Analysis of Metal Distribution in Sc Type Galaxies Using the

SDSS-IV DR17 MaNGA Survey

Zifeng Gao

Beijing International Bilingual Academy, Beijing, China

Keywords: Spiral Galaxy, Metallicity, Data Analysis.

Abstract: The study of spiral galaxies has yielded fruitful results over the past half-century. The metallicity of a galaxy,

the ratio of metal elements to hydrogen and helium, has been shown to decrease as the distance to the center

of the galaxy increase. This study verifies the metallicity distribution of Sc type galaxies, with more definite

metallicity gradients. In this paper, the author utilized the SDSS-IV MaNGA survey to plot out the metallicity

gradient calculated with the O3N2 calibrator. The result shows a large amount of scattering after a certain

distance, and that the metallicity gradient is mostly flat, with the exception of a number of galaxies. This

shows that the metallicity gradient conforms with the traditional view. The scattering can be explained by the

spiral structure of the galaxy, and the exceptions may be due to the observational issues or higher redshifts,

which has demonstrated a positive metallicity gradient. These results allowed the confirmation of the

metallicity gradient at lower redshifts, and it has given more insight into the metallicity distribution of Sc type

galaxies, and thus more insight into the formation of spiral galaxies.

1 INTRODUCTION

Spiral galaxies (SG) have been the centre of

astronomical research for decades after Edwin

Hubble differentiated galaxies from ordinary nebulae

in 1926 (Dobbs & Baba, 2014). Hubble constructed

the Hubble Type classification schemes, separating

elliptical galaxies, SG’s and barred spirals. Hubble

then separated SG’s, both barred and unbarred, into 3

major types with differing structures: Sa galaxies with

a larger bulge, compact arms and higher luminosity;

Sb galaxies with smaller bulges loosely wound arms;

Sc galaxies with a smaller bulge to arm ratio and

generally the loosest arms. SG’s allowed researchers

to deduce conclusions such as the existence of Dark

Matter, from the peculiar shape of the rotation curves

all SG’s exhibit which was noticed in the 1970s

(Rubin, 1983; Rubin, et al., 1985). This utterly

important result, which has fuelled many simulations

and theories ever since its proposal, has allowed a

clearer view of the formation of the entire universe.

Another active field of research regarding spirals is

the study of the galaxy’s metallicity. Metallicity is the

ratio between the masses of elements heavier than He

to the combined masses of He and H (Henry &

Worthey, 1999). Metallicity is an essential part in the

investigation of the formation of the Solar System,

since the heavier elements such as Silicon, Carbon

and Nitrogen would contribute to the formation of

planets (Winter, et al., 2024). Thus, the study of

metallicity in galaxies allow researchers to

understand the formation of stars and planets more

thoroughly, thus pushing the boundaries in the studies

of the Solar System. SG’s have long perplexed

researchers and has yielded many fruitful results for

the scientific community such as the DM theory and

the metallicity results. Thus, this field is of great

future prospect, as more theories could potentially

arise from the study of SG’s.

The focus of this paper is on the metallicity

distribution of SG’s. Older studies, like the paper

published in 1999 by Henry and Worthey focuses on

the analysis of the metallicities for all types of

galaxies, ranging from the earlier HT’s to later HT’s,

concluding that the metallicity showed a negative

correlation with the distance to the centre (Henry &

Worthey, 1999). More recent papers focused on

analyzing the gas-phase metallicity (GP) by

calculating the oxygen abundance. One paper from

2025 used JWST data to analyse the gas-phase

metallicity gradient from galaxies of redshift z=0.5 to

z=1.7, testifying that the metallicity is lower in the

interstellar medium (ISM) of the outer regions of a

246

Gao, Z.

Analysis of Metal Distribution in Sc Type Galaxies Using the SDSS-IV DR17 MaNGA Survey.

