University of Hertfordshire

Master of Physics (MPhys) in Astrophysics

Bayfordbury Observatory Supernova Search,

including the review of the Paramount Telescope.

Thomas Spriggs

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Supervisor: Elias Brinks

2nd Supervisor: Mark Gallaway

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Abstract A review to characterise the Bayfordbury observatory, determining whether or not a

Supernova Survey is conductible with the current equipment and operation available, via a

quantitative and qualitative overview of the Paramount telescope. The aim is to design a

survey that will cover a suitable range of targets, over a time period of October 2015 through

to March 2016, a comparatively small window that will allow the instrumentation to be tested

and deployed successfully. This short time-frame will limit the chances of observing or

detecting a supernova, it is then advantageous that a review of the limitations and feasibility

be carried out to help determine if any future supernova surveys, carried out with the

Bayfordbury Observatory, would be viable.

This paper will introduce the subject of Supernova surveying, including an overview of the

current understandings and models of Supernovae, highlighting their importance within

astronomy and cosmology. Surveying the night sky for supernovae is a task that must be

planned accordingly, taking account of factors such as weather, instrumental limitations as

well as the limiting magnitude of the observatory.

To properly assess the Bayfordbury Observatory against the requirements of a Supernova

survey, an understanding of how well the equipment performs and the effectiveness of

applying various observational techniques is required. The testing of manual versus

autonomous observing, determining the limiting magnitude and carrying out a full

characterization of the Paramount telescope will highlight the strengths and failings of the

observatory. As well as system research, a survey will be carried out to deduce the feasibility

of observing galaxies for such a survey, including an analysis of the varying traits that will

affect the outcome of observations.

Making use of the available software is crucial to the success of any further attempts at

observing supernovae from Bayfordbury, so an introduction to the different software suites

currently installed is included, as well as brief descriptions of what each programme controls

or can achieve, i.e. camera and dome control, or stacking images so as to reduce CCD and sky

noise.

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Acknowledgements First and foremost, a thank you to Elias Brinks for the continued encouragement, enthusiasm

and wealth of knowledge that has helped form this report, whilst also keeping it on track with

intriguing questions about different aspects.

Thank you also to Mark Gallaway and Sugata Kaviraj who helped with their knowledge and

insights on the matters of telescope operation and supernovae.

Finally, a thank you to all my lecturers and fellow students for the past 4 years of university,

an unforgettable journey filled with the best of times.

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Contents Abstract .............................................................................................................................. - 2 -

Acknowledgements ............................................................................................................ - 3 -

1 Initial Plan .................................................................................................................. - 5 -

1.1 Background and Topics of Interest ..................................................................... - 5 -

1.2 Objective: ........................................................................................................... - 6 -

1.3 Projected Timeline: ............................................................................................ - 6 -

1.4 Comments and Changes from Initial plan. ......................................................... - 7 -

2 Introduction ................................................................................................................ - 8 -

2.1 Background ........................................................................................................ - 8 -

2.2 Observing Supernovaie ...................................................................................... - 9 -

2.3 Scientific Purpose ............................................................................................. - 10 -

2.4 The Bayfordbury Observatory .......................................................................... - 11 -

3 Supernovae ............................................................................................................... - 13 -

3.1 Stellar Evolution Review .................................................................................. - 13 -

3.2 Classification .................................................................................................... - 15 -

3.2.1 Type Ia ..................................................................................................... - 15 -

3.2.2 Type Ib & Ic ............................................................................................. - 16 -

3.2.3 Type II-P / II-L ......................................................................................... - 17 -

4 Bayfordbury Review ................................................................................................ - 19 -

4.1 Observing with Bayfordbury ............................................................................ - 19 -

4.2 Characterization of the Paramount Telescope .................................................. - 19 -

4.2.1 Calibration methods ................................................................................. - 21 -

4.2.2 Limiting Magnitude .................................................................................. - 22 -

4.2.3 Autonomous vs Manual Observations ...................................................... - 24 -

4.3 Feasibility of Observing Supernovae ................................................................ - 25 -

4.4 Limitations ....................................................................................................... - 27 -

5 Selection Criteria and Survey ................................................................................... - 29 -

5.1 Target Selection ............................................................................................... - 29 -

5.1.1 Galaxy selection criteria ........................................................................... - 29 -

5.1.2 Observed Galaxies .................................................................................... - 29 -

5.2 The Survey ....................................................................................................... - 30 -

5.3 Processing Data and Image Analysis ................................................................ - 30 -

6 Results and Discussion ............................................................................................. - 34 -

6.1 Observations ..................................................................................................... - 34 -

6.2 Feasibility of using Bayfordbury ...................................................................... - 34 -

6.3 Future Surveying .............................................................................................. - 34 -

Appendix A – Galaxy Images .......................................................................................... - 35 -

References ........................................................................................................................ - 40 -

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1 Initial Plan

1.1 Background and Topics of Interest The light given off from a supernova (SN) can outshine its host galaxy, this alone makes them

fairly simple to detect and observe with either a ground- or space-based telescope. Over the

centuries many supernovae (SNe) have been observed, and certain parameters have been

recorded. These parameters include the apparent magnitude, and how it varies over the

duration of the SN. In more recent years spectra have been employed to determine the

chemical composition of the SN. All this information can be used to determine information

about the progenitor of the SN; it could be the collapse of a star more massive than 8 ‘solar

masses’ (Msol) which has exhausted its fuel supply, or a white dwarf which through mass

accretion from a binary companion star collapses due to its core mass exceeding the

Chandrasekhar limit (Zeilik, M. 1991).

Scientists have used data from the spectrum from observed SNe to determine the redshift of

galaxies. This is done by comparing the spectra from lab data and the spectra taken from the

SN. Redshift is linked to the recession velocity of an object relative to the observer, therefore

measuring the redshift from the data leads to finding the recession velocity of the host galaxy.

The use of SNe in this fashion has led two teams of physicists to share the Nobel prize in

Physics 2011 for their work on the accelerating universe model. SNe have also played a crucial

part in the field of stellar astrophysics, providing information about how heavy elements

(heavier than iron) form from the death of stars via the process known as neutron capture via

both slow and fast timescales. The immense release of energy in a SN is among the few things

in the universe energetic enough to overcome the strong nuclear force, that binds the nuclei of

atoms together (Seeger, P. A. 1965).

What are Supernovae:

o Types and classifications of SNe.

o What processes cause each type of SNe.

o How we observe SNe (light curves and spectra).

o What we can infer from SN detection (Distance, molecular abundances, progenitor

star class).

o How have SNe been used to date?

Telescope and software:

o Telescope to use: Paramount, Meade LX200R, H-alpha and B bands

o Techniques used for imaging galaxy targets and reduce noise/interference.

o Differential photometry

o Software includes: AstroImageJ.

o The forms of media used to find out about current SNe events to be recorded (email

listings, sites etc.)

Recorded measurements:

o Plots of light curves recorded over several spanning periods of weeks where

possible.

o Determine what type of SNe it is, and which are more common from the observed

set?

o Determine distance from measurements and compare to known, recorded

measurements in databases.

o Potentially look at the effects and presence the expansion of the SN shell.

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1.2 Objective: The overall objective of this project will be an in-depth examination of SNe. This includes

examining the light-curves, i.e. how the light decays over time, as well as potentially capturing

spectra of any SNe that occur over the period of the project. If it proves not possible to capture

live SNe using the available equipment, there are other observatories that can provide the

required information. In order to measure the light curves from potential SNe, The Paramount

telescope at Bayfordbury observatory will be used, a Meade LX200R class telescope. This

was chosen because of the narrow-band filters equipped to the telescope, which will help

compensate for the elevated sky background. This will in turn lead to better resolution of the

actual wavelengths, allowing for more accurate scientific observations.

It is estimated that 40 or fewer SNe will happen over the course of the project, which sets a

limit on the amount of data it will be possible to gather. The data will be used to form the

aforementioned light-curves for each individual SN, which in turn will allow identification of

the type of SN that has been observed. By holding this information up with the physical

location of the SN, this might lead to further conclusions about the progenitor star and the

galaxy or a specific region it is part of.

As well as any observations, an in-depth background on SNe will be included to help the

reader understand the physical processes behind SNe and why they are crucial to creating a

complete picture on nucleosynthesis. “Topics of interest” includes the areas that will be

presented to the reader, as well as helping to understand what we do with the acquired data.

By the end of the project the reader will know about SNe, the processes believed to be behind

what triggers them, as well as seeing first-hand how the data is processed.

1.3 Projected Timeline: October / November

Getting to grips with the software package AstroImageJ by playing around with a few images

from the Bayfordbury archive. Sessions will be scheduled with Mark Gallaway for reviewing

the operation and methods of detection that will be used in this project; getting as early a start

with this allows for a larger observational window to start the ‘supernova search’. The methods

include the use of differential photometry, potential for setting up the spectrograph equipment,

looking at image stacking and ways of reducing noise and error throughout the observation

part of this project.

Reviewing recently published papers in the field of SNe will help with any new discoveries

that have been made or new hypothesis made. While looking at newer material, there will be

a review of the material that has already been taught on SN and how they occur, while looking

at sources; books, websites and papers to gather a more detailed picture of this phenomenon.

Eventually ending with the collection of sources that can be used to help start the writing of

the theoretical side of this investigation. Topics to include: types of SN, what triggers them

and what has been learnt from the observations to date.

Beginning to image a selection of galaxies so as to put into practice what has been covered in

any revision sessions with the telescopes, equipment and software. Recording all relevant data;

i.e. filters (B, V, R, H-alpha etc.), light curves, the observed galaxies. Observations will

continue over the duration of the report.

