence (TAMS), and have masses ranging from 1.5 to about 7 M.

Based on their spectroscopic characteristics, Preston (1974) divided the CP stars into the following groups: Am/Fm (CP1), Ap/Bp (CP2), Hg-Mn (CP3), He weak and He strong (CP4) stars. Renson & Manfroid (2009) compiled an up-to-date catalog of 8205 CP stars. A subset of Ap and Am stars shows photometric variability with periods ranging from a few minutes to a few hours, and are the focus of the Nainital-Cape Survey.

The Am/Fm stars are relatively cool stars of spectral type F5-A8, with temperatures ranging from 6500 K to 10 000 K. The spectra of these stars exhibit an underabundance (weak lines) of Ca or Sc (or of both elements) and overabundance (strong lines) of Sr, Eu and other rare-earth elements. Some of the members of this group show δ Sct-type pulsational variability (Joshi et al. 2003, 2006, 2009; Smalley et al. 2011; Catanzaro & Ripepi 2014; Hou et al. 2015). The Am stars rotate slower than chemically normal A-type stars and the frequency of binarity among these stars is much higher than among normal stars of the same mass (Abt & Golson 1962; Abt & Snowden 1973). It is well understood that these stars do not exhibit strong global magnetic fields, however based on the observations from Kepler space mission, Balona et al. (2015) found flares in two Am stars, which strongly suggests that at least some Am stars possess significant magnetic fields.

The Ap/Bp stars have effective temperatures in the range of 6400 K to 15 000 K. These stars exhibit the most conspicuous chemical anomalies of all the CP stars: enhanced lines of some elements, particularly Si, Cr, Sr, Mn, Fe, Eu, Gd, and Ce (overabundant by up to a factor of 106), and weak lines of light elements (underabundant by a factor of 10-2). The Ap stars show low rotation velocities with vesini usually not exceeding 100 km s-1. These stars have strong global magnetic fields with an intensity ranging from hundreds of Gauss to tens of kilogauss.

The coolest subgroup of Ap stars (6400 K Teff ≤ 8700 K) located near the main-sequence (MS) part of the classical instability strip, are known as roAp stars. Since the discovery of first roAp star HD 101065 (Kurtz 1978), 61 other members of this class have been discovered (Smalley et al. 2015). The roAp stars show pulsational variability in both the broad photometric bands and in narrow spectral lines. These pulsations are characterized as high-overtone, low-degree p-modes with typical periods between 5.6 min and 23.6 min and photometric amplitudes ranging from a few micro-magnitudes (μmag) up to tens of milli-magnitudes (mmag) and radial velocity (RV) amplitudes ranging from a few m s-1 to km s-1. The roAp stars possess strong magnetic fields with typical strengths of a few kG to tens of kG (Hubrig et al. 2012) with overabundances of some rare earth elements that can exceed the solar value by 106 (Ryabchikova et al. 2004). To date, there have been no roAp stars found in close binary systems though a few Ap stars are in close binaries. The roAp stars are among the more challenging MS stars to model owing to their pulsations in the combined presence of a strong global magnetic field together with element segregation and stratification, but at the same time they can be considered as stellar atomic physics laboratory.

The pulsation frequency spectrum of some of the roAp stars shows frequency multiplets with spacings corresponding to the frequency of rotation of the star. This phenomenon can be explained using the oblique pulsator model (Kurtz 1982), in which the pulsation axis is aligned with the axis of the magnetic field, which is assumed to be roughly a dipole inclined with respect to the axis of rotation. As a star rotates, the observed aspect of the pulsation changes, leading to amplitude modulation and, in some cases, phase modulation. The driving mechanism of the pulsations in roAp stars is thought to be the classical κ-mechanism operating in the partial hydrogen ionization zone (Balmforth et al. 2001). Cunha & Gough (2001) suggested an alternative excitation mechanism for roAp stars where pulsation is driven by the turbulent pressure in the convection zone.

Some roAp stars have highly stable pulsation frequencies and amplitudes, even on timescales of years while other roAp stars show frequency and amplitude variations on timescales as short as hours (Medupe et al. 2015). Whether this is a result of driving and damping, mode coupling or some instability is not known. It is important to know where in the roAp instability strip the stable and unstable pulsators lie.

The Kepler mission, launched in 2009 with the aim to detect and characterize Earth-sized planets in the habitable zone, has revolutionized our ability to detect and study very low-amplitude light variations of the order of a few μ-mag in rather faint stars (Koch et al. 2010). The Kepler mission has enabled the discovery of five roAp stars, all which have pulsation amplitudes much below the detection limits of ground-based photometry.

While initially roAp stars were discovered and studied with photometric methods, time-resolved spectroscopy has allowed the study of wider physical aspects of the pulsating stellar atmosphere. The rapid radial velocity variations of spectral lines of certain chemical elements allow us to sample the velocity field in the stellar atmosphere as a function of atmospheric depth. Of the 61 known roAp stars, about a quarter of them were discovered using spectroscopic methods. A combination of simultaneous spectroscopy and photometry constitutes the most sophisticated asteroseismic data set for any roAp star. The observed phase lag between the variations in luminosity and in RV is an important parameter for modeling the stellar structure.

Similar to other pulsating stars, the roAp stars are also excellent asteroseismic candidates through which one can compare the observed frequency spectrum to the asymptotic pulsation theory and then obtain information about the spherical harmonic degrees of the pulsation modes, the distortion of the modes from normal modes, atmospheric structures, evolutionary status and the geometry of the magnetic field. Using such information one can derive the various physical parameters such as rotation periods, temperatures, luminosities, radii and their masses (see Joshi & Joshi 2015 for a recent review on asteroseismology of pulsating stars). Although the extent of the roAp phenomenon has been fairly well delineated in photometric and spectroscopic terms, there is as yet no known combination of these (and other) observable parameters that can be used as a predictors of pulsation in any given Ap star. In other words, one can have two Ap stars that are apparently similar in all observable parameters, where one is a pulsating roAp star and the other has no detectable pulsations and is a so-called “noAp” star.