DOI: 10.5220/0013823000004708

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Innovations in Applied Mathematics, Physics, and Astronomy (IAMPA 2025), pages 246-251

ISBN: 978-989-758-774-0

galaxy and also showing that most metallicity

gradients are indeed flat (Ju, et al., 2025). They have

also found that some galaxies at higher redshifts

greater than 0 could demonstrate a positive radial

metallicity gradient with sometimes a steep slope,

which is consistent with the results from the TNG

simulations (Ju, et al., 2025). The metallicity gradient

at z=0 could be explained by an inside-out growth

model of galaxies, stating that the initial

accumulation of matter at the beginning of the galaxy

would spread out over time, which would make the

gradient less steep (Ju, et al., 2025). This model

explains negative, flat slope observed at low redshifts,

but fails to account for the situation at higher redshifts

(Ju, et al., 2025). This team utilized integral field

units(IFU) from JWST observations, thus to construct

three dimensional spectroscopies (Ju, et al., 2025).

Another paper from 2019 reached a similar

conclusion, and also linked the higher metallicity

with other values which showed an increase in that

region, such as ionization, which led the researchers

to conclude that star formation plays a role in the

enrichment of the ISM (Kreckel, et al., 2019).

Furthermore, another study from 2025 also

substantiated the negative metallicity gradient in low-

redshift galaxies, using the MaNGA survey. They

also found that the slope becomes steep at a mass

smaller than 3×10

solar

and then flattens at masses

greater than this limit (Khoram & Belfiore, 2025).

This study would further examine the radial

metallicity gradient as a whole in Sc type spirals using

the newer IFU methods to collect data, thus

constructing a comprehensive view of larger galaxies,

which can further substantiate that the metallicity

gradients of SG’s are negatively correlated with the

radius. The Sc type is particularly selected, as Sc type

galaxies are galaxies early in their process of

evolution. Being early in its evolution, the Sc’s ISM

has not yet been supplied with a large amount of

metals, which would limit the amount of time

available for the redistribution effect achieved by the

inside-out growth theory as previously described.

This would contribute to a steeper metallicity gradient,

benefitting the analysis of metal distribution.

Furthermore, as the bulge is smaller, this paper would

analyse the combined metallicity in a certain region

of a galaxy, using mainly the GP metallicity to

compute the metallicity distribution.

In the following part, first, the author will

introduce detailed description of SG’s. Then, the

MaNGA and SDSS would be talked about, giving

insight into their technical aspects. Afterwards, the

author will talk about the methodology used to

analyse the data from MaNGA. The results would

follow this, then a discussion of the potential reasons

that lie behind the results would be given. Lastly, the

paper will discuss the conclusion, limitations and

future prospects.

2 SPIRAL GALAXIES AND

DETECTION

SG’s are essentially a type of galaxy with long arms

wrapped around them. As aforementioned, spirals are

a Hubble Type with three major categories. Although

the Sa type galaxy is commonly called the early type

is now thought to be older than Sb and Sc types, due

to their star formation rates being lower than that

which exists in Sb and Sc types. Thus, indicating that

the age should be the oldest for Sa’s, then Sb’s, with

the youngest being the Sc galaxy.

For the data collection part, the author will be

using the MaNGA survey from the seventeenth data

release from SDSS-IV. The SDSS survey has been

carried on for nearly thirty years, beginning in 1998

(Abdurro’uf, et al., 2022). The MaNGA survey is one

of the surveys of the SDSS, with the full name

Mapping Nearby Galaxies at Apache Point Observer

(APO). In the northern hemisphere, SDSS uses the

2.5-meter aperture telescope at the Sloan foundation

observatory. They also use the La Campanas

Observatory located in Chile to observe the southern

hemisphere. This allows for a comprehensive view of

the entire night sky.

The MaNGA survey uses IFU, a technology

aforementioned, to construct three dimensional,

spatially resolved surveys of galaxies and clusters.

Thus, MaNGA is capable of constructing full

spectroscopic data on a 2D maps, differing it from the

traditional spectroscopes, which only allows users to

analyze data at a certain region within the galaxy. The

MaNGA is capable of taking large field spectroscopic

data of entirety of galaxies using integral field units.

This, combined with the 2D view, allows a more

integral view of galaxies, facilitating future

researches (Bundy, 2014).

