WILLIAMS COLLEGE LIBRARIES COPYRIGHT ASSIGNMENT AND INSTRUCTIONS FOR A STUDENT THESIS

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3 PLANETARY NEBULAE AS TRACERS OF THE CHEMICAL HISTORY OF THE ANDROMEDA GALAXY by KERRIN HENSLEY Karen Kwitter, Advisor A thesis submitted in partial fulfillment of the requirements for the Degree of Bachelor of Arts with Honors in Astrophysics WILLIAMS COLLEGE Williamstown, Massachusetts MAY 14, 2014

4 Contents Executive Summary 3 1 Introduction 4 2 Planetary Nebulae Formation and Characteristics of Planetary Nebulae Studying Planetary Nebulae Planetary Nebulae in a Galactic Context An Introduction to Galaxy Structure and Evolution Detection of Extragalactic Planetary Nebulae Project Background and Goals The Andromeda Galaxy Neighborhood M31 Planetary Nebulae Observations and Data Reduction Observing Log Reduction Steps Extraction and Measurement of Nebular Spectrum with IRAF Electron Temperature and Density Calculation with ELSA Abundance Calculation with ELSA Results and Discussion Chemical Abundance Gradients Halo Membership Candidates Peimbert Types and Progenitor Mass Estimates Assumptions Conclusions and Future Work 49 Acknowledgements 50 References 51 Appendix A: Fluxes and Intensities 54 Appendix B: Ionic Abundances 63 Appendix C: Temperatures, Densities, and Chemical Abundances 66 1

5 List of Figures 1 Hertzsprung-Russell diagram of the evolution of a low- to intermediatemass star Spiral galaxy structure Observed and predicted radial velocity curves for a spiral galaxy Hα images of two spiral galaxies On- and off-band images of planetary nebulae in M Local Group diagram Neutral hydrogen clouds between M31 and M Location of M31 planetary nebulae in relation to inner disk Raw and reduced 2-D emission line spectrum of M Extracted 1-D spectrum of M Metastable levels of [O III] and [N II] and their transitions Metastable levels of [O II] and [S II] and their transitions Variation of density-dependent nebular emission lines M31 oxygen abundance results Oxygen gradient for M Spatial distribution of oxygen abundances in M Neon gradient of M Ne/H versus O/H for M31 planetary nebulae Stellar evolutionary tracks M31 planetary nebula luminosity function

6 Executive Summary Planetary nebulae (PNe) are the ejected outer layers of low- to intermediatemass stars that have ceased hydrogen fusion in their cores. Because PN progenitor stars are not sufficiently massive to synthesize oxygen, they preserve the metallicity of the interstellar medium at the time they were formed. We can use the abundances of oxygen found in PNe to probe galactic chemical evolution. We present chemical abundances for 8 PNe in the Andromeda Galaxy, M31. The average 12+log(O/H) value for this sample is 8.41±0.15, consistent with previous studies of M31 PNe (e.g. Balick et al. 2013). Combining the results from this sample to results for additional M31 PNe from Balick et al. (2013) and Kwitter et al. (2012), we obtain an oxygen abundance gradient slope of ± dex kpc -1. This slope is inconsistent with theories of spiral galaxy structure, which predict metal-rich inner regions and relatively metal-poor outer regions; the observed oxygen abundance gradient for M31 is much shallower than that of similar spiral galaxies like our own. Possible causes of unexpectedly high metallicity outer regions, such as an encounter between M31 and neighboring galaxy M33, are discussed. Chapters 1 and 2 present introductory material crucial to the understanding of the efficacy and importance of PN studies. In Chapter 3 I present the background and goals of the project. Chapter 4 covers observing specifications as well as the steps taken to reduce the data. Chapter 5 contains a discussion of the results and Chapter 6 contains a brief summary of the findings as well as a look at the trajectory of future projects. The appendices contain measured linestrengths and calculated temperatures, densities, and chemical abundances for all PNe in this sample. 3

7 1 Introduction In 1764, Charles Messier, comet hunter and cataloguer of nebulous heavenly bodies, entered the first of four planetary nebulae into the now famous Messier Catalog. That object, known as the Dumbbell Nebula, or M27, was the first of many such objects to be labeled with the misnomer planetary nebula, a term coined in 1784 by William Herschel, who believed that the vaguely circular disks resembled the outer planets of our solar system (Kwok 2000). A century after the first planetary nebula (PN, plural PNe) was discovered, astronomer William Huggins became the first person to record the spectrum of a PN. He was unable to identify some strong emission lines in the spectrum and proposed the existence of a new element, nebulium, that gave rise to these emission lines (Huggins and Miller 1864). Now we are able to explain these lines by invoking fundamental rules of quantum mechanics rather than a new element. In the course of the past two centuries, PNe have advanced from misnamed objects of curiosity to cosmic laboratories at the forefront of astronomy, ideal templates for studies of the interaction between matter and radiation or the creation of complex hydrodynamical models to explain their myriad morphologies. As the bulk of our collective observations of PNe increases, so too does our understanding of these objects and the physical processes underlying their formation, dispersion, element creation and role in the chemical evolution of the universe. Of particular importance to those who study PNe is the archive PNe provide of the chemical makeup of the gas from which their progenitor stars were formed. Since PN progenitor stars are not sufficiently massive to fuse heavy elements like sulfur, 4