Preparation for the poster and talk session will begin within the last week of October, as by

this time enough should be known already to begin putting it together. This start time allows

for any subject areas to be smoothed out, while collecting and producing appropriate material.

[To be completed by 20/11/15 for review, with the end date of 30/11/15].

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December / January

By December, there should be ample information gathered to have already started the project

report. By the end of January, the report will be including a suitably finished sample chapter

and contents page for the next deadline in February. The plan for the report so far is to write

out the structure so that the content can flow into the report without too much consideration

on which topic heading it will fit under. [Sample chapter and contents page hand-in:

01/02/2016]

Continuing on from November: observation sessions will continue to take place, with the data

being stored and reviewed. The report will continue to develop with continuous meetings,

literature reading and feedback helping to mould and shape the contents.

February / March

Once the sample chapter and contents page are handed in, work on the report aspect will

continue, while preparation for the ‘Talk’ presentation will begin, wherein a review of the

topic so far will be necessary, as well as key data that has been taken so far will be included.

[Talk presentation hand in: week beginning 14/03/2016]

The data recorded so far should be enough to allow for final interpretation, along with

implementing the findings into the final report, along with any relevant data analysis points.

A log of all activities will be kept over the period of the report and should by this time be

written up and commented on in the report.

April / May

Reaching the final stretch of the report, this time is crucial for going over the project so far,

tying off loose ends and making sure the structure is on par with set requirements.

The final report version needs to be ready for submission on [18/04/2016]. In the weeks and

months leading up to this date, the contents will be revised for any anomalies and grammatical

mistakes. These final touches will ensure that the paper is up to standards, makes sense with

the language used for the intended reader (i.e. a fellow physicist).

After the paper is handed in, the viva is the next and final stage of the project. For the viva a

presentation will be made along with key notes to touch upon in a pre-made and practised

speech. The viva takes place the week beginning [09/05/2016]. The presentation will consist

of the interpreted data, key points of the project and milestones reached, concluding with how

and why the project was undertaken.

1.4 Comments and Changes from Initial plan. During January, the survey was considered to be too limited, both by unsatisfactory weather

and technical limitations, and hence the project needed to be expanded so as to account for the

outcome of no supernovae being detected or observed. It was realized that a review of the

Bayfordbury Observatory, a characterization of the Paramount telescope, would be beneficial

for future surveys using the observatory, providing the relevant information on the capabilities

while considering the requirements and planning needed to achieve a successful survey

attempt.

The survey itself was continued with galaxies periodically being targeted whenever the

weather permitted. The alteration of the report required manual use of the telescopes so as to

ascertain how the systems and equipment would impact observations, if future surveys were

to be viable, while also reviewing the capabilities of the Bayfordbury Observatory.

The timeline set out in the above ‘Initial plan’ was not altered, rather the application of time

and the contents of the report was redefined to reflect the change in subject, allowing for a

successful review the observatory.

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2 Introduction

2.1 Background In an effort to observe and record the universe around us, numerous telescopes have been

designed, built and maintained over the centuries that allow for continuous research.

Beginning with the visible spectrum viewable via the use of optics and the naked eye,

astronomers have over the decades developed means by which to observe more of the

electromagnetic (EM) spectrum that was previously inaccessible. Radio waves, microwave

radiation, X-rays and gamma rays are some of the regions that are observed with current

telescopes. Achieved mainly by Earth and space based optical telescopes equipped with

various filters, while radio dishes and other receiving devices have been built around the world

to observe the longer wavelengths present in the universe. These windows into the other EM

regions have led to 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 grown significantly in scientific

interest over the past century, with notable works from Edwin Hubble, and the more recent

Perlmutter and Riess Nobel prize winning discoveries. Observing SNe can be a lengthy

undertaking, with many nights required for carrying out surveys on the sky, in the hopes of

spotting a supernova (SN) within a host galaxy. SN surveys requires planning, potential targets

need to be considered and approved for whether or not they can be observed by the intended

observatory, including a summary of the abilities of the telescope that is to undertake the

majority of the survey’s requirements. This is where characterizations, as well as an in-depth

analysis of the observatory are required before proceeding with the intended survey.

Once a star can no longer support itself against gravitational forces, either by termination of

core fusion reactions that supply the balancing thermal pressure, or by instabilities, it will then

reach critical conditions, as explained in chapter 3, and explode, it is this process that is of

great interest and the subject of this report. These explosions are theorised to be the reaction

for producing the heavier elements that contribute to the 4% baryonic matter content of the

known universe, due to the energies and temperatures that are reached within such explosions

causing the fusion of smaller nuclei into heavier elements.

The Sun is the closest star that allows for detailed observations, allowing astronomers an

insight into the internal structure and processes that powers a star. It is generally accepted,

within the current model of stellar evolution, that the Sun is on the Main Sequence (MS), and

has been for around close to 4.6 billion years. It is then good practise to look out into the disk

of the Milky Way (MW), our host galaxy, to observe and note all the different spectral types

or stages of stellar evolution surrounding our Sun, ranging from gas clouds to proto-stars, MS

to Red Giants (RG), and even the redder Asymptotic Giant Branch (AGB) stars that are

shedding their outer envelopes. One of the problematic stars to spot are known as White

Dwarfs (WD), stars that have a high luminosity, but shine dimly in comparison to their

surroundings or companion star, the closest WD is named Sirius B and is located 8.6 light

years away, with its binary companion Sirius A.

SN are featured in many scientific discoveries and journals, with a growing catalogue of their

discoveries and properties. Some well-known SN surveys to-date include the Sloan Digital

Sky Survey (SDSS) which is currently on its fourth data release since its first in 2001 (SDSS,

2004). Another survey is the Dark Energy Survey (DES), having started in 2013 and currently

running in the Chilean Andes, it was designed with the intent of observing and measuring SNe

so as to help constrain both the Hubble constant, H0 (i.e. the expansion of the universe), and

the acceleration term for the expansion of the universe, via the theorised presence of Dark

Energy (DES, 2013).

The cataloguing of SNe is the main goal behind most smaller surveys operating today, with

the aim of collecting as much scientific data from each event as physically possible, including

light curve profiles and emission spectra. The large community of astronomers means that

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new discoveries can be reported, verified and released to the rest of the world in a small time

frame so as to alert many more observatories to currently occurring SNe. Due to their

somewhat rare and varied nature, SNe are not completely agreed upon by all astronomers, the

current models are continuously being tested and occasionally broken by new observations

that defy the current theories. It is timely then to reconsider the nature of SNe, continuing to

catalogue their properties while also searching for a complete model.

2.2 Observing Supernovaie Type Ia SN, described in chapter 3, are the most observed objects within the field of SN

surveying, due in part to their progenitor; a lower mass star. These stars are considered as the

most abundant of stellar objects in the known universe. This notion stems from the study of

how gas and dust is distributed within a galaxy, contributing to the formation of different mass

stars, as set out in the Initial Mass Function (IMF), which finds that the majority of the gas is

found within the lower mass stars, whilst the largest luminosity contribution originates from

the larger stars within galaxies.

The greater number of lower mass stars leads to a greater occurrence of the Type Ia SN, which

marks the death of such progenitors. It is accurate then to predict that a survey will detect a

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. From the IMF it is reasonable to select spiral type galaxies, which

contain a mix of both high and low mass stars and a rich abundance of gases, for observations,

increasing the likelihood of observing any SNe, compared to targeting elliptical galaxies that

yield a statistically lower change of observing any SNe as they contain only older low mass

stars, and little to no gas that could lead to further star formation.

Much can be gained from observing a SN, with their infrequent occurrences and varying

properties, and astronomers race to gather as much data per observation as possible. The

techniques employed to observe them, as with any bright astrophysical process, are based on

analysing the wavelengths of light, either by photometry with a ‘Charge Coupled Device’

(CCD) or splitting the light into its constituent parts and examining the spectrum to distinguish

the different wavelengths present. This process allows for the determination of the elemental

abundances within the SNe, while also enabling the calculation of redshift.

Light Curves are a useful way of displaying the light decay profiles of different SNe and their

recorded brightness’s over consecutive observations and nights. SNe decay rate, as well as the

width of the peak, are characteristics that have proven their use in probing the different

processes that lead to the apparent diversity in SNe, as later discussed in section 3.2.

Spectral analysis of SNe reveals a wealth of information in regards to molecular abundances

and compositions that arise from the extreme conditions within them. Learning what elements

are present in the wake of a SN helps to determine both the progenitor and the type of SNe,

an example being the presence of Hydrogen lines in a type II SN spectra, but faint, if any, for

a type Ia SN spectra. This variation is due to the different environments and causes of SNe, as

discussed in the next chapter. Another use for spectral analysis is the detection and

measurement of redshift, as seen in the shift in wavelength, of known elements, towards longer

wavelength values, allowing astronomers to refine the redshift of a host galaxy, as other

methods of estimation are available.

There are other methods of observing SNe, though such methods will not be practised here.

One such method is to apply different light filters to a telescope so as to probe the X-ray region

of the EM spectrum, where SNe remnants are known to emit the most intensely. Another is

the use of ground based radio telescopes to observe the Radio continuum, specifically the

frequency band of 4-6 GHz for synchrotron emissions. Synchrotron has proven to be useful at

indicating ongoing star formation within galaxies.