The Nainital-Cape Survey was initiated in 1999 by the Aryabhatta Research Institute of Observational Sciences (ARIES) at Manora Peak, Nainital, India, and the South African Astronomical Observatory (SAAO) in Sutherland to search for pulsations in CP stars. The goals of the survey were: (i) to increase the number of known pulsating CP stars; (ii) to determine the observational limits of the roAp phenomenon; and (iii) to broaden the number and distribution (in parameter space) of established constant (noAp) stars, so as to shed some light on what distinguishes the pulsating from the apparently constant CP stars of similar spectral type and other observable physical parameters. This is the only survey of its kind that was conducted from both the northern and southern hemisphere. The first three papers of this survey described the scope and methods of the survey and reported the discovery of pulsations in several CP stars (Martinez et al. 2001; Paper I, Joshi et al. 2006; Paper II, Joshi et al. 2009: Paper III). The present paper is the fourth in this series and presents the null results obtained for 108 stars observed during the period of 2006 to 2009.

Similar to other papers of this series, the present paper is also based on photoelectric photometry of the sample stars and is organized as follows: the target selection, observations and data reduction procedures are described in Sect. 2, followed by the frequency analysis of the time series photometric data in Sect. 3. In Sect. 4, the observational limits for the detection of light variations at the ARIES and SAAO sites are discussed. The stars classified as null results and their basic astrophysical parameters are given in Sect. 5. In Sect. 6, we provide the basic physical parameters of all the currently known roAp stars. In this section, we also compare the evolutionary status of the known roAp stars to the sample of stars observed under the Nainital-Cape Survey. The statistics of several surveys to search for new roAp stars are discussed in Sect. 8. Finally, we outline the conclusions drawn from our study in Sect. 9.

2. Target selection, observations and data reduction

2.1. Selection criteria

Following the target selection strategy of Martinez et al. (1991), the primary source of candidates for the Nainital-Cape Survey was the subset of CP stars with Strömgren photometric indices similar to those of the known roAp stars. In this range, we also found many Am stars and included them in the list of targets. Apart from the sources of target mentioned in Martinez et al. (1991), we also included Ap/Am stars from Renson et al. (1991) and magnetic stars from Bychkov et al. (2003).

On the basis of the Strömgren photometric indices of known roAp stars (see Table A.1), we revised the range of indices that encompass the roAp phenomenon:

0.082 ≤ by ≤ 0.431

0.178 ≤ m1 ≤ 0.387

−0.204 ≤ δm1 ≤ 0.012

0.002 ≤ c1 ≤ 0.870

−0.370 ≤ δc1 ≤ 0.031

2.64 ≤ β ≤ 2.88

where by is the color index and β measures the strength of the Hβ line, which is indicator of temperature for stars in the spectral range from around A3 to F2. The m1 and c1 indices indicate enhanced metallicity and increased line blanketing, respectively. The parameters δm1 and δc1 measure the blanketing difference and Balmer discontinuity relative to the ZAMS for a given β, respectively. Indices in the ranges given above are not an unambiguous indicator of roAp pulsation, although they serve to narrow down the field of candidates to the most promising subset. It is interesting to note that, whereas previously the roAp phenomenon seemed to be confined to the temperature range of the δ Scuti instability strip, it now appears that the roAp instability strip has a considerably cooler red edge, well into the F-type stars (see Fig. 2). As can be seen by the paucity of cooler stars tested for pulsation, this is an area for future work, to establish more firmly the cool edge of the roAp instability strip.

2.2. Photometric observations

For many roAp stars, the pulsational photometric variations have amplitudes less than 20 mmag. The detection of such low-amplitude variations demands high-precision photometric observations that can be attained with fast photometers mounted on small telescopes at observing sites such as ARIES Nainital in India and SAAO Sutherland South Africa. The ARIES observations presented in this paper were acquired using the ARIES high-speed photoelectric photometer (Ashoka et al. 2001) attached to the 1.04-m Sampurnanand telescope at ARIES. The SAAO observations were acquired using the Modular Photometer attached to the 0.5-m telescope and the University of Cape Town Photometer attached to the 0.75-m and 1.0-m telescopes at the Sutherland site of SAAO.

Each star was observed in high-speed photometric mode with continuous 10-sec integrations through a Johnson B filter. The observations were acquired in a single-channel mode (i.e. no simultaneous comparison star observations), with occasional interruptions to measure the sky background, depending on the phase and position of the moon. To minimize the effects of seeing fluctuations and tracking errors, we selected a photometric aperture of 30′′. Each target was observed continuously for 1–3 h at a time. Since the amplitudes of the rapid photometric oscillations in roAp stars exhibit modulation due to rotation and interference among frequencies of different pulsation modes, a null detection for pulsation may be obtained simply owing to a coincidence of the timing of the observations. Hence, each candidate was observed several times.

2.3. Data reduction

The data reduction process began with a visual inspection of the light curve to identify and remove obviously bad data points, followed by correction for coincidence counting losses, subtraction of the interpolated sky background, and correction for the mean atmospheric extinction. After applying these corrections, the time of the midpoint of the each observation was converted into a heliocentric Julian date (HJD) with an accuracy of 10-5 day (~1 s). The reduced data comprise a time-series of HJD and ΔB magnitude with respect to the mean of the light curve.

3. Frequency analysis

A fast algorithm (Kurtz 1985) based on the Deeming discrete Fourier transform (DFT) for unequally spaced data (Deeming 1975) was used to calculate the Fourier transformation. The light curves were also inspected visually for evidence of δ Sct oscillations with periods of a few tens of minutes and longer. On these timescales, single-channel photometric data are affected by sky transparency variations and it is not always possible to distinguish between oscillations in the star and variations in sky transparency. This is where the comparison of data of the same star acquired under different conditions on different nights is helpful for confirming the tentative detection of coherent oscillations in a given light curve.

After visual inspection of the light curves to search for indications of δ Sct pulsations in a given light curve on timescales longer than about half an hour, we removed the sky transparency variations from the DFT data to reduce the overall noise level to approximately the scintillation noise. This is practicable for single-channel data because, on good photometric nights, the roAp oscillation frequencies are generally well resolved from the sky transparency variations. To remove the effect of sky transparency variations, the DFT data were prewhitened to remove signals with frequencies in the range 0–0.9 mHz, which is the frequency range commonly affected by sky transparency variations in single-channel photometric data. These frequencies were removed until the noise level in the DFT of the residuals approximated a white noise spectrum. Depending on the stability of the photometric transparency of a given night, it was generally possible to correct for the effects of sky transparency by removing 3 to 5 frequencies in the above mentioned frequency range.