8 chlorine, argon, and so on, any amount of these elements found in a PN must have been present in the protostellar material that condensed to form the star. While the accurate determination of the chemical abundances in a single PN is certainly worthwhile, even more useful is the compilation and comparison of abundances in a large sample of PNe over a range of galactocentric distances or even in a variety of galaxies. By synthesizing these discrete data points into a continuous whole, we can find ways to probe the characteristics of different parts of galaxies and learn about the way they form and evolve over time. 5

9 2 Planetary Nebulae 2.1 Formation and Characteristics of Planetary Nebulae Planetary nebulae form late in the evolutionary sequence of stars with masses between 0.8 and 8 solar masses (M ). A star in this mass range spends most of its life on the main sequence, fusing hydrogen into helium in its core, the outward pressure of nuclear fusion in the core balancing the inward force of gravity. When the star exhausts its supply of core hydrogen, it departs the main sequence and becomes aredgiant;theouterlayersofthestarexpandgentlyandcoolasthestellarcore, no longer able to fend off gravity s advances in the absence of an outward-pushing agent, contracts, its temperature rising. After the temperature in the core grows hot enough, the helium in the core begins to fuse into carbon and oxygen and the star enters the horizontal branch. The evolutionary path of a star in this mass range is depicted in Figure 1 on the following page. The core supply of helium is eventually depleted and the star becomes an asymptotic giant branch (AGB) star, leaving an inert carbon and oxygen core. Surrounding the core are concentric shells: a helium shell nearest the core and a hydrogen shell farther out. These two shells alternate in dominance, making the stars helium-shellburning tenure fraught with instability. Repeated contractions and expansions of the outer layers cause the diffuse exterior of the star to be lofted into the interstellar medium (ISM) at velocities of a few kilometers per second. As the outer layers drift away from the core, the surface temperature of the central star rises until the emitted radiation is sufficiently energetic to ionize the surrounding diffuse gas. Recombination cascades follow photoionization of the sur- 6

10 rounding material, now a bona fide planetary nebula. These recombination cascades are observable mainly in hydrogen and helium, the most abundant elements. These atoms emit photons with wavelengths determined by the differences in energy between quantum states unique to each atom. In addition, free electrons colliding with ions populate metastable states that give rise to forbidden lines, the strongest components of PN spectra.! Figure 1: Hertzsprung-Russell (HR) diagram showing the evolutionary track of a sun-like star with evolutionary stages labeled. Temperature in kelvins increases to the left and luminosity in units of solar luminosity increases along the vertical axis, as is standard for HR diagrams. Diagram courtesy of edu-observatory.org. The planetary nebula stage, lasting on the order of 10,000 years, ends when the central star cools to below approximately 30,000 K and the gas has expanded sufficiently until it is no longer photoionized. The transparent, rarefied gas, once the outer layers of a shining main sequence star, rejoins the ISM from whence it came to enrich future generations of stars. 7

11 2.2 Studying Planetary Nebulae Unlike continuum sources, which radiate at all wavelengths, PNe radiate energy predominantly at a few discrete wavelengths, the values of which arise from bound-bound electronic transitions in atoms in the nebular gas. Because the relative strengths of PN emission lines are dependent upon the physical characteristics of the nebular gas, such as temperature and density, as well as the relative chemical abundances, the study of PNe mandates a reliable method of determining emission line strengths. The discrete emission lines of a PN allow for the measurement of its radial velocity via the Doppler-shift deviation of the observed wavelength from the expected, and also the determination of atomic and ionic abundances as well as electron temperatures and densities. Each atom and ion has a set of emission lines particular to its electronic configuration, many of which are readily producible in a laboratory setting and have been well documented. Some emission lines of PNe cannot be produced or measured in a laboratory. Transitions that violate electric dipole selection rules are menacingly named forbidden transitions and the emission lines that arise from this type of transition are denoted with square brackets around the ion name (e.g. [O III]). Though called forbidden, these transitions are, in fact, possible, but very unlikely. If a substance is of sufficiently low density to allow electrons excited to higher states from which only forbidden radiative transitions are possible to spontaneously decay before being de-excited by another collision, forbidden spectral lines will be observable. However, even the best possible vacuum on Earth containing roughly 10 3 molecules/cm 3 (Genz 2002) is too dense to allow spontaneous forbidden-line photon emission. 8

