Exoplanet Transit Search with the Westerlund Telescope

M A S T E R’S T H E S I S

2006:353 CIV

NATHALIE ÖSTBERG

Exoplanet Transit Search with the Westerlund Telescope

MASTER OF SCIENCE PROGRAMME Space Engineering

Luleå University of Technology

Department of Applied Physics and Mechanical Engineering

Division of Physics

E ^XOPLANET T ^RANSIT S ^EARCH

WITH THE

W ^ESTERLUND T ^ELESCOPE

- Nathalie Östberg -

Luleå University of Technology

2006

A ^BSTRACT

More than 200 exoplanets have been found to this day, and the quest continues.

The work behind this master thesis in Space Engineering at Luleå Univer- sity of Technology was conducted at the Uppsala Astronomical Observatory.

The purpose was to inspect if the Westerlund Telescope could be used for extra-solar planetary transit searches by photometry. Observations were made during two nights in the fall of 2005 with the 90-cm cassegrain telescope.

The centre point of the observed field had coordinates RA 20h 51min 20s,

Dec 36º 52’ 32’’. No exoplanets were found, but detection of a 1% dimming

in the light intensity was confirmed. Six variable stars were mapped and pe-

riods were calculated for four of these. A total of 32 interesting light-curves

were kept for further investigation, tentatively by another Master of Science

student.

A CKNOWLEDGEMENTS

I would like to thank my co-supervisor Johan Warell for all the help with the Westerlund telescope and for always taking time to answer my questions.

Thanks to my supervisor Claes-Ingvar Lagerkvist for his support, to Bertil Petterson for all the help with computer difficulties and Göran Henriksson for taking time to explain his computer programme used for period determina- tion. Further acknowledgement goes to my examiner Sverker Fredriksson for general advice and for carefully and constructively reading my manuscript.

Many thanks as well to my coworkers Carolina Bergfors and Jill Håkansson for good cooperation and many interesting discussions around related topics.

I would like to thank Helene Holmgren for proofreading my report and Karin Ågren for the good company during all very much needed coffee breaks.

Last but not least, loving thanks to my husband Hugo for his help with the

layout, for the illustrations of the spectrum of a cool and hot star and for his

patience during stressful times through this thesis work.

C ^ONTENTS

C HAPTER 1 - I NTRODUCTION 1

C ^HAPTER 2 - D ^{ISCOVERY METHODS} 3

2.1. D

...3

2.1.1. Radial velocity measurements ... 3

2.1.2. Astrometry ... 4

2.2. P

...4

2.2.1. Search for microlensing events ... 4

2.2.2. Planetary transits ... 5

2.3. D

...6

2.4. H

...6

2.4.1. Adaptive optics ... 7

2.4.2. Coronagraphs ... 7

2.4.3. Nulling interferometry ... 7

2.5. T

–

...7

2.5.1. CoRoT (Convection, Rotation and planetary Transits) ... 7

2.5.2. Kepler ... 8

2.5.3. Eddington ... 8

C HAPTER 3 - D IVERSITY OF EXOPLANETS 9 3.1. O

...9

3.2. E

...10

3.3. M

...10

3.4. S

...10

3.5. M

-

...11

3.6. P

-

...11

C ^HAPTER 4 - V ^{ARIABLE STAR TYPES} 13 4.1. C

...13

4.1.1. Supernovæ (SN) ... 13

4.1.2. Novæ ...14

4.1.4. Dwarf novæ ...14

4.2. E

...15

4.2.1. Luminous Blue variables (LBVs)/S Dor stars ... 15

4.2.2. Wolf-Rayet stars (WR) ... 15

4.2.3. Pre-main-sequence stars (PMS) ... 15

4.2.4. Flare stars or UV Ceti stars ... 15

4.2.5. R Coronae Borealis (RCBs) ... 15

4.3. R

...15

4.4. E

...16

4.4.1. Algol ... 16

4.4.2. β Lyrae ... 16

4.4.3. W UMa ... 16

4.5. P

...16

4.5.1. β Cephei variables ... 17

4.5.2. Be stars ... 17

4.5.3. 53 Per/slowly pulsating B variables (SPBs) ... 17

4.5.4. δ Scuti variables ... 17

4.5.5. Cepheids ... 17

4.5.6. RR-Lyrae stars ... 17

4.5.7. RV Tau stars ... 18

4.5.8. Mira-stars ... 18

4.5.9. ZZ Ceti variables ... 18

C ^HAPTER 5 - A STRONOMICAL O BSERVATIONS 19 5.1. T

W

T

...19

5.2. P

...19

5.3. C

...20

5.3.1. Bias and dark images ... 20

5.3.2 Flat-field frames ... 20

C ^HAPTER 6 – P ^{ICTURE REDUCTION} 23 6.1. C

...23

6.1.1. Master bias ... 23

6.1.2. Master dark ... 24

6.1.3. Master flat ... 24

6.1.4. Calibrated images ... 24

6.2. M

-

...25

6.3. M

...26

C ^HAPTER 7 - R ^ESULTS 27 7.1. E

...27

7.2. V

...28

7.2.1. Temperature ... 28

7.2.2. Period ... 29

7.2.3. Star #1 ... 30

7.2.4. Star #2 ... 30

7.2.5. Star #3 ... 31

7.2.6. Star #4 ... 31

7.2.7. Star #5 ... 32

7.2.8. Star #6 ... 32

C ^HAPTER 8 - C ^ONCLUSIONS 35

B IBLIOGRAPHY 37

A ^PPENDIX 1 41

A ^PPENDIX 2 53

C ^HAPTER 1 - I NTRODUCTION

Mankind has always been adventurous and curious about unknown places.

Questions as to the uniqueness of our existence have long been discussed and have driven us to explore more and more of the Universe. One way to shed light on the matter has been to find planets in other solar systems. Many different search methods are used today to fulfill the task. Since the first exo- planet was discovered in 1995 (Mayor & Queloz 1995), vigorous diversity in the extra-solar planet community has been revealed. Since this thesis work was based on the transit method, and the procedure revealed a fruitful by- product – variable stars – an introduction on their different kinds is given.

In this survey, the Westerlund telescope at the Uppsala Astronomical Obser-

vatory was used. The observation procedure is explained just as well as the

mechanism behind the picture reductions. Finally the results are depicted and

improvements on the search manner are discussed.

