JINA Horizons 2020 – Robert Izzard 1

How did the stars get there?How do the stars function?Why so many stars of each type?What are the stars going to do?

Stellar Population Synthesis

Stellar Population Synthesis

Robert IzzardRobert IzzardUniversity of SurreyUniversity of Surrey

UKUK

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The era of big and bigger data● Now: Gaia/ESO, Kepler,

SDSS (APOGEE etc)● Now/soon:

– Gaia DR3, LIGO, … – More NS/BH mergers– LSST, TESS, SKA, LISA – … many more to come.

● How can we use this data?

(Graph is not necessarily to scale)

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Stellar AccountancyLet’s count stars – in a PC

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Star formation rate

Simplest approximation: S = const → count number ratios and S cancels

Dolphin+2005

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Stellar birth function

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Single stars : vary M

Initial mass / M¯

5 15 25 35 45 55 65 75 85 955

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Initial primary mass M1

Initial secondary mass M2

Initial orbit (period or separation)

Binary stars

● Single, binary, triple, quadruples...e.g. Moe and di Stefano (2017)

● f(metallicity) and location?

Image by Sophie Dykes based on Moe’s data

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Stellar evolutiond is: 1 if in the evolutionary phase of interest

0 otherwise

So, in theory, you “just” need a stellar evolution code...

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The parameter-space problem● Input parameter space is already large:

metallicity, M1,2,3,4, a1,2,3, e1,2,3, i1,2,3, vrot1,2,3,4… and distributions of the above are often poorly known.

● But even given these, still many parameters:mass-loss rates, mixing in stars, reaction rates,mass-transfer efficiency, common-envelope evolution, stellar mergers, supernova kicks, …..

● Desired objects are often rare → requires high resolutione.g. NS/BH-NS/BH mergers.

● Stellar evolution codes are not that fast, may not model all stars … and tend to “crash”.

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● Offload ~detached (“well-understood”) stellar evolution→ “Synthetic” stellar evolution codesGoals are:

● Fast enough – grid or analytic function fits can replace relatively-slow, repeated, highly detailed calculations

● Accurate enough: “good enough for government work” ~5%● Single stars + stellar interactions for binary

● Public/open source codes + datareally help! (e.g. MESA)

Code summary: De Marco & Izzard (2017) Table 2

1,000,000+ binary stars easily 24hr≲

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● “Synthetic” stellar evolution codes– SSE/BSE based: BSE (Hurley), binary_c (Izzard), startrack (Belczynski),

biseps (Kolb), Seba (Nelemans,Toonen) (SSE++), MSE (Hamers+), COMPAS, etc.– Others: Ibis (Tutukov), Scenario machine (Lipunov), Brussels,

COMBINE (Kruckow), BPASS (Eldridge+Stanway) ● Hybrid codes

– BSE + NBODY6 (Aarseth, Hurley) also MOCCA (Giersz), MSE (Giersz+)– BSE + STARS (Church), BSE + MESA (Chen+ 2014)

Code summary: De Marco & Izzard (2017, arXiv 1611.03542) Table 2Try binary_c now: http://personal.ph.surrey.ac.uk/~ri0005/binary_c.html

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Predictions: numbers and rates

Image: Sophie Dykes (BSc student) using binary_c

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Predictions: chemical yieldsM

ass l

oss r

ate

of 12

C

binary_c solar metallicity starburst

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Predictions vs obs: ratesTy

pe Ia

SN

rate

Claeys et al. (2014)

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Predictions vs obs.: chemistry

Synthetic population of old, Milky Way bulge stars → these are old and should all have M

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Given L, Teff and g, what is M?

Best model fit:Torres et al. (2010) V3903 Sgr A:

http://www.astro.uni-bonn.de/stars/bonnsai/ Schneider et al. (2014)

Obs. vs theory: Bayesian methods

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Bayes for populations

Stevenson et al. (2017)

e.g. BHBH mergers → Preferred population parameters based on Bayseian likelihoods / posteriors.

The way forward!

● But hard with many parameters

● Can use expertise/toolsfrom other fieldse.g. nuclear physics

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Predicting what is observable

Evans+2020 (arxiv 2006.00849)

Hypervelocity stars: can they be from binaries?

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Nova progenitor properties

Alex Kemp et al. (2020)

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“You can get what you want”● Fallacy: we have good, modern constraints● Errors may be “big”

– But that’s just honesty– Many same uncertainties in all stellar ev.– Most parameters “do not matter”

● Do need to take care– Parameter spaces poorly resolved by models

e.g. common-envelope evolution chemical yields e.g. NSNS, (super)novae

– Only as good as input models: extrapolation dangers!→ Don’t use popsyn models as black boxes! ←

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Population synthesis is a valuable tool that links stellar/nuclear astro to observations through statistics.

Can constrain many parameters and combinations thereof, make quantified predictions, solve some problems, ….. yet many remain.

Needs: ● Stellar evolution data (hence nuclear physics)● Stellar interaction models● Input distributions (observational astro.)● Observational selection effects● Statistics toolchains

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