Observations of the radio spectrum allow for the detection and mapping of synchrotron

emissions, where Synchrotron emissions arise from highly relativistic electrons that have been

accelerated by the expanding SN shock front, or from highly magnetic spinning neutron stars

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known as magnetars, or from an Active Galactic Nucleus (AGN). As well as Synchrotron

emission, neutrino detection is a viable future detection method, though currently there are

few ways in which to observe neutrino fluxes to such an extent as to conclude that the source

was an SN.

Due to SN light profile curves appearing most prominently in the optical, this survey will

observe them in the optical bandwidth of the EM spectrum, using the various Johnson filters

that are installed within the CCD cameras at Bayfordbury Observatory and listed in table 1.

2.3 Scientific Purpose With the use of the magnitude system, the logarithmic measurement of light as scaled

according to the eye, SNe are prime targets to measure distances via their apparent brightness,

often as bright as their host galaxy. Before SNe it was the use of Cepheid Variable stars that

distance was calculated, Cepheids being stars that pulsate in peak brightness over a measurable

period, but due to a drop in apparent brightness at increasingly distant sources, another

‘standard candle’ was required for deeper observations.

Going 400 years, astronomers have catalogued different objects in the night sky, those

including comets, galaxies, star clusters and more recently SNe. Over that time period, models

for many more objects than those listed here have been developed and altered to fit physical

observations that did not entirely agree. Of all the different SNe discussed in this paper, and

due to their greater frequency in occurrence, type Ia SN*e are the most observed and hence

are understood the best, with a well understood model that has been established to explain

what occurs within the cosmologically fast peak in brightness. One model is the ‘Standard

Candle Model’ and predicts that all type Ia are the result of a White Dwarf star exceeding a

known mass limit and exploding, exhibiting the same light curve profile, with a one to one

relation between the peak magnitude and the light curve width. The mass required to exceed

this mass limit is acquired via the accretion of mass from a neighbouring star, or the rarer case

of two White Dwarfs merging.

As previously mentioned, SNe are useful for indicating recent star formation, though only if

the SN in question is classified as Type Ib, Ic or II, as these are from the core collapse process

within the younger more massive stars. These are, as discussed in the introduction, found only

in spiral type galaxies. These SNe emit in the radio continuum at 1.4 GHz, a result of

relativistic electrons circling in a galaxy’s magnetic field that are accelerated due to

interactions with shock fronts emanating from SNe.

𝑆𝐹𝑅 (𝑀ʘ 𝑦𝑟−1) = 5.9 × 10−22 𝐿1.4 𝐺𝐻𝑧 (𝑊 𝐻𝑧−1) (1.0)

Using equation (1.0) it is possible to estimate the rate of star formation, in solar mass per year,

from the luminosity of the radio continuum at 1.4 GHz. The spectra from star forming

galaxies, in the radio frequencies, can be described by a simple power law in the frequency,

making use of a ‘spectral index’, α, ranging in value from 0.7 to 1.1, with the intensity being

related to the frequency: Sν ∝ ν-α.

Then finding the luminosity required for equation (1.0) can be achieved from re-arranging

equation (1.1):

𝑆1.4 𝐺𝐻𝑧 =𝐿1.4 𝐺𝐻𝑧

4𝜋𝑑𝐿2(1+𝑧)(𝛼−1) (1.1)

Where S1.4 GHz is measured intensity, dL is the distance to the luminous source and z is the

redshift.

In Cosmology, SNe are the primary interest in Riess, Schmidt, and Perlmutter’s (Riess et al.

1998, Perlmutter et al. 1999) Nobel Prize winning discovery of the accelerating expansion of

the universe. As well as being used for distance estimations, SNe are useful for finding the

redshift of a host galaxy, where redshift is the measure of how fast a galaxy is moving in a

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radial motion away from Earth, with the light emitted being shifted toward the reddened end

of the EM spectrum due to the expansion of space-time.

2.4 The Bayfordbury Observatory The observatory at Bayfordbury, established in 1969 by the University of Hertfordshire,

comprises of seven optical telescopes, with the addition of four radio telescopes. The location

was decided upon due to the remoteness of the area, staying clear of as much light pollution

as was feasible, compared to other university observatories that are located closer or within

cities and have a harder time of reducing interference from external, earth based sources.

Of the seven telescopes, two can currently be controlled remotely, as well as being set to

robotic mode where they will utilise software packages to run queued requests. The software

includes SkyX, ACP Observatory control software which uses custom scripts in Remote

Telescope Markup Languate (RTML) form, while also using MaximDL to control the CCD

mounted onto the rear of the telescope. The telescopes mentioned here are named CKT and

Paramount: the CKT is a Meade LX200GPS telescope, while Paramount is a LX200R Meade

telescope.

The Bayfordbury Observatory includes a 4.5m radio telescope dish named the R.W. Forrest

Radio Telescope, used mainly for 21cm and 4 GHz observations within the spiral arm of the

Milky Way. 21cm is the wavelength used to observe molecular hydrogen clouds that can be

tracked, and their relative velocity determined, whereas the 4 GHz frequency looks at the

previously stated synchrotron emissions.

Bayfordbury has observed SNe in the past, one example is the SN that occurred within M82,

named SN2014J, seen in Figure 1. First officially reported by staff and students of University

College London (UCL), however it was imaged by Bayfordbury, but unfortunately the

irregularity was not taken note of, or the file stored. SN2014J was a type Ia SN, reaching a

peak magnitude of 10.5 in the R band, though discovered with a V band magnitude of 11.7

(AAVSO, 2014). SN2014J’s light curve profile and spectral analysis are seen in Fig. 2 and

Fig. 3 respectively.

Figure 1 - M82, B band, 120 second exposure, highlighted is SN2014J

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Figure 2 - Light curve plotted in different filters for 2014J, apparent magnitude plotted against Julian Date (OBSN,

2014). The different colours represent the different filters used in tracking the magnitude, clearly showing that SNe

can vary significantly in value depending on which filter is used in the observation. The B filter is the primary filter

due to the standard candle light profile being most evident.

Figure 3 - Spectrum from 2014J, with easily identifiable traits of a SN-Ia supernova: Si II peak being the most

prominent (OBSN, 2014)

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3 Supernovae Type Ia Supernovae are the violent phenomena that occur at the end of stars’ lives, occurring

after they evolve off the Main Sequence (MS) and onto the Red Giant Branch, most becoming

a WD. The mass, and sometimes the surroundings, of the progenitor star dictates the

mechanism for the event: triggered by accretion from a neighbouring star. Core Collapse SNe

are the result of internal hydrostatic instabilities followed by gravitational collapse. In this

section an overview of stellar evolution, supernova (SN) classification and scientific

experiments that use SN observations are discussed, with the intent of bringing the reader up

to speed with current theories and applications.

3.1 Stellar Evolution Review Star formation is the result of over densities within molecular clouds, mainly comprised of

hydrogen in the form of H2, by the collapse and fragmentation of self-gravitating regions

within these clouds. This process is typically found in the arms of Spiral Galaxies, where the

Interstellar Medium (ISM), comprising of gas and dust, is most abundant and far enough from

an AGN to allow for collapse. This is relevant as star formation can be truncated by AGN

feedback, as well as by Supernovae, either due to evacuation or heating of the surrounding

gas, leaving areas devoid of star-forming material, or gas that is of a temperature, and hence

kinetic energy, to collapse.

The requirement for collapse is that a certain mass of gas is contained within a volume. This

mass lower limit is called the Jeans Mass:

𝑀𝐽 ~ (𝑘𝐵

𝜇𝑚𝐻𝐺)

3 2⁄

𝑇3 2⁄ 𝜌−1 2⁄ (1.2)

When the Jeans Mass is contained within the Jeans Length (a radius which sets up a volume

within which the Jeans Mass must be located to initiate collapse), the cloud will then fragment

due to its self-gravity becoming greater than the thermal pressure supporting it. Unless the

cloud is heated by an external source, contraction cannot be halted and stellar formation can

commence.

Once stars evolve out of the proto-stellar phase and onto the MS they don’t undergo much

variation for quite some time, anywhere between Myrs to Gyrs (106 – 109 years), dependent

upon their mass. In this case we will look at a typical solar mass star and how it is predicted

to evolve. Once the core stops producing sufficient energy via hydrogen burning, it starts to

contract while the outer envelope of hydrogen and helium expands, leaving a hydrogen-

burning shell around an isothermal core. This outer envelope is convective, causing the

distributions of the H and He to become mixed, though due to gravity and the continuous

convective movement, the helium will fall into the 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 a polytropic index of n = 3 (Ball et al., 2012),

the maximum fraction of a star’s mass that can exist in an isothermal core and still support the

material surrounding it, the star will evolve one of two ways:

Helium core mass is less than the S-C limit:

The core remains in a hydrostatic equilibrium during the hydrogen-burning-shell

phase. As helium is produced from this shell it falls into the core increasing its mass,

potentially causing it to become degenerate. While in this stage the star is evolving

along the sub-giant and giant branches at a slower rate. When the core mass reaches

~0.48 Mʘ (solar masses) and is highly degenerate, the temperature reaches values of

~108 K, the helium ignites in what is called a helium flash, this is where the degeneracy

of the core leads to a thermonuclear runaway effect, emitting ~1011 Lʘ (solar

luminosity, where Lʘ = 3.846x1026 W) in a matter of seconds.

- 14 -

Helium core mass is greater than the S-C limit:

The core contracts on a thermal timescale, i.e. the timescale required to radiate the

thermal energy outward so as to contract. Collapse will continue until the electron

degeneracy pressure is strong enough to support the core, or when the helium within

the core ignites when temperatures reach ~108 K. The helium will ignite ‘quiescently’

and the nuclear fusion process can again start within the core. The star is then on the

Red Giant Branch (RGB) of the Hertzsprung-Russel (H-R) Diagram.