C ^HAPTER 2 - D ^{ISCOVERY METHODS}

A planet exerts a gravitational tug at its mother star, which in turn makes the star wobble with the same period as the planet. This dynamical effect can either be directly observed (astrometry) or detected by the means of the Doppler effect in the star’s spectral lines (radial velocity). Other techniques that are commonly used today are based on photometry, such as searches for microlensing effects and planetary transits. Last but not least, the dream of every astronomer in quest of an exoplanet is of course to get a snapshot of a planet by direct imaging. To optimize these techniques there are a few tools available today, such as the use of coronagraphs, adaptive optics and nulling interferometry. Let us look a little further into the techniques for exoplanet discovery and the telescopes used, both today and in the future.

2.1. D ^{YNAMICAL EFFECTS}

2.1.1. Radial velocity measurements

This indirect search method has been the most fruitful among today’s tech- niques. A spectrograph is used to monitor the successive red- and blueshifts of the star’s spectrum, caused by the radial movement of the star. The star’s radial velocity is then given by

, (1)

where M

is the planet’s mass in Jupiter masses, M* the star’s mass in solar masses, a the semi-major axis of the planet’s orbit in AU and i the inclina-

M

M

a

sin i

.

tion from the sky-plane (Clark 1998). Since the amplitude of the oscillation is small, detections require stabile and precise measurements; the radial velo- city ought to be four times higher than the sensitivity of the spectrograph. In spite of good instruments, the radial velocity method remains dependent on the inclination of the observed star-planet system and thus only a minimum mass can be estimated.

2.1.2. Astrometry

The same physical phenomenon as in radial velocity measurements is used in astrometry – the wobble of stars caused by planets in orbit. The differen- ce is that instead of measuring the Doppler effect, real observations of the oscillations are made. The movement, measured in microarcseconds, can be approximated by the following formula

, (2)

where the input data are the same as in equation (1) and D is the distance to the star in parsec. The downside of this method is the requirement for the star to be relatively near. As equation (2) shows, the magnitude of the observed movement will half when the distance to the star is doubled. Furthermore, only large planets in large orbits can be expected to be detected in earth-based astrometric searches, because a planet in larger orbit will make the star’s orbit larger. From a distance of 10 pc, Jupiter seems to cause the Sun to swing with a maximum movement of 500 microarcseconds. The Earth, on the other hand, contributes to the Sun’s dance with a meagre 0.3 microarcseconds at the same distance. Since the signals are faint, space-based interferometers are needed to detect them (Clark 1998).

2.2. P ^HOTOMETRY

A lot of information can be found when monitoring the intensity of light reaching us from stars. Regarding the quest for extra- solar planets, one can proceed in the following two manners. Either one looks for intensifica- tion of the light intensity due to microlensing events, or drops in the light-curves, which in turn are caused by planetary transits.

2.2.1. Search for microlensing events When a foreground object passes either through or nearby the line of sight of an observed background star, the light-curve of the latter shows a well-known pattern: the in- tensity of light increases symmetrically. This Figure 1. Plot of the gravi-

tational microlensing effect created from theoretical cal- culations by Benett & Rhie (1996). The axes show the number of times the inten- sity is magnified versus time (retrieved at http://www.as- tro.livjm.ac.uk/courses/one/

NOTES/smlens.htm).

M

M

D .

space and behaves like a lens (Bond et al. 2004). If that star has a planetary companion in orbit, a small disturbance can be detected in the light-curve, as shown in figure 1. To date, four planets have been found with the microlensing technique, of which the latest is one of the smallest exoplanets ever found, a planet of 5.5 Earth masses orbiting at 2.6 AU from its parent star, an M-dwarf (Beaulieu et al. 2006).

2.2.2. Planetary transits

When a planet passes in front of its parent star it causes a dip in the monitored light intensity curve, as illustrated by figure 2. The amplitude of the dimming is proportional to the ratio of the radii, as shown in equation 3:

, (3)

where F is the flux, Rp and R* the radii of the planet and star (Bordé et al.

2001). The duration of the intensity drop depends on the distance between the two objects, a. After timing the transit duration t and orbital period P, it is possible to calculate the impact parameter k – the height over the equator at which the planet is passing:

, (4)

Figure 2. Superposed light- curves of star HD 209458 showing transits occurring during two nights in Septem- ber 1999, detected by STARE project astronomers. The axes show the relative inten- sity flux versus time (Char- bonneau et al. 2000).

R

R

F =

2

cos k = P . R

Finally, the inclination can be calculated as follows:

, (5)

revealing the true planet mass missed in the radial velocity searches. Even though thousands of stars can be monitored at the same time, only a few planetary transits can be detected. The Earth must lie near the plane of the planet’s orbit in order for it to produce a transit. The geometrical probability of transit at an inclination close to 90° making the transit visible is given by the following ratio (Bordé et al. 2001):

. (6)

Obviously, the probability increases for close orbiting planets. Furthermore, a planet the size of Jupiter would cause a 1% drop in the light intensity from a Sun-like star, whereas an earth-like planet would cause a drop of only 0.01%, which is only detectable from space (BEST homepage). The transit method is therefore best suited for giant planets in close orbits, at least for ground-based observations. The biggest challenge is to identify the planetary transits from anomalies. Light-curves emanating from eclipsing binary stars, triple systems or even stellar companions of planetary size but not planetary masses can easily be mistaken for planetary transits (Brown 2003). The transit method has though been useful as a complement to radial velocity searches as to determine exact mass and radius (Bouchy et al. 2005).

2.3. D ^{IRECT IMAGING}

There are many advantages with direct imaging. There are no restrictions to star types, masses or system inclination. Long-period planets do not require long observation times like those needed for radial velocity surveys (Lagrange et al. 2004). To date, only four possible candidates have been directly detected. The main discussion has been around the type of the com- panions because of their large masses: how does one tell if the companion is indeed a planet or a brown dwarf? To differentiate extra-solar planets from the failed stars, the International Astronomical Union has come forward with the following two criteria: first, brown dwarfs have masses above 13.6 M _Jup , which is the minimum mass of deuterium burning. Second, the formation of the object plays an essential role; either the object has started its life by gravitational collapse, which is the case of a star, or it has formed due to core accretion and finally become a planet (Chauvin et al. 2005).

2.4. H ^{ELPFUL TOOLS}

The two major problems to overcome when looking for the weak signal of an exoplanet are the turbulence of the atmosphere in earth-based observations and the weakness of the planet’s signal compared to the one originating from the parent star. To compensate, a few helpful tools are at hand, like adaptive cos i = R

. sin ka

R

P

= a

2.4.1. Adaptive optics

An incoming wave front is constantly broken into different rays in the at- mosphere, causing a smeary disc instead of a bright spot on the image plane.

This distorted beam can be contorted back to its original uniform pattern by adapting the optics to the turbulence of the atmosphere. The distortions in the wavefront of a guide star in the same field of view than an observed star can be measured and used to calculate the corrections needed to the deformable mirrors. However, this procedure must be extremely fast because the varia- tions in the atmosphere are of a fiftieth of a second (Clark 1998).

