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AI for Determining Chemical Abundances: New Opportunities & Future Ideas

Explore the use of AI in deducing chemical abundances in galaxies, HII regions, and nebulae. Discover indicators and calibrations for accurate metallicity determination and evolutionary history insights. Dive into innovative strategies for line ratios and dimensionless ratios analysis. Embrace the potential of AI to revolutionize abundance studies.

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AI for Determining Chemical Abundances: New Opportunities & Future Ideas

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  1. Using to Deduce Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es Sun M51 Rosette CNSFR

  2. Abundances: “1-slide summary” Abundances AI - A new opportunity n-D Calibrations Ideas for the future Gas Metallicity Z Evolutionary History of Galaxies Why? It’s determined by the star formation history Z =12+log(O/H) other elements (* based on Fe) Why? O+ and O++ and other ions emit prominent spectral emission lines Accurate Tgas Accurate Z (using nebular/auroral ratios xi,j) But N.B. ICFs & the Δt2-problem There are observational limits! Why? 1) General faintness of auroral lines 2) High redshift  fainter lines &line redshifting outside range (for z~0.5) 3) High Z Efficient cooling by Far-IR lines  suppression of CELs Theoretical /+ photoionisation models  Z=f(xi,j) Why?  DIAGNOSTICS for other objects with unknown Z Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  3. The IDEAL Indicator xi,j? Abundances AI - A new opportunity n-D Calibrations Ideas for the future Would be MONOTONIC with respect to metallicity Z Would be observationally detectable to high Z Would have low average dispersion (least-square error) Would span a W I D E range of Zwhen empirically-calibrated using REAL galaxy data & IF ALL THAT WENT PERFECTLY… Would be independent of chemical evolution and have physically-interpretable behaviour with Z Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  4. Indicators in “HII-like” regions Abundances AI - A new opportunity n-D Calibrations Ideas for the future Galactic HII-Regions Extra-Galactic HII-Regions HII Galaxies CNSFRs? Perez-Montero 2002 Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  5. AI: An opportunity Abundances AI - A new opportunity n-D Calibrations Ideas for the future Scale-Invariant Genetic Algorithm Network(SIGAN) Architecture Weights Node Functions Dimensional Analysis Taylor & Diaz 2006 Net DNA Ecoding Multi-Layer Perceptron + Genetic Operators Mutation Cross-over + Back-Propagation + Pruning Algorithm UNIVERSAL FUNCTION APPROXIMATOR Taylor 2005 103 ERROR REDUCTION Taylor 2005 EQUATIONS Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  6. A new strategy Abundances AI - A new opportunity n-D Calibrations Ideas for the future LINE RATIOS 1 Emission line fluxes 4 5 6 2 3 GA (Genetic Algorithm) DIAGNOSTICS About the sample Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  7. How it Works: e.g. Newton’s Law Abundances AI - A new opportunity n-D Calibrations Ideas for the future IDEAL SOLUTION Neural Node Functions m h3 Identities 1 Power Laws 1 a h3 h2 F Sigmoids Harmonic Functions e h3 PRUNED NODES Gaussian Constants inputs outputs Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  8. Newton’s Law: F=ma (EXACT) Abundances AI - A new opportunity n-D Calibrations Ideas for the future G=2 G=5 G=8 G=38 Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  9. Newton’s Law: F=ma (10% Errors) Abundances AI - A new opportunity n-D Calibrations Ideas for the future G=38 10% Errors G=780 G=995 G=161 Error Generation Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  10. “HII-like” Regions: HIIGs, GHIIRs & EGHIIRs Abundances AI - A new opportunity n-D Calibrations Ideas for the future log(S23) elog(S23) SIGAN h3 h2 eZ Z e h3 e-space Z (direct method) Vs S23 Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  11. “HII-like” Regions: First Results Abundances AI - A new opportunity n-D Calibrations Ideas for the future SIGAN offers a simple way to do fits  overcoming the the problem of “subjectivity” Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  12. Fitting & n-D Calibrations Abundances AI - A new opportunity n-D Calibrations Ideas for the future Dimensionless Line Ratios Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  13. Ideas for the Future Abundances AI - A new opportunity n-D Calibrations Ideas for the future To test & improve 1-D calibrations of the form: Z=af(x)+b using new data from SDSS RL4 HII-like regions To find new n-D indicators & improve calibrations of the form: Z=af(x1,x2…xn)+b for HII-like regions To look for new n-D indicators & calibrators for AGNs and PNs On behalf of myself and Angeles, I would like to thank Guille Hägele and Enrique Perez-Montero for kindly making some of the observational data available and also to Monica Cardaci for helpful discussions Many thanks Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  14. Evolutionary History of Z Abundances AI - A new opportunity n-D Calibrations Ideas for the future Tremonti et al 2005 Nagao et al 2004 Redshift 0 2.5 Edmunds 2005 Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  15. Δt2 & the O23 (R23) Indicator Abundances AI - A new opportunity n-D Calibrations Ideas for the future Baskin et al 2006 U=0.6 U=0.3 ORLs Transition Region CELs Bresolin 2006 Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  16. Observational Limits Abundances AI - A new opportunity n-D Calibrations Ideas for the future Z=12+log(O/H)=8.66±0.05 Asplund et al 2004 Commonly used auroral-to-nebular emission line ratios… Bresolin 2006 8m telescope observing limit Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  17. O23: The “standard” diagnostic Abundances AI - A new opportunity n-D Calibrations Ideas for the future Degeneracy Need another diagnostic to break it Sensitivity on p (p=ionisation parameter) Yin et al 2006 Correcting for p-effect Pilyugin & Thuan 2005 Pilyugin & Thuan 2005 Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  18. N2 & Sensitivity to reddening Abundances AI - A new opportunity n-D Calibrations Ideas for the future Liang et al 2006 De-reddened Reddened Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  19. Going INFRA-RED… Abundances AI - A new opportunity n-D Calibrations Ideas for the future Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  20. Training & Evaluation Data Abundances AI - A new opportunity n-D Calibrations Ideas for the future Exponential Space Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

  21. “HII-like” Regions: First Results Abundances AI - A new opportunity n-D Calibrations Ideas for the future Using AI to Deduce Chemical Abundances Mike Taylor & Angeles Diaz michael@damir.iem.csic.es

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