12 The timescales necessary for spontaneous emission are given by 1/Amn, where A is the Einstein spontaneous emission coefficient: the likelihood of the transition between energy states m and n, givenins -1. The Einstein coefficient for the transition leading to emission of a 5007 Angstrom (Å) photon by a doubly-ionized oxygen atom is 1.96 x 10-2 s -1,givingatransitionlifetimeofaboutoneminute(Kogureetal. 2007). For comparison, the Einstein coefficient for the Hα transition of hydrogen is 4.41 x 10 7 s -1, giving a transition lifetime on the order of 10 nanoseconds (Wiese and Fuhr 2009). We can use the observed abundances of a subset of chemical elements to gain insight into the conditions of the ISM at the time the stars were born. Since heavy elements like argon, sulfur, and chlorine are not produced by PN progenitor stars, any amount of these elements detected in a PN must have been present in the interstellar matter from which the PN progenitor was formed. Low- and intermediate-mass PN parent stars can, however, affect the abundances of lighter elements like helium, carbon, nitrogen, and, to a lesser extent, oxygen, and abundances of these elements yield information about the rate and extent of chemical enrichment of our galaxy and others by PNe. The abundance of oxygen is particularly useful. Oxygen is synthesized in the cores of massive stars (> 8M ), which have brief lifetimes and therefore relatively rapidly return the oxygen they create to the ISM to be incorporated into new generations of stars. We expect objects with higher oxygen abundances to be younger and can use oxygen abundance as a stand-in for cosmic time. 9

13 2.3 Planetary Nebulae in a Galactic Context An Introduction to Galaxy Structure and Evolution Agoodmodelofgalaxyformationandstructuremustbeabletoexplainas well as predict observable properties of galaxies, from expansive spiral arms and the featureless bulges of elliptical galaxies to bizarre objects like ring galaxies and the jumbles of stars seen in galaxies in the midst of colliding. Galaxies can be divided into a few basic subclasses, including spiral, elliptical, and dwarf galaxies, each subclass with particular theories of formation and evolution, but I will focus on spiral galaxies, the class to which Andromeda, our target galaxy, belongs. Spiral galaxies possess several distinctive features that seem to be common across all galaxies given that classification. The features described here are illustrated in Figure 2 below. First, spiral galaxies are flattened disks that can be divided into two parts: the thin disk and the thick disk. The thin disk contains the bulk of star-forming material, the gas and dust that trace the spiral arms when viewed face-on; our sun lies within the thin disk of the Milky Way. The relatively old thick disk reaches above and below the vertical extent of the thin disk. Enclosing these two layers is a roughly spherical distribution of old, metal-poor globular clusters in the galactic halo. The globular clusters are posited to be nearly as old as the galaxy itself, having formed from the first stars before the angular momentum of the material caused the galaxy to collapse into a thin disk. Beyond the halo is the corona, which reaches out about 100 kiloparsecs (1 parsec = 3.26 light-years) and encloses several of the satellite galaxies of the Milky Way (Murdin 2001). 10

14 Figure 2: Side-view of spiral galaxy structure. The sun lies in the thin disk of the Milky Way, which is enclosed on both sides by the thick disk and the halo. Image: gaia-eso.eu. One feature of galactic structure that must be inferred rather than discerned is the dark matter halo, which is spherically distributed throughout the galaxy. The presence of the dark matter halo is inferred from the discrepancy between predicted and observed galactic rotation curves. If we assume that the only matter in a galaxy is the luminous matter that we can directly image, we would expect the rate at which stars, nebulae, etc. orbit the galactic center to decrease as galactocentric radius increases. However, measurements of the rotation rates of objects in our galaxy and others show that the rotation curve is surprisingly flat (Figure 3). According to our current theory of gravity, this is only possible if the total mass present is exceeds the visible mass and extends to radii far beyond the luminous disk of the galaxy. Researchers have attempted to alleviate this discrepancy by suggesting that objects like 11

15 white dwarfs, which are very faint and relatively low-mass, but prevalent, could make up some of the missing mass, but the generally accepted explanation is the presence of dark matter a noninteracting but massive substance, the true nature of which is unknown. Figure 3: Simplification of expected and observed rotation curves for a spiral galaxy similar to our own. A shows what we expect to find based on the amount of luminous matter, and B represents what we actually observe. Note that agreement between the model and the observations declines as galactocentric radius increases. Image courtesy of psu.edu. At the center of each of these structures lies the galactic nucleus, which in the case of the Milky Way is surrounded by a large bulge which extends well past the extent of the thin disk. Although our home spiral galaxy has a central bulge, it is not anecessarycomponentofspiralgalaxystructure(steinmetz2012). Inthegalactic nucleus, partially shrouded from view by dust in the galactic plane, there is a supermassive black hole, the feedback from which partially determines the development of the outer regions of our galaxy. Just as one would expect for a gravitationally-bound collection of matter, galaxies are densest at the middle and become more diffuse moving away from the galactic nucleus out to the spiral arms and halo. The density of gas and dust is one factor that affects the rate of star formation, as can easily be seen in Hα images of spiral galaxies 12