A quick note on electron degeneracy: degeneracy arises due to Pauli Exclusion Principle,

where electrons are forced to occupy the lowest available energy levels. As more electrons are

packed in due to increases in density or gravitational contraction within the core, electrons

reach a state where they can no longer be compressed to lower energy states, leading to an

outward pressure supporting the inward gravitational contraction.

Polytropic state refers to a solution of the Lane-Emden equation, which describes the pressure

as dependent on the density, with the equation of state:

𝑃 = 𝐾𝜌𝛾 (1.3)

𝛾 = 1 +1

𝑛 (1.4)

Where K and γ are constants for a star, and n is the polytropic index for the star.

The mass of the star determines which path a star will take along the H-R diagram, each with

a different internal structure and lifetime. These differences allow for classification and

simpler identification of the progenitor. Once the star reaches the Red Giant Branch (RGB),

dependent upon its mass, it can take the form of different sub-branches, most notably the

Asymptotic Giant Branch (AGB); stars < 8-10 Mʘ (considered low mass) follow this branch

in their evolutionary tracks. Running parallel with the main RGB, AGBs appear similar in size

and luminosity, though their spectral emissions may vary.

The internal structure of an AGB is composed of an inactive core of carbon and oxygen

supported entirely by electron degeneracy pressure, surrounding the core are helium- and

hydrogen-burning shells, though the helium shell burning is periodic. Outside of these shells

is a mixed, deep, convective layer, containing elements 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, revealing the core. The mechanism by which an AGB star loses mass is radiation

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

luminosity of the star, alongside the energy released from continuous helium ignition, impacts

upon dust that now has a larger cross-section with which photons can interact, thus setting up

a strong stellar wind that drives material outwards, essentially stripping the outer layers.

The remnant left behind by the mass loss is typically a carbon/ oxygen (C/O) core surrounded

by thin, helium and hydrogen layers, the star is now a WD. There are no more nuclear reactions

taking place within a WD, thus its surface begins to cool, the only pressure left to the core that

is keeping the star from collapsing is the aforementioned electron degeneracy pressure.

Dwarf Stars are found in the lower left corner of the HR diagram [Fig. 4]. WDs form the most

abundant of the dwarf classes, due to the fact that WDs generally evolve from lower mass

stars, and as can be seen from the IMF, there is a larger number of lower mass stars compared

to higher mass stars.

- 15 -

Figure 4- A Hertzsprung-Russel Diagram, depicting the main distinguishable branches that occur over stellar

evolution. [Credit: Chandra X-ray Observatory]

3.2 Classification Supernovae are classified based on their origin: low or high mass star, accretion or unstable

core collapse. Classification is useful for cataloguing, providing astronomers with a filter that

can lead to comparisons in the rate of each type, leading to a better understanding of the initial

mass function (IMF).

3.2.1 Type Ia

The most prominent of SNe, observed in both spiral and elliptical galaxies, and assumed to

only occur in binary systems on the account 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, commonly found in binary

systems, and it is generally accepted that a star with MS mass MMS ≤ 5 Mʘ (Das and

Mukhopadhyay, 2013) will evolve until the WD stage. Stars above this limit undergo core

collapse, as discussed in sections 3.2.2 and 3.2.3.

A Type Ia SN is the product of a WD undergoing a thermonuclear detonation. There are

currently two different models that describe the conditions required: the first is the Single

Degenerate (SD) channel and is achieved by accreting matter from a companion binary star,

up to a limit known as the Chandrasekhar mass limit: MCh ≈ 1.4 Mʘ. The other model is called

the Double Degenerate (DD) channel where a WD will merge with another WD, resulting in

a combined mass of greater than MCh.

The mass inflow rate from the SD channel, can allow for helium and hydrogen burning to

occur in the outer shells (Yoon, 2004), which leads to an increase in the internal temperature.

Due to no internal fusion reactions, the WD that is currently supported by electron degeneracy

pressure cannot expand to compensate for any increase in core temperature. Once the required

temperature for carbon burning is met, the burning causes a further increase in core

temperature over a period of ~1000 years. Degenerate pressure is only dependent on density

(1.3), but independent of temperature, so as the internal temperature rises, the WD cannot alter

its pressure to reduce the energy production as a MS star would, instead the increase in

temperature leads to further nuclear burning processed, resulting in a run-away incineration

of the internal material, ending with a thermonuclear detonation.

The energy released by these nuclear reactions entirely destroys the star and sends the resulting

material outwards in a fast moving shock front. What keeps the SN from dissipating faster

than currently observed is the formation of radioactive isotopes of 56Ni, which acts to increase

the opacity of the SN, decreasing the number of photons, produced from the beta decay, that

can escape from within the expanding volume, it can be concluded then that the peak

luminosity is proportional to the amount of 56Ni produced.

- 16 -

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 curve profile,

as seen in Fig.5. The initial beta decay of 56Ni into 56Co is the reaction that controls the profile

of the initial peak, with the second beta decay process being linked with the width of the light

curve (Blondin et al., 2012).

Spectral analysis of typical Type Ia SNe shows prominent Si II lines in the wavelength region

of 6150Å to 6355Å (Blondin et al., 2012). Other elements present, 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 calcium

Ca, all produced via the nucleosynthesis that arises from the extreme temperatures within the

thermonuclear detonation of the WD.

The general lack of hydrogen lines is itself a reasonable indicator that the observed SN is a

Type Ia. Whereas for any other type of SNe, there are indications of H and He lines in the

emission spectra, due to both elements being present in surrounding shells of the collapsed

core (see description below). For the case of the exploding WD however, the presence of H

or He is minimal, the overall contribution of these elements to the star’s mass is such a small

fraction that it will almost certainly be burnt up in the runaway nuclear explosion occurring.

3.2.2 Type Ib & Ic

Type Ib and Ic SNe are believed to be the result of stars in the Wolf-Rayet (WR) phase that

undergo core collapse. With masses greater than 20 Mʘ, WR stars are notable for their H-

deficiency, due to mass loss of their outer envelope, inferred from spectra that indicate mass

loss rates in the order of tens of solar masses. The mechanism behind this envelope stripping

is the interaction with high velocity stellar winds, travelling at ~3000 km s-1. The star is

stripped of its envelope leaving a 20-30 Mʘ core; it is the core that then collapses after burning

up its fuel supply, hence these two sub-categories of supernova are referred 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 the outer edges, leading towards O and Si surrounding the centre. The layers

are at a high enough temperature to continue nuclear burning processes, producing

increasingly higher fractions of 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. Once Si burning ceases, the core density and temperature

increases, supported only by the electron degeneracy that arises from this contraction.

The condition for collapse is that the mass of the iron core be greater than the Chandrasekhar

mass limit for the case of 56Fe, only then can gravity become dominant against the pressure

from the electron degeneracy. The Chandrasekhar mass limit is different from that of a WD,

here MCh = 1.26 Mʘ and is calculated via equation (1.5):

𝑀𝐶ℎ = 5.83 𝜇𝑒−2 (1.5)

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

1

𝜇𝑒= ∑

𝑋𝑖

𝐴𝑖𝑍𝑖𝑖 (1.6)

Xi is the mass fraction of the element, Ai is the atomic mass and Zi is the atomic number of

the element.

Core collapse is a runaway effect and cannot be halted, as the radius decreases, temperature

and density increase rapidly causing the central 56Fe to form a very dense core. The energy

released by such a collapse of the surrounding material is due to photodisintegration by high

energy photons, where ~2 MeV per nucleon is released. Protons and neutrons are released via

photon stripping of the lower mass elements, i.e. helium, which is a highly endothermic

process:

𝐻𝑒 4 + 𝛾 → 2𝑝 + 2𝑛 (1.7)

- 17 -

As thermal energy is removed from the surrounding gas, pressure support drops, resulting in

the collapse onto the core. When the core reaches T~109 K and ρ~1013kg m-3, the electrons

that contributed to the degeneracy and subsequent core support are captured via proton

interaction: p + e- → n + ν. The neutrinos released in this manner cause a huge energy flux

outward from the star, carrying stellar material with it.

Observationally Type Ib and Ic are great indicators of ongoing star formation, as higher mass

stars live shorter lifespans and end up going SN, attributing to the formation of lower mass

stars with the expelled material. In their spectra, as seen in Fig.6 there are fewer peaks, with

either limited or undetectable amounts of Si II, along with Fe II from the core, there may also

be a few elements that are left over from the nuclear fusion within the shells that gets ejected.

HeI lines, at ~587 nm, are present in spectra for Type Ib SNe, though neither Ib nor Ic show

any H lines, due to the pre-mentioned absence.

3.2.3 Type II-P / II-L

Much like with Type Ib and Ic SNe, Type II SNe are believed to be the result of core collapse

within evolved, higher mass (M > 8 to 10 Mʘ) (Anderson, 2015) stars consistently found in

the arms (within HII regions) of late type spiral galaxies, where there is ongoing star

formation. This characterization of location allows for the interpretation that the progenitors

are both young and massive, known as Red Supergiants (RSB).

Core collapse of these young, massive progenitors occurs due to a drop in nuclear fusion

reactions within the core, generally because iron has become the most abundant element there.

Once the core reaches this saturation point it can no longer produce the outward pressure

required to keep the star stable, the surrounding envelope of matter then collapses inward

under gravitational attraction. Upon collision with the core the matter rebounds outward,

leaving a compact and extremely dense neutron star in its wake, or if the progenitor was

massive enough, a black hole.