The first and second panels of Fig. A.1 show the light curves of the candidate stars filtered for low frequency sky transparency variations. The third and fourth panels show the prewhitened amplitude spectra of the sample stars filtered for low-frequency sky transparency variations.

4. Noise level characterization

The detection limit for photometric variability depends upon the atmospheric noise, which consists of scintillation noise and sky transparency variations, and the photon noise. For the brighter (~10 mag) stars, the atmospheric scintillation noise dominates over the photon noise and is one of the fundamental factors limiting the precision of ground based photometry. In order to characterize the two observing sites used in the Nainital-Cape Survey and to put constraints on the detection limits for low amplitude variability, we estimated the observational and the theoretical scintillation noise values for both the sites.

Given the altitude and diameter of the telescope, and the observational exposure time and airmass, one can find the contribution of scintillation noise in photometric measurements using the Young approximation (Young 1967; 1974). Using this scaling relation, it is possible to compare the level of scintillation noise at different observatory sites. Although the precise amount of scintillation changes from night to night, the Young’s scaling relation appears to hold very well for telescope apertures up to 4 m, and for different sites (Kjeldsen & Frandsen 1991; Gilliland & Brown 1992; Gilliland et al. 1993). However, recent studies by Kornilov et al. (2012) and Osborn et. al (2015) showed that this equation tends to underestimate the median scintillation noise at several major observatories around the world. Osborn et. al. (2015) presented a modified form of the Young approximation (Eq. (1)) that uses empirical correction coefficients to give more reliable estimates of the scintillation noise at a range of astronomical sites: σY2=10×10-6CY2D4/3t-1(cosγ)-3exp(2hobs/H),\begin{equation} \sigma_{Y}^2 = 10\times10^{-6}C_Y^2 D^{-4/3}t^{-1}(\cos{\gamma})^{-3} \exp{\left(-2h_\mathrm{obs}/H\right)}, \label{scieq} \end{equation}(1)where CY is the empirical coefficient, D is the diameter of the telescope, t is the exposure time of the observation, γ is the zenith distance, hobs is the altitude of the observatory and H the scale height of the atmospheric turbulence, which is generally accepted to be approximately 8000 m. All parameters are in standard SI units. The empirical coefficients CY for the major observatories around the world are listed by Osborne et al. (2015).

The theoretical values of scintillation noise for Sutherland and Nainital were estimated using Eq. (1). The scintillation noise in terms of amplitude was obtained by taking the square root of σY. However, we have to scale the theoretical value to compare the two sites with different telescope diameters. Therefore, the theoretical scintillation noise for SAAO (50 cm telescope) was scaled to the aperture of the ARIES telescope (104 cm) using the same relation. The input parameters used to estimate the theoretical scintillation noise are: height (ARIES: 1958-m, SAAO: 1798 m), sec(Z) (airmass): 1, CY: 1.5, integration time: 10 sect. The estimated scintillation values of ARIES (D: 104 cm) and SAAO (D: 50 cm) are 0.0338 mmag and 0.0433 mmag, respectively. The scaled value of the scintillation noise for SAAO (scaled to 104 cm) is 0.0340 mmag. Figure 1 shows the theoretical noise levels for the ARIES and SAAO sites (both scaled and unscaled).

thumbnail Fig. 1

Noise characteristics at the ARIES site at Nainital and SAAO Sutherland site. The acspline-fitted curve of ARIES and SAAO amplitude spectra are shown in solid blue and dot-dashed red curves, respectively. The theoretical scintillation noise levels of ARIES and SAAO are shown with blue long-dashed and red small-dashed horizontal lines, respectively, and the scintillation noise level of SAAO (scaled to 104 cm diameter) is also shown with a green dotted horizontal line.

Since the observations in the Nainital-Cape Survey were carried out over many nights and in a variety of atmospheric conditions, the noise levels in the Fourier spectra of the individual light curves are expected to be higher than the theoretical scintillation values for each site, and they are also not expected to be white noise. We first transformed the time-series data of stars observed from ARIES during 2006–2009 and from SAAO during 2006–2007 into their individual periodograms to estimate the observational values of the noise in our amplitude spectra as a function of frequency. We then combined all the periodograms from each site into a single pseudo-periodogram and fitted an acspline function to obtain the average estimated noise profile as a function of frequency. These observational noise curves are shown in Fig. 1 in solid blue for ARIES and dot-dashed red for SAAO. These noise profiles provide a useful first check of the significance of possible oscillation frequencies identified in the Fourier spectra in Fig. 3 of this paper.

More than half of the known roAp stars were discovered photometrically from SAAO. One of the basic reasons behind this is that the Sutherland site has stable and good sky transparency, facilitating a closer match to scintillation noise than at many other observing sites used in other roAp surveys. However, in the last ten years that we have been running the Nainital-Cape Survey, we have noticed a gradual increase in sky brightness and atmospheric noise owing to enhanced human activities around the ARIES and Sutherland observatories. It can be inferred from the scaling relation (Eq. (1)) that the combined atmospheric noise can be minimized by installing bigger telescopes at a good observing site where one can find stable photometric sky conditions (Young 1967). A new 1.3 m optical telescope is now operational at a new astronomical site of ARIES observatory known as Devasthal (longitude: 79°40′57′′ E, latitude : 29°22′26′′ N, altitude: 2420-m). In addition, a new 3.6 m telescope has been recently installed at the Devasthal site and is likely to be operational by 2016. The theoretical scintillation noise estimated for this telescope is 0.0217 mmag making the telescope very efficient for detecting tiny amplitude variations. The 0.5-m telescope of SAAO is also soon to be replaced with a 1.0-m robotic telescope. These upcoming observing facilities equipped with modern state-of-the-art instruments at ARIES and SAAO will be the next step to boost the Nainital-Cape Survey and other projects aimed at the detection of sub-mmag light variations.