16 (Figure 4); the spiral arms are the result of density waves propagating through the galactic matter and bright, Hα-emitting star-forming regions trace the spiral arms (Murdin 2001). Figure 4: Spiral galaxies M51 (left) and M101 (right) in Hα. Images: David A. Thilker, NRAO. Aconsequenceofenhancedstarformationisthechemicalenrichmentofthe interstellar medium and, by extension, young generations of stars. Whether the stars being formed are high mass stars which quickly expire in supernova explosions, hurling heavy metals into the ISM, or low-to-intermediate mass stars that lose their hydrogen-rich envelopes late in their lives, more stars means more nuclear fusion and greater abundances of heavier elements. If we start with the assumption that the star-formation rate is greater in the denser areas near the galactic center, we would expect to find that the abundance of certain elements is highest near the galactic center and decreases as galactocentric radius increases. One tracer of chemical abundance and the youth of stars is the 13

17 O/H ratio. Measurements of the O/H ratio in our galaxy show that the abundance of elements heavier than hydrogen and helium what is referred to as the metallicity of outer regions is indeed lower than inner regions. In particular, the gently sloped decline of oxygen abundance with increasing radius is referred to as the oxygen abundance gradient. Chemical abundance gradients can be measured with a variety of objects like certain types of stars, ionized hydrogen regions, and PNe. As emission line objects, PNe are extremely bright at a few wavelengths and can be distinguished from a field of stars even at intergalactic distances, as discussed below Detection of Extragalactic Planetary Nebulae A few thousand PNe have been identified in our galaxy and a few hundred have been observed and studied, their colorful visages glorified in space telescope images and as likely to grace the computer screen of an amateur astronomy enthusiast as a scientist. Extragalactic PNe, though visually unimpressive at such a distance, nevertheless provide a unique laboratory for testing models of galaxy formation and cosmic chemical enrichment. Since the first detection of a PN in the Andromeda Galaxy by Walter Baade in 1955 (Baade 1955), PNe have been studied not only in M31, but also in the neighboring Large and Small Magellanic Clouds, many of the galaxies in the Local Group of galaxies to which we belong, and even out to galaxies in the Virgo Cluster, about 16.5 Mpc away. M31 lies approximately 785 kpc (McConnachie et al. 2005) distant in the direction of the constellation Andromeda. At that distance, PNe, typically with radii < 0.15 pc would be unresolved in an image. Thus, detection of extragalactic PNe 14

18 requires some cleverness on the part of the observer, and there now exist several strategies for identifying distant PNe: the Planetary Nebula Spectrograph allows observers to simultaneously obtain spectra and determine radial velocities of PNe for kinematic surveys (Merrett et al. 2006) and photometric sky surveys like the Sloan Digital Sky Survey permit identification of PNe over a huge area by making color cuts in the various filter combinations (Kniazev et al. 2013). A common method requires the use of [O III] λ5007 or Hα λ6563 narrowband filters; since a typical PN radiates much of its energy at those two wavelengths, it is possible to see PNe in on- and off-band images of a star field. PNe brightness will be greatly reduced in the nearby off-band filter, but stellar brightnesses will be essentially unchanged. Figure 5: From left to right: off-band, on-band, and on-band grism images of a PN-containing field in spiral galaxy M82. Far right image is an Hα image from the Hubble Space Telescope. Three PN candidates are within all fields of view and can be identified by their absence in the off-band frame. The PN candidates are point sources in the grism frame that have been shifted upward as a function of emission feature wavelength. The wavelength of the emission feature allows for radial velocity calculation. Image: Johnson et al

