Bayfordbury Observatory Supernova Searchwithinerror.space/resources/Project Supernova.pdf · A&A proofs: manuscript no. "Project Supernova" 2001 (SDSS (2016)). Another survey is the

Astronomy & Astrophysics manuscript no. "Project Supernova" c©ESO 2017February 16, 2017

Bayfordbury Observatory Supernova Search

Including the review of the Paramount Telescope

Thomas Spriggs

University of Hertfordshire

May 21, 2016

ABSTRACT

Aims. A review to characterise the Bayfordbury observatory, determining whether or not a Supernova Survey is conductible withthe current equipment and operation available, via a quantitative and qualitative overview of the Paramount telescope. The aim is todesign a survey that will cover a suitable range of targets, over a time period of October 2015 through to March 2016, a comparativelysmall window that will allow the instrumentation to be tested and deployed successfully.Methods. This paper will introduce the subject of Supernova surveying, including an overview of the current understandings andmodels of Supernovae, highlighting their importance within astronomy and cosmology. Surveying the night sky for supernovae isa task that must be planned accordingly, taking account of factors such as weather, instrumental limitations as well as the limitingmagnitude of the observatory. To properly assess the Bayfordbury Observatory against the requirements of a Supernova survey, anunderstanding of how well the equipment performs and the effectiveness of applying various observational techniques is required. Thetesting of manual versus autonomous observing, determining the limiting magnitude and carrying out a full characterization of theParamount telescope will highlight the strengths and failings of the observatory. As well as system research, a survey will be carriedout to deduce the feasibility of observing galaxies for such a survey, including an analysis of the varying traits that will affect theoutcome of observations.Results. Making use of the available software is crucial to the success of any further attempts at observing supernovae from Bay-fordbury, so an introduction to the different software suites currently installed is included, as well as brief descriptions of what eachprogramme controls or can achieve, i.e. camera and dome control, or stacking images so as to reduce CCD and sky noise.

1. Introduction

1.1. Backgrond

In an effort to observe and record the universe around us, numer-ous telescopes have been designed, built and maintained over thecenturies that allow for continuous research. Beginning with thevisible spectrum viewable via the use of optics and the nakedeye, astronomers have over the decades developed means bywhich to observe more of the electromagnetic (EM) spectrumthat was previously inaccessible. Radio waves, microwave ra-diation, X-rays and gamma rays are some of the regions thatare observed with current telescopes. Achieved mainly by Earthand space based optical telescopes equipped with various filters,while radio dishes and other receiving devices have been builtaround the world to observe the longer wavelengths present inthe universe. These windows into the other EM regions have ledto some of the most fundamental discoveries of the last century,of note: The Cosmic Microwave Background (CMB) radiation.The observation and detection of Supernovae (SNe) has grownsignificantly in scientific interest over the past century, with no-table works from Edwin Hubble, and the more recent Perlmutterand Riess Nobel prize winning discoveries. Observing SNe canbe a lengthy undertaking, with many nights required for carry-ing out surveys on the sky, in the hopes of spotting a supernova(SN) within a host galaxy. SN surveys requires planning, poten-tial targets need to be considered and approved for whether ornot they can be observed by the intended observatory, includinga summary of the abilities of the telescope that is to undertakethe majority of the survey’s requirements. This is where charac-terizations, as well as an in-depth analysis of the observatory are

required before proceeding with the intended survey. Once a starcan no longer support itself against gravitational forces, eitherby termination of core fusion reactions that supply the balanc-ing thermal pressure, or by instabilities, it will then reach criti-cal conditions, as explained in chapter 3, and explode, it is thisprocess that is of great interest and the subject of this report.These explosions are theorised to be the reaction for producingthe heavier elements that contribute to the 4% baryonic mattercontent of the known universe, due to the energies and tempera-tures that are reached within such explosions causing the fusionof smaller nuclei into heavier elements. The Sun is the closeststar that allows for detailed observations, allowing astronomersan insight into the internal structure and processes that powersa star. It is generally accepted, within the current model of stel-lar evolution, that the Sun is on the Main Sequence (MS), andhas been for around close to 4.6 billion years. It is then goodpractise to look out into the disk of the Milky Way (MW), ourhost galaxy, to observe and note all the different spectral typesor stages of stellar evolution surrounding our Sun, ranging fromgas clouds to proto-stars, MS to Red Giants (RG), and even theredder Asymptotic Giant Branch (AGB) stars that are sheddingtheir outer envelopes. One of the problematic stars to spot areknown as White Dwarfs (WD), stars that have a high luminosity,but shine dimly in comparison to their surroundings or compan-ion star, the closest WD is named Sirius B and is located 8.6 lightyears away, with its binary companion Sirius A. SN are featuredin many scientific discoveries and journals, with a growing cata-logue of their discoveries and properties. Some well-known SNsurveys to-date include the Sloan Digital Sky Survey (SDSS)which is currently on its fourth data release since its first in

Article number, page 1 of 14

A&A proofs: manuscript no. "Project Supernova"

2001 (SDSS (2016)). Another survey is the Dark Energy Sur-vey (DES), having started in 2013 and currently running in theChilean Andes, it was designed with the intent of observing andmeasuring SNe so as to help constrain both the Hubble constant,H0 (i.e. the expansion of the universe), and the acceleration termfor the expansion of the universe, via the theorised presence ofDark Energy (Dark Energy Survey (2013)). The cataloguing ofSNe is the main goal behind most smaller surveys operating to-day, with the aim of collecting as much scientific data from eachevent as physically possible, including light curve profiles andemission spectra. The large community of astronomers meansthat new discoveries can be reported, verified and released to therest of the world in a small time frame so as to alert many moreobservatories to currently occurring SNe. Due to their somewhatrare and varied nature, SNe are not completely agreed upon byall astronomers, the current models are continuously being testedand occasionally broken by new observations that defy the cur-rent theories. It is timely then to reconsider the nature of SNe,continuing to catalogue their properties while also searching fora complete model.

1.2. Observing Supernovae

Type Ia SN, described in chapter 3, are the most observed objectswithin the field of SN surveying, due in part to their progenitor; alower mass star. These stars are considered as the most abundantof stellar objects in the known universe. This notion stems fromthe study of how gas and dust is distributed within a galaxy, con-tributing to the formation of different mass stars, as set out in theInitial Mass Function (IMF), which finds that the majority of thegas is found within the lower mass stars, whilst the largest lumi-nosity contribution originates from the larger stars within galax-ies. The greater number of lower mass stars leads to a greateroccurrence of the Type Ia SN, which marks the death of suchprogenitors. It is accurate then to predict that a survey will detecta greater number of Type Ia SN, as compared to the Type Ib, Ic,and II SNe that arises from the death of higher mass stars. Fromthe IMF it is reasonable to select spiral type galaxies, which con-tain a mix of both high and low mass stars and a rich abundanceof gases, for observations, increasing the likelihood of observingany SNe, compared to targeting elliptical galaxies that yield astatistically lower change of observing any SNe as they containonly older low mass stars, and little to no gas that could leadto further star formation. Much can be gained from observinga SN, with their infrequent occurrences and varying properties,and astronomers race to gather as much data per observation aspossible. The techniques employed to observe them, as with anybright astrophysical process, are based on analysing the wave-lengths of light, either by photometry with a ‘Charge CoupledDevice’ (CCD) or splitting the light into its constituent parts andexamining the spectrum to distinguish the different wavelengthspresent. This process allows for the determination of the elemen-tal abundances within the SNe, while also enabling the calcula-tion of redshift. Light Curves are a useful way of displaying thelight decay profiles of different SNe and their recorded bright-ness’s over consecutive observations and nights. SNe decay rate,as well as the width of the peak, are characteristics that haveproven their use in probing the different processes that lead tothe apparent diversity in SNe, as later discussed in section 3.2.Spectral analysis of SNe reveals a wealth of information in re-gards to molecular abundances and compositions that arise fromthe extreme conditions within them. Learning what elements arepresent in the wake of a SN helps to determine both the pro-genitor and the type of SNe, an example being the presence of

Hydrogen lines in a type II SN spectra, but faint, if any, for atype Ia SN spectra. This variation is due to the different envi-ronments and causes of SNe, as discussed in the next chapter.Another use for spectral analysis is the detection and measure-ment of redshift, as seen in the shift in wavelength, of known ele-ments, towards longer wavelength values, allowing astronomersto refine the redshift of a host galaxy, as other methods of es-timation are available. There are other methods of observingSNe, though such methods will not be practised here. One suchmethod is to apply different light filters to a telescope so as toprobe the X-ray region of the EM spectrum, where SNe rem-nants are known to emit the most intensely. Another is the useof ground based radio telescopes to observe the Radio contin-uum, specifically the frequency band of 4-6 GHz for synchrotronemissions. Synchrotron has proven to be useful at indicating on-going star formation within galaxies. Observations of the radiospectrum allow for the detection and mapping of synchrotronemissions, where Synchrotron emissions arise from highly rel-ativistic electrons that have been accelerated by the expandingSN shock front, or from highly magnetic spinning neutron starsknown as magnetars, or from an Active Galactic Nucleus (AGN).As well as Synchrotron emission, neutrino detection is a viablefuture detection method, though currently there are few ways inwhich to observe neutrino fluxes to such an extent as to concludethat the source was an SN. Due to SN light profile curves ap-pearing most prominently in the optical, this survey will observethem in the optical bandwidth of the EM spectrum, using the var-ious Johnson filters that are installed within the CCD cameras atBayfordbury Observatory and listed in table 1.