2.4.2. Coronagraphs

In order to detect an exoplanet by direct imaging, the intensive light from the parent star must be blocked since the flux ratio between the two objects is huge. An earth-like exoplanet would typically be 6x10 ⁹ times fainter than its stellar companion in the visible and 7x10 ⁶ times fainter in the thermal infra- red (Mawet & Riaud 2005). Thus, coronagraphs are used to produce artificial stellar eclipses.

2.4.3. Nulling interferometry

An alternative way to extinct the intensive stellar light is to use destructive interference between two coherent beams. Before combining the beams of light recovered in two separate telescopes, one ray is delayed by half a wave- length. Peaks from one beam are then added to the slopes of the other, leaving no starlight at all. This canceling procedure works only on objects that are directly pointed at. Thus, the light coming from an orbiting planet will be slightly off-axis and even though one of the beams is delayed as well, the light will rather be reinforced than cancelled out.

2.5. T ELESCOPES – TODAY AND IN THE FUTURE

Only experiments based on planetary transits will be mentioned here, because it is the procedure used in this thesis work and because of the promising pros- pects of the transit method in space-based telescopes. More than 20 surveys focused on planetary transits are either ongoing or planned in the near future (Horne 2001), of which the following three are space-based.

2.5.1. CoRoT (Convection, Rotation and planetary Transits)

A 27-cm telescope equipped with four CCD wide-field cameras will be

launched in December 2006 for a 2.5-year long mission. The satellite will be

placed in polar circular orbit at an altitude of 896 km. The project is led by

french CNES and is focusing on terrestrial planets, just as well as asteroseis-

mology (CoRoT homepage).

2.5.2. Kepler

Kepler is a 1.4-metre telescope with a large field-of-view and four CCD cameras. The launch of the satellite is planned for 2008 by NASA. The instrument will monitor more than 100,000 stars for planetary transits during a period of four years from an earth-trailing heliocentric orbit. The mission’s focus will be on finding earth-like planets in the habitable zone around stars (distances from the star where liquid water can be found) and examine the diversity and structure of planetary systems (Kepler homepage).

2.5.3. Eddington

‘It would indeed be rash to assume that nowhere in the Universe has Nature repeated the strange experiment which she performed on the Earth’. Arthur Eddington’s words from 1933 will follow the European Space Agency’s satel- lite Eddington on its journey to the second Lagrangian point (L2), 1.5 million km in the anti-Sun direction, in 2008. The advantages of L2 are stable ther- mal and radiation environment and the fact that the Sun, Earth and Moon are always behind the satellite’s viewing direction. This precision photometer will search for planetary transits during three years of its five-year long mission.

The other goal of its mission is stellar seismology, just as it is for CoRoT

(Eddington homepage).

C ^HAPTER 3 - D ^{IVERSITY OF EXOPLANETS}

To date, 179 planetary systems and a total of 209 exoplanets have been found.

As many as 21 of the stars harbour more than one planet (Schneider 2006).

The following properties are derived from the ongoing 18-year search of 1330 stars of spectral classes F, G, K or M at Lick, Keck and the Anglo-Australian Telescopes that provide uniform Doppler precision of 3 m/s. Different masses, semimajor-axes and eccentricities were reported among the discovered planets and a preliminary planet occurrence rate could be established. A correlation between the metallicity of the host star and the probability of orbiting planets was determined and a few multiplanet systems were found (Marcy et al. 2004).

Furthermore, planets tend to be spotted in the most extraordinary places, around pulsars just as well as floating on their own.

3.1. O ^CCURRENCE

Of the 1330 monitored stars, 88 have been found to harbour planets of masses

M < 13 M _Jup . In other words, 6.6% of the stars in the survey have planetary

companions within 5 AU. This should be seen as a lower limit since stars

between 3 and 5 AU are not effectively detected because of the restricted dura-

tion (6 - 8 years) of the Doppler measurements. In addition, low-mass planets

beyond 1 AU are certainly missed because of their only subtle wobble. About

5% of the stars in the survey seem to have long-term velocity disturbances,

which could be caused by a planetary companion at a distance between

5 and 20 AU. Bearing this in mind, an extrapolation of the statistics suggests

a 12% occurrence of extra-solar giant planets (EGPs) within 20 AU (Marcy

et al. 2005).

3.2. E CCENTRICITY

Eccentric orbits tend to dominate within the extra-solar planet community, on average e = 0.34 for planets within 0.2 - 3.5 AU (Marcy et al. 2004). Close orbiting planets have near-circular orbits though, probably due to tidal effects.

Furthermore, massive planets are connected to high eccentricities, posing the question about the nature of their initial orbits. High-mass planets have the vastest resistance to perturbations that are needed to force them out of their initial orbits.

3.3. M ASS DISTRIBUTION

Fewer high-mass than low-mass planets have been spotted. Figure 3 depicts the planet mass distribution, decreasing as M ^-1.05 with rising masses (Marcy et al.

2005). It is important to remember that, as mentioned before, only mini- mum masses can be calculated by radial velocity measurements because of the uncertainty in the inclination i, although it should affect the distribution only slightly.

3.4. S EMIMAJOR AXIS AND MIGRA -

TION

As shown in figure 4, the orbits of the 104 planets found in the survey have semi- major axes in the interval 0.02 - 6.0 AU.

Of them, 16 have been detected within 0.1 AU, suggesting that 1.2% of FGK main-sequence stars harbour hot Jupiters – gas giants in close orbits. The fact that EGPs have been detected as close as 0.022 AU (Heap et al. 2005) from their mother star, can be explained by migra- tion processes. Giant planets ought to form beyond 3 AU where large amounts of cool gas can be accreted. The planets may then lose energy and angular mo- mentum to the disk, which causes them to move inwards (type I). Another expla- nation would be that the gas disk itself would accrete onto the star and thus tug planets along with it (type II) (Marcy et al. 2005).

Figure 3. Planet mass distri- bution of the 104 exoplanets, following the best fit negative power law. Axes show the number of planets versus minimum masses (Marcy et al. 2005).

Figure 4. Distribution of

planets according to the

semimajor axes of their orbits

(Marcy et al. 2005).

3.5. M ETALLICITY AND MULTI - PLANET SYSTEMS

Stars with high metallicity tend to harbour more planets. In the above men- tioned survey, about 25.0% of the most metal-rich stars have a planetary companion, while less than 3.0% of the stars with low metallicity harbour planets (Marcy et al. 2005). The probability of forming planets can be featured in the following power law:

, (7)

which figure 5 illustrates (Fisher & Va- lenti 2005).