5. New null results from the Nainital-Cape Survey

We report the non-detections of pulsation in 108 CP stars. The first and second panels of Fig. A.1 depict the light curves of the candidate stars observed from ARIES and SAAO. The prewhitened frequency spectra of the respective time-series are plotted in the third and fourth columns. The name of the star, duration of observations in hours and the heliocentric Julian dates are denoted in each panel.

Here it is worth recalling that roAp stars show amplitude modulation due to rotation and beating between multiple pulsation frequencies. Therefore, the nondetection of light variations may be due to fact that the observations are acquired at a time when the pulsations are below the detection limit of the survey. For example, Joshi et al. (2006) classified HD 25515 as a null result and then subsequently, after further observations, classified it as a δ Scuti-type pulsating variable (Joshi et al. 2009). Hence, a nulldetection of pulsations does not mean that the star is nonvariable, but rather that its light output was not detected to vary during the particular interval of the observations. This demonstrates the necessity for repeated observations of the candidate stars. These null results are also an important contribution toward understanding the distinction between pulsating and nonpulsating CP stars that are otherwise similar in all other observational respects (Murphy et al. 2015). As mentioned above, a by-product of these null results is an observational characterization of a particular observing site for data acquired on many nights over a wide range of observing conditions.

6. Comparison of known roAp stars with the null results

At the time the Nainital-Cape Survey began, only 23 roAp stars were known. Therefore, our knowledge of the extent of the roAp phenomenon at that time was used to define the target selection and observing strategy. Since then, the number of known roAp stars has more than doubled, and currently stands at 61 confirmed members of this class. The compilation of the various physical parameters of the known roAp stars are important to study the roAp and noAp (“non-roAp”) phenomena in Ap stars. Tables A.1 and A.2 list the astrophysical parameters of the known roAp stars extracted from the available sources in the literature. For each star Table A.1 lists, the table entry number, the HD number of roAp star, their popular name, spectral type, Strömgren indices by, m1, c1, β, δm1, δc1, effective temperature Teff, and reference(s) from which the data were taken. Table A.2 lists the table entry number, HD or HR catalog number and other name(s) of the roAp star, visual magnitude mv, parallax π, distance d, absolute magnitude Mv, luminosity parameter log (LL)\hbox{$\left(\frac{L_\star}{L_\odot}\right)$}, pulsational period corresponding to the highest amplitude, frequency separation Δμ, maximum photometric amplitude variation Amax, maximum radial velocity variation RVmax, rotational period Prot, surface gravity log g, mass M, radius R, mean longitudinal magnetic field, and the projected rotational velocity vsini. Where no data is available in the data archives or in the literature for a given parameter, this is denoted with a “-” symbol in the relevant column. It is instructive to compare the coverage of the Nainital-Cape Survey with the currently established extent of the roAp phenomenon. Therefore, the catalog of the basic parameters of the known roAp stars can be used for the statistical analysis of roAp and noAp phenomena in Ap stars located in the same part of the H-R diagram.

7. Evolutionary states of the studied samples

To establish the evolutionary status of the sample null result stars, we first established their luminosities and effective temperatures, which then allowed us to compare them with the known roAp stars. The absolute magnitudes and luminosities of the candidate stars observed in the Nainital-Cape Survey were determined based on the data taken from the Hipparcos catalog (van Leeuwen 2007). The photometric Teff is calculated from the Strömgren β indices using the grids of Moon & Dworetsky (1985) that give a typical error of about 200 K. The various astrophysical parameters of the stars observed in the Nainital-Cape Survey are listed in Table A.3. These parameters are either taken from the Simbad database or calculated using the standard relations (Cox 1999). For each star, this Table lists the HD number, right ascension α2000, declination δ2000, visual magnitude mv, spectral type, parallax π, Strömgren indices by, m1, c1, β, δm1, δc1, effective temperature Teff, luminosity parameter log (LL)\hbox{$\left(\frac{L_\star}{L_\odot}\right)$}, duration of the observations Δt, heliocentric Julian dates (HJD:2 450 000+) and year of observations (2000+) when the star was observed. The Strömgren indices δm1 and δc1 are calculated using the calibration of Crawford (1975, 1979).

The absolute magnitude Mv in the V-band was determined using the standard relation (Cox 1999), Mv=mv+5+5logπAv,\begin{equation} M_v = m_v + 5 + 5\log\, \pi -Av, \end{equation}(2)where π is trigonometric parallax measured in arcsec, the interstellar extinction in the V band is AV = RVE(BV) = 3.1E(BV). The reddening parameter E(BV) is obtained by taking the difference of the observed colour (taken from the Simbad data base) and intrinsic colour (estimated from Cox 1999).

The stellar luminosity was calculated using the relation logLL=MV+BCMbol,2.5,\begin{equation} \log\dfrac{L}{L_{\odot}} = - \dfrac{M_V + BC - M_{{\rm bol},\odot}}{2.5}, \end{equation}(3)where we adopted the solar bolometric magnitude Mbol, ⊙ = 4.74 mag (Cox 1999), and used the standard bolometric correction BC from Flower (1996). Taking all of the contributions to the Mv and LL\hbox{$\frac{L_\star}{L_\odot}$} error budgets into account, we find a typical uncertainty of 20–25% for both parameters.

thumbnail Fig. 2

Positions of the null results (filled triangle) and δ-Scuti type variables discovered under the Nainital-Cape Survey (filled square). For comparison, positions of known roAp stars are also shown (open star). The solid lines show theoretical evolutionary tracks from the ZAMS (Christensen-Dalsgaard 1993). The dashed lines indicate the red and blue edges of the instability strip.