1.3. Scientific Purpose

With the use of the magnitude system, the logarithmic measure-ment of light as scaled according to the eye, SNe are prime tar-gets to measure distances via their apparent brightness, often asbright as their host galaxy. Before SNe it was the use of CepheidVariable stars that distance was calculated, Cepheids being starsthat pulsate in peak brightness over a measurable period, but dueto a drop in apparent brightness at increasingly distant sources,another ‘standard candle’ was required for deeper observations.Going 400 years, astronomers have catalogued different objectsin the night sky, those including comets, galaxies, star clustersand more recently SNe. Over that time period, models for manymore objects than those listed here have been developed and al-tered to fit physical observations that did not entirely agree. Ofall the different SNe discussed in this paper, and due to theirgreater frequency in occurrence, type Ia SNe are the most ob-served and hence are understood the best, with a well understoodmodel that has been established to explain what occurs within thecosmologically fast peak in brightness. One model is the ‘Stan-dard Candle Model’ and predicts that all type Ia are the result ofa White Dwarf star exceeding a known mass limit and exploding,exhibiting the same light curve profile, with a one to one relationbetween the peak magnitude and the light curve width. The massrequired to exceed this mass limit is acquired via the accretionof mass from a neighbouring star, or the rarer case of two WhiteDwarfs merging. As previously mentioned, SNe are useful forindicating recent star formation, though only if the SN in ques-tion is classified as Type Ib, Ic or II, as these are from the corecollapse process within the younger more massive stars. Theseare, as discussed in the introduction, found only in spiral typegalaxies. These SNe emit in the radio continuum at 1.4 GHz,a result of relativistic electrons circling in a galaxy’s magneticfield that are accelerated due to interactions with shock fronts


Thomas Spriggs: Bayfordbury Observatory Supernova Search

emanating from SNe.

S FR (Msun yr−1) = 5.9 × 10−22L1.4 GHz (W Hz−1) (1.0)

Using equation (1.0) it is possible to estimate the rate of star for-mation, in solar mass per year, from the luminosity of the radiocontinuum at 1.4 GHz. The spectra from star forming galaxies,in the radio frequencies, can be described by a simple power lawin the frequency, making use of a ‘spectral index’, α, rangingin value from 0.7 to 1.1, with the intensity being related to thefrequency: S ν ∝ ν−α. Then finding the luminosity required forequation (1.0) can be achieved from re-arranging equation (1.1):

S 1.4 GHz =L1.4 GHz

4 π d2L (1 + z)α−1

(1.1)

Where S 1.4GHz is measured intensity, dL is the distance to theluminous source and z is the redshift. In Cosmology, SNe are theprimary interest in Riess, Schmidt, and Perlmutter’s (Riess et al.1998, Perlmutter et al. 1999) Nobel Prize winning discovery ofthe accelerating expansion of the universe. As well as being usedfor distance estimations, SNe are useful for finding the redshiftof a host galaxy, where redshift is the measure of how fast agalaxy is moving in a radial motion away from Earth, with thelight emitted being shifted toward the reddened end of the EMspectrum due to the expansion of space-time.

1.4. The Bayfordbury Observatory

The observatory at Bayfordbury, established in 1969 by the Uni-versity of Hertfordshire, comprises of seven optical telescopes,with the addition of four radio telescopes. The location was de-cided upon due to the remoteness of the area, staying clear of asmuch light pollution as was feasible, compared to other univer-sity observatories that are located closer or within cities and havea harder time of reducing interference from external, earth basedsources. Of the seven telescopes, two can currently be controlledremotely, as well as being set to robotic mode where they willutilise software packages to run queued requests. The softwareincludes SkyX, ACP Observatory control software which usescustom scripts in Remote Telescope Markup Languate (RTML)form, while also using MaximDL to control the CCD mountedonto the rear of the telescope. The telescopes mentioned here arenamed CKT and Paramount: the CKT is a Meade LX200GPStelescope, while Paramount is a LX200R Meade telescope. TheBayfordbury Observatory includes a 4.5m radio telescope dishnamed the R.W. Forrest Radio Telescope, used mainly for 21cmand 4 GHz observations within the spiral arm of the MilkyWay. 21cm is the wavelength used to observe molecular hydro-gen clouds that can be tracked, and their relative velocity de-termined, whereas the 4 GHz frequency looks at the previouslystated synchrotron emissions. Bayfordbury has observed SNe inthe past, one example is the SN that occurred within M82, namedSN2014J, seen in Figure 1. First officially reported by staff andstudents of University College London (UCL), however it wasimaged by Bayfordbury, but unfortunately the irregularity wasnot taken note of, or the file stored. SN2014J was a type IaSN, reaching a peak magnitude of 10.5 in the R band, thoughdiscovered with a V band magnitude of 11.7 (AAVSO (2014)).SN2014J’s light curve profile and spectral analysis are seen inFig. 2 and Fig. 3 respectively.

2. Supernovae

Type Ia Supernovae are the violent phenomena that occur at theend of stars’ lives, occurring after they evolve off the Main Se-quence (MS) and onto the Red Giant Branch, most becoming aWD. The mass, and sometimes the surroundings, of the progeni-tor star dictates the mechanism for the event: triggered by accre-tion from a neighbouring star. Core Collapse SNe are the resultof internal hydrostatic instabilities followed by gravitational col-lapse. In this section an overview of stellar evolution, supernova(SN) classification and scientific experiments that use SN obser-vations are discussed, with the intent of bringing the reader up tospeed with current theories and applications.

2.1. Stellar Evolution

Star formation is the result of over densities within molecularclouds, mainly comprised of hydrogen in the form of H2, bythe collapse and fragmentation of self-gravitating regions withinthese clouds. This process is typically found in the arms of Spi-ral Galaxies, where the Interstellar Medium (ISM), comprisingof gas and dust, is most abundant and far enough from an AGN toallow for collapse. This is relevant as star formation can be trun-cated by AGN feedback, as well as by Supernovae, either due toevacuation or heating of the surrounding gas, leaving areas de-void of star-forming material, or gas that is of a temperature, andhence kinetic energy, to collapse. The requirement for collapseis that a certain mass of gas is contained within a volume. Thismass lower limit is called the Jeans Mass:

MJ ∼ (kB

µmHG)

23 T

32 ρ−

12 (1.2)

When the Jeans Mass is contained within the Jeans Length (aradius which sets up a volume within which the Jeans Massmust be located to initiate collapse), the cloud will then frag-ment due to its self-gravity becoming greater than the thermalpressure supporting it. Unless the cloud is heated by an exter-nal source, contraction cannot be halted and stellar formationcan commence. Once stars evolve out of the proto-stellar phaseand onto the MS they don’t undergo much variation for quitesome time, anywhere between Myrs to Gyrs (106 - 109 years),dependent upon their mass. In this case we will look at a typicalsolar mass star and how it is predicted to evolve. Once the corestops producing sufficient energy via hydrogen burning, it startsto contract while the outer envelope of hydrogen and helium ex-pands, leaving a hydrogen-burning shell around an isothermal

Fig. 1. M82, B band, 120 second exposure, highlighted is SN2014J



Fig. 2. Light curve plotted in different filters for 2014J, apparent magni-tude plotted against Julian Date (OBSN (2014)). The different coloursrepresent the different filters used in tracking the magnitude, clearlyshowing that SNe can vary significantly in value depending on whichfilter is used in the observation. The B filter is the primary filter due tothe standard candle light profile being most evident.