MaNGA stores data in the form of data cubes,

which can be extracted individually from the Marvin

API via Python by inputting a specific identification

number, for individual data cubes, known as the

plate-ifu (Cherinka, et al., 2019). In total, MaNGA

made surveys of 10,010 galaxies using the IFU

method. The IFU is made up of small packets of fiber

optic organized in hexagons (Dory, et al., 2015). In

total, 1423 fibers are utilized in the MaNGA. Each of

these fibers will form harnesses, which are larger

Analysis of Metal Distribution in Sc Type Galaxies Using the SDSS-IV DR17 MaNGA Survey

247

bundles of optic fibers and their corresponding

hardware used to hold them in place. The light signals

captured by the telescope would be sent to the sensors

via the harnesses. The instrument, via this set-up, is

capable of resolving lights of wavelength 3600 to

10300Å.

3 METHODOLOGIES

This paper will thus be using the MaNGA survey to

construct maps of metallicities of entire galaxies and

their corresponding metallicity gradient. The study

will be using Marvin as a tool to extract and represent

data from the MaNGA survey.

This study intends to use the 12+log(O/H)

indicator to calculate the GP metallicity for SG’s,

using the O3N2 calibrator to eliminate the disruptive

effects of dust on the observed light (Boardman, et al.,

2023). Furthermore, the O3N2 calibrator has an

advantage over the N2 calibrator, as the latter tends to

be less accurate with IFU data as mentioned by

Marino et al., 2013 (Marino, et al., 2013). Hence, the

O3N2 calibrator will be utilized in combination with

the 12+log(O/H). The O3N2 calibrator described in

Ma2013 takes the value of

O3N2 = log (





















) (1)

and the 12+log(O/H) takes the value of

12 + log









= 8.533 − 0.214 × O3N2 (2)

This paper will not be taking into account the effect

of redshift. This is because, firstly, this study will

only take samples from regions of low redshift, at z =

0, that is, this paper will only account for galaxies at

a distance that is near to us. Hence, it will not result

in a high redshift. Thus, the effect of the redshift will

be minimal. Secondly, the research only desires to

acquire the shape of the metallicity distribution across

the radius of the SG, discovering the relative

distribution of metal elements. Thus, it is unnecessary

to determine specific metal elements. For further

calculations to be accomplished, the Sc types must be

selected first, which can be accomplished by

accessing the MaNGA visual morphology catalogue

(MVM-VAC). The Sc Type galaxies filtered out is

then inputted into a csv file by using the Pandas

library in Python. 20 Sc galaxies will be drawn

randomly from the 418 Sc galaxies that are included

in the MVM-VAC. The 20 Sc galaxies and their

corresponding data is visible in Table 1. Then, the

plate-ifu of the individual galaxies will be inputted

into Marvin, thus to acquire the metallicity data using

the aforementioned O3N2 calibrator. And after

investigations, due to the messy nature of

observational data, the 2D metallicity maps of the

SDSS-IV will not be utilized, instead, the metallicity

data will be plotted onto a graph with metallicity

against radius in kpc. Furthermore, it is also necessary

to obtain the radius, which can be easily done by the

following code found in the Marvin Documentation

(Cherinka, et al., 2019):

radius = 0.7*(galaxy.spx_ellcoo_r_kpc.value) (3)

The 0.7 is multiplied as the radius within the SDSS

survey is presented in the units of kpc/h, where h is

the dimensionless Hubble parameter(dHp). The h in

this paper will be taken as 0.7 as presented by a

review in 2013 (Croton, 2013). Multiplying the radius

by 0.7 will rid of the dHp thus returning a value in

kpc. Then, it is possible to plot the metallicity results

against the radius, returning a scatter plot showing the

general trend of the metallicity distribution.

Table 1: The 20 Sc galaxies filtered from MVM-VAC. All of these galaxies are randomly selected from 418 samples available

in the MVM-VAC. The galaxies are presented with their plate-ifu, the MangaID and their redshifts (Cherinka, et al., 2019).