The null objects shown in Fig. 2 include all the objects from Papers I–IV (this paper) of the Nainital-Cape Survey. The positions of known roAp stars and the newly discovered δ-Scuti type variables in our survey are also shown. The evolutionary tracks for stellar masses ranging from 1.5 to 3.0 M (Christensen-Dalsgaard 1993) are overplotted. The position of the blue (left) and red (right) edges of the instability strip are shown with two oblique lines (Turcotte et al. 2000). Figure 2 clearly shows that most of the sample stars are located within the instability strip. For reasons given above, we may expect that some of the stars listed as null results in this paper may well turn out to be variables in near future. However, with each subsequent nondetection of pulsations, the constraint on nonvariability will be strengthened and they are established as “noAp” stars, thus helping to shed light on the other observational characteristics that allow us to distinguish between pulsating and constant CP stars, which is one of the long-term goals of the Nainital-Cape Survey.

8. Ground-based surveys on pulsation in chemically peculiar stars

In the past, several surveys have been conducted around the globe to search for roAp stars with different instrumental setups independently in both the northern and southern hemisphere. Such surveys required much telescope time, hence the photometric surveys were performed on 1 m class telescopes, where it was possible to secure ample telescope time. Spectroscopic surveys became more popular in recent years because of improved sensitivity of the high-resolution spectroscopic instruments used to search for low amplitude oscillations in roAp candidates. The major drawback of this technique remains the small amount of observing time available on large telescopes. In this section, we provide a short description of the various surveys conducted for pulsation in CP stars.

8.1. Cape survey

Following the discovery of first roAp star HD 101065 in 1978, only 14 stars were known prior to 1990. A systematic survey of roAp stars in the southern hemisphere was initiated by Don Kurtz and Peter Martinez at SAAO with two objectives: first to increase the number of members of this class and, second, to study the relationship between the roAp stars and the other pulsating stars located at the same region of the H-R diagram. The observations for this survey were acquired with the photoelectric photometers attached to the 0.5-m and 1.0-m telescopes at Sutherland. Under the Cape survey 134 Southern Ap SrCrEu stars were checked for the pulsational variability and 12 new roAp stars were discovered (Martinez et al. 1991; Martinez & Kurtz 1994a, 1994b).

8.2. Nainital-Cape survey

The detection of the small amplitude light variations needs a lot of observational expertise. As mentioned above most of the roAp stars known prior to 2000 were discovered under the Cape survey, where the SAAO astronomers gained a lot of observational experience. However, this meant that most of the known roAp stars were southern objects. The Nainital-Cape Survey was initiated in 1999 as a collaboration between South African and Indian astronomers to increase the number of known roAp stars in the northern sky. This survey was started in 1999 and lasted for ten years making it the most extensive survey for pulsation in CP stars, where a total of of 337 Ap and Am stars were monitored. Although only one new roAp star, HD 12098, was discovered under this survey but the milli-magnitude level light variations with periods similar to those of the δ-Scuti stars was dicovered in seven Am stars. This survey is thus unique in a sense that both the Ap and Am stars were included in the samples, hence there were plenty of chances to discover pulsations in CP1 and CP2 stars. The null results of this survey have been published in Martinez et al. (2001), Joshi et al. (2006; 2009) and in the present paper. The archive of well established null results is useful to delineate the extent of the roAp phenomenon and also to shed light on the distinction between roAp and noAp stars.

8.3. Lowell-Wisconsin survey

Between 1985 to 1991, Nelson & Kreidl (1993) conducted a survey of pulsation in 120 northern Ap stars of spectral range B8–F4. Although these authors did not report the discovery of any new roAp stars from their survey, their main finding was the absence of pulsation in the spectral range B8–A5, indicating that roAp-like oscillations are likely to be confined to the cooler peculiar stars.

8.4. The Hvar survey

A photometric survey was initiated in 2011 to search for new northern roAp stars at the Hvar observatory (Paunzen et al. 2012, 2015). For this survey, a CCD based photometer attached to the 1.0 m Austrian-Croatian telescope was used for the observations of candidate stars. Under this survey, 80 candidate roAp stars were examined for a total duration of 100 h. Differential CCD photometry was performed to detect the light variations in the sample Ap stars. The authors have not reported any positive detections and have presented the frequency spectra and the basic parameters of the null results they observed.

8.5. Other minor photometric surveys

In addition to the above surveys, a number of smaller photometric surveys have also been conducted independently in the northern and southern hemisphere by Dorokhova & Dorokhov (1998), Kurtz (1982), Matthews et al. (1988), Heller & Kramer (1990), Schutt (1991), Belmonte (1989), Hildebrandt (1992), and Handler & Paunzen (1999). Though these surveys are small in terms of sample size and number of newly discovered roAp stars, they have helped to define candidate selection criteria for other roAp surveys.

8.6. Spectroscopic surveys

Spectroscopy of high spectral and temporal resolution using large telescopes permits the detailed study of line profile variations (Hatzes & Mkrtichian 2005). After the discovery of significant RV pulsational variations in some known roAp stars (Kanaan & Hatzes 1998), in the last ten years candidate roAp stars have been monitored with time resolved high resolution spectroscopic observations by several observers. These observations revealed that the highest RV amplitudes are observed in the spectral lines of the rare earth elements, while spectral lines of the other elements show weak or undetectable oscillations. Using spectroscopic techniques, about 15 roAp stars have been discovered (Kochukhov 2006; Kochukhov et al. 2008, 2009, 2013; Alentive et al. 2012; Elkin et al. 2005a; 2005b; Kurtz et al. 2006).

9. Conclusions

In this paper, we presented the light curves and frequency spectra of the 108 candidate stars observed in the Nainital-Cape Survey. Analyses of the photometry acquired at Sutherland and Nainital indicate that we have achieved a detection level of about 0.6 mmag in the frequency range 1–5 mHz in the Nainital-Cape Survey. Using the standard relations and data extracted from the literature we presented the various astrophysical parameters of the null results. We also compiled the basic physical parameters of the known roAp stars. On comparing the positions of the known roAp stars to the observed sample stars in the H-R diagram, we infer that the boundary of the roAp phenomenon extends beyond the cool edge of the classical instability strip.

Acknowledgments

This work was carried out under the Indo-South Africa Science and Technology Cooperation INT/SAFR/P-3(3)2009) and NRF grant UID69828 funded by Departments of Science and Technology of the Indian and South African Governments. S.C. acknowledges support under the Indo-Russian grant INT/RFBR/P-118 through which he received a stipend to perform this work. We acknowledge use of SIMBAD, NASA’s ADS and ESA’s Hipparcos database.