More and more stars with multiplanet systems are discovered each year. Al- though too few such stars have been found so far in order to establish statis- tics, the following trend has been noted.

The mean metallicity of stars with mul- tiple-planet systems is higher than for those with only one detected planet (Fisher & Valenti 2005).

3.6. P ^{ULSAR PLANETS AND FREE} - ^{FLOATING PLANETS}

The first exoplanets were discovered around a rapidly rotating neutron star through pulsar timing. In 1991, Wolszczan and Frail detected anomalies in the pulses emanating from the millisecond pulsar PSR1257+12, due to planets in orbit (Wolszczan & Frail 1992). A circumstellar disk resembling the proto- planetary disks found around ordinary young stars has recently been spotted around a pulsar, suggesting that planets are born around the dead remnants (Chakrabarty 2006).

Planets have just as well been found to be ‘alone’ in the interstellar medium and their origin is still a mystery. These free-floating planets could have been formed – like the favoured theory of planet formation today states – by accreting matter from the surrounding disk of a star and then by being ejected into the surrounding interstellar space due to gravitational perturbations. Or, they might have been born out of the gravitational collapse of molecular gas and dust (Boss 1997).

Figure 5. Percentage of stars harbouring planets with re- gard to the metallicity of the parent star (Marcy et al.

2005).

N

N

N

N

Sun

P

= 0.03

C ^HAPTER 4 - V ^{ARIABLE STAR TYPES}

The classification of variable stars is founded on the origin of the light intensity variations. If the disturbance is due to physical changes in the stellar system, it is called intrinsic. On the other hand, an extrinsic variation is caused by either stellar rotation or an eclipse of one star by another. Following the General Cata- logue of Variable Stars, also called the GCVS, variables can be filed in the following categories: cataclysmic, eruptive, pulsating, rotating and eclipsing variables (Sterken & Jaschek 1996; AAVSO).

4.1. C ^{ATACLYSMIC VARIABLES}

Stars that occasionally burst out because of thermonuclear processes within their interiors or their surface layers are categorized in the following four sub- classes of novæ: supernovæ, novæ, recurrent novæ and dwarf novæ.

4.1.1. Supernovæ (SN)

The catastrophic explosion of a massive star is shown by a dramatic increase

of its light intensity up to 20 magnitudes, followed by a slow decline. Super-

novæ can be classified into two groups: type I and type II. The latter shows

a plateau in its light-curve, and is typically two orders of magnitude fainter

than type I. Different mechanisms are found behind the explosions. Type I SN

is due to the thermonuclear runaway process in a massive white dwarf that

has accreted enough mass from a close neighbouring main-sequence star

to overcome the Chandrasekhar limit. It starts to burn carbon and disinte-

grates eventually because of a sufficient amount of released energy. As for the

type II SN, gravitational core collapse triggers the explosion.

4.1.2. Novæ

Just as for the type I SN, a nova is the outcome of a white dwarf that has accreted enough mass from a close main-sequence star to initiate thermo- nuclear processes, although the outbursts are located in the surface layers.

The typical characteristic in the light-curve is the fast and large amplitude increase by the time of the ejection of the outer shell (8 - 15 magnitudes increase). After the outburst, the intensity slowly decreases to its original brightness, typically after a couple of hundred days. Near its peak, the spec- trum is comparable to that of an A or F giant star.

4.1.3. Recurrent novæ

The mechanism behind a recurrent nova seems to be the same as for a nova with the exception that the secondary star is a red giant. The outbursts have furthermore been observed more than once, and the decline of the intensity is faster after the peak. Periods span from 1 to 200 days and the amplitude of the variations can be from 4 to 9 magnitudes. All novæ might be recurrent though, given enough time.

4.1.4. Dwarf novæ

This category of cataclysmic variables contains a white dwarf, its surround- ing accretion disk and a red main-sequence star losing mass to the primary.

This group is divided into three sub-classes – U Geminorum, Z Camelopar- dalis and SU Ursa Majoris – and their characteristics are as follows.

- U Geminorum or SS Cygni variables

Instability in either the accretion disk or the secondary star creates an augmentation of the mass flow to the primary, which in turn bursts out. The light-curves show a sudden brightening of 3 - 8 magnitudes within a day, followed by a bright phase of 3 - 10 days and finally a decay of a few days. The process has a periodicity of 30 - 100 days.

- Z Camelopardalis

These systems show cyclic variations, which are interrupted by an epoch of constant brightness, called standstills. The intensity level is fixed at approxi- mately two thirds of minimum brightness and lasts for several cycles. Stand- stills occur when the mass transfer rate from the secondary and the mass accretion rate are temporarily stable, and they end when the mass flow declines under a critical level.

- SU Ursa Majoris

The light-curves of SU Ursa Majoris show faint, frequent and short outbursts

every 15 - 40 days as well as bright, sparse and 10 - 20 days long explosions,

occurring at intervals of six months to several years. The latter, so-called

superoutbursts, are believed to be the fruit of tidal instabilities in the accretion

superoutbursts, periodic variations called superhumps occur, and are 3 - 5%

longer than the orbital period. These are thought to be the result of elliptical, tidal-driven deformations in the accretion disk.

4.2. E RUPTIVE VARIABLES

4.2.1. Luminous Blue variables (LBVs)/S Dor stars

Hypergiants, LBVs or S Dor variables are massive and luminous stars that have three types of variation: large eruptions, which occur on time-scales of centuries, moderate photometric variations at time-scales of decades and microvariations that are not strictly periodic. During outbursts, S Dor stars are the brightest stars in the Universe – apart from SN. At present, only a few dozen LBVs have been spotted in our galaxy.

4.2.2. Wolf-Rayet stars (WR)

All massive stars above a certain mass limit pass through a WR-phase when going from the main-sequence to the end of their lives. The period is characterized by high temperatures between 30,000 and 50,000 K and extreme brightness. Absorption lines matching spectral types O and B are found, as well as strong C, N, O, He and Si emission lines.

4.2.3. Pre-main-sequence stars (PMS)

PMS stars have recently been born out of interstellar matter and have not yet ignited hydrogen-burning in their cores. These stars show large and com- plex variety in their variations, with both quasi-periodic and mostly irregular variations of several different amplitudes.

4.2.4. Flare stars or UV Ceti stars

These are stars of spectral class K or M, which often show emission lines in their spectrum. They are either late-type dwarf or main-sequence stars that burst out locally on their surface. The eruptions result in an intensity augmen- tation of several seconds up to 6 magnitudes, succeeded by a decline down to normal brightness in about 10 - 20 minutes.

4.2.5. R Coronae Borealis (RCBs)

Stars belonging to this category are hydrogen-low, carbon-rich F or G supergiants, which irregularly decline up to 9 magnitudes in brightness. The decline is abrupt – about a few weeks – compared to the slow recovery, which can persist up to three years.