19 3 Project Background and Goals 3.1 The Andromeda Galaxy Neighborhood The Andromeda Galaxy (M31) is the largest galaxy in the Local Group, the cluster of galaxies to which the Milky Way also belongs (Figure 6). M31 is flanked by many small satellite galaxies, the largest of which are M32 and M110, and lies 230 kiloparsecs (Freedman et al. 1991) from M33, the third largest member of the Local Group. Collisions and mergers appear to be common events that greatly affect the formation and morphology of galaxies; there is evidence for a close interaction between M31 and M33 approximately 2-3 Gyr ago that would have had consequences for the star formation rate and chemical evolution of the outer disk of M31. Stellar population studies of the outer disk of M31 (e.g. Bernard et al. 2011) confirm a burst of star formation 2-3 Gyr ago that could have been caused by a close encounter with M33. Stars with lifetimes of 2-3 billion years have masses of M just the sort of intermediate-mass stars that produce PNe. The major movers and shakers in the chemical evolution of the ISM are supernovae and planetary nebulae. Supernovae, which occur at a rate of approximately one per century per galaxy, fling heavy-element-enriched gas far into the ISM in violent explosions, leaving behind exotic remnants like neutron stars and black holes. PNe, though gentler and smaller than supernovae, are much more common, as expected by the relative populations of the high- and low-to-intermediate mass stars that produce supernovae and PNe, respectively. Galaxies also gradually accrete matter from the intergalactic medium and may lose or gain gas as a result of collisions with neighboring galaxies or cannibalism of smaller galaxies. 16

20 Figure 6: Diagram of the Local Group of galaxies. The Milky Way is at the center of the image. M33 is called Triangulum here. Image: Richard Powell. One tracer of galaxy interactions is the 21-cm hyperfine transition of neutral hydrogen, caused by the spin flip of the hydrogen atoms single electron from parallel to the protons spin to antiparallel. Radio observations of the apparently vacant area between M31 and M33 reveal a neutral hydrogen bridge spanning the gap between the two galaxies (e.g. Lockman et al. 2012). The measured velocities of these clouds of neutral hydrogen, plotted in Figure 7 on the next page, suggest that they are associated with M31 and M33 rather than the system of high-velocity clouds that surround the individual galaxies. One theory for the origin of this bridge is that as M33 passed M31, neutral 17

21 hydrogen in the disk of M31 was drawn out and now traces the path M33 took over the past few billion years. However, some models show that features like the neutral hydrogen bridge are feasible without such an interaction (Cooper et al. 2010) and the proposition that the bridge originated from a near pass by M33 requires further study. Figure 7: Velocity with respect to the Local Group Standard of Rest as a function of angle from M31. Stars represent velocity measurements of high-velocity clouds within M31 and M33. Circles represent measurements of neutral hydrogen clouds in the space between M31 and M33. Image: Lockman et al One piece of evidence that is particularly important to the investigation of a possible encounter between M31 and M33 is the deviation of the observed oxygen gradient of M31 from the expected. The oxygen gradient has been determined by 18

22 various abundance studies (i.e. PNe, H II regions, B stars) for relatively nearby spiral galaxies. 1 Of the studies using PN oxygen abundances as a determinant of chemical enrichment, comparable values of the gradient slope were found for the Milky Way and M81, for example (Table 1). However, for comparable studies using PNe in M31 and M33, the measured oxygen gradients have shallower slopes. One of the many possible explanations for the shallowness of the gradient slope is the previously described interaction between M31 and M33. This possibility and others will be explained further in Chapter 5. Table 1. Measured Oxygen Gradient for Nearby Spiral Galaxies Galaxy Gradient Slope (dex kpc -1 ) Milky Way M81 NGC2403 M33 M ±0.006 a ±0.007 b ±0.007 c ±0.013 d ±0.004 e a Henry et al b Stanghellini et al c Berg et al d Magrini et al e Kwitter et al

23 3.2 M31 Planetary Nebulae Fortunately, because PNe preserve information about the chemical makeup of the galaxy at the time their progenitor stars formed, they too are a useful tracer of past events. Previous observations of PNe in M31 (e.g. Kwitter et al. 2012; Balick et al. 2013) support the theory that the observed PN progenitors could have been formed in the burst of star formation that accompanied the encounter. We present observations of eight PNe in the outer disk of M31, an area typically characterized as lacking in recent star formation and relatively metal-poor. These PNe were selected because they are intrinsically luminous, with m 5007,theapparentmagnitudeofthe[O III] 5007 Åline,rangingfrom21.0to22.0(m 5007 is defined as -2.5 log F ), and have measured radial velocities that hint that they may have been involved in the previously mentioned M31-M33 interaction. Kinematic studies of these PNe (Ibata et al. 2005) indicate that among them, five are located beyond the limit of the inner disk, and may reveal information regarding the encounter between M31 and M33. These five PNe have greater galactocentric radii (R g ) than the sixteen PNe analyzed by Kwitter et al. (2012) or the two PNe studied by Balick et al. (2013) which had R g between 18 and 43 kiloparsecs and approximately 56 kiloparsecs, respectively. Positions of the eight PNe in this study are plotted on an inverse black and white image of M31 in Figure 8. Due to uncertainties in the kinematics of the remaining three PNe, these may instead be members of the halo component of M31 and can contribute to our understanding of such a structure. 20

24 Figure 8: The red ellipse shows the approximate location of the inner disk of M31. Note that this is beyond the visible extent of the galaxy. The green circles represent two PNe previously studied by Balick et al. (2013). M31 image: Lorenzo Comolli. 21