Fig. 3. Spectrum from 2014J, with easily identifiable traits of a SN-Iasupernova: Si II peak being the most prominent (OBSN (2014))

core. This outer envelope is convective, causing the distributionsof the H and He to become mixed, though due to gravity andthe continuous convective movement, the helium will fall intothe core, increasing its mass and gas pressure. The Schönberg-Chandrasekhar limit (S-C limit) (Schönberg & Chandrasekhar(1942)) states that for a star with a polytropic envelope with apolytropic index of n = 3 (Ball et al. (2012)), the maximum frac-tion of a star’s mass that can exist in an isothermal core andstill support the material surrounding it, the star will evolve oneof two ways: Helium core mass is less than the S-C limit: Thecore remains in a hydrostatic equilibrium during the hydrogen-burning-shell phase. As helium is produced from this shell itfalls into the core increasing its mass, potentially causing it tobecome degenerate. While in this stage the star is evolving alongthe sub-giant and giant branches at a slower rate. When the coremass reaches ∼ 0.48M� (solar masses) and is highly degenerate,the temperature reaches values of ∼ 108K, the helium ignites inwhat is called a helium flash, this is where the degeneracy of thecore leads to a thermonuclear runaway effect, emitting ∼ 1011L�(solar luminosity, where L� = 3.846×1026 W) in a matter of sec-onds. Helium core mass is greater than the S-C limit: The corecontracts on a thermal timescale, i.e. the timescale required to ra-

diate the thermal energy outward so as to contract. Collapse willcontinue until the electron degeneracy pressure is strong enoughto support the core, or when the helium within the core igniteswhen temperatures reach ∼ 108K. The helium will ignite ‘qui-escently’ and the nuclear fusion process can again start withinthe core. The star is then on the Red Giant Branch (RGB) of theHertzsprung-Russel (H-R) Diagram. A quick note on electrondegeneracy: degeneracy arises due to Pauli Exclusion Principle,where electrons are forced to occupy the lowest available en-ergy levels. As more electrons are packed in due to increasesin density or gravitational contraction within the core, electronsreach a state where they can no longer be compressed to lowerenergy states, leading to an outward pressure supporting the in-ward gravitational contraction. Polytropic state refers to a solu-tion of the Lane-Emden equation, which describes the pressureas dependent on the density, with the equation of state:

P = Kργ (1.3)

γ = 1 +1n

(1.4)

Where K and γ are constants for a star, and n is the polytropicindex for the star. The mass of the star determines which path astar will take along the H-R diagram, each with a different in-ternal structure and lifetime. These differences allow for classifi-cation and simpler identification of the progenitor. Once the starreaches the Red Giant Branch (RGB), dependent upon its mass,it can take the form of different sub-branches, most notably theAsymptotic Giant Branch (AGB); stars < 8 − 10M� (consideredlow mass) follow this branch in their evolutionary tracks. Run-ning parallel with the main RGB, AGBs appear similar in sizeand luminosity, though their spectral emissions may vary. Theinternal structure of an AGB is composed of an inactive coreof carbon and oxygen supported entirely by electron degener-acy pressure, surrounding the core are helium- and hydrogen-burning shells, though the helium shell burning is periodic. Out-side of these shells is a mixed, deep, convective layer, containingelements like carbon and nitrogen, hydrogen and helium (Iben(1967)). AGB stars are not long lived, as brief as ∼ 106 years,but are important for stripping the star of its mass, revealingthe core. The mechanism by which an AGB star loses mass isradiation driven, where the envelopes pulsate due to instability,causing material to be left in cooler regions surrounding the star,this colder matter clumps together to form dust. The high lumi-nosity of the star, alongside the energy released from continuoushelium ignition, impacts upon dust that now has a larger cross-section with which photons can interact, thus setting up a strongstellar wind that drives material outwards, essentially strippingthe outer layers. The remnant left behind by the mass loss is typ-ically a carbon/ oxygen (C/O) core surrounded by thin, heliumand hydrogen layers, the star is now a WD. There are no morenuclear reactions taking place within a WD, thus its surface be-gins to cool, the only pressure left to the core that is keeping thestar from collapsing is the aforementioned electron degeneracypressure. Dwarf Stars are found in the lower left corner of theHR diagram [Fig. 4]. WDs form the most abundant of the dwarfclasses, due to the fact that WDs generally evolve from lowermass stars, and as can be seen from the IMF, there is a largernumber of lower mass stars compared to higher mass stars.



Fig. 4. A Hertzsprung-Russel Diagram, depicting the main distinguish-able branches that occur over stellar evolution. (Observatory (2012))

2.2. Classification

Supernovae are classified based on their origin: low or high massstar, accretion or unstable core collapse. Classification is usefulfor cataloguing, providing astronomers with a filter that can leadto comparisons in the rate of each type, leading to a better un-derstanding of the initial mass function (IMF).

2.2.1. Type Ia

The most prominent of SNe, observed in both spiral and ellipti-cal galaxies, and assumed to only occur in binary systems on theaccount that they require a source of stellar mass to accrete from.The progenitor of a type Ia SN is believed to be a WD star, com-monly found in binary systems, and it is generally accepted that astar with MS mass MMS ≤ 5M� (Das & Mukhopadhyay (2013))will evolve until the WD stage. Stars above this limit undergocore collapse, as discussed in sections 3.2.2 and 3.2.3. A TypeIa SN is the product of a WD undergoing a thermonuclear det-onation. There are currently two different models that describethe conditions required: the first is the Single Degenerate (SD)channel and is achieved by accreting matter from a companionbinary star, up to a limit known as the Chandrasekhar mass limit:MCh ≈ 1.4M�. The other model is called the Double Degenerate(DD) channel where a WD will merge with another WD, result-ing in a combined mass of greater than MCh. The mass inflowrate from the SD channel, can allow for helium and hydrogenburning to occur in the outer shells (Yoon & Langer (2004)),which leads to an increase in the internal temperature. Due to nointernal fusion reactions, the WD that is currently supported byelectron degeneracy pressure cannot expand to compensate forany increase in core temperature. Once the required temperaturefor carbon burning is met, the burning causes a further increasein core temperature over a period of ∼ 1000 years. Degeneratepressure is only dependent on density (1.3), but independent oftemperature, so as the internal temperature rises, the WD can-not alter its pressure to reduce the energy production as a MSstar would, instead the increase in temperature leads to furthernuclear burning processed, resulting in a run-away incinerationof the internal material, ending with a thermonuclear detonation.The energy released by these nuclear reactions entirely destroysthe star and sends the resulting material outwards in a fast mov-

ing shock front. What keeps the SN from dissipating faster thancurrently observed is the formation of radioactive isotopes of56Ni, which acts to increase the opacity of the SN, decreasingthe number of photons, produced from the beta decay, that canescape from within the expanding volume, it can be concludedthen that the peak luminosity is proportional to the amount of56Ni produced. 56Ni undergoes beta decay (half-life of 6.1 days)to 56Co, then again into 56Fe (half-life of 77.3 days): 56Ni→56Co→56Fe. This is the mechanism that drives the Type Ia light curveprofile, as seen in Fig.5. The initial beta decay of 56Ni into 56Cois the reaction that controls the profile of the initial peak, withthe second beta decay process being linked with the width of thelight curve (Blondin et al. (2012)). Spectral analysis of typicalType Ia SNe shows prominent Si II lines in the wavelength re-gion of 6150Åto 6355Å(Blondin et al. (2012)). Other elementspresent, as seen in Fig.6, are Iron, Fe II and Fe III, Cobalt, Co II,as well as smatterings of oxygen O, magnesium Mg and calciumCa, all produced via the nucleosynthesis that arises from the ex-treme temperatures within the thermonuclear detonation of theWD. The general lack of hydrogen lines is itself a reasonable in-dicator that the observed SN is a Type Ia. Whereas for any othertype of SNe, there are indications of H and He lines in the emis-sion spectra, due to both elements being present in surroundingshells of the collapsed core (see description below). For the caseof the exploding WD however, the presence of H or He is mini-mal, the overall contribution of these elements to the star’s massis such a small fraction that it will almost certainly be burnt upin the runaway nuclear explosion occurring.

2.2.2. Type Ib / Ic

Type Ib and Ic SNe are believed to be the result of stars inthe Wolf-Rayet (WR) phase that undergo core collapse. Withmasses greater than 20 M�, WR stars are notable for their H-deficiency, due to mass loss of their outer envelope, inferredfrom spectra that indicate mass loss rates in the order of tensof solar masses. The mechanism behind this envelope strippingis the interaction with high velocity stellar winds, travelling at∼ 3000kms−1. The star is stripped of its envelope leaving a 20-30 M� core; it is the core that then collapses after burning up itsfuel supply, hence these two sub-categories of supernova are re-ferred to as ‘stripped-core supernovae’ (CC-SNe) (Takaki et al.(2013)). The core’s internal structure is that akin to an onion,with layers of different elements, ranging from H and He at theouter edges, leading towards O and Si surrounding the centre.The layers are at a high enough temperature to continue nu-clear burning processes, producing increasingly higher fractionsof the heavier elements that build up and fall further into the core.Nuclear burning continues until the inner core consists of 56Fe,from here on no further exothermic fusion reactions occur. OnceSi burning ceases, the core density and temperature increases,supported only by the electron degeneracy that arises from thiscontraction. The condition for collapse is that the mass of theiron core be greater than the Chandrasekhar mass limit for thecase of 56Fe, only then can gravity become dominant against thepressure from the electron degeneracy. The Chandrasekhar masslimit is different from that of a WD, here MCh = 1.26M� and iscalculated via equation (1.5):