4.3. R ^{OTATING STARS}

Small changes in light intensity can depend on bright and dark star spots on

stellar surfaces or thermal and chemical irregularities in stellar atmospheres.

These occur when the rotation axis does not coincide with the magnetic axis of the star.

4.4. E CLIPSING BINARY STARS

Binaries with orbital planes near our line of sight eclipse one another periodically.

The light-curves show typical dips in the apparent brightness, with a period corresponding to the orbital period of the system. These spread from minutes to years. Depending on the inclination of the binary’s plane, a plateau will or will not form in the minimum of the light-curve. This feature is shown in figure 6 where a total eclipse is observed. Eclipsing binaries are further clas- sified in the following three groups; Algol, β Lyrae and W UMa systems.

4.4.1. Algol

Just as depicted in figure 7, a light-curve of an Algol type system shows a noticeably large difference in minima. This indicates that the binary is com- posed of one significantly brighter star than the other. Furthermore, the

constant brightness illustrated by the flat-topped feature in the light-curve reveals that the two stars are very distant from one another, having either large periods or orbits.

4.4.2. β Lyrae

As illustrated in figure 8, β Lyrae systems have just as Algol types noticeable differences in the light drops. The main difference is the constant variation in brightness, showing the proximity of the two stars.

4.4.3. W UMa

A W UMa system is constantly changing in its luminosity and no difference can be discerned between the two minima (see figure 9). Thus, the two stars are similar in surface brightness and are usually in contact with each other, resulting in short periods (7 hours up to one day).

4.5. P ^{ULSATING VARIABLES}

These stars have periodically expanding and contracting surface layers. The phenomenon can be either radial or non-radial. In the first case, the star keeps a spherical shape, while in the other it can deviate from its spherical form.

The following star types are identified by the mass, the evolutionary status Figure 6. Computer gene-

rated plot of an eclipsing binary, both with and without a total eclipse. Axes show the intensity of light in the visual band versus the phase of the period, with the origin at the first minimum (retrieved at http://binaries.boulder.swri.

edu/binaries/papers/rew_

iappp_94/).

Figure 7. Light curve of a binary of Algol type. Notice the large difference between the two minima caused by two stars with a large tempera- ture difference. Axes show magnitude versus the phase of the deepest light drop (retrieved at http://hal9000.

ps.uci.edu/Shih%20Thesis.

doc).

4.5.1. β Cephei variables

Stars belonging to this category are B giants and subgiants, which show both photometric and radial velocity variations of short periods (2 to 7 hours).

Purely geometric effects (rotation or binary motion) cannot explain the short periods, which are in fact due to pulsa- tions. The range of the light variation is less than 0.2 mag.

4.5.2. Be stars

Variables of spectral types from O6 to B9 with emission lines in the Balmer series and a rapidly-rotating circumstellar envelope or shell are categorized as Be stars.

4.5.3. 53 Per/slowly pulsating B variables (SPBs)

O8 and B5 stars with variable periods of the order of a day and amplitudes of a few 0.01 mag are classified as non-radial pulsators.

4.5.4. δ Scuti variables

Pulsating variables of spectral classes A or F with periods less than 0.3 days and amplitudes of a few thousands of a magnitude to about 0.8 mag fall under this category. The amplitudes can vary strongly from day to day due to super- position of many pulsations, caused by a complex internal structure.

4.5.5. Cepheids

Massive stars with high luminosity of spectral types from F to K, Cepheids, have a period-luminosity relationship; the brighter the star, the longer the period. Variations in amplitude are small (0.1 - 2.0 mag) and periods can be from 1 day to 70.

4.5.6. RR-Lyrae stars

These white giant stars have short periods (0.2 - 1.0 days) and are generally older and more massive than Cepheids. They are of spectral type A and do not vary immensely (0.3 - 2.0 mag).

Figure 8. Light-curve of a β Lyrae binary. Axes show the variation of the light in- tensity versus the phase of the light drops (retrieved at http://hal9000.ps.uci.edu/

Shih%20Thesis.doc).

Figure 9. Light-curve of a W UMa binary. The constant variation of the light inten- sity is due to the vicinity of the two stars. Axes show the magnitude versus the phase of the variation (retrieved at http://hal9000.ps.uci.edu/

Shih%20Thesis.doc).

4.5.7. RV Tau stars

These pulsating stars are yellow supergiants of spectral class extending from F to K. Their light intensity can vary by up to 3.0 magnitudes, with alterna- ting deep and shallow minima during periods of 30 - 150 days.

4.5.8. Mira-stars

Giant red variables with periods of 80 - 1000 days, amplitudes of variation of 2.5 - 5.0 magnitudes and of spectral types M, C and S that have well defined periodicities are long-period variables. Mira-stars show characteristic emis- sion lines due to shock waves associated with pulsations. In the Hertzsprung- Russel diagram, these giants are found at the tip of the asymptotic giant branch where they are short-lived. Their next phase is becoming a planetary nebula.

4.5.9. ZZ Ceti variables

Non-radially pulsating white dwarfs with amplitudes reaching 0.2 mag during

periods ranging from 30 seconds to 25 minutes fall under this last category of

pulsating variables.

C ^HAPTER 5 - A STRONOMICAL O BSERVATIONS

5.1. T ^HE W ^ESTERLUND T ^ELESCOPE

Observations were made with the Westerlund telescope at the Uppsala Astronomical Observatory on several nights during the fall of 2005 (figures 10 and 11). Only observations on the nights of September 6 and October 18, 2005 gave useful data, without cloud formations cutting short the studies. The telescope shown in figure 12 is a 90-cm classical Cassegrain reflector. The mounted CCD-camera (figure 13), an SBIG STL-1001E, with a pixel array of 1024x1024, has a field-of-view of 18.8’x18.8’.

5.2. P ^ROCEDURE

The field of interest in Cygnus has centre coordinates RA 20h 51min 20s, Dec 36º 52’ 32’’ and is located in the outskirts of the Milky Way. The field was chosen not too close to zenith in order for the derotator (which the camera is mounted on) to be able to compensate for the rotation of the field. After syn- chronizing the angle of rotation with the actual field of interest by comparing a taken picture with the planetarium software used (The Sky), only one last matter had to be attended to before the sequence of pictures could begin. The telescope had to be focused, which could be difficult depending on the night.

Also, refocusing might be necessary during the night.

The sequence of pictures was taken in the following manner. The field was

split into 9 squares of width 18’. Every square of the mosaic overlaid its neigh-

bour by 3’ in order to compensate for possible drift during the night. Two

next. The first picture was taken in the upper right corner of the field, the following two under the first.