References

  1. Abt, H. A., & Golson, J. C. 1962, ApJ, 136, 35 [NASA ADS] [CrossRef] [Google Scholar]
  2. Abt, H. A., & Snowden, M. S. 1973, ApJS, 25, 137 [NASA ADS] [CrossRef] [Google Scholar]
  3. Alentiev, D., Kochukhov, O., Ryabchikova, T., et al. 2012, MNRAS, 421, L82 [NASA ADS] [Google Scholar]
  4. Ashoka, B. N., Kumar, Babu, V. C., et al. 2001, JA&A, 22, 131 [Google Scholar]
  5. Babel, J. 1992, A&A, 258, 449 [NASA ADS] [Google Scholar]
  6. Balmforth, N. J., Cunha, M. S., Dolez, N., et al. 2001, MNRAS, 323, 362 [NASA ADS] [CrossRef] [Google Scholar]
  7. Balona, L. A., & Laney, C. D. 2003, MNRAS, 344, 242 [NASA ADS] [CrossRef] [Google Scholar]
  8. Balona, L. A., Cunha, M. S., Gruberbauer, M., et al. 2011, MNRAS, 413, 2651 [NASA ADS] [CrossRef] [Google Scholar]
  9. Balona, L. A., Catanzaro, G., Crause, L., Cunha, M., et al. 2013, MNRAS, 432, 2808 [NASA ADS] [CrossRef] [Google Scholar]
  10. Balona, L. A., Catanzaro, G., Abedigamba, O. P., et al. 2015, MNRAS, 448, 1378 [NASA ADS] [CrossRef] [Google Scholar]
  11. Belmonte, J. A. 1989, Ph.D. Thesis, Universidad de La Laguna, Tenerife [Google Scholar]
  12. Bychkov, V. D., Bychkova, L. V., & Madej, J. 2003, A&A, 407, 631 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  13. Catanzaro, G., & Ripepi, V. 2014, MNRAS, 441, 1669 [NASA ADS] [CrossRef] [Google Scholar]
  14. Christensen-Dalsgaard, J. 1993, Proc. IAU Coll., 137, Inside the stars (ASP: San Francisco), eds. Baglin, A., Weiss, W. W., ASP Conf. Ser., 40, 483 [NASA ADS] [Google Scholar]
  15. Cox, A. N. 1999, Allen’s Astrophysical Quantities (Springer) [Google Scholar]
  16. Crawford, D. L. 1975, AJ, 80, 955 [NASA ADS] [CrossRef] [Google Scholar]
  17. Crawford, D. L. 1979, AJ, 84, 1858 [NASA ADS] [CrossRef] [Google Scholar]
  18. Cunha, M. S., & Gough, D. 2001, ESASP, 464, 419 [NASA ADS] [Google Scholar]
  19. Deeming, T. J. 1975, Ap&SS, 36, 137 [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  20. Dorokhova, T. N., & Dorokhov, N. I. 1998, Contrib. Astron. Obser. Skalnate Pleso, 27, 338 [Google Scholar]
  21. Elkin, V. G., Riley, J. D., Cunha, M. S., Kurtz, D. W., & Mathys, G. 2005a, MNRAS, 358, 665 [NASA ADS] [CrossRef] [Google Scholar]
  22. Elkin, V. G., Kurtz, D. W., & Mathys, G. 2005b, MNRAS, 364, 864 [NASA ADS] [CrossRef] [Google Scholar]
  23. Elkin, V. G., Kurtz, D. W., Mathys, G., & Freyhammer, L. M. 2010, MNRAS, 402, 1883 [NASA ADS] [CrossRef] [Google Scholar]
  24. Elkin, V. G., Kurtz, D. W., Worters, H. L., et al. 2011, MNRAS, 411, 978 [NASA ADS] [CrossRef] [Google Scholar]
  25. Flower, P. J. 1996, ApJ, 469, 355 [NASA ADS] [CrossRef] [Google Scholar]
  26. Gilliland, R. L., & Brown, T. M. 1992, PASP, 104, 582 [NASA ADS] [CrossRef] [Google Scholar]
  27. Gilliland, R. L., Brown, T. M., Kjeldsen, H., et al. 1993, AJ, 106, 2441 [NASA ADS] [CrossRef] [Google Scholar]
  28. Girish, V., Seetha, S., Martinez, P., et al. 2001, A&A, 380, 142 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  29. González, J. F., Hubrig, S., Kurtz, D. W., Elkin, V. G., & Savanov, I. 2008, MNRAS, 384, 1140 [NASA ADS] [CrossRef] [Google Scholar]
  30. Handler, G., & Paunzen, E. 1999, A&AS, 135, 57 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  31. Handler, G., Weiss, W. W., Paunzen, E., et al. 2002, MNRAS, 330, 153 [NASA ADS] [CrossRef] [Google Scholar]
  32. Handler, G., Weiss, W. W., Shobbrook, R., et al. 2006, MNRAS, 366, 257 [NASA ADS] [CrossRef] [Google Scholar]
  33. Hatzes, A. P., & Mkrtichian, D. E. 2004, MNRAS, 351, 2 [Google Scholar]
  34. Hatzes, A. P., & Mkrtichian, D. E. 2005, A&A, 430, 279 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  35. Heller, C. H., & Kramer, K. S. 1990, MNRAS, 244, 372 [NASA ADS] [Google Scholar]
  36. Hildebrandt, G. 1992, Astron. Nachr., 313, 233 [Google Scholar]
  37. Holdsworth, D. L. 2015, Ph.D. Thesis, Keele University, UK [Google Scholar]
  38. Holdsworth, D. L., Smalley, B., Gillon, M., et al. 2014a, MNRAS, 439, 2078 [NASA ADS] [CrossRef] [Google Scholar]
  39. Holdsworth, D. L.,Smalley, B., Kurtz, D. W., et al. 2014b, MNRAS, 443, 2049 [NASA ADS] [CrossRef] [Google Scholar]
  40. Hou, W., Luo, A., Yang, H., et al. 2015, MNRAS, 449, 1401 [NASA ADS] [CrossRef] [Google Scholar]
  41. Hubrig, S., Kurtz, D. W., Schöller, M., et al. 2012, ASPC, 462, 318 [NASA ADS] [Google Scholar]
  42. Joshi, S., & Joshi, Y. C. 2015, JA&A, 36, 33 [NASA ADS] [Google Scholar]
  43. Joshi, S., Girish, V., Sagar, R., et al. 2003, MNRAS, 344, 431 [NASA ADS] [CrossRef] [Google Scholar]
  44. Joshi, S., Mary, D. L., Martinez, P., et al. 2006, A&A, 455, 303 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  45. Joshi, S., Mary, D. L., Chakradhari, N. K., Tiwari, S. K., & Billaud, C. 2009, A&A, 507, 1763 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  46. Kanaan, A., & Hatzes, A. P. 1998, ApJ, 503, 848 [NASA ADS] [CrossRef] [Google Scholar]
  47. Kjeldsen, H., & Frandsen, S. 1991, A&AS, 87, 119 [NASA ADS] [Google Scholar]
  48. Koch, D. G., Borucki, W. J., Basri, G., et al. 2010, ApJ, 713, L79 [NASA ADS] [CrossRef] [Google Scholar]
  49. Kochukhov, O. 2006, A&A, 446, 1051 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  50. Kochukhov, O., & Ryabchikova, T. 2001, A&A, 374, 615 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  51. Kochukhov, O., Ryabchikova, T., Bagnulo, S., & Lo Curto, G. 2008, A&A, 479, L29 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  52. Kochukhov, O., Bagnulo, S., Lo Curto, G., & Ryabchikova, T. 2009, A&A, 493, L45 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  53. Kochukhov, O., Alentiev, D., Ryabchikova, T., et al. 2013, MNRAS, 431, 2808 [NASA ADS] [CrossRef] [Google Scholar]