MCh = 5.83µ−2e (1.5)



Where µe is the electron mean weight for a given element, in thiscase it is for 56Fe:

1µe

=∑

i

Xi

AiZi (1.6)

Xi is the mass fraction of the element, Ai is the atomic massand Zi is the atomic number of the element. Core collapse isa runaway effect and cannot be halted, as the radius decreases,temperature and density increase rapidly causing the central 56Feto form a very dense core. The energy released by such a collapseof the surrounding material is due to photodisintegration by highenergy photons, where ∼ 2MeV per nucleon is released. Protonsand neutrons are released via photon stripping of the lower masselements, i.e. helium, which is a highly endothermic process:4He + γ → 2p + 2n (1)

As thermal energy is removed from the surrounding gas, pres-sure support drops, resulting in the collapse onto the core. Whenthe core reaches T ∼ 109 K and ρ ∼ 1013kgm−3, the electronsthat contributed to the degeneracy and subsequent core supportare captured via proton interaction: p + e− → n + ν. The neu-trinos released in this manner cause a huge energy flux outwardfrom the star, carrying stellar material with it. ObservationallyType Ib and Ic are great indicators of ongoing star formation, ashigher mass stars live shorter lifespans and end up going SN,attributing to the formation of lower mass stars with the ex-pelled material. In their spectra, as seen in Fig.6 there are fewerpeaks, with either limited or undetectable amounts of Si II, alongwith Fe II from the core, there may also be a few elements thatare left over from the nuclear fusion within the shells that getsejected. HeI lines, at ∼ 587 nm, are present in spectra for TypeIb SNe, though neither Ib nor Ic show any H lines, due to thepre-mentioned absence.

2.2.3. Type II-P / II-L

Much like with Type Ib and Ic SNe, Type II SNe are believedto be the result of core collapse within evolved, higher mass (M> 8 to 10 M�) (Anderson (2016)) stars consistently found in thearms (within HII regions) of late type spiral galaxies, where thereis ongoing star formation. This characterization of location al-lows for the interpretation that the progenitors are both youngand massive, known as Red Supergiants (RSB). Core collapse ofthese young, massive progenitors occurs due to a drop in nuclearfusion reactions within the core, generally because iron has be-come the most abundant element there. Once the core reachesthis saturation point it can no longer produce the outward pres-sure required to keep the star stable, the surrounding envelopeof matter then collapses inward under gravitational attraction.Upon collision with the core the matter rebounds outward, leav-ing a compact and extremely dense neutron star in its wake, orif the progenitor was massive enough, a black hole. Type II SNspectra show varying H lines, as seen in Fig. 6: Hγ, Hβ, Hα.The presence of H lines is a good indicator for Type II SNe, asno other SNe have such abundances, it can be concluded thenthat the RSB progenitors maintain an outer, convective shell ofH atoms even before core collapse occurs. There are a few dif-ferent sub categories for Type II and classified appropriately viatheir light curve profile, seen in Fig.5. Type II-P (plateau) SNeshow nearly constant luminosity, with small variation, over thefirst 100 days since the peak luminosity is reached, while TypeII-L (linear) shows a more rapid, linear decline in luminosityover the observational time period (Anderson (2016)). As for an

average peak absolute magnitude, Bardon et al. (Barbon et al.(1979)) observed 38 Type II SNe and found a mean B band ab-solute magnitude of MB = -16.

Fig. 5. Light curve profiles of SNe, with duration from peak magnitudeagainst absolute B magnitude. Notable profiles are that of the Type Ia,Ib, Ic, II-L and II-P lines (Filippenko (1997)).

Fig. 6. Spectra from each type of SNe, with the Rest Wavelength inangstroms along the horizontal axis, and log flux along the vertical axis,plus correction constant (Filippenko (1997)).

3. Bayfordbury Review

3.1. Observing with Bayfordbury

Both the CKT and Paramount telescopes can be fully au-tonomous when in robotic mode, i.e. the use of RTML scriptswithin ACP, they are controlled, along with the domes andCCDs, by the connected computer. This allows for remote ac-cess and operation with a Remote Desktop Connection (RDC)program via a Virtual Private Network (VPN), allowing users



to login through the university’s own VPN. Remote access isa feature implemented by most observatories and is highly val-ued as it minimises the requirement for manual operation of atelescope, especially when optimal observing conditions are in-frequent. Stationed at the Bayfordbury campus is a central hut,named after Sir Patrick Moore for his dedication and contribu-tions to astronomy. This hut is the central nervous system forthe telescopes and radio dishes, weather stations and computers.The observatory is manned by one to two staff members, primar-ily maintaining the systems and telescopes, while overseeing theuse of the telescopes by undergraduates / graduates and the pub-lic alike. There have been a few occasions when having a staffmember on site or close by to resolve an issue with the tele-scopes has been beneficial, when either a lens cap has been lefton, or the telescope has disconnected itself from the computerdue to restrictions in movement. Bayfordbury is ideally located;positioned away from most major light pollution sources, on ahill above the local surroundings and in a part of England thathas quite stable weather patterns. By locating the observatory insuch conditions, sky survey efficiency can be improved due tothe telescope being exposed to a higher limiting magnitude anda large field of view on the sky, increasing the distance out towhich observations can be made and how well targets can beresolved, though still with limits on how often or how faint thetelescopes can observe to.

3.2. Characterization of the Paramount Telescope

For the purpose of this paper, the Paramount telescope has beenchosen for characterization. As of writing this, the Paramounttelescope and connected equipment is the optimal choice outof the seven other telescopes at Bayfordbury, due in part to therobotic abilities and general upkeep that is carried out on to keepit operational. The light collected by a telescope can be quanti-fied by the following expression:

N(t) = Q A t ∆λ np (1.8)

With A as the area of the aperture, t is the exposure time,∆λ is the wavelength bandwidth, np is the photon flux, and Qis the Quantum Efficiency (Cheng (2010)). The Paramount isa Meade LX200R, catadioptric1 telescope, which utilizes boththe Cassegrain reflector in conjunction with a Schmidt correc-tor plate, also known as a Schmidt-Cassegrain telescope. Fig.7 shows the telescope in action, the secondary mirror is at-tached to the inside of the corrector plate so as to remove theneed to suspend the plate inside the telescope, introducing anintrusive element to the observations that would also need ac-counting for. The aperture and focal length of both CKT andParamount are 406.4mm and 4064mm respectively. From equa-tion (1.8), it is clear that it is advantageous to have a larger aper-ture, A, which is why astronomers are always building largertelescopes. The other controllable value is the exposure time,sometimes referred to as the integration time, it is measured inseconds and the greater t is the higher N(t) will be. Both ∆λand np are derived from the observed source, and Q is deter-mined for each telescope, beyond these factors it is clear thatthe CCD readout increases linearly with both aperture and ex-posure time. Paramount is equipped with an SBIG STL-6303CCD unit that has a FOV of 23.4′x15.6′, large enough to capturethe majority of Andromeda M31, the closest galaxy to the MW.

1Catadioptric telescope: a combination of specific mirrors andlenses to correct for any errors in light rays passing down the telescope,i.e. any aberrations of the light.

The plate scale of the CCD is 50.75′′mm−1, and is a measure ofhow much sky is covered per mm of the pixel array. Recentlytwo new CCD sensors have been delivered to the Bayfordburycampus and have a FOV 2.7 times greater than the above men-tioned SBIG units. This larger FOV would be beneficial for asurvey as it would allow for larger patches of sky to be cov-ered per exposure, with the potential of reducing the scanningtime. This improvement would be more substantial for a largersky survey, i.e. SDSS, compared to what can be achieved here.In an ideal telescope, the Quantum Efficiency (QE) would be100%, with Q=1 in equation (1.8), both the telescope and theCCD achieving a 0% reflective loss of the incident light, mean-ing no dead pixels or light loss on the way from the lens downthe length of the telescope, passing through potentially multi-ple mirrors and lens before impacting onto the CCD array. Forthe CCD, the QE is the measure of how efficiently will a pho-ton liberate an electron once impacted upon the silicon layer ofthe CCD pixel array, with each pixel treated as a bucket for thephotons, any dead pixels will incorrectly read off the liberatedelectron count within itself. Different filters that are applied tothe CCD also have their own QE values and must be accountedfor when calibrating the telescope, the QE value never exceedsanything more than 98% due to imperfections in the manufac-turing process. The telescope’s reflective components contributeto the overall QE of the system due to photons potentially beingabsorbed within the material of the telescope itself or reflectingin a different direction than intended. One method to overcomethe problem is to apply a coating to the mirrors used inside tele-scopes, a chemical silver coating used to be applied which re-duced the reflective loss down to 5%, but any sulphur dioxidein the surrounding air would corrode and tarnish the coating andreducing the effectiveness of the applied coating. More recentpractises include the use of a vacuum chamber to apply an alu-minium coating, though more resilient to erosion, the reflectiveefficiency varies between different wavelengths of light: 10% foroptical, 12% in UV emissions at wavelengths of 250nm, thenimproving as it is exposed to the IR spectrum (∼ 1νm). Whendealing with more than one mirror, just as Paramount uses, thereflective efficiency is the square of the value as determined for asingle mirror configuration. (Cheng (2010)) The filters in CCDs,installed via a filter wheel for ease of access, are used to filter thephotons that will be incident on the pixel arrays, allowing for thedifferent parts of the EM spectrum to be observed without bleedthrough from the other wavelengths. Paramount is equipped withthe filters listed in Table 1, with U B V R and I belonging to theJohnson filter group, and the ESO La Silla filters [O III]2 , H-alpha and [Si II] deal with the broad and narrow bands of theEM spectrum to do with the element the filter is named after.