Tile number 4 was placed at the centre upper corner and its followers beneath. The three remaining tiles were at the left upper corner and below. The se- quence is illustrated by figure 14. Since the CCD’s highest quantum efficiency is in the red wavelength region, the R-filter was used and the exposure times were 5 and 30 seconds. The full sequence took about 7 minutes, meaning that about 35 pictures of each square could be taken during one night. On the night of September 6, two fields were observed.

Thus only half as many pictures were taken that night on this particular field, compared to the night of October 18.

5.3. C ALIBRATION IMAGES

A picture consists of more than just useful data.

There are different kinds of noises automatically integrated in the image: a bias level, a dark current and the response of the optical system. These disturbances must be removed in order for the pho- tometric studies to be correct.

5.3.1. Bias and dark images

In every image there is a constant bias level, re- sulting from internal electronics (fixed pattern) and nearby interferences (unpatterned events).

In order to remove this noise, a sequence of bias images (exposure time 0 seconds) was taken after each night.

A time-dependent dark current must be subtracted as well. This unwanted current is caused by ther- mal emission of electrons from the silicon substrate of the CCD. Obviously atomic agitation increases with temperature, therefore the CCD must be held at a constant low temperature (about 20 ºC below the dome temperature) both during observation and during the sequence of calibration images. Dark images of exposure times 5 and 30 seconds were taken after each night.

5.3.2 Flat-field frames Figure 10. The Uppsala As-

tronomical Observatory.

Figure 11. The opening shaft

of the dome.

to a uniform field of light of the mirrors, filters, the telescope itself and so on, as well as the CCD sensi- tivity variations (Berry & Burnell 2000). There are several ways to take flat-field frames.

-Twilight flats

Exposures of the twilight sky are taken. These can correct for all types of sensitivity variations. The disadvantage of the method is that the brightness of the sky changes rapidly and it can be difficult to take enough pictures before it is either too dark or too bright (Oliver 2004).

-Dome flats

Exposures are taken on a white screen mounted into the dome. The target is completely out of focus and thus effectively uniform. This method is very good on pixel to pixel variations but not as good on penumbral shadowing (dust or dirt on the mirror or filters appearing as smudged doughnuts on the images). Even vignetting (a gradual dar- kening towards the corners and sides of the image caused by various out-of-focus obstacles in the light path, such as the support for the secondary mirror) is badly corrected for. This is due to the slightly different angle at which the light reflected from the dome is incident on the telescope compared to the light coming from the sky (Davenhall et al. 2001).

-Sky flats

Raw images are median combined in order to remove stars and are then used as flats. This gives a good correction to vignetting and penumbral shadowing but poor correction to pixel to pixel variations (Oliver 2004).

Dome flats were taken after each night, including bias and dark images to calibrate the flats. The procedure will be explained in the next chapter.

Figure 14. The sequence of pictures was taken just as the map over the 9 tiles of the mosaic shows, starting in the upper right corner. Two images were taken in each tile before the telescope was slewed into the next. Each picture overlaped its neigh- bour by 3’.

Figure 13. The derotator and

the CCD-camera.

C ^HAPTER 6 – P ^{ICTURE REDUCTION}

The reduction pipeline used for photometry with the Westerlund Telescope is an updated version of the same programme used by the Institut für Planeten- forschung in Berlin, where it has been run with success for photometry with BEST (Berlin Exoplanet Search Telescope). The programming language is IDL.

6.1. C ^{ALIBRATION OF THE PICTURES}

While the signal coming from the observed object is constant, noise is ran- dom; it changes from image to image. By adding two images, the signal from the object is doubled while the noise is increased by only 40% (Starizona 2006). And so, in order to minimize random noise, one should combine as many bias, dark and flat field frames as possible. This, of course, requires more observing time but is rewarded by significantly more accurate calibrated images with high signal-to-noise ratios. A total of 100 bias images and 50 dark frames were taken after each night, right after the observations.

6.1.1. Master bias

The 100 bias pictures were median combined. By choosing the median

instead of the average of the frames, precautions were taken against extreme

pixel values due to possible cosmic-ray events (Berry & Burnell 2000). Thus,

a mean level of internal static over all pixels was recovered in a master bias

frame, depicted in figure 15.

6.1.2. Master dark

The dark frames contain both the bias level and the thermal electrons captured during the integration time. The mas- ter bias frame has to be subtracted from each dark image before these are, in turn, median combined, resulting in a master dark frame shown in figure 16.

6.1.3. Master flat

The flat field screen mounted inside the dome was used. A prewritten routine took bias, dark and flat-field images on the screen. Both master bias and master dark frames were created in the same way as explained before, and subtracted from the flat-field images. These were in turn median com- bined, resulting in a master flat frame. Smudged doughnuts caused by dust or dirt on the mirrors or filters can be seen in the master flat shown in figure 17.

6.1.4. Calibrated images

Figure 18 shows an uncalibrated light frame where the back- ground varies significantly from the centre of the image towards the edges and corners, due to vignetting. The master bias and master dark frames were subtracted from the raw images and the result was then divided by the master flat frame.

As shown in figure 19, the calibrated images had back- ground brightness variations extending to 20%. It seemed though that the calibrated images from the end of the night had less background variations. The fact that the dome flats were taken after the observation session – with the derotator at the same angle as the last sequence of images – could explain the variation differences. To test the assump- tion, the master flat was first rotated backwards in order to correspond to the same angle at which the light frames of each sequence were taken and then used to calibrate the images. Unfortunately, the optical system of the Wester- lund telescope has asymmetrically rotating components;

the primary, secondary and tertiary mirrors as well as the filter wheel, CCD-camera and the focal reducer/corrector.

Lacking the symmetry, a rotated master flat ended up cor- recting for misplaced variations in the light frame.

As a second option, a sequence of dome flats was taken for every angle of rotation and a master flat was created Figure 15. Master bias.

Figure 16. Master dark.

background brightness variations persisted. As mentioned before, dome flats tend to correct poorly on vignetting and penumbral shadowing, just as witnessed.

Finally, a different approach was made. The nine light frames taken in each sequence were median-combined with the soft- ware MaximDL and one master flat frame was created for every sequence from the background of the images. By median-combining the frames, stars were cancelled out and left was a grainy surface that needed to be smoothened. By using IRAF, a smooth surface function was applied on the flats resulting in a statistically smoothened image. These corrected flats were then used to flatten the pictures, and they gave the best results just as figure 20 shows. The two black margins are due to the alignment of the pictures, as mentioned further on.