25 4 Observations and Data Reduction The study of distant PNe requires use of a large telescope. In order to extract quantitative information from the spectrum of a PN, careful data reduction must occur to correct for factors such as interstellar reddening, cosmic rays striking the detector, and wavelength-dependent sensitivity of the detector, to name a few. In this chapter I will outline both the observing specifications and the steps taken to reduce the data. 4.1 Observing Log Asuccessfultelescopeproposalfor22hoursofobservingtimebyprincipalinvestigator Dr. Romano Corradi and co-investigators Dr. Bruce Balick, Dr. Karen Kwitter, and Dr. Dick Henry led to observations of eight M31 PNe between 7 October, 2013 and 15 October, 2013 with the Gran Telescopio Canarias (GTC). Object specifications and exposure times are listed in Table 2 on the next page. The GTC is the largest of the many telescopes comprising the Observatorio del Roque de los Muchachos, which is located on the perimeter of Caldera de Taburiente National Park, 2,396 meters above sea level on the island of La Palma, Spain. The observatory s high altitude and the restrictions placed on light pollution from the surrounding area make it an excellent site for ground-based observing of faint objects. The primary mirror of the GTC consists of 36 hexagonal segments that interlock to make a mirror the equivalent of 10.4 meters in diameter. Spectra were taken using the Optical System for Imaging and low-intermediate- 22

26 1 Resolution Integrated Spectroscopy instrument (OSIRIS). 1 This instrument, which has imaging and spectroscopic capabilities over the wavelength range of 3650 to Å, is well suited to the long-slit spectroscopy necessary for PN studies. Observations of this group of PNe called for the use of the R1000B grating prism (grism), which is sensitive in the 3630 to 7500 Årange.Grismsareusefulinspectroscopybecausethe refraction due to the prism corrects for the diffractive effects of the grating. However, this causes non-linear dispersion that must be corrected, as discussed in Chapter 4. Table 2. GTC Observations PN Name R.A (hh mm ss) Dec ( ) m5007 Total Exp. Time (s) M M M M JF M M M Reduction Steps Extraction and Measurement of Nebular Spectrum with IRAF I used the Image Reduction and Analysis Facility (IRAF) for all data reduction steps (Tody 1986). 2 First, the bias frames zero-second exposures taken to allow 1 Grand Telescopio Canarias: OSIRIS, 2 IRAF is distributed by the National Optical Astronomy Observatories, which are operated by the Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the National Science Foundation. 23

27 elimination of electronic noise are averaged using zerocombine, and this average frame is subtracted from all science and calibration frames using ccdproc. As part of this step, the object, standard star, arc lamp, and flat frames are also trimmed to the desired dimensions. Flat-field frames, usually referred to as flats, are images taken of a featureless surface like the twilight sky or a specially manufactured blank screen that provides uniform illumination of the charge-coupled device (CCD). Due to inconsistent pixel sensitivity, dead pixels, and dust in the optics, observed flat frames are never uniform. The factors that disrupt the uniformity of the flat frames affect each frame approximately equally, so science frames can be divided by flat frames to eliminate these issues. The bias-subtracted flat frames are combined using flatcombine and normalized with response. Themainpurposeoftheresponsetaskistodividethecombinedflat by its average value so that the numbers of counts in the data frames are preserved, allowing valid statistical assessment. The response task also allows us to remove underlying structure in the combined flat that is caused by variations in the flat field source (i.e. the twilight sky or lamp). Division by the flat is necessary for precise flux determination but not wavelength determination, so the reference lamp frames were not divided by the normalized flat. Since at this stage the horizontal axis of the science frames has units of pixels, we want to convert to units of Angstroms. In order to achieve this, we use a source with emission lines of known wavelength. Emission line spectra of a neon arc lamp and a mercury-argon arc lamp are combined to form one comparison spectrum. By identifying a few known lines in the lamp spectrum and fitting a low order curve to 24

28 the data, we find a dispersion solution that can be applied to all other frames. In the case of this GTC data, the spectral dispersion is Åperpixel. The standard star and nebula frames, which have been biased, flatted, and trimmed, are then transformed using the dispersion solution. The transform step removes the bowed effect easily seen in the pair of bright night sky lines to the red of the [O III] 5007 Å line in Figure 9. The science frames undergo an additional step; because the nebular emission lines are so faint relative to any cosmic rays striking the CCD during the exposure, the cosmic ray hits must be removed. To accomplish this, I used a Laplacian cosmic ray removal IRAF task written by Pieter G. van Dokkum (2001). The signal from the standard star, however, is so strong that this somewhat time-consuming step is not necessary in those frames. Raw and reduced two-dimensional spectrum are presented in Figure 8. The standard star spectrum is extracted using the task apall, whichallowsyou to define an aperture centered on the stellar signal and background regions to either side. The stellar aperture is traced along the dispersion axis, and the resultant stellar spectrum is used to define a sensitivity function that will be used to correct the science frames by comparing the flux at each bandpass to what is known for that star. The spectrum of the nebula is extracted in much the same way, but because the PN does not have a continuous spectrum it cannot be traced, so a standard star trace is used instead. Lastly, each frame is divided by the sensitivity function and all frames of a given PN are averaged. The emission lines of the extracted one-dimensional spectra (see Figure 10) are measured in splot, as is the level of the background to either side of the line in order to estimate the signal-to-noise ratio. 25