name

lateifu MANGAID Redshift

man

a-7443-6101 7443-6101 12-84726 0.03091249

man

a-7443-6103 7443-6103 12-84665 0.01834222

manga-7443-9101 7443-9101 12-84660 0.0404705

manga-9871-3703 9871-3703 1-322258 0.018230092

man

a-9871-9101 9871-9101 1-321936 0.017267063

man

a-9872-12701 9872-12701 1-322161 0.018649809

man

a-9872-12702 9872-12702 1-322506 0.04083086

manga-9872-6102 9872-6102 1-322507 0.019473994

manga-9872-6104 9872-6104 1-322353 0.018495463

manga-9876-3703 9876-3703 1-456616 0.016713664

man

a-9891-12703 9891-12703 1-593748 0.01753549

man

a-9891-6102 9891-6102 1-373878 0.045699038

man

a-8145-12704 8145-12704 1-152587 0.023471711

manga-8146-12701 8146-12701 1-604839 0.02784799

manga-8147-12703 8147-12703 1-146028 0.026618272

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man

a-8149-12701 8149-12701 1-604930 0.042103108

manga-8150-3703 8150-3703 1-390130 0.09668134

manga-8154-12701 8154-12701 1-603920 0.03146515

man

a-8154-12703 8154-12703 1-37546 0.03965886

man

a-8154-12705 8154-12705 1-37547 0.028330915

4 RESULTS AND DISCUSSIONS

Firstly, one has to eliminate certain results from the

data selection, thus to be able to find a general trend

that governs metallicity distribution. There are two

sets of data that do not show any clear trends, that is,

8146-12701 and 8154-12703. The distribution of data

is very loose in these samples; thus, it is more difficult

to utilize this data and state any conclusions about the

gas-phase metallicity distribution of SG’s. Therefore,

these samples will not be considered during analysis,

as it will confound the results. These anomalies may

be due to the data from the SDSS as the ifu itself may

be damaged or of low quality.

The graphs are clearly separated into 2 parts, one,

the distance nearer to the centre of the galactic bulge,

which had less varied metallicity values. This

distance took up about half the entirety of each

sample. However, 8149-12701, 9891-6102, 9872-

12702, 8150-3703 and 8971-12702 showed a

different trend, having less of a region with smaller

dispersions in metallicity. These exceptions showed a

greater range of distribution in the GP metallicity of

galaxies. Furthermore, 9871-3703 also showed the

exception of having more of its region with GP

metallicity scattered across a smaller range of

metallicity values. These exceptions are likely due to

the properties of individual galaxies being different to

each other. This could potentially be explained by the

difference in morphology or size of the galaxies, as

some of the galaxies with metallicity being more

varied tend to also have a larger size, like 9872-12702.

However, the more intriguing result comes from

the general trend of scattering after a certain distance.

This could be explained by the loose spiral arms of

Sc-type galaxies. Therefore, the metallicity, after an

initial distance within the central bulge with a more

stable metallicity distribution, will tend to scatter as it

moves onto the spiral arms. Because, then, the

metallicity will be accounting for both the spiral arms

with a more compact mass and metal distribution, and

the region between the spiral arms with less luminous

matter, thus giving rise to the great variation in GP

metallicity after about one half the radius. Fig. 1 rom

the SDSS-IV data release illustrates the loose spiral

arms, and as one can see, the sample includes the

entirety of the galaxy, from the centre to the edge

(Cherinka, et al., 2019). Fig. 2 shows the scattering of

metallicity values after a certain distance.

Figure 1: The spiral Sc galaxy from the SDSS-IV survey,

plateifu = 8145-12704 (Cherinka, et al., 2019).

Figure 2: The spiral Sc galaxy from the SDSS-IV survey,

plateifu = 7443-6101. The metallicity value stars to scatter

above Radius = 2kpc (Photo/Picture credit: Original).

After providing an explanation to one trend

observed in the graphs, it is then possible to organize

the other samples into two groups: those with

Analysis of Metal Distribution in Sc Type Galaxies Using the SDSS-IV DR17 MaNGA Survey

249

decreasing or flat trends of metallicity, and those with

increasing metallicity. The majority of galaxies, of

about 12 galaxies, had a rather flat metallicity, with

very small amounts of fluctuations near the centre of

the galaxy. And two of the galaxies had an increase

and then abrupt decrease in metallicity. These are

expected results, as most SG’s do show either

decreasing or flat trends across its radius as a result of

inside-out growth. Similar results are present in Ju et

al. and furthermore, their results also included a

galaxy with an increasing then decreasing metallicity

trend (Ju et al., 2025). This is due to the inside-out

growth model as aforementioned. The inside-out

growth model enriches the centre with more metal

elements; because the model suggests that the centre

of the galaxy is where the galaxy begins growing,

meaning that the initial star formation occurs in the

centre, thus resulting in higher metallicity. The

smooth decreasing curve or flat curve is a result of the

later diffusion and spreading of metal elements after

the initial formation at the centre.