  54. Kornilov, V., Sarazin, M., Tokovinin, A., Travouillon, T., & Voziakova, O. 2012, A&A, 546, A41 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Kreidl, T. J., & Kurtz, D. W. 1986, MNRAS, 220, 313 [NASA ADS] [Google Scholar]
  56. Kreidl, T. J., Kurtz, D. W., Bus, S. J., et al. 1991, MNRAS, 250, 477 [NASA ADS] [CrossRef] [Google Scholar]
  57. Kurtz, D. W. 1978, IBVS, 1436, 1 [NASA ADS] [Google Scholar]
  58. Kurtz, D. W. 1982, MNRAS, 200, 807 [NASA ADS] [CrossRef] [Google Scholar]
  59. Kurtz, D. W. 1985, MNRAS, 213, 773 [NASA ADS] [CrossRef] [Google Scholar]
  60. Kurtz, D. W. 1991, MNRAS, 249, 468 [NASA ADS] [CrossRef] [Google Scholar]
  61. Kurtz, D. W., & Martinez, P. 1987, MNRAS, 226, 187 [NASA ADS] [CrossRef] [Google Scholar]
  62. Kurtz, D. W., & Martinez, P. 1994, IBVS, 4013, 1 [NASA ADS] [Google Scholar]
  63. Kurtz, D. W., & Martinez, P. 1995, IBVS, 4209, 1 [NASA ADS] [Google Scholar]
  64. Kurtz, D. W., Sullivan, D. J., Martinez, P., & Tripe, P. 1994a, MNRAS, 270, 674 [NASA ADS] [Google Scholar]
  65. Kurtz, D. W., Martinez, P., & Tripe, P. 1994b, MNRAS, 271, 421 [NASA ADS] [Google Scholar]
  66. Kurtz, D. W., Martinez, P., Koen, C., & Sullivan, D. J. 1996, MNRAS, 281, 883 [NASA ADS] [CrossRef] [Google Scholar]
  67. Kurtz, D. W., van Wyk, F., Roberts, G., et al. 1997a, MNRAS, 287, 69 [NASA ADS] [CrossRef] [Google Scholar]
  68. Kurtz, D. W., Martinez, P.,Tripe, P., & Hanbury, A. G. 1997b, MNRAS, 289, 645 [NASA ADS] [CrossRef] [Google Scholar]
  69. Kurtz, D. W., Elkin, V. G., & Mathys, G. 2003, MNRAS, 343, L5 [NASA ADS] [CrossRef] [Google Scholar]
  70. Kurtz, D. W., Elkin, V. G., & Mathys, G. 2005a, MNRAS, 358, L6 [NASA ADS] [CrossRef] [Google Scholar]
  71. Kurtz, D. W., Elkin, V., Savanov, I., et al. 2005b, MNRAS, 358, 651 [NASA ADS] [CrossRef] [Google Scholar]
  72. Kurtz, D. W., Elkin, V. G., & Mathys, G. 2006, MNRAS, 370, 1274 [NASA ADS] [CrossRef] [Google Scholar]
  73. Kurtz, D. W., Cunha, M. S., Saio, H., et al. 2011, MNRAS, 414, 2550 [NASA ADS] [CrossRef] [Google Scholar]
  74. Martinez, P., & Kurtz, D. W. 1990, MNRAS, 242, 636 [NASA ADS] [CrossRef] [Google Scholar]
  75. Martinez, P., & Kurtz, D. W. 1994a, MNRAS, 271, 118 [NASA ADS] [CrossRef] [Google Scholar]
  76. Martinez, P., & Kurtz, D. W. 1994b, MNRAS, 271, 129 [NASA ADS] [CrossRef] [Google Scholar]
  77. Martinez, P., Kurtz, D. W., & Heller, C. H. 1990, MNRAS, 246, 699 [NASA ADS] [Google Scholar]
  78. Martinez, P., Kurtz, D. W., & Kauffmann, G. M. 1991, MNRAS, 250, 666 [NASA ADS] [CrossRef] [Google Scholar]
  79. Martinez, P., Kurtz, D. W., & Meitjes, P. J. 1993, MNRAS, 260, 9 [NASA ADS] [CrossRef] [Google Scholar]
  80. Martinez, P., Weiss, W. W., Nelson, M. J., et al. 1996, MNRAS, 282, 243 [NASA ADS] [Google Scholar]
  81. Martinez, P., Meintjes, P., Ratcliff, S. J., & Engelbrecht, C. 1998, A&A, 334, 606 [NASA ADS] [Google Scholar]
  82. Martinez, P., Kurtz, D. W., Ashoka, B. N., et al. 2001, A&A, 371, 1048 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  83. Matthews, J. M., Wehlau, W. H., & Kurtz, D. W. 1987, ApJ, 313, 782 [NASA ADS] [CrossRef] [Google Scholar]
  84. Matthews, J. M., Kreidl, T. J., & Wehlau, W. H. 1988, PASP, 100, 255 [NASA ADS] [CrossRef] [Google Scholar]
  85. Medupe, R., Kurtz, D. W., Elkin, V. G., Mguda, Z., & Mathys, G. 2015, MNRAS, 446, 1347 [NASA ADS] [CrossRef] [Google Scholar]
  86. Michaud, G. 1970, ApJ, 160, 641 [NASA ADS] [CrossRef] [Google Scholar]
  87. Michaud, G., Charland, Y., & Megessier, C. 1981, A&A, 103, 244 [NASA ADS] [Google Scholar]
  88. Mkrtichian, D. E., & Hatzes, A. P. 2005a, A&A, 430, 263 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  89. Mkrtichian, D. E., & Hatzes, A. P. 2005b, JApA, 26, 185 [NASA ADS] [Google Scholar]
  90. Mkrtichian, D. E., Hatzes, A. P., & Kanaan, A. 2003, MNRAS, 345, 781 [NASA ADS] [CrossRef] [Google Scholar]
  91. Moon, T., & Dworetsky, M. M. 1985, MNRAS, 217, 305 [NASA ADS] [CrossRef] [Google Scholar]
  92. Murphy, S. J., Bedding, T. R., Niemczura, E., Kurtz, D. W., & Smalley, B. 2015, MNRAS, 447, 3948 [NASA ADS] [CrossRef] [Google Scholar]
  93. Nelson, M. J., & Kreidl, T. J. 1993, AJ, 105, 1903 [NASA ADS] [CrossRef] [Google Scholar]
  94. Osborn, J., Föhring, D., Dhillon, V. S., & Wilson, R. W. 2015, MNRAS, 452, 1707 [NASA ADS] [CrossRef] [Google Scholar]
  95. Paunzen, E., Netopil, M., Rode-Paunzen, M., et al. 2012, A&A, 542, A89 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  96. Paunzen, E., Netopil, M., Rode-Paunzen, M., et al. 2015, A&A, 575, A24 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  97. Preston, G. W. 1974, ARA&A, 12, 257 [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  98. Renson, P., & Manfroid, J. 2009, A&A, 498, 96 [Google Scholar]
  99. Renson, P., Gerbaldi, M., & Catalano, F. A. 1991, A&AS, 89, 429 [NASA ADS] [Google Scholar]
  100. Richer, J., Michaud, G., & Turcotte, S. 2000, ApJ, 529, 338 [NASA ADS] [CrossRef] [Google Scholar]
  101. Ryabchikova, T., Nesvacil, N., Weiss, W. W., Kochukhov, O., & Stütz, Ch. 2004, A&A, 423, 705 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  102. Schneider, H., Kreidl, T. J., & Weiss, W. W. 1992, A&A, 257, 130 [NASA ADS] [Google Scholar]
  103. Schutt, R. 1991, AJ, 101, 2177 [NASA ADS] [CrossRef] [Google Scholar]
  104. Smalley, B., Kurtz, D. W., Smith, A. M. S., et al. 2011, A&A, 535, A3 [CrossRef] [EDP Sciences] [Google Scholar]
  105. Smalley, B., Niemczura, E., Murphy, S. J., et al. 2015, MNRAS, 452, 3334 [NASA ADS] [CrossRef] [Google Scholar]
  106. Turcotte, S., Richer, J., Michaud, G., & Christensen-Dalsgaard, J. 2000, A&A, 360, 603 [NASA ADS] [Google Scholar]
  107. van Leeuwen, F. 2007, A&A, 474, 653 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  108. Young, A. T. 1967, AJ, 72, 747 [NASA ADS] [CrossRef] [Google Scholar]
  109. Young, A. T. 1974, ApJ, 189, 587 [NASA ADS] [CrossRef] [Google Scholar]