29 Figure 9: Raw (top) and reduced (bottom) 2-dimensional emission-line spectrum of M2541. Wavelength increases to the right. Horizontal lines are spectra from stars in the spectrograph slit. Vertical lines are night sky lines from the Earth s atmosphere. The nebular spectrum is located just beneath the second horizontal line from the top and is nearly in the center of the reduced spectrum. The reduced image has been bias subtracted, flatted, trimmed, and transformed to a uniform dispersion in the wavelength direction. Cosmic rays have also been removed, though a few remain in the reduced image. Any cosmic rays that are not in line with the nebular spectrum will not impact final abundance determinations Electron Temperature and Density Calculation with ELSA The line fluxes measured in IRAF become the input for the Emission Line Spectrum Analyzer (ELSA), a program written in C by Matthew Johnson and Jesse Levitt (Johnson et al. 2006) that uses an iterative five-level atom routine to determine ionic and chemical abundances as well as electron temperatures and densities. In order to calculate electron temperatures and densities, ELSA uses the fluxes of forbidden emission lines originating from electrons occupying collisionally-excited 26

30 Extracted 1-D Spectrum for M Flux (erg/cm 2 /s/å) Wavelength (Å) Extracted 1-D Spectrum for M Flux (erg/cm 2 /s/å) Wavelength (Å) Figure 10: Extracted 1-D spectrum of M2541. Full spectrum (top) and scaled spectrum (bottom). Wavelength increases to the right. The strongest line is [O III] 5007 Å. The bottom image has been rescaled in order to show relative intensities of weaker emission lines. [O III] 5007 Ålineisoffscaleinthebottomimage. 27

31 metastable levels in the ground state. These excited states are sufficiently low-energy to be populated by collisions, and transitions from these states can be sensitive to changes in either temperature or density of the nebular gas. For temperature, either the [O III] λ4363, λ4959, and λ5007 lines or the [N II] λ5755, λ6548, and λ6584 lines are used, as shown in Figure 11. Figure 11: Metastable levels of [O III] and [N II] and their transitions. Wavelengths are given in Å. Image: Osterbrock & Ferland (2005). The energy levels of the ground state in doubly ionized oxygen and singly ionized nitrogen atoms produces transitions that can effectively probe the temperature of the nebular gas. The probability of an electron being excited to the 1 S 0 level in [O III] or [N II] is a function of the statistical weight of the level the number of electrons that can fit in a given level and the temperature; an electron is more likely to be found in an excited state if the statistical weight is greater, and higher temperatures 28

32 translates to higher collision energies and hence greater likelihood of higher energy levels being populated. Taking [O III] as an example, the temperature is dependent upon the relative intensities of the λ4363, λ4959, and λ5007 lines. The density is calculated using either the pair of [O II] lines at λ3729 and λ3726 or the [S II] lines at λ6716 and λ6731. The transitions that produce these lines are depicted in Figure 12. The wavelengths of the transitions in a given pair are very similar, so a collision that is capable of populating one state is likely able to populate the other. However, these two states have differing statistical weights (6:4 in the case of the [S II] lines) as well as different radiative transition probabilities. Combining these two factors gives you an intensity ratio that is dependent upon density, as shown in Figure 13. Clearly, this method of determining density is less precise at either the high- or low-density limit. Below a certain intensity ratio cutoff, ELSA uses a value of e - cm -3 to calculate abundances. At low densities, these collisionally-excited electrons which can only decay radiatively via forbidden transitions are able to do so before being de-excited by another collision. Because the difference in the radiative lifetimes of the states does not determine whether or not an electron may decay and emit a photon in the low density case, the ratio of the intensities is dependent only upon the ratio of the occupancies. Therefore, the maximum observed intensity ratio is just the ratio of the statistical weights. At the high-density limit, electrons collisionally excited to higher energy states are rapidly de-excited by another collision. The intensity ratio is dependent upon both the relative statistical weights as well as the relative radiative lifetimes of the excited states. 29