Table 2: the galaxies categorized with the trend of their

graphs.

Galax

Trend

7443-6101

Flat

7443-6103

Decrease after increase

7443-9101

Decrease after increase

9871-3703

Flat

9871-9101

Flat

9872-12701

Flat

9872-12702

Flat

9872-6102

Flat

9872-6104

Flat

9876-3703

Flat

9891-12703

Flat

9891-6102

Flat

8145-12704

Increase

8146-12701

Discarded

8147-12703

Flat

8149-12701

Flat

8150-3703

Increase

8154-12701

Increase

8154-12703

Discarded

8154-12705

Increase

The samples with the increasing metallicity as

radius increase demands different explanations as it

opposes the classic results from the inside-out growth

model. High redshift regions could result in a positive

metallicity gradient. However, the values in Table 2

indicate that most of the samples do not have a high

redshift. Only one galaxy 8150-3703 has a relatively

high redshift of 0.967, and simultaneously, its radius

and metallicity have a weak positive correlation,

rendering it the only galaxy that could be potentially

explained by the high redshift proposition. The other

galaxies mostly have lower redshifts below 0.5.

Therefore, it may be the issues with the data, or the

individual morphological characteristics of these Sc

normal spirals.

5 LIMITATIONS AND

PROSPECTS

It is no doubt that this paper has reached some results.

However, there were many issues and limitations

with the methodology and the data. Firstly, there were

flaws in the method. The author did not account for

issues with the data cubes, for instance, potential data

that were corrupted, or cannot be used, or lacks

validity. The paper can be improved if masks were to

be used in the Python code to decrease the number of

spaxels that contained unreliable data, thus increasing

the reliability and confidence with the final results.

Furthermore, this paper focused only on using the

oxygen abundance to derive the GP, which has been

shown by Fraser-McKelvie et al. in 2021 to be only a

rough estimate of the GP in a galaxy, as other

elements are also present in the ISM (Fraser-

McKelvie, et al., 2021). Potentially, in the future,

stellar metallicity should also be considered so to

acquire the overall metallicity of the entire galaxy,

giving new insights into the inside-out model, as the

inside-out model is proposed based upon GP

metallicity, examining it using a stellar metallicity

result might yield valuable results.

This field also has many limitations currently.

Due to the lack of better means of probing the

universe and the limitations in the technique, the data

sent from all-sky surveys still has uncertainties.

Surveys like such may lack details when probing

galaxies, hence limiting the current researches.

Furthermore, the existence of dust, nebulae and other

matter in the Milky Way can also impede further

inspections on extragalactic objects. Although there

are algorithms that can reduce noise and other sources

of uncertainty, there exists, still, a physical constraint

on further investigating objects at distant locations

like galaxies.

This field is still an active one. In the future, it is

also possible that the observation techniques improve.

SDSS is in fact starting to release their new SDSS-V,

making the data more reliable and more accurate,

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250

which can offer newer insights in the formation and

evolution of galaxies. Furthermore, more accurate

simulations, such as Illustris TNG and Thesan can

also be integrated with actual observations so to

further test the understanding of galaxies and the

universe. These simulations, in the future, could be

used to test the validity of galaxy formation theories,

if fed with more accurate results from observations.

The development of machine learning in the past few

years can also be used to analyse and interpret data

from surveys and simulations, providing more

solutions to issues like the price and time for

simulations. This can and will improve the results

from the field, making researches more fruitful.

6 CONCLUSIONS

In conclusion, this research has discussed the metal

distribution in normal Sc type galaxies by utilizing

the SDSS-IV DR17 MaNGA survey. The research

has concluded that most galaxies do follow a nearly

flat metallicity gradient, thus indicating the validity

of the inside-out growth model of galaxies, further

substantiating the theory. Furthermore, the data used

in the paper has also yielded some anomalous results,

showing 4 galaxies with a clear increasing trend and

a positive gradient, and most of which do not

necessarily have a satisfactory explanation, since only

one out of 4 has a redshift greater than 0.5. In the

future, this field still holds many potentials, as

machine learning develops and new technology arises.