Appendix

Table A.1

The known roAp stars and their physical parameters.

Table A.2

Additional parameters for the known roAp stars.

Table A.3

CP stars observed for pulsation from ARIES and SAAO and classified as null results in this survey.

thumbnail Fig. A.1

The light curves (left columns) of the pulsation candidate stars observed from ARIES/SAAO and their corresponding prewhitened amplitude spectra (right columns). The light curves have been binned to 40-s integrations.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

thumbnail Fig. A.1

continued.

All Tables

Table A.1

The known roAp stars and their physical parameters.

Table A.2

Additional parameters for the known roAp stars.

Table A.3

CP stars observed for pulsation from ARIES and SAAO and classified as null results in this survey.

All Figures

thumbnail Fig. 1

Noise characteristics at the ARIES site at Nainital and SAAO Sutherland site. The acspline-fitted curve of ARIES and SAAO amplitude spectra are shown in solid blue and dot-dashed red curves, respectively. The theoretical scintillation noise levels of ARIES and SAAO are shown with blue long-dashed and red small-dashed horizontal lines, respectively, and the scintillation noise level of SAAO (scaled to 104 cm diameter) is also shown with a green dotted horizontal line.

In the text
thumbnail Fig. 2

Positions of the null results (filled triangle) and δ-Scuti type variables discovered under the Nainital-Cape Survey (filled square). For comparison, positions of known roAp stars are also shown (open star). The solid lines show theoretical evolutionary tracks from the ZAMS (Christensen-Dalsgaard 1993). The dashed lines indicate the red and blue edges of the instability strip.

In the text
thumbnail Fig. A.1

The light curves (left columns) of the pulsation candidate stars observed from ARIES/SAAO and their corresponding prewhitened amplitude spectra (right columns). The light curves have been binned to 40-s integrations.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text
thumbnail Fig. A.1

continued.

In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.