33 Figure 12: Metastable levels of [O II] and [S II] and their transitions. Wavelengths are given in Å. Image: Osterbrock & Ferland (2005) Abundance Calculation with ELSA ELSA uses electron temperatures and densities calculated using the method described above in tandem with observed emission line intensities to calculate chemical and ionic abundances. Before calculating abundances or other nebular properties such as electron temperature or density, ELSA corrects for interstellar reddening 30

34 Figure 13: Intensity ratios of [O II] lines λ3729 and λ3726 and [S II] lines λ6716 and λ6731as a function of density. At high- and low-density limits, the intensity ratios approach constant values. Image: Osterbrock & Ferland (2005). weakening of fluxes at shorter wavelengths due to preferential transmission of longer wavelengths through interstellar dust. Due to the atomic properties and the particular spacing of energy levels in the hydrogen atom, the ratio of intensities of hydrogen Balmer lines in the absence of interstellar reddening is as follows: Hα λ6563/hβ λ4861= 2.86 and Hγ λ4340/hβ λ4861 = If interstellar reddening is present, the Hα/Hβ ratio will be greater than 2.86 and the Hγ/Hβ ratio will be less than ELSA corrects for reddening using an iterative process that determines c, the reddening coefficient. First, ELSA calculates a value for c based on the Balmer ratio Hα λ6563/hβ λ4861= Next, a reddening correction is applied which allows for 31

35 contamination of Hα and Hβ due to He +2 to be removed. ELSA then rereddens Hα and Hβ in order to calculate a new value of c. Thisprocessisrepeateduntilthe value for c converges. After correcting for interstellar reddening and converging upon values for the electron temperature and density, ELSA calculates abundances of each ion present based upon the measured line intensity. If more than one emission line of a particular ion is present, the abundances calculated from those two lines will be combined in a weighted mean. If all possible ionization states of a given atom were observed, the abundances of each ionic species could be summed to give the total abundance of that atom. However, relatively few ionization states are observable for some elements, especially when restricted to the optical portion of the electromagnetic spectrum. In the case of missing ionization states, ELSA exploits ionization potential coincidences between atoms to account for unobserved ionic species and estimate the total chemical abundance. For example, the first ionization energy (the energy required to remove one electron from an atom and create an ion with a charge of +1) of hydrogen is ev and the first ionization energy of oxygen is ev. Given the closeness of these two energies, we can assume that the fraction of oxygen that is ionized is similar to the fraction of hydrogen that is ionized. Other ionization potential coincidences exist, but as the differences between the potentials stretch to a few ev or more, the accuracy of the ionization correction factor (ICF) method decreases; for oxygen, the ICF tends to be of order 1, but for nitrogen, this number can grow to 30 or more. Without ultraviolet spectra, which often reduce 32

36 the need for these corrections but can only be obtained with space telescopes, we must continue to rely on the ICF method to determine chemical abundances. 33

37 5 Results and Discussion 5.1 Chemical Abundance Gradients O/H values for this sample of PNe are roughly solar (12 + log(o/h) = 8.69), with an average 12 + log(o/h) value of 8.41 ± This is consistent with previous studies of outer disk PNe (e.g. Balick et al. 2013). I combined results from this sample of 8 PNe to the results from Kwitter et al, (2012) and Balick et al. (2013), giving a total sample size of 26 PNe. Though this paper adds analysis of only 8 PNe to the existing bank of data, the maximum R g reached has nearly been doubled. Abundance results of PNe in this sample are compared to results from other M31 PNe studies and H II region studies in Figure 14 below. 9 X 12+log(O/H) 8.5 X X 8 M31 PNe (This Study) M31 B I Stars (Trundle02) M31 H II Regions (Dennefeld81) H II Regions (Zurita12) M31 H II Regions (Blair82) Kwitter et al. 2012; Balick et al X Fang et al. 2013, ApJ, 774, R g (kpc) R g (kpc) Figure 14: Oxygen abundance of PNe, H II regions, and B I stars in M31 as a function of galactocentric radius. PNe from this study are the pink (disk) and blue (halo) dots. Red dots are PNe studied by Kwitter et al. (2012) and Balick et al. (2013). The black X s are PNe in the same range of R g as those studied by Kwitter and Balick. Fang et al. (2013) determined oxygen abundances consistent with those from previous studies. 34

38 y 9 M31 Oxygen Abundance Gradient Disk PNe Halo PNe Uncertainty m1 m2 Chisq R log(o/h) R g (kpc) Figure 15: The oxygen gradient of M31. Galactocentric radius increases to the right, log(o/h) increases along the y-axis. Measured slope is ± for disk PNe. Red circles are halo PNe and are not included in the calculation of the least-squares fit. Table 3. M31 Oxygen Gradient Slope Study Gradient Slope (dex kpc -1 ) Sample Size Maximum R g (kpc) Kwitter et al ± Balick et al ± > 55 This Paper ±