6.2. M ^{AKING LIGHT} - ^CURVES

Images of the same part of the sky were aligned with MaximDL to compensate for drift during the night. Dif- ferential photometry was applied by the reduction pipeline, which first searched for the brightest objects in the images to use as reference stars. It calculated then the average magnitude difference for each bright star from image to image. Stars with most constant brightness and highest signal-to-noise ratio were automatically chosen as references to correct for atmospheric turbulence during the night.

Finally, Julian date was calculated for all images (number of days from January 1st, 2000) and magnitude plots were drawn for every star. Each and every one of the 18,000 light-curves was manually scrutinized and interesting light- curves were saved for further inspection.

Light-curves with errors caused by the following were discarded:

- Irregular flat-field in the area (could be detected when comparing nearby stars for the same odd variations).

- Stars drifting partly or totally in and out of the frame during the night. The telescope could not be pointed at exactly the same field centre for each sequence, and that is why the images were aligned in order to compensate for the drift. This caused stars in the edges to disappear in some images.

- The programme could catch two different stars in one light-curve if they were too close to each other.

- In crowded areas, the part of the aperture monitoring the background light could capture a star instead.

Figure 18. Raw light frame.

Figure 19. Unsuccessful flat-

tened picture.

6.3. M AGNITUDE CORRECTION BETWEEN THE TWO NIGHTS

In order to adjust for atmospheric opacity and transparency between the two

nights, five stars with constant intensity in the neighbourhood of every inte-

resting star were chosen. The mean difference between the magnitudes of

the stars from the night of October 18 and the night of September 6 was cal-

culated and inserted in the pipeline. The night of October 18 was used as a

reference against which the light-curves of the stars from the night of

September 6 were corrected. This means that the same magnitude correction

was taken for the whole night and no correction was made from image to

image. Higher photometric precision would have been obtained in the light-

curves if the magnitude correction was made for each interesting star and

for each frame. For future reference, this could be coded and automatically

executed by the pipeline.

C ^HAPTER 7 - R ^ESULTS

7.1. E ^XOPLANETS

At the Institute for Planetary Research of the German Aerospace Center (DLR), a 19.5-cm Schmidt telescope is used for planetary transit search. The Berlin Exoplanet Search Telescope (BEST) can detect about 30,000 - 40,000 stars in a field. Of these, about 4000 are in the magnitude range 10 - 14, where high-precision measurements of a 1% dimming of the light intensity can be done. As mentioned earlier, a planet the size of Jupiter would cause a 1% drop in the light intensity from a Sun-like star, whereas an earth-like planet would cause a 0.01% drop, only detectable from space. Furthermore, only 20%

of the stars are FGKM main-sequence stars. The rest of the stars are too large compared to a Jupiter-sized planet, resulting in a light-intensity drop too small to be detected by the telescope. Considering data from observations during 20 - 50 nights, the expected number of detected transiting planets is one (Rauer et al. 2004).

Within the observed field by the Westerlund telescope, about 14,000 stars were

detected. Of these, 1400 were in the magnitude range where planetary transits

could be spotted. The light intensity drop must be deeper than the error due to

instrumental noise. This is illustrated by the RMS-plot in figure 21, where

the horizontal line shows the 1% noise limit. As shown, stars down to magni-

tudes of 14 can be monitored for planetary transits. Furthermore, only two

nights were spent on observation. A quick comparison between the conditions

of the two searches, and bearing in mind the singularity of the probability of

planetary findings with BEST, it is not surprising to not have detected any

planetary transits with the Westerlund telescope during this study.

Although no planets were spotted, it does not mean that there are none in this particular field. There could be a planet around a star not bright enough for this survey (< 14 mag) resulting in the planet’s signal lost in the noise.

Another cause of losing the signal could be a too large difference between the size of the planet and its parent star. Stars must be solar type or cooler in order for the magnitude drop due to a Jupiter-sized planet transit to be visible.

Furthermore, no small planets can be detected. The geometry of the system plays an essential role as well; the orbit must be edge-on (or near) for a transit to occur. Another reason as to why no exoplanets were found could just be because none did transit during the two nights of observation.

7.2. V ^{ARIABLE STARS}

The digital sky survey Guide8 was used to find the coordinates of each star of interest. As many as 849 catalogues of binaries and variable stars were checked on Vizier (http://cdsweb.u-strasbg.fr/viz-bin/VizieR) by inserting the coordinates; none of the stars were previously known as variables. The tem- perature of each star could be calculated as well as the period of variability for four of them. Data on the interesting variables are given in table 1.

7.2.1. Temperature Figure 21. RMS-plot showing

the distribution of the noise level of the stars in tile 5.

Axes show the percentage

of noise, versus red magni-

tudes of the stars. The hori-

zontal line indicates the 1 %

noise-limit showing that

photometric precision of 1 %

can be detected in stars with

magnitudes down to 14.

emitted energy varies with wavelength. Therefore, the colour of a star indicates its temperature: blue stars are hotter than red stars. By using two different filters, a colour index can be extracted. For example, a blue filter (B) will let through only a narrow band of wavelengths centred on blue colours just as a ‘visual’ filter (V) stops all wavelengths except those in the green-yellow band. The colour index B-V is then given by the difference between the blue and visual magnitudes. As seen in figure 22,

a cool star has a lower energy flux (higher magnitude) in the blue band than in the visible band, resulting in a positive colour index. Fi- gure 23 shows the same procedure for a hot star; a higher intensity (lower magnitude) in the blue band than in the visual band will re- sult in a negative colour index (http://www.

astronomynotes.com).

In order to calculate the temperature of each star of interest, the USNO A2 catalogue was used (http://cdsweb.u-strasbg.fr/viz-bin/Vi- zieR-3). Both blue (B) and red (R) magni- tudes were obtained. This catalogue is based on observations made in 1951 and there is a time lapse between the measured magni- tudes through red and blue plates resulting in photometric errors. Furthermore, the given magnitudes are not mean magnitudes of variable stars. This results in further errors in the temperature estimates. To establish the spectral type and temperature, table II by Johnson (1966) was used. Both B - V and V - R columns were applied in order to get B - R values.

7.2.2. Period

When possible, the variables’ periods were calculated with a programme made by Göran Henriksson at the Uppsala Astronomical Observatory. The inserted data consisted of Julian dates and magnitudes from both nights, for each star of interest. Since the duration of the observations was about six hours, a rough approximation of the period could be established by just looking at the light- curves. The value was then used as an interval in which the programme was to search for a period. The continuity condition is the primary aspect for period determination, and it must be fullfilled. Data points from the two nights must blend together in one light-curve and not be plotted one after the other. Their gradients should be the same and at least one minimum (the same one for both nights) should be present. In order to gain good accuracy, data from at least three nights should be used. Although only two data sets were available for the stars, a relatively good accuracy of ±0.0003 and ±0.0004 was

Figure 22. Continuous spec- trum of a cool star with blue and visible (green-yellow) bands marked; the peak at redder wavelengths (courte- sy H. Östberg).