The study of SG’s is capable of ridding of more

physical constraints in the near future. And, this field

also has great potential and significant meaning.

Integrating results from metallicity gradients can also

provide more insight into DM, for metallicity is a

very fundamental characteristic of galaxies and could

potentially have connections with DM, which plays a

significant role in spiral galaxies.

REFERENCES

Abdurro’uf, A., K., Aerts, C., Silva Aguirre, V., et al., 2022.

The seventeenth data release of the sloan digital sky

surveys: Complete release of Manga, MaStar, and

apogee-2 data. The Astrophysical Journal Supplement

Series, 259(2), 35.

Boardman, N., Wild, V., Heckman, T., Sanchez, S. F.,

Riffel, R., Riffel, R. A., Zasowski, G., 2023. Gas

metallicity distributions in SDSS-IV manga galaxies:

What drives gradients and local trends? Monthly

Notices of the Royal Astronomical Society, 520(3),

4301–4314.

Bundy, K., 2014. Manga: Mapping nearby galaxies at

apache point observatory. Proceedings of the

International Astronomical Union, 10(S311), 100–103.

Cherinka, B., Andrews, B. H., Sánchez-Gallego, J., et al.,

2019. Marvin: A tool kit for streamlined access and

visualization of the SDSS-IV manga data set. The

Astronomical Journal, 158(2), 74.

Croton, D. J., 2013. Damn you, little H! (or, real-world

applications of the Hubble constant using observed and

simulated data. Publications of the Astronomical

Society of Australia, 30.

Dobbs, C., Baba, J., 2014b Dawes Review 4: Spiral

structures in disc galaxies. Publications of the

Astronomical Society of Australia, 31.

Dory, N., MacDonald, N., Bershady, M. A., et al., 2015.

The manga integral field unit fiber feed system for the

sloan 2.5 m telescope. The Astronomical Journal,

149(2), 77.

Fraser-McKelvie, A., Cortese, L., Groves, B., et al., 2021.

The Sami Galaxy Survey: The drivers of gas and stellar

metallicity differences in Galaxies. Monthly Notices of

the Royal Astronomical Society, 510(1), 320–333.

Rubin, V. C., 1983. Dark matter in spiral galaxies. Scientific

American, 248(6), 96–108.

Rubin, V. C., Burstein, D., Ford, W. K., Thonnard, N., 1985.

Rotation velocities of 16 SA galaxies and a comparison

of SA, SB, and SC Rotation Properties. The

Astrophysical Journal, 289, 81.

Henry, R. B. C., Worthey, G., 1999. The distribution of

heavy elements in Spiral and elliptical galaxies.

Publications of the Astronomical Society of the Pacific,

111(762), 919–945.

Ju, M., Wang, X., Jones, T., Barišić, I., Nanayakkara, T.,

Bundy, K., Faucher-Giguère, C. A., Feng, S.,

Glazebrook, K., Henry, A., Malkan, M. A.,

Obreschkow, D., Roy, N., Sanders, R. L., Sun, X., Treu,

T., Zhou, Q., 2025. MSA-3D: Metallicity gradients in

galaxies at Z ∼ 1 with JWST/NIRSpec slit-stepping

spectroscopy. The Astrophysical Journal Letters, 978,

Khoram, A. H., Belfiore, F., 2025. Direct-method

metallicity gradients derived from spectral stacking

with SDSS-IV manga. Astronomy & Astrophysics, 693.

Kreckel, K., Ho, I. T., Blanc, G. A., et al., 2019. Mapping

metallicity variations across nearby Galaxy Disks. The

Astrophysical Journal, 887(1), 80.

Marino, R. A., Rosales-Ortega, F. F., Sánchez, S. F., et al.,

2013. The O3N2 and N2 abundance indicators

revisited- improved calibrations based on CALIFA and

Te-based literature data.

Astronomy & Astrophysics,

559.

Winter, A. J., Benisty, M., Andrews, S. M., 2024. Planet

formation regulated by Galactic-scale interstellar

turbulence. The Astrophysical Journal Letters, 972, 1.

Analysis of Metal Distribution in Sc Type Galaxies Using the SDSS-IV DR17 MaNGA Survey

251