Type II SN spectra 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, as no other SNe have such abundances, it can be

concluded then that the RSB progenitors maintain an outer, convective shell of H atoms even

before core collapse occurs.

There are a few different sub categories for Type II and classified appropriately via their light

curve profile, seen in Fig.5. Type II-P (plateau) SNe show nearly constant luminosity, with

small variation, over the first 100 days since the peak luminosity is reached, while Type II-L

(linear) shows a more rapid, linear decline in luminosity over the observational time period

(Anderson, 2015). As for an average peak absolute magnitude, Bardon et al.(1978) observed

38 Type II SNe and found a mean B band absolute magnitude of MB = -16.

- 18 -

Figure 5 – Light curve profiles of SNe, with duration from peak magnitude against absolute B magnitude. Notable

profiles are that of the Type Ia, Ib, Ic, II-L and II-P lines. (Filippenko, A.V. 1997)

Figure 6 – Spectra from each type of SNe, with the Rest Wavelength in angstroms along the horizontal axis, and

log flux along the vertical axis, plus correction constant (Filippenko 1997).

- 19 -

4 Bayfordbury Review

4.1 Observing with Bayfordbury Both the CKT and Paramount telescopes can be fully autonomous when in robotic mode, i.e.

the use of RTML scripts within ACP, they are controlled, along with the domes and CCDs,

by the connected computer. This allows for remote access 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 is a feature implemented by most

observatories and is highly valued as it minimises the requirement for manual operation of a

telescope, especially when optimal observing conditions are infrequent.

Stationed at the Bayfordbury campus is a central hut, named after Sir Patrick Moore for his

dedication and contributions to astronomy. This hut is the central nervous system for the

telescopes and radio dishes, weather stations and computers. The observatory is manned by

one to two staff members, primarily maintaining the systems and telescopes, while overseeing

the use of the telescopes by undergraduates / graduates and the public alike. There have been

a few occasions when having a staff member on site or close by to resolve an issue with the

telescopes has been beneficial, when either a lens cap has been left on, or the telescope has

disconnected itself from the computer due to restrictions in movement.

Bayfordbury is ideally located; positioned away from most major light pollution sources, on

a hill above the local surroundings and in a part of England that has quite stable weather

patterns. By locating the observatory in such conditions, sky survey efficiency can be

improved due to the telescope being exposed to a higher limiting magnitude and a large field

of view on the sky, increasing the distance out to which observations can be made and how

well targets can be resolved, though still with limits on how often or how faint the telescopes

can observe to.

4.2 Characterization of the Paramount Telescope For the purpose of this paper, the Paramount telescope has been chosen for characterization.

As of writing this, the Paramount telescope and connected equipment is the optimal choice

out of the seven other telescopes at Bayfordbury, due in part to the robotic abilities and general

upkeep that is carried out on to keep it operational.

The light collected by a telescope can be quantified by the following expression:

𝑁(𝑡) = 𝑄 𝐴 𝑡 Δ𝜆 𝑛𝑝 (1.8)

With A as the area of the aperture, t is the exposure time, Δλ is the wavelength bandwidth, np

is the photon flux, and Q is the Quantum Efficiency (Cheng. J, 2010).

The Paramount is a Meade LX200R, catadioptric1 telescope, which utilizes both the

Cassegrain reflector in conjunction with a Schmidt corrector plate, also known as a Schmidt-

Cassegrain telescope. Fig. 7 shows the telescope in action, the secondary mirror is attached to

the inside of the corrector plate so as to remove the need to suspend the plate inside the

telescope, introducing an intrusive element to the observations that would also need

accounting for. The aperture and focal length of both CKT and Paramount are 406.4mm and

4064mm respectively.

From equation (1.8), it is clear that it is advantageous to have a larger aperture, A, which is

why astronomers are always building larger telescopes. The other controllable value is the

exposure time, sometimes referred to as the integration time, it is measured in seconds and the

greater t is the higher N(t) will be. Both Δλ and np are derived from the observed source, and

Q is determined for each telescope, beyond these factors it is clear that the CCD readout

increases linearly with both aperture and exposure time.

1 Catadioptric telescope: a combination of specific mirrors and lenses to correct for any errors in light

rays passing down the telescope, i.e. any aberrations of the light.

- 20 -

Paramount is equipped with an SBIG STL-6303 CCD unit that has a FOV of 23.4’ x 15.6’,

large enough to capture the majority of Andromeda M31, the closest galaxy to the MW. The

plate scale of the CCD is 50.75” mm-1, and is a measure of how much sky is covered per mm

of the pixel array. Recently two new CCD sensors have been delivered to the Bayfordbury

campus and have a FOV 2.7 times greater than the above mentioned SBIG units. This larger

FOV would be beneficial for a survey as it would allow for larger patches of sky to be covered

per exposure, with the potential of reducing the scanning time. This improvement would be

more substantial for a larger sky survey, i.e. SDSS, compared to what can be achieved here.

In an ideal telescope, the Quantum Efficiency (QE) would be 100%, with Q=1 in equation

(1.8), both the telescope and the CCD achieving a 0% reflective loss of the incident light,

meaning no dead pixels or light loss on the way from the lens down the length of the telescope,

passing through potentially multiple mirrors and lens before impacting onto the CCD array.

For the CCD, the QE is the measure of how efficiently will a photon liberate an electron once

impacted upon the silicon layer of the CCD pixel array, with each pixel treated as a bucket for

the photons, any dead pixels will incorrectly read off the liberated electron count within itself.

Different filters that are applied to the CCD also have their own QE values and must be

accounted for when calibrating the telescope, the QE value never exceeds anything more than

98% due to imperfections in the manufacturing process. The telescope’s reflective

components contribute to the overall QE of the system due to photons potentially being

absorbed within the material of the telescope itself or reflecting in a different direction than

intended.

One method to overcome the problem is to apply a coating to the mirrors used inside

telescopes, a chemical silver coating used to be applied which reduced the reflective loss down

to 5%, but any sulphur dioxide in the surrounding air would corrode and tarnish the coating

and reducing the effectiveness of the applied coating. More recent practises include the use of

a vacuum chamber to apply an aluminium coating, though more resilient to erosion, the

reflective efficiency varies between different wavelengths of light: 10% for optical, 12% in

UV emissions at wavelengths of 250nm, then improving as it is exposed to the IR spectrum

(~1μm). When dealing with more than one mirror, just as Paramount uses, the reflective

efficiency is the square of the value as determined for a single mirror configuration. (Cheng,

J. 2010)

The filters in CCDs, installed via a filter wheel for ease of access, are used to filter the photons

that will be incident on the pixel arrays, allowing for the different parts of the EM spectrum

to be observed without bleed through from the other wavelengths. Paramount is equipped with

the filters listed in Table 1, with U B V R and I belonging to the Johnson filter group, and the

ESO La Silla filters [O III]2, H-alpha and [Si II] deal with the broad and narrow bands of the

EM spectrum to do with the element the filter is named after.

Figure 7- A Schmidt-Cassegrain telescope, combining a corrector plate with a spherical primary mirror resulting

in an image that would have been produced by a parabolic primary mirror. This design reduces both physical size

and production costs.

2 Square brackets are used for certain elements to denote that they are ‘Forbidden lines’ as seen in the

H II region.

- 21 -

Table 1 - Johnson Filters and their effective midpoint wavelengths. (Gallaway, 2015; O’Dell, 2001)

4.2.1 Calibration methods

When dealing with a large array of pixels, ranging from millions to billions per detector, there

are expectations for the array to be plagued by background and thermal noise that accompanies

each reading. Whether it be due to a manufacturing defect, or in some cases cosmic rays, a

CCD is never 100% efficient in reading off the counts, and so calibration is required to reduce

such intrusions. This calibration is carried out via flats; frames that are designed and recorded

in such a manner to reduce each contribution of unwanted noise.

The Bias Frame (BS) is an exposure of zero seconds, forcing the CCD to take a reading while

the shutter is closed. This technique highlights the nature of the pixels, as each will vary ever

so slightly in comparison to next, this is an unavoidable but accountable problem arising from

the manufacturing of the pixels and how well each will hold the supplied electrons.

A light frame is the exposure of the CCD to an intended target, with the shutter open, with an

exposure time, it is this frame that the calibration is applied to. The Dark Frame (DF), much

like the bias, is an exposure with the shutter closed, but with a duration matching that of the

light frame it is to be subtracted from. The DF is ideal for removing the noise generated via

the Dark Current (DC), where the DC arises from thermal electrons, not originating from

photon interactions but rather from surrounding sources close to the CCD. DC noise increases

linearly with temperature and exposure: longer exposures and higher temperatures (due to

external heating or from a faulty fan) result in a higher noise count from the DC (Gallaway,

2015).

Both the BS and the DF are subtracted from the light frame so as to remove thermal and

random background electrons originating near to the CCD. The next technique is called flat

fielding; where a series of images are taken and a set count is reached (~30,000 for an average

16-bit camera), this is done for each of the filters. A median value for each pixel is found and

used to make a science flat, then after several repeats of this process, in each filter, the mean

value is used to construct a Master flat for each filter (Gallaway, 2015).

Flat fields are taken when the telescope is pointed toward a flat/ uniform source, i.e. opposite

the Sun during twilight hours (Sky flat) or the more convenient option; a square white surface

attached to the inside of the dome (Dome flat). Such flats are taken to help account for

irregularities in the overall reading from the CCD, including checks on the pedestalling3 of

images, then ranging from the telescopes’ optics, any dust on the filters and dealing with

having a circular aperture exposure onto a rectangular pixel array (Gallaway, 2015).