3.2.1. Calibration Methods

When dealing with a large array of pixels, ranging from millionsto billions per detector, there are expectations for the array tobe plagued by background and thermal noise that accompanieseach reading. Whether it be due to a manufacturing defect, orin some cases cosmic rays, a CCD is never 100% efficient inreading off the counts, and so calibration is required to reducesuch intrusions. This calibration is carried out via flats; framesthat are designed and recorded in such a manner to reduce eachcontribution of unwanted noise. The Bias Frame (BS) is an ex-posure of zero seconds, forcing the CCD to take a reading while

2Square brackets are used for certain elements to denote that theyare ‘Forbidden lines’, as seen in the H II region.



Filter U B V R I [O III] H alpha Si IIλe f f (nm) 365 440 550 700 900 500.7 656 672

Table 1. Johnson Filters and their effective midpoint wavelengths. (Gallaway (2015)) (O’dell (2001))

the shutter is closed. This technique highlights the nature of thepixels, as each will vary ever so slightly in comparison to next,this is an unavoidable but accountable problem arising from themanufacturing of the pixels and how well each will hold thesupplied electrons. A light frame is the exposure of the CCDto an intended target, with the shutter open, with an exposuretime, it is this frame that the calibration is applied to. The DarkFrame (DF), much like the bias, is an exposure with the shut-ter closed, but with a duration matching that of the light frameit is to be subtracted from. The DF is ideal for removing thenoise generated via the Dark Current (DC), where the DC arisesfrom thermal electrons, not originating from photon interactionsbut rather from surrounding sources close to the CCD. DC noiseincreases linearly with temperature and exposure: longer expo-sures and higher temperatures (due to external heating or from afaulty fan) result in a higher noise count from the DC (Gallaway(2015)). Both the BS and the DF are subtracted from the lightframe so as to remove thermal and random background elec-trons originating near to the CCD. The next technique is calledflat fielding; where a series of images are taken and a set countis reached ( 30,000 for an average 16-bit camera), this is donefor each of the filters. A median value for each pixel is foundand used to make a science flat, then after several repeats of thisprocess, in each filter, the mean value is used to construct a Mas-ter flat for each filter (Gallaway (2015)). Flat fields are takenwhen the telescope is pointed toward a flat/ uniform source, i.e.opposite the Sun during twilight hours (Sky flat) or the moreconvenient option; a square white surface attached to the insideof the dome (Dome flat). Such flats are taken to help accountfor irregularities in the overall reading from the CCD, includ-ing checks on the pedestalling3 of images, then ranging from thetelescopes’ optics, any dust on the filters and dealing with hav-ing a circular aperture exposure onto a rectangular pixel array(Gallaway (2015)). Once an image has been calibrated with theabove methods, first by subtraction of the Bias and Dark frames,then dividing the results by the Flat frame, which itself will have

Fig. 7. A Schmidt-Cassegrain telescope, combining a corrector platewith a spherical primary mirror resulting in an image that would havebeen produced by a parabolic primary mirror. This design reduces bothphysical size and production costs.

3A ‘pedestal’ is the application of a fixed count number, increasingthe counts by a linear step is the method applied to counteract any po-tential readings from the pixels when the charge is not correctly storedwithin them. The pedestal is then later removed in the ‘pipeline’ processfor astronomical images.

had the Bias frame subtracted from, it is then referred to as ascience frame. From here the science frame is ready for anyfurther photometry or analysis, having had the majority of thebackground noise removed. Aperture Photometry is a processthat can be carried out by a variety of astronomy software pack-ages, including MaximDL, DS9 and AstroimageJ. An apertureis created for the user to manipulate and place, with the optionsof increasing and decreasing the size and diameter of the an-nulus, the goal is to surround the object of interest, normally astar, within the inner annulus, while reducing the noise or countsfrom external sources (i.e. other surrounding stars near the tar-get) within the outer annulus, which is tasked with reading offa sky / background count. This method enables the program toread the source target count and the sky count at the same time,resulting in a ‘signal minus sky’ counts value. The applicationof this process is discussed and used in section 4.2.2, and 5.3(Gallaway (2015)).

3.2.2. Limiting Magnitude

The limiting magnitude of an observatory is the faintest mag-nitude that can be observed before the sky noise dominates thesource counts, with a slight variation between each filter and anyfurther increase in exposure length will lead to no discernibleimprovement. This means that the telescope can only see ob-jects out to a limited apparent magnitude, restricting both howmany objects can be detected as well as how far out the obser-vatory can detect object to. The following experiment will deter-mine the upper limit apparent magnitude, though other factorswill reduce distance further: i.e. lunar luminosity, atmosphericthickness and density, and finally light pollution. To determinethe limiting magnitude, an exercise in exposure and calibrationwill determine a result of how faint an object can be, and stillbe detected, while also testing for the point of diminishing re-turns of higher exposure lengths. A series of exposures; 30s,60s, 120s, 180s, 240s, 300s and 600s will be taken, calibrationof each exposure against an already known apparent magnitudefor a pre-selected star will result in accurate values for the mag-nitudes from the counts. Fig. 8 is a finder chart, indicating thestar Cl* NGC 1039 W1368, as chosen for the calibration mag-nitude in the B V R bands. Using AstroImageJ to carry out theabove process on the images taken by Paramount, of M34, viathe automated queuing system, it was then a case of exportingthe results of each star selected as the faintest object of fromeach exposure to an excel spreadsheet. After some research intoconversion between sky counts into magnitude, equation (1.9)was applied along with using the known apparent magnitude ofthe reference star, so as to correct the value via a scaling factor,per filter. (Craig (2014))

m = −2.5 log10(NS ource − NS ky) + 2.5 log10(t) (1.9)

Using the values for ‘sky minus source’ and exposure time (inseconds), as taken from AstroImageJ, it is possible to calculatean observed magnitude. Once the reference star has been passedthrough this conversion a known apparent magnitude for eachfilter has been found, the other targeted stars can be dealt with.Once the actual magnitudes have been calculated, the data pointswere plotted against exposure time, as seen in Fig. 9, showing



Fig. 8. Finder Chart of M34 with NGC 1039 W 1368 highlighted. Thiswas the calibration star, with the apparent magnitude taken from theSIMBAD online catalogue.

that as the exposure time increases, the fainter the telescope canobserve out to. The reason behind finding the limiting magni-tude is to find the point at which an increase in exposure timewill result in diminishing returns of the counts received due toa decrease in the Signal to Noise Ratio (SNR). By definition, alimiting magnitude introduces a limiting distance, a volume cen-tred on Earth within which it is possible to observe targets whilesky brightness levels remain lower than the limiting magnitude.Taking a limiting apparent magnitude of 17, which takes into ac-count an average clear night with low levels of lunar luminosity,and an average absolute magnitude of a Type Ia SNe: -19, it ispossible to find a limiting distance via the use of the magnitudeequation (1.10), re-arranging to make d(pc) the subject:

m − M = 5 log(d(pc)) − 5 (1.10)

d(pc) = 10(m−M)+5

5 (1.11)

The limiting distance, d(pc), comes out to be ≈158Mpc, a dis-tance that is not reached within the scope of the paper, thoughpredicted to be achievable if required. This is an important re-sult, and is referred to in later sections, the result though is a dis-tance and magnitude out to which this survey could theoreticallyobserve too, although such extremes would not be warranted dueto the abundance of galaxies within even a 20 Mpc range.