Figure 23. Continuous spec-

trum of a hot star with the

intensity peak at shorter,

bluer wavelengths (courtesy

H. Östberg).

Star Right Ascension Declination B R B-R T [K] Class Δmag Period [days] Standard deviation 1 20h 50m 26.39s +36° 41’ 51.59’’ 15.2 14.4 0.8 6400 F5 0.35 0.1947±0.0003 0.07752 2 20h 52m 04.69s +36° 47’ 12.35’’ 13.8 13.9 -0.1 11,300 B8 0.36 0.4894 ±0.0004 0.08162 3 20h 52m 07.97s +36° 34’ 53.21’’ 16.9 16.6 0.3 8260 A5 0.69/0.63 - 0.11398 4 20h 52m 47.38s +37° 08’ 17.41’’ 16.8 16.0 0.8 6400 F5 0.24 - 0.17118 5 20h 52m 13.71s +36° 42’ 42.45’’ 17.0 15.9 1.1 5900 G0 0.61 0.2409 ±0.0003 0.12940 6 20h 51m 56.08s +36° 31’ 05.72’’ 12.9 12.3 0.6 7030 F0 0.05 0.0677 ±0.0003 0.09404

7.2.3. Star #1

This variable positioned at RA 20h 50min 26.395s, Dec +36° 41’ 51.59’’ can belong to two categories of variables:

Its short period of 0.1947±0.0003 days (4h 40m) together with a low ampli- tude of 0.35 mag raises the probability for a δ Scuti variable. Although being of spectral class F5, it falls under the coolest end of the spectral type with its temperature of 6400 K. The relatively low temperature could speak against the pulsating category. In that case, star #1 could be classified as an eclipsing binary of W UMa type with the two stars of the same surface temperature and in contact with one another. Further investigation into a possible amplitude variation, such as seen in δ Scuti variables, could comfirm the guess about the origin of the variability. The standard deviation between the two nights in this particular area of the field was very low (0.07752). The light-curves of star #1 are given in figure 24.

7.2.4. Star #2

With a period of 0.4894 ±0.0004 (11h 44m), star #2 is most probably an eclip- sing binary with a combined temperature of 11,300 K. The two minima are of the same depth (amplitude of 0.36 mag), pointing to the fact that the two stars would be of the same spectral class. Two nights are too few though Table 1. Coordinates (J2000),

blue and red magnitudes, colour index, temperature, spectral class, magnitude amplitude, period and stan- dard deviation for stars 1-6.

Figure 24. Light-curves of

star #1 from the nights of

September 6 (left plot) and

October 18 (right plot). Axes

show magnitude versus time

in Julian date.

tions. A smooth recovery from the eclipse (see figure 25) indicates that the stars are of similar sizes and near each other. Until another minimum is shown, one would file this variable under the W UMa type of eclipsing binaries. Just as for star #1, the standard deviation between the two nights was fairly low in this part of the field (0.08162).

7.2.5. Star #3

Considering the two minima in the light-curve on the left-hand side of figure 26, this variable is probably an eclipsing binary of β Lyrae type. No period could be established due to the poor quality of the light-curve from the night of September 6. The binary is positioned at RA 20h 52min 07.974s, +36° 34’ 53.21’’ and has a combined surface temperature of 8260 K.

7.2.6. Star #4

Because of the length of its variation, not much can be determined about star #4.

A few more nights of observation time is required to calculate a period and most of all to see how the star’s variation continues. A magnitude amplitude of 0.24 can be preliminary spotted in this F5-star positioned at RA 20h 52min 47.377s,

Figure 26. Light-curves of star #3 from the nights of October 18 (left plot) and September 6 (right plot).

Axes show magnitude versus time in Julian date.

Figure 25. Light-curves of star #2 from the nights of October 18 (left plot) and September 6 (right plot).

This star is most probably a

binary of W UMa type. Axes

show magnitude versus time

in Julian date.

7.2.7. Star #5

As shown in figure 28, star #5 is a rather nice example of a W UMa type eclipsing binary. A period of 0.2408 ±0.0003 (5h 46m) and steep pits in the light-curves show close orbiting small stars of spectral class G0.

7.2.8. Star #6

The interesting light-curves in figure 29 belong to a star positioned at RA 20h 51min 56.08s, Dec +36° 31’ 05.72’’. With a temperature of 7030 K, it belongs to a spectral type F0. Its period is estimated to be as short as 0.0677 ±0.0003 days (approximately 1h 37m), and a magnitude range of 0.05 mag is determined. This star is most probably a δ Scuti variable. These light-curves could though belong to a close binary system of W Uma type with a short period. In that case the two stars would have approximately the same surface temperature. No consecutive plateaus are shown in the light-curves (the first plateau in figure 29 can be discarded as data errors). This indicates an angle of inclination < 90°. Further investigation is needed to establish the Figure 27. Light-curves of

star #4 from the nights of September 6 (right plot) and October 18 (left plot). Axes show magnitude versus time in Julian date.

Figure 28. Light-curves of variable #5, a most probable W UMa binary, observations from September 6 (right plot) and October 18 (left plot).

Axes show magnitude versus

time in Julian date.

The last data points in the light-curve from the night of September 6 are not reliable. The slope is due to flat field errors in this particular part of the field.

Another point worth mentioning is the very low magnitude range in this variable, showing that variations of < 1% can be detected with the Westerlund telescope.

Figure 29. Light-curves be-

longing to a most probable

δ Scuti variable, observa-

tions from October 18 (left

plot) and September 6 (right

plot). Axes show magnitude

versus time in Julian date.

C ^HAPTER 8 - C ^ONCLUSIONS

No exoplanets were detected during the two nights of observation. However, as witnessed in the light-curves of star #6, a 1% dimming in the light intensity is possible to observe with the Westerlund telescope. In order to detect depres- sions caused by planetary transits, and most importantly periodicity in the depressions, more observing time is required. Furthermore, a better accuracy in the frame-to-frame magnitude correction is demanded. It is possible to take the mean value of five to ten stars with constant brightness in the neighbour- hood of the interesting star for each frame in order to reduce magnitude error in the light-curves. This could be coded and inserted in the pipeline.

Although no planets were found, interesting objects did reveal themselves in

the field. Six variable stars were mapped and for four of these a period could

be calculated. Further investigation is needed to establish the nature of the

variability, especially for the 26 stars given in Appendix 1. An interesting

follow-up to this thesis could be additional research into the variable stars in

order to determine periods, masses and types.