Once an image has been calibrated with the above methods, first by subtraction of the Bias

and Dark frames, then dividing the results by the Flat frame, which itself will have had the

Bias frame subtracted from, it is then referred to as a science frame. From here the science

frame is ready for any further photometry or analysis, having had the majority of the

background noise removed.

Aperture Photometry is a process that can be carried out by a variety of astronomy software

packages, including MaximDL, DS9 and AstroimageJ. An aperture is created for the user to

manipulate and place, with the options of increasing and decreasing the size and diameter of

the annulus, the goal is to surround the object of interest, normally a star, within the inner

annulus, while reducing the noise or counts from external sources (i.e. other surrounding stars

3 A ‘pedestal’ is the application of a fixed count number, increasing the counts by a linear step is the

method applied to counteract any potential readings from the pixels when the charge is not correctly

stored within them. The pedestal is then later removed in the ‘pipeline’ process for astronomical images.

Filter U B V R I [O III] H alpha Si II

λ eff (nm) 365 440 550 700 900 500.7 656 672

- 22 -

near the target) within the outer annulus, which is tasked with reading off a sky / background

count. This method enables the program to read the source target count and the sky count at

the same time, resulting in a ‘signal minus sky’ counts value. The application of this process

is discussed and used in section 4.2.2, and 5.3 (Gallaway, 2015).

4.2.2 Limiting Magnitude

The limiting magnitude of an observatory is the faintest magnitude that can be observed before

the sky noise dominates the source counts, with a slight variation between each filter and any

further increase in exposure length will lead to no discernible improvement. This means that

the telescope can only see objects out to a limited apparent magnitude, restricting both how

many objects can be detected as well as how far out the observatory can detect object to. The

following experiment will determine the upper limit apparent magnitude, though other factors

will reduce distance further: i.e. lunar luminosity, atmospheric thickness and density, and

finally light pollution.

To determine the limiting magnitude, an exercise in exposure and calibration will determine

a result of how faint an object can be, and still be detected, while also testing for the point of

diminishing returns of higher exposure lengths. A series of exposures; 30s, 60s, 120s, 180s,

240s, 300s and 600s will be taken, calibration of each exposure against an already known

apparent magnitude for a pre-selected star will result in accurate values for the magnitudes

from the counts. Fig. 8 is a finder chart, indicating the star Cl* NGC 1039 W1368, as chosen

for the calibration magnitude in the B V R bands.

Using AstroImageJ to carry out the above process on the images taken by Paramount, of M34,

via the automated queuing system, it was then a case of exporting the results of each star

selected as the faintest object of from each exposure to an excel spreadsheet. After some

research into conversion between sky counts into magnitude, equation (1.9) was applied along

with using the known apparent magnitude of the reference star, so as to correct the value via

a scaling factor, per filter. (Craig et. al. 2014)

𝑚 = −2.5 log10(𝑁𝑆𝑜𝑢𝑟𝑐𝑒 − 𝑁𝑠𝑘𝑦) + 2.5 log10(𝑡) (1.9)

Using the values for ‘sky minus source’ and exposure time (in seconds), as taken from

AstroImageJ, it is possible to calculate an observed magnitude. Once the reference star has

been passed through this conversion a known apparent magnitude for each filter has been

found, the other targeted stars can be dealt with. Once the actual magnitudes have been

calculated, the data points were plotted against exposure time, as seen in Fig. 9, showing that

as the exposure time increases, the fainter the telescope can observe out to. The reason behind

finding the limiting magnitude is to find the point at which an increase in exposure time will

result in diminishing returns of the counts received due to a decrease in the Signal to Noise

Ratio (SNR).

By definition, a limiting magnitude introduces a limiting distance, a volume centred on Earth

within which it is possible to observe targets while sky brightness levels remain lower than

the limiting magnitude. Taking a limiting apparent magnitude of 17, which takes into account

an average clear night with low levels of lunar luminosity, and an average absolute magnitude

of a Type Ia SNe: -19, it is possible to find a limiting distance via the use of the magnitude

equation (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 distance that is not reached within

the scope of the paper, though predicted to be achievable if required. This is an important

result, and is referred to in later sections, the result though is a distance and magnitude out to

which this survey could theoretically observe too, although such extremes would not be

warranted due to the abundance of galaxies within even a 20 Mpc range.

- 23 -

Figure 8- Finder Chart of M34 with NGC 1039 W 1368 highlighted. This was the calibration star, with the apparent

magnitude taken from the SIMBAD online catalogue.

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

Filter /

exposure

Source –

Sky

(counts)

Calculated magnitude (before

calibration)

Calibrated

magnitude

B

30 220.81 -2.18 15.54

45 319.91 -2.13 15.58

60 307.58 -1.77 15.93

90 340.04 -1.44 16.26

120 273.02 -0.89 16.82

180 219.28 -0.21 17.49

240 279.13 -0.16 17.54

300 335.06 -0.12 17.59

600 310.05 0.72 18.43

V

30 266.17 -2.37 15.61

45 213.91 -1.69 16.28

60 291.60 -1.72 16.26

90 245.11 -1.09 16.89

120 207.50 -0.59 17.38

240 180.89 0.31 18.28

300 154.60 0.72 18.69

600 197.54 1.21 19.18

R

30 1860.31 -4.48 16.68

60 3192.07 -4.31 16.84

90 2517.14 -3.62 17.54

120 2281.40 -3.20 17.96

180 2716.17 -2.95 18.21

240 2365.96 -2.48 18.67

300 2910.74 -2.47 18.69

600 5293.85 -2.36 18.79

- 24 -

Figure 9 – Graph showing the Limiting magnitude experiment, imaging M34 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 apparent magnitude,

whereas V and B show trends that the limiting magnitude is ~19 mag. An important experiment in determining the point at which increasing the exposure leads to diminishing returns for the counts the CCD reads from the source,

and the Signal to Noise Ratio (SNR) decreases.

4.2.3 Autonomous vs Manual Observations

Each of the telescopes are connected to a computer which acts as the interface, allowing

control of the telescope and CCD: pointing coordinates, target selection and other settings.

The computer and installed software have the ability to run a range of varying tasks as set-out

by custom scripts, such as making calibration frames, retrieving queued jobs for the telescope

and many more tasks that can be achieved autonomously. The main software package, ACP

Observatory Control Software paired with TheSky X, allows for full automation in the form

of RTML scripted jobs that can be submitted via the online Bayfordbury internal website.

The scripts are generated after using a web-friendly user interface that first allows target

selection and verification that it can be observed, exposures, filters, binning, moon avoidance

and how many repeat observations should be carried out. Once filled in, the form creates a

RTML script, it is then first approved by a member of the Bayfordbury Observatory staff, to

make sure the request is within reason, then judging from the supplied description and any

other factors, they will assign the job a priority rank between 0 and 100, where a number

results in a greater priority within the queue.

If the onsite weather station reports that the weather is suitable and within safety margins for

observations, the automation can begin, the dome opened and the queue observations can

commence.

During this survey, it was decided that a mix of both manual and autonomous observations

should be taken, so as to help with the assessment of the telescope equipment, as well as gain

valuable hands on experience with the observatory. This decision would limit the survey

though as it would require the telescope to be operating at peak efficiency, with minimal

tracking and locating errors throughout the usage. That is more of an ideal scenario and more

often than not the telescope would have trouble finding a target, often time needing to have

the pointing location synced against the observed stars. This alignment was possible via plate-

solving of the image; where the image is uploaded to a website (astrometry.net) that would

- 25 -

compare the image with an archive, returning either a successful match and central pointing

coordinates, or an ‘unsuccessful’ message.

Both with manual and automated observing, MaximDL is used as the control interface for the

CCD, selecting which filter to use, exposure length, what type of frame (light, dark or bias)

the observation is and what level of calibration is to be applied. MaximDL also displays the

end product of the observation, once downloaded from the CCD, from here further

observations can be decided upon or else see if the telescope is in need of pointing correction.

When manually selecting targets ACP 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 viewable and not outside the declination limits as set

by the dome and local, for the Paramount telescope, these limits are: lower: 10°, upper: +90°.

This method of target selection is less desirable in practical uses for such a survey due to

locating errors related to star charts being out of sync between the computer and the night sky,

with the star finder returning error messages. The way to resolve such errors is to plate solve4

the image, retrieve the central coordinates in R.A and Decl., then syncing ACP to those

coordinates and exposing again once the target has been selected.

While using the autonomous system, and included within the web browser applet included

with ACP, the telescope will attempt to find and verify that the target is within the FOV before

continuing to execute the plan for that target. This reduces the rate of which the telescope

returns a false response or a field of stars that cannot always be plate-solved.

4.3 Feasibility of Observing Supernovae Observing SNe is quite the challenge in itself, especially first finding such an event, so much

so that numerous measures are employed to increase the chances of detecting and then

subsequently observing SNe. In regards to the feasibility of observing SNe at Bayfordbury,

there are numerous limiting factors that need consideration and attention if ever an SNe survey

were to be carried out in the future, and be successful.

When considering the site for a telescope that will be used for sky surveys, it is normally good

practise to place it at a high altitude, somewhere not exposed to major storm fronts or

unwanted weather conditions (i.e. cloudy skies, humid atmosphere, large variations in weather

patterns). Bayfordbury is located in the county of Hertfordshire, England, and as such is not

positioned atop a mountain above cloud level, and nor is it excluded from the various weather

fronts that England is known for; high wind speeds, rain, numerous clouds and the occasional

snow.