3.2.3. Autonomous vs Manual Observations

Each of the telescopes are connected to a computer which acts asthe interface, allowing control of the telescope and CCD: point-ing coordinates, target selection and other settings. The com-puter and installed software have the ability to run a range ofvarying tasks as set-out by custom scripts, such as making cal-ibration frames, retrieving queued jobs for the telescope andmany more tasks that can be achieved autonomously. The mainsoftware package, ACP Observatory Control Software pairedwith TheSky X, allows for full automation in the form of RTMLscripted jobs that can be submitted via the online Bayfordburyinternal website. The scripts are generated after using a web-friendly user interface that first allows target selection and veri-fication that it can be observed, exposures, filters, binning, moonavoidance and how many repeat observations should be carriedout. Once filled in, the form creates a RTML script, it is then firstapproved by a member of the Bayfordbury Observatory staff, tomake sure the request is within reason, then judging from the

Fig. 9. Graph showing the Limiting magnitude experiment, imagingM34 open cluster, as undertaken in the B V and R filter light bands.R band shows a definite levelling off once it reaches past 18.5 apparentmagnitude, whereas V and B show trends that the limiting magnitude is∼19 mag. An important experiment in determining the point at whichincreasing the exposure leads to diminishing returns for the counts theCCD reads from the source, and the Signal to Noise Ratio (SNR) de-creases.

supplied description and any other factors, they will assign thejob a priority rank between 0 and 100, where a number results ina greater priority within the queue. If the onsite weather stationreports that the weather is suitable and within safety margins forobservations, the automation can begin, the dome opened andthe queue observations can commence. During this survey, itwas decided that a mix of both manual and autonomous obser-vations should be taken, so as to help with the assessment of thetelescope equipment, as well as gain valuable hands on experi-ence with the observatory. This decision would limit the surveythough as it would require the telescope to be operating at peakefficiency, with minimal tracking and locating errors through-out the usage. That is more of an ideal scenario and more oftenthan not the telescope would have trouble finding a target, oftentime needing to have the pointing location synced against the ob-served stars. This alignment was possible via plate-solving of theimage; where the image is uploaded to a website (astrometry.net)that would compare the image with an archive, returning either asuccessful match and central pointing coordinates, or an ‘unsuc-cessful’ message. Both with manual and automated observing,MaximDL is used as the control interface for the CCD, selectingwhich filter to use, exposure length, what type of frame (light,dark or bias) the observation is and what level of calibration isto be applied. MaximDL also displays the end product of theobservation, once downloaded from the CCD, from here furtherobservations can be decided upon or else see if the telescope isin need of pointing correction. When manually selecting targetsACP has a function that can search from the different catalogues(M, NGC, IC etc.). When searching for a name via this method,ACP will also determine if the search result is currently viewableand not outside the declination limits as set by the dome and lo-cal, for the Paramount telescope, these limits are: lower: 10◦,upper: +90◦. This method of target selection is less desirable inpractical uses for such a survey due to locating errors related tostar charts being out of sync between the computer and the nightsky, with the star finder returning error messages. The way to re-solve such errors is to plate solve4 the image, retrieve the central

4Plate Solving is the act of comparing an image of either knownstars or a galaxy with a catalogue, either by the use of Maxim DL, or by



Filter / exposure Source - Sky (counts) Calculated Magnitude (before calibration) Calibrated magnitudeB30 220.81 -2.18 15.5445 319.91 -2.13 15.5860 307.58 -1.77 15.9390 340.04 -1.44 16.26

120 273.02 -0.89 16.82180 219.28 -0.21 17.49240 279.13 -0.16 17.54300 335.06 -0.12 17.59600 310.05 0.72 8.43V30 266.17 -2.37 15.6145 213.91 -1.69 16.2860 291.60 -1.72 16.2690 245.11 -1.09 16.89

120 207.50 -0.59 17.38240 180.89 0.31 8.28300 154.60 0.72 8.69600 197.54 1.21 9.18R30 1860.31 -4.48 16.6860 3192.07 -4.31 16.8490 2517.14 -3.62 17.54

120 2281.40 -3.20 17.96180 2716.17 -2.95 18.21240 2365.96 -2.48 18.67300 2910.74 -2.47 18.69600 5293.85 -2.36 18.79

Table 2. Limiting Magnitude data, the various exposures as recorded in each filter, with the appropriate data values.

coordinates in R.A and Decl., then syncing ACP to those co-ordinates and exposing again once the target has been selected.While using the autonomous system, and included within theweb browser applet included with ACP, the telescope will at-tempt to find and verify that the target is within the FOV beforecontinuing to execute the plan for that target. This reduces therate of which the telescope returns a false response or a field ofstars that cannot always be plate-solved.

3.3. Feasibility of Observing Observations

Observing SNe is quite the challenge in itself, especially firstfinding such an event, so much so that numerous measures areemployed to increase the chances of detecting and then subse-quently observing SNe. In regards to the feasibility of observ-ing SNe at Bayfordbury, there are numerous limiting factors thatneed consideration and attention if ever an SNe survey were tobe carried out in the future, and be successful. When consider-ing the site for a telescope that will be used for sky surveys, itis normally good practise to place it at a high altitude, some-where not exposed to major storm fronts or unwanted weatherconditions (i.e. cloudy skies, humid atmosphere, variations in

using the website: astrometry.net. The result is a labelled image of theobject, as well as RA and Decl. coordinates for the center of the image,these are used for the syncing of telescopes.

weather patterns). Bayfordbury is located in the county of Hert-fordshire, England, and as such is not positioned atop a moun-tain above cloud level, and nor is it excluded from the variousweather fronts that England is known for; high wind speeds,rain, numerous clouds and the occasional snow. Due to the lo-cation of Bayfordbury the weather requires extended considera-tion in regards to the time allotted for observing. The lower alti-tude, compared to other notable observatories that are mountainbased, results in an increase in atmospheric absorption interfer-ence, as well as greater cloud coverage and low levels of lightpollution. Appendix A contains inverse contrast images of thegalaxies observed and tracked throughout this survey, each la-belled by their respective apparent magnitudes. Though the lim-iting magnitude has been established to be ∼ 19 mag, it is notalways possible to reach such objects due to the seeing, a termused to describe the angular deflection of light from stars by theturbulence in the atmosphere, causing stars to blur or twinkle asthe refractive index varies through the atmosphere. Sky Bright-ness is another factor that will limit how deep of an observa-tion can be undertaken, while Bayfordbury is located away fromlarge sources of light pollution, sky brightness will be an issueif the Moon is at a phase of 50% or more, this is discussed fur-ther in the next section. Winter is an ideal period of the yearto conduct deep sky surveys due to the extended observationaltime made available from the longer nights, as well as the darker



SNe Mean m Median m Faintest m Brightest mIa 18.94 18.5 25.0 10.5Ib 17.9 17.8 23.7 13.8Ic 17.81 17.7 23.4 12.0II 17.9 17.8 25.1 11.2

Table 3. Values calculated from the 2000-2015 dataset of observed andrecorded SNe.

skies from reduced light explicitly from the sun, resulting in afainter limiting magnitude. Table 3 consists of statistical valuesfor each of the SN classifications, as calculated from the data setof SNe between 2000 and 2015. Notice the difference in magni-tude between type Ia and the three other classifications, it wouldappear in agreement with the model of Ia occurring due to differ-ent circumstances than the core collapse of the others. Galaxiesare the largest collection of stars known to us, with masses vary-ing from ≥ 105 for dwarf galaxies to ≥ 1011 for most late-typespiral galaxies, the MW is calculated to be ∼ 1012M�. The massto light relation shows a linear increase and is assumed to befairly constant for all galaxies, M/L ≈1. As massive as galaxiesare, they appear faint in comparison to the local stars within theMW, though they tend to cluster due to gravity (or a combina-tion of Dark Matter haloes / Dark Energy), and the result is agroup of galaxies that constitute the local galactic Neighbour-hood. M31, the Andromeda Galaxy, is our nearest neighbour,both in structure similarity and distance. At a distance of ∼780kpc, M31 is the closest and thus brightest galaxy, viewable bythe naked eye at Bayfordbury. The observed brightness is great-est at the 7 to 8 kpc diameter bulge at the centre that outshinesthe surrounding spiral bar and disk regions, due partly to thelarge stellar population of both young low-mass and high-massstars, surrounding a supermassive black hole, a prediction thatapplies to all galactic cores. Galaxy bulge mass, Mbulge, esti-mates currently stand at ∼ 5 × 1010M� (Häring & Rix (2004)),this is the majority of galactic mass as compared to estimatedgalaxy mass, within 300kpc, of ∼ 1.4 × 1012M� (Watkins et al.(2010)). Galaxy mass estimates are derived by either Jeans equa-tion modelling, virial theorem with velocity dispersion readingsor via the mass to light relation. Bright central regions will leadto over-saturation and bleed through to other regions, less thandesirable for observations, especially when searching for notablybright sources in the spiral arms, which can be faded in compar-ison. Other galaxies show similar light distribution which acts tolimit how much of the galaxy can be resolved from the bleed-outof the bulge. For instance, both NGC 891 and M82 are viewedas edge-on to Earth in inclination, both with large, bright bulgesthat shine through the surrounding gas and dust within their spi-ral arms. If a SN were to occur anywhere near the centre of M31,NGC 891 and M82, it is possible that it could be overlooked asover-exposure, and hence dismissed. There are methods to sub-tract and reduce the central brightness of such targets, and areapplied by professional astronomers or photographers when ob-serving and manipulating such galaxies. The survey plan was toobserve when possible, through the use of remote control and /or using the queuing system ACP utilises. Over the three to fourmonths of optimum observing time, it is estimated that three tofour nights a week would be allocated to observing. It was esti-mated that this survey would at best include the observation of 1SN, with the potential to spot as many as possible that occurredwithin the range of time and sky location that this survey could

cover. This is a ballpark figure, not best supported by the short-ened timescale that this survey will cover.