Due to the location of Bayfordbury the weather requires extended consideration in regards to

the time allotted for observing. The lower altitude, compared to other notable observatories

that are mountain based, results in an increase in atmospheric absorption interference, as well

as greater cloud coverage and low levels of light pollution.

Appendix A contains inverse contrast images of the galaxies observed and tracked throughout

this survey, each labelled by their respective apparent magnitudes. Though the limiting

magnitude has been established to be ~ 19 mag, it is not always possible to reach such objects

due to the seeing, a term used to describe the angular deflection of light from stars by the

turbulence in the atmosphere, causing stars to blur or twinkle as the refractive index varies

through the atmosphere.

4 Plate Solving is the act of comparing an image of either known stars or a galaxy with a catalogue,

either by the use of Maxim DL, or by using the website: astrometry.net. The result is a labelled image

of the object, as well as RA and Decl. coordinates for the center of the image, these are used for the

syncing of telescopes.

- 26 -

Sky Brightness is another factor that will limit how deep of an observation can be undertaken,

while Bayfordbury is located away from large sources of light pollution, sky brightness will

be an issue if the Moon is at a phase of 50% or more, this is discussed further in the next

section. Winter is an ideal period of the year to conduct deep sky surveys due to the extended

observational time made available from the longer nights, as well as the darker skies from

reduced light explicitly from the sun, resulting in a fainter limiting magnitude.

Table 3 consists of statistical values for each of the SN classifications, as calculated from the

data set of SNe between 2000 and 2015. Notice the difference in magnitude between type Ia

and the three other classifications, it would appear in agreement with the model of Ia occurring

due to different circumstances than the core collapse of the others.

Galaxies are the largest collection of stars known to us, with masses varying from ≥ 105 for

dwarf galaxies to ≥ 1011 for most late-type spiral galaxies, the MW is calculated to be ~1012

Mʘ. The mass to light relation shows a linear increase and is assumed to be fairly constant for

all galaxies, M/L ≈1. As massive as galaxies are, they appear faint in comparison to the local

stars within the MW, though they tend to cluster due to gravity (or a combination of Dark

Matter haloes / Dark Energy), and the result is a group of galaxies that constitute the local

galactic Neighbourhood.

M31, the Andromeda Galaxy, is our nearest neighbour, both in structure similarity and

distance. At a distance of ~780 kpc, M31 is the closest and thus brightest galaxy, viewable by

the naked eye at Bayfordbury. The observed brightness is greatest at the 7 to 8 kpc diameter

bulge at the centre that outshines the surrounding spiral bar and disk regions, due partly to the

large stellar population of both young low-mass and high-mass stars, surrounding a

supermassive black hole, a prediction that applies to all galactic cores. Galaxy bulge mass,

Mbulge, estimates currently stand at ~5 × 1010𝑀ʘ (Häring, N. 2004), this is the majority of

galactic mass as compared to estimated galaxy mass, within 300kpc, of ~ 1.4 × 1012𝑀ʘ

(Watkins et al. 2010). Galaxy mass estimates are derived by either Jeans equation modelling,

virial theorem with velocity dispersion readings or via the mass to light relation.

Bright central regions will lead to over-saturation and bleed through to other regions, less than

desirable for observations, especially when searching for notably bright sources in the spiral

arms, which can be faded in comparison. Other galaxies show similar light distribution which

acts to limit how much of the galaxy can be resolved from the bleed-out of the bulge. For

instance, both NGC 891 and M82 are viewed as edge-on to Earth in inclination, both with

large, bright bulges that shine through the surrounding gas and dust within their spiral 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 as over-exposure, and hence dismissed. There are methods to subtract

and reduce the central brightness of such targets, and are applied by professional astronomers

or photographers when observing and manipulating such galaxies.

The survey plan was to observe when possible, through the use of remote control and / or

using the queuing system ACP utilises. Over the three to four months of optimum observing

time, it is estimated that three to four nights a week would be allocated to observing. It was

estimated that this survey would at best include the observation of 1 SN, with the potential to

spot as many as possible that occurred within the range of time and sky location that this

survey could cover. This is a ballpark figure, not best supported by the shortened timescale

that this survey will cover.

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

SNe Mean m Median m Faintest m Brightest m

Ia 18.94 18.5 25.0 10.5

Ib 17.9 17.8 23.7 13.8

Ic 17.81 17.7 23.4 12.0

II 17.9 17.8 25.1 11.2

- 27 -

4.4 Limitations With the feasibility of carrying out a SNe survey discussed, it is appropriate to next consider

the limitations that will constrain such surveys, and most importantly highlight those that can

or cannot be accounted for by the survey carried out with Bayfordbury. The main limitations

that face any survey, on any scale, are time dependent and will have numerous implications

that need addressing when setting out an initial plan for the survey. Factors like the time of

year that is most suited to deep sky observations and longer observational runs, the phase of

the moon and how it will impact the limiting magnitude, plus weather dependencies.

SNe are not always occurring within our range of observations or targets, or at all, surveys can

run for many years and can observe a small number of occurrences. The online community

and sharing of discoveries has helped many astronomers in keeping up-to-date on if any SNe

are currently viewable, leading to the telescope not needing to scan, only find and observe the

host galaxy that was tagged within the online reports. This is how SNe are reported, verified

and then depending on the outcome, catalogued.

Observatory location can be another limitation that can impact a survey’s chances of observing

continuously. Comparing the Very Large Telescope (VLT) in Chile, with Bayfordbury here

in England, there is an extreme difference in both geographical location and altitude. VLT is

part of the European Southern Observatory (ESO) and sits at an altitude of 3635m above sea

level, it is exposed to consistently clearer skies than those available to Bayfordbury. High

altitudes afford a telescope with less atmosphere to interfere with incoming light, and the

remoteness of VLT’s location means no light pollution. Bayfordbury is only 66m above sea

level and subject to sometimes adverse weather conditions and some light pollution, plus a

thicker atmosphere for light to penetrate. (ESO, 2016)

Dependent upon where an observatory looks at the night sky, it will see different stars,

constellations seen from the northern hemisphere will look different if seen from the southern

hemisphere. The same is true for galaxies, many galaxies are unavailable to Bayfordbury due

to their negative declination. This difference in global location will therefore limit the number

of galaxies available for repeated observations, potentially the factor that limits any SNe from

being observed by a survey.

The statistical likelihood of a SN occurring within any one galaxy is 1 in every 100 years,

though there are many galaxies within observable limits, it is not possible to always observe

them, with factors such as weather and lunar phase, interrupting observations. To observe at

least 1 SNe during a survey, either the same galaxy must be traced for 100 years, or a minimum

of 100 galaxies must have repeated observations made over the course a year. The latter option

is the path that modern surveys will take, observing more than 100 galaxies over their allotted

survey period.

Increasing the number of galaxies targets is not the only factor that can overcome this statistic,

determining how often a single galaxy is to be observed will also yield a noticeable outcome.

If 10 galaxies were to be observed each night, then a rotation could be implemented so as to

still be within the timeframe of a type Ia SN and still detect it, even if the SN went off during

another observational run. This method would increase the total number of galaxies that a

survey could cover, while also making the most use of an autonomous system that can be

programmed to carry out the plan.

The luminosity of the Moon at larger phases will alter the limiting magnitude so as to wash

out fainter objects, increasing the sky brightness to a point that observing to fainter than an

apparent magnitude 10 object will be wasted observational time. Fig. 10 shows how the phase

of the moon will impact the sky brightness, in magnitudes, it is then evident that observing

with a full moon in the sky will hinder any observational attempts of fainter magnitude objects.

Like most other systems that can control autonomous telescopes, ACP will take into

consideration a pre-set lunar avoidance demand, as decided upon per observational run.

- 28 -

Options include what upper lunar phase will be tolerated, sky brightness levels, as well as

dealing with the cloud levels, (i.e. good, fair, poor).

Going back to the problem of galaxy inclination and bulge brightness, as mentioned in section

4.3, there is a distance, and magnitude, out to which observing SNe will not be possible, due

in part to the host galaxy outshining the SNe, even if it is not located within the bulge. NGC

1023 is an example of a galaxy that, when observed, appears faint but identifiable, a target

that would prove hard to certify whether or not a SN was occurring within.

Figure 10- How the Moon's luminosity will alter the visual magnitude that a telescope can observe up to, increasing the sky brightness to the extent of observing becoming almost impossible under such conditions. (Lewis, G. 2016)

Figure 11 - Comparison of the four main SN types: Ia, Ib, Ic and II. Taken from data covering the years 2000 to 2015 of observed and reported SNe. Type Ia is the most frequent as this is to do with the IMF of galaxies, with the

majority of stars being of the lower mass class, and hence leading to white dwarf stars at the end of their evolution,

resulting in type Ia SNe occurring more often than any other type.

- 29 -

5 Selection Criteria and Survey

5.1 Target Selection Applying the background knowledge that was discussed in the limitations and feasibility

sections previously, it is possible to construct a criterion by which the selection of galaxies

that the survey will cover can be limited to.

5.1.1 Galaxy selection criteria

By their very nature, late type spiral galaxies are the best candidates for continued observation

due to their mixed abundances of both low and higher mass stars, especially in regions of star

formation. Spiral galaxies are found to contain all types of SNe, therefore it will be beneficial

to filter galaxies down to spirals to improve both the chance and statistical likelihood of

spotting a SN.

The telescopes at Bayfordbury aren’t designed, or located ideally, for deep sky observations,

limiting the distance that it can observe out to before reaching the limiting magnitude. There

is a wealth of close, bright targets that can be observed with the correct conditions and

instrumental setup.

The limiting magnitude is the constraint that has to be applied when considering how faint the

target galaxy is. On most occasions, going fainter than an absolute magnitude of ~12 did not

resolve a detectable galaxy, mainly due to atmospheric conditions and the SNR decreasing.

When looking at galaxies this faint, a greater exposure length is required, resulting in an

increase to an already lengthy schedule. Fainter galaxies, if practically detectable, would be

left until last in the observation run, so as to prioritize time for the closer, brighter sources that

can be tracked and observed more reliably each night.

5.1.2 Observed Galaxies

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 12

M 33 (NGC 598) 01 33 50.9 + 30 39 37 6.27 0.84 8

M 51 (NGC 5194) 13 29 52.7 + 47 11 43 8.96 8.0 1

M 81 (NGC 3031) 10 03 20.6 + 68 44 04 10.61 3.82 3

M 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 3

M 106 (NGC 4258) 12 18 57.5 + 47 18 14 9.10 7.98 1

M 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 2

NGC 1023 02 40 24.0 + 39 03 48 10.35 10.5 1

NGC 2403 07 36 51.4 + 63 36 09 8.93 3.22 1

NGC 3147 10 16 53.6 +73 24 02 11.43 39.26 1

NGC 6946 20 34 52.3 + 60 09 14 9.61 5.9 2

NGC 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, distance in Mpc and the number of observations made of that galaxy over the survey. Number of observations is over different nights; multiple observations were made on the same targets each night.

(Kennicutt et al. 2008), (Tully et al. 2013)

- 30 -

5.2 The Survey Using Bayfordbury, the survey took place between October 2015 and March 2016, taking

advantage of the longer nights afforded by winter. The aim was to select and repeatedly track

galaxies that met the criteria, while also gaining hands-on experience with the telescope and

seeing how the system worked first hand, so as to more effectively carry out the

characterization on the paramount telescope.

A scanning exposure of between 60 and 120 seconds was implemented at first, so as to first

verify the target was in sight, then progressing onto determining whether or not a SN was

present in the image.

During two separate observational runs, one by manual control and the other carried out during

robotic queuing mode, it was thought that a SN had been discovered. When the images were

compared after the observation with known archival images stored on the Bayfordbury

internal 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 an

object has been highlighted in Fig. 12, but not present in Fig. 13, this is due to residual bulk

imaging (RBI), also apparent in Fig. 14 and 15 of M101.

RBI is effectively the residual charge left on pixels that have been over saturated in a previous

image, a situation that can lead to false reports if unverified by a third party. Light sources

such as stars show a Gaussian profile in the photon count received in each pixel, an RBI source

will show a larger and flatter Gaussian profile curve, as compared to a real source, indicating

saturation. The solution for dealing with identified RBI sources is to carry out the observation

again as these sources will fade significantly in the next image and will disappear entirely, as

seen in comparison between Fig. 12 and 13, 14 and 15.

Such misidentifications are not rare, and have to be considered, with potential SNe verified

either by peer assessment, or by investigation into the light sources origin. If a SN is believed

to have been spotted, and RBI is ruled out, observing with another telescope is ideal, so as to

reduce the possibility of equipment error that would lead to ghost stars appearing due to

previous over exposure.

Table 4 contains all the galaxies imaged, their relevant information and number of recorded

observations made. Both M82 and M31 share the highest number of observations due to the

testing of the autonomous queuing system, these galaxies were selected for repeat

observations over the entire survey period by applying a ‘repeat every 7 days’ command to

the script.

5.3 Processing Data and Image Analysis The software package AstroImageJ is one of the many software suites that deals with the

output files from the CCD, in the file format of ‘.fits’. AstroImageJ offers many tools that are

essential for noise reduction / calibration, contrast alterations, aperture photometry and plate-

solving via astrometry.net. Within the software, it is possible to apply the science frames that

were discussed in section 4.2.1, reducing the background noise from the CCD thermal

emissions, correct for bad pixels and reducing cosmic ray noise.

Another technique used to reduce the noise in an exposure is to stack multiple exposures

together, increasing the SNR. Stacking requires multiple images of the same target to be

aligned, the best way to approach this is to align by the WCS coordinates and can be achieved

by the software. The result can be used in multiple ways, most novice astronomers will utilise

stacking for RGB colour images of a target, here stacking would be applied to images

containing SNe.

Tracking SNe over a period of time requires the measurement of the changing magnitude, as

well as position within the galaxy for other astronomers to more easily locate and verify the

source. Over the course of tracking an SNe, multiple images would be taken each night, with

a minimum of 5 all within the same light band, so as to create an image stack per night with

- 31 -

reduced noise. From there the SN would be observed over the period of its existence, and the

subsequent stacks from each night stacked again, creating a 3D plot of the SN over the

observational period, easing the process of both aperture photometry and magnitude plotting.

Though this is a useful procedure for tracking the light curve of SNe, it does require continued

observations of the target: the more frequently it can be imaged, the higher the accuracy is of

the final light curve. Another use of stacking is to track galaxies over several different

observing nights for any significant changes or SNe appearances, especially if the problem of

RBI occurs, as the ‘ghost’ object will quickly disappear as you progress along the stack.

Using Aperture Photometry, it is then possible, once a stack has been achieved, to track the

evolution of the SN’s magnitude, making sure to calibrate it with a known star’s magnitude

that is located near the target. The downside though is that it will be increasingly difficult to

reduce the noise from the host galaxy when taking the readings, which could affect the final

estimate, however it is possible to adjust a light curve value to account for such situations, due

to the one to one nature of the curves, as expressed in section 2.3.

- 32 -

Figure 12 - M82 with believed SN, highlighted in red. Image taken in B filter, exposure time of 120 seconds.

Observation made via script and automation process.

Figure 13 - M82 as observed on the following night. B filter and exposure time of 120s. Image taken as request

was made to continue observations on M82 on concurrent nights, so as to verify the SN.

- 33 -

Figure 14 - M101, with believed SN highlighted in red. Observation was made via remote control from VPN

connection. Observed in I filter at 240 seconds exposure.

Figure 15 - M101 as observed several minutes after Fig.14. The believed SN appears fainter, a tell-tail sign that

this is not a SN, instead it is the result of RBI. Observed in I filter at 240 seconds exposure.

- 34 -

6 Results and Discussion

6.1 Observations During the course of this survey, no supernovae were discovered or observed by the

Bayfordbury Observatory. The selected galaxies were observed as and when possible to do

so, limiting the chance of missing a SN, while also making use of online forums and

noticeboards dedicated to the reporting of SNe. The galaxies observed during the course of

this short-term survey are included in Appendix A. Though some CCD RBI instances arose,

they were soon identified as non-Gaussian and hence were not SNe.

6.2 Feasibility of using Bayfordbury A full characterization has been achieved on the Paramount Telescope, including the facilities

of Bayfordbury that would lend aid to such a survey.

Both autonomous and manual observations have been conducted with the telescope, with

varying results. It was however required so as to assess the capabilities and structure, so as to

reach the conclusion that a Supernova survey could be carried out with the Bayfordbury

Observatory and return a successful result. Apart from the obvious limit of whether or not a

SN occurs over the course of such a survey, the equipment and systems would not limit a

survey to the point of failure. If this survey had made use of the automated system from the

start, many more repeated observations on potential targets would have been made, allowing

for an increase in number of potential galaxies for scanning.

The fact that no SNe occurred over the course of the survey, or were potentially detectable

from Bayfordbury, was unfortunate, however it is a factor that must be taken into account

upon deciding to undertake a survey.

6.3 Future Surveying Future surveys that would use the Bayfordbury Observatory would require almost sole use of

the autonomous observations made available by the queuing of RTML plans, such a system

allows the user to construct a plan of the intended targets, filters and exposure times without

the requirement for continued monitoring of weather patterns so as to decide upon when to

observe manually.

To further increase the success rate for such a survey that would be carried out using

Bayfordbury, having reviewed the included assessment of the telescopes, would be to produce

multiple plans so as to stage each selection of galaxies over several nights, widening the

selection criteria and increasing the number of targets for repeatable observations. Introducing

such a step early on allows for a longer period of observation, increasing the already small

chance of observing a SN.

Once observed though, a potential SN should be noted, compared against archival images as

taken from Bayfordbury, including a repeat observation from one of the other telescopes will

also help define the target to either be an SN or a CCD anomaly.

Surveys such as SDSS use a scanning system of mapping out the sky by progressively moving

along a path that will cover the majority of the sky each night, storing the images on the

internal servers, from there the images are passed through a pre-calibrated software that will

detect and flag any instance that it believes to be a SN, this is done by comparison with an

image known not to contain any SNe. It is the conclusion of this paper that such an undertaking

is not feasible via the use of the Bayfordbury Observatory, and hence a selection criterion is

required. With such a vast catalogue of known galaxies within the limiting distance

determined previously, there will not be a shortage of potential targets for repeated

observations. It is then a matter of constructing an efficient plan that will scan the targets.

- 35 -

Appendix A – Galaxy Images Galaxies observed twice or more over different nights.

Image 1 – M31, B filter, 60 second exposure.

Image 2 – M33, Clear filter, 60 second exposure.

- 36 -

Image 3 - M81, Clear filter, 60 second exposure

Image 4- M82, B filter, 120 second exposure

- 37 -

Image 5- M101, I filter, 240 second exposure

Image 6- M106, B filter, 180 second exposure

- 38 -

Image 7- NGC 891, I filter, 120 second exposure

Image 8 - NGC 6946, clear filter, 60 second exposure.

- 39 -

Image 9 - NGC 7331, clear band, 60 seconds

- 40 -

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