3.4. Limitations

With the feasibility of carrying out a SNe survey discussed, itis appropriate to next consider the limitations that will constrainsuch surveys, and most importantly highlight those that can orcannot be accounted for by the survey carried out with Bayford-bury. The main limitations that face any survey, on any scale, aretime dependent and will have numerous implications that needaddressing when setting out an initial plan for the survey. Factorslike the time of year that is most suited to deep sky observationsand longer observational runs, the phase of the moon and how itwill impact the limiting magnitude, plus weather dependencies.SNe are not always occurring within our range of observationsor targets, or at all, surveys can run for many years and can ob-serve a small number of occurrences. The online community andsharing of discoveries has helped many astronomers in keepingup-to-date on if any SNe are currently viewable, leading to thetelescope not needing to scan, only find and observe the hostgalaxy that was tagged within the online reports. This is howSNe are reported, verified and then depending on the outcome,catalogued. Observatory location can be another limitation thatcan impact a survey’s chances of observing continuously. Com-paring the Very Large Telescope (VLT) in Chile, with Bayford-bury here in England, there is an extreme difference in both ge-ographical location and altitude. VLT is part of the EuropeanSouthern Observatory (ESO) and sits at an altitude of 3635mabove sea level, it is exposed to consistently clearer skies thanthose available to Bayfordbury. High altitudes afford a telescopewith less atmosphere to interfere with incoming light, and the re-moteness of VLT’s location means no light pollution. Bayford-bury is only 66m above sea level and subject to sometimes ad-verse weather conditions and some light pollution, plus a thickeratmosphere for light to penetrate. (European Southern Observa-tory (2016)) Dependent upon where an observatory looks at thenight sky, it will see different stars, constellations seen from thenorthern hemisphere will look different if seen from the southernhemisphere. The same is true for galaxies, many galaxies are un-available to Bayfordbury due to their negative declination. Thisdifference in global location will therefore limit the number ofgalaxies available for repeated observations, potentially the fac-tor that limits any SNe from being observed by a survey. Thestatistical likelihood of a SN occurring within any one galaxy is1 in every 100 years, though there are many galaxies within ob-servable limits, it is not possible to always observe them, withfactors such as weather and lunar phase, interrupting observa-tions. To observe at least 1 SNe during a survey, either the samegalaxy must be traced for 100 years, or a minimum of 100 galax-ies must have repeated observations made over the course a year.The latter option is the path that modern surveys will take, ob-serving more than 100 galaxies over their allotted survey period.Increasing the number of galaxies targets is not the only factorthat can overcome this statistic, determining how often a singlegalaxy is to be observed will also yield a noticeable outcome. If10 galaxies were to be observed each night, then a rotation couldbe implemented so as to still be within the timeframe of a typeIa SN and still detect it, even if the SN went off during anotherobservational run. This method would increase the total numberof galaxies that a survey could cover, while also making the mostuse of an autonomous system that can be programmed to carryout the plan. The luminosity of the Moon at larger phases willalter the limiting magnitude so as to wash out fainter objects, in-



Fig. 10. How the Moon’s luminosity will alter the visual magnitudethat a telescope can observe up to, increasing the sky brightness to theextent of observing becoming almost impossible under such conditions.(Lewis (2012))

creasing the sky brightness to a point that observing to fainterthan an apparent magnitude 10 object will be wasted observa-tional time. Fig. 10 shows how the phase of the moon will impactthe sky brightness, in magnitudes, it is then evident that observ-ing with a full moon in the sky will hinder any observationalattempts of fainter magnitude objects. Like most other systemsthat can control autonomous telescopes, ACP will take into con-sideration a pre-set lunar avoidance demand, as decided upon perobservational run. Options include what upper lunar phase willbe tolerated, sky brightness levels, as well as dealing with thecloud levels, (i.e. good, fair, poor). Going back to the problem ofgalaxy inclination and bulge brightness, as mentioned in section4.3, there is a distance, and magnitude, out to which observingSNe will not be possible, due in part to the host galaxy outshin-ing the SNe, even if it is not located within the bulge. NGC 1023is an example of a galaxy that, when observed, appears faint butidentifiable, a target that would prove hard to certify whether ornot a SN was occurring within.

4. Selection Criteria and Survey

4.1. Target Selections

Applying the background knowledge that was discussed in thelimitations and feasibility sections previously, it is possible toconstruct a criterion by which the selection of galaxies that thesurvey will cover can be limited to.

4.1.1. Galaxy Selection criteria

By their very nature, late type spiral galaxies are the best candi-dates for continued observation due to their mixed abundancesof both low and higher mass stars, especially in regions of starformation. Spiral galaxies are found to contain all types of SNe,therefore it will be beneficial to filter galaxies down to spirals toimprove both the chance and statistical likelihood of spotting aSN. The telescopes at Bayfordbury aren’t designed, or locatedideally, for deep sky observations, limiting the distance that itcan observe out to before reaching the limiting magnitude. There

Fig. 11. Comparison of the four main SN types: Ia, Ib, Ic and II. Takenfrom data covering the years 2000 to 2015 of observed and reportedSNe. Type Ia is the most frequent as this is to do with the IMF of galax-ies, with the majority of stars being of the lower mass class, and henceleading to white dwarf stars at the end of their evolution, resulting intype Ia SNe occurring more often than any other type.

is a wealth of close, bright targets that can be observed with thecorrect conditions and instrumental setup. The limiting magni-tude is the constraint that has to be applied when consideringhow faint the target galaxy is. On most occasions, going fainterthan an absolute magnitude of ∼12 did not resolve a detectablegalaxy, mainly due to atmospheric conditions and the SNR de-creasing. When looking at galaxies this faint, a greater exposurelength is required, resulting in an increase to an already lengthyschedule. Fainter galaxies, if practically detectable, would be leftuntil last in the observation run, so as to prioritize time for thecloser, brighter sources that can be tracked and observed morereliably each night.

4.2. The Survey

Using Bayfordbury, the survey took place between October 2015and March 2016, taking advantage of the longer nights affordedby winter. The aim was to select and repeatedly track galax-ies that met the criteria, while also gaining hands-on experiencewith the telescope and seeing how the system worked first hand,so as to more effectively carry out the characterization on theparamount telescope. A scanning exposure of between 60 and120 seconds was implemented at first, so as to first verify thetarget was in sight, then progressing onto determining whetheror not a SN was present in the image. During two separate ob-servational runs, one by manual control and the other carried outduring robotic queuing mode, it was thought that a SN had beendiscovered. When the images were compared after the obser-vation with known archival images stored on the Bayfordburyinternal system, a discrepancy was noted by the appearance of‘new’ light sources where there had not been anything before.Fig. 12 and 13 show M82 as observed in the B filter, where anobject has been highlighted in Fig. 12, but not present in Fig.13, this is due to residual bulk imaging (RBI), also apparent inFig. 14 and 15 of M101. RBI is effectively the residual chargeleft on pixels that have been over saturated in a previous im-age, a situation that can lead to false reports if unverified by a



Galaxy Name R.A J2000(hh mm ss.s)

Decl. J2000(◦ ′ ′′) B apparent mag. Distance

(Mpc)No. of

Observations

M 31 (NGC 224) 00 42 44.3 + 41 16 09 4.39 0.79 12M 33 (NGC 598) 01 33 50.9 + 30 39 37 6.27 0.84 8M 51 (NGC 5194) 13 29 52.7 + 47 11 43 8.96 8.0 1M 81 (NGC 3031) 10 03 20.6 + 68 44 04 10.6 13.82 3M 82 (NGC 3034) 09 55 52.2 + 69 40 47 9.30 3.53 14

M 101 (NGC 5457) 14 03 12.5 + 54 20 55 8.31 6.70 3M 106 (NGC 4258) 12 18 57.5 + 47 18 14 9.10 7.98 1M 108 (NGC 3556) 11 11 31.0 + 55 40 27 10.0 14.1 1

NGC 891 02 22 33.4 + 42 20 57 10.81 9.2 2NGC 1023 02 40 24.0 + 39 03 48 10.35 10.5 1NGC 2403 07 36 51.4 + 63 36 09 8.93 3.22 1NGC 3147 10 16 53.6 +73 24 02 11.43 39.26 1NGC 6946 20 34 52.3 + 60 09 14 9.61 5.9 2NGC 7331 22 37 04.1 + 34 24 57 10.35 13.9 2

Table 4. Observed galaxies, listed with their Right Ascension (R.A.) and Decl. in Julian date, along with their app1arent magnitudes in B, distancein Mpc and the number of observations made of that galaxy over the survey. Number of observations is over different nights; multiple observationswere made on the same targets each night. (Tully et al. (2013))

third party. Light sources such as stars show a Gaussian profilein the photon count received in each pixel, an RBI source willshow a larger and flatter Gaussian profile curve, as compared toa real source, indicating saturation. The solution for dealing withidentified RBI sources is to carry out the observation again asthese sources will fade significantly in the next image and willdisappear entirely, as seen in comparison between Fig. 12 and13, 14 and 15. Such misidentifications are not rare, and have tobe considered, with potential SNe verified either by peer assess-ment, or by investigation into the light sources origin. If a SN isbelieved to have been spotted, and RBI is ruled out, observingwith another telescope is ideal, so as to reduce the possibility ofequipment error that would lead to ghost stars appearing due toprevious over exposure. Table 4 contains all the galaxies imaged,their relevant information and number of recorded observationsmade. Both M82 and M31 share the highest number of obser-vations due to the testing of the autonomous queuing system,these galaxies were selected for repeat observations over the en-tire survey period by applying a ‘repeat every 7 days’ commandto the script.

4.3. Processing Data and Image Analysis

The software package AstroImageJ is one of the many softwaresuites that deals with the output files from the CCD, in the fileformat of ‘.fits’. AstroImageJ offers many tools that are essen-tial for noise reduction / calibration, contrast alterations, aper-ture photometry and plate-solving via astrometry.net. Within thesoftware, it is possible to apply the science frames that were dis-cussed in section 4.2.1, reducing the background noise from theCCD thermal emissions, correct for bad pixels and reducing cos-mic ray noise. Another technique used to reduce the noise in anexposure is to stack multiple exposures together, increasing theSNR. Stacking requires multiple images of the same target to bealigned, the best way to approach this is to align by the WCScoordinates and can be achieved by the software. The result canbe used in multiple ways, most novice astronomers will utilisestacking for RGB colour images of a target, here stacking wouldbe applied to images containing SNe. Tracking SNe over a pe-

riod of time requires the measurement of the changing magni-tude, as well as position within the galaxy for other astronomersto more easily locate and verify the source. Over the course oftracking an SNe, multiple images would be taken each night,with a minimum of 5 all within the same light band, so as to cre-ate an image stack per night with reduced noise. From there theSN would be observed over the period of its existence, and thesubsequent stacks from each night stacked again, creating a 3Dplot of the SN over the observational period, easing the processof both aperture photometry and magnitude plotting. Thoughthis is a useful procedure for tracking the light curve of SNe,it does require continued observations of the target: the morefrequently it can be imaged, the higher the accuracy is of the fi-nal light curve. Another use of stacking is to track galaxies overseveral different observing nights for any significant changes orSNe appearances, especially if the problem of RBI occurs, asthe ‘ghost’ object will quickly disappear as you progress alongthe stack. Using Aperture Photometry, it is then possible, once astack has been achieved, to track the evolution of the SN’s mag-nitude, making sure to calibrate it with a known star’s magnitudethat is located near the target. The downside though is that it willbe increasingly difficult to reduce the noise from the host galaxywhen taking the readings, which could affect the final estimate,however it is possible to adjust a light curve value to account forsuch situations, due to the one to one nature of the curves, asexpressed in section 2.3.

5. Results and Discussion

5.1. Observations

During the course of this survey, no supernovae were discov-ered or observed by the Bayfordbury Observatory. The selectedgalaxies were observed as and when possible to do so, limitingthe chance of missing a SN, while also making use of online fo-rums and noticeboards dedicated to the reporting of SNe. Thegalaxies observed during the course of this short-term surveyare included in Appendix A. Though some CCD RBI instancesarose, they were soon identified as non-Gaussian and hence werenot SNe.



5.2. Feasibility of using Bayfordbury

A full characterization has been achieved on the Paramount Tele-scope, including the facilities of Bayfordbury that would lendaid to such a survey. Both autonomous and manual observationshave been conducted with the telescope, with varying results. Itwas however required so as to assess the capabilities and struc-ture, so as to reach the conclusion that a Supernova survey couldbe carried out with the Bayfordbury Observatory and return asuccessful result. Apart from the obvious limit of whether ornot a SN occurs over the course of such a survey, the equip-ment and systems would not limit a survey to the point of fail-ure. If this survey had made use of the automated system fromthe start, many more repeated observations on potential targetswould have been made, allowing for an increase in number ofpotential galaxies for scanning. The fact that no SNe occurredover the course of the survey, or were potentially detectable fromBayfordbury, was unfortunate, however it is a factor that must betaken into account upon deciding to undertake a survey.

5.3. Future Surveying

Future surveys that would use the Bayfordbury Observatorywould require almost sole use of the autonomous observationsmade available by the queuing of RTML plans, such a systemallows the user to construct a plan of the intended targets, fil-ters and exposure times without the requirement for continuedmonitoring of weather patterns so as to decide upon when to ob-serve manually. To further increase the success rate for such asurvey that would be carried out using Bayfordbury, having re-viewed the included assessment of the telescopes, would be toproduce multiple plans so as to stage each selection of galaxiesover several nights, widening the selection criteria and increas-ing the number of targets for repeatable observations. Introduc-ing such a step early on allows for a longer period of observation,increasing the already small chance of observing a SN. Once ob-served though, a potential SN should be noted, compared againstarchival images as taken from Bayfordbury, including a repeatobservation from one of the other telescopes will also help de-fine the target to either be an SN or a CCD anomaly. Surveyssuch as SDSS use a scanning system of mapping out the sky byprogressively moving along a path that will cover the majorityof the sky each night, storing the images on the internal servers,from there the images are passed through a pre-calibrated soft-ware that will detect and flag any instance that it believes to bea SN, this is done by comparison with an image known not tocontain any SNe. It is the conclusion of this paper that such anundertaking is not feasible via the use of the Bayfordbury Ob-servatory, and hence a selection criterion is required. With sucha vast catalogue of known galaxies within the limiting distancedetermined previously, there will not be a shortage of potentialtargets for repeated observations. It is then a matter of construct-ing an efficient plan that will scan the targets.

Acknowledgements. First and foremost, a thank you to Elias Brinks for the con-tinued encouragement, enthusiasm and wealth of knowledge that has helped formthis report, whilst also keeping it on track with intriguing questions about differ-ent aspects. Thank you also to Mark Gallaway and Sugata Kaviraj who helpedwith their knowledge and insights on the matters of telescope operation and su-pernovae. Finally, a thank you to all my lecturers and fellow students for the past4 years of university, an unforgettable journey filled with the best of times.

ReferencesAAVSO. 2014, American Association of Variable Star Observers, AAVSO

Anderson, J. P. 2016, IAU Focus Meeting, 29, 443Ball, W. H., Tout, C. A., & Zytkow, A. N. 2012, MNRAS, 421, 2713Barbon, R., Ciatti, F., & Rosino, L. 1979, A&A, 72, 287Blondin, S., Matheson, T., Kirshner, R. P., et al. 2012, AJ, 143, 126Cheng, J. 2010, The Principles of Astronomical Telescope Design (Springer Sci-

ence and Business Media)Craig, M., C. J. 2014, ObsAstro – 7.4 Magnitude and airmassDark Energy Survey, D. 2013, Dark Energy SurveyDas, U. & Mukhopadhyay, B. 2013, Physical Review Letters, 110, 071102European Southern Observatory, E. 2016, Very Large TelescopeFilippenko, A. V. 1997, ARA&A, 35, 309Gallaway, M. 2015, An Introduction to Observational Astrophysics (Springer)Häring, N. & Rix, H.-W. 2004, ApJ, 604, L89Iben, Jr., I. 1967, ApJ, 147, 624Lewis, G. 2012, Space Surveillance: The Visual Brightness and Size of Space

ObjectsObservatory, C. X.-R. 2012, Stellar Evolution – Pulsating Variable Stars and the

Hertzsprung-Russell (H-R) DiagramOBSN. 2014, SN2014JO’dell, C. R. 2001, ARA&A, 39, 99Schönberg, M. & Chandrasekhar, S. 1942, ApJ, 96, 161SDSS, S. D. S. S. 2016, SDSS Data Release 1Takaki, K., Kawabata, K. S., Yamanaka, M., et al. 2013, ApJ, 772, L17Tully, R. B., Courtois, H. M., Dolphin, A. E., et al. 2013, AJ, 146, 86Watkins, L. L., Evans, N. W., & An, J. H. 2010, MNRAS, 406, 264Yoon, S.-C. & Langer, N. 2004, A&A, 419, 623


Documents

Bayfordbury Observatory Supernova Searchwithinerror.space/resources/Project Supernova.pdf · A&A proofs: manuscript no. "Project Supernova" 2001 (SDSS (2016)). Another survey is the