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Exploring Astrochemical Models: Understanding the Universe's Beauty and Complexity

Discover the importance and intricacies of astrochemical models, from their flexibility to input and output parameters, and the need for experimental data. Learn how these models calculate density, temperature, chemical rates, and abundances over time and space, guiding us in understanding the chemical richness and diversity of astronomical objects.

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Exploring Astrochemical Models: Understanding the Universe's Beauty and Complexity

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  1. Inside a typical astrochemical model Serena Viti IFSI-CNR (Rome)

  2. Preview • Why bother with astrochemical models • A tour inside one • Its ‘beauties’ and ‘horrors’ • How to use it • Improvements

  3. Why astrochemistry? • The universe is chemically rich • There is a large degree of diversity in a variety of interstellar and circumstellar regions • There is a large degree of diversity in the same region as a function of time

  4. Why do we need astrochemical models? • To represent the chemical and physical behaviour of astronomical objects • To interpret astronomical data • To test astronomical and chemical ideas • To estimate chemical abundances of the ISM, taking into account most of the chemical and dynamical processes affecting the gas and dust.

  5. Needs of an astrochemical model • Flexibility: • Time dependent/Time independent • Depth dependent/Single Point • Gas-grain/Gas chemistry • Static/Dynamic • Modularity • Easy to implement new experimental and theoretical input data

  6. Inside a chemical model: examples of input parameters • Initial elemental abundances • Initial temperature • Initial density • Size • Radiation field • Cosmic ray ionization rate • Dynamical ‘switches’ • Chemical species and rate file • Degree of depletion

  7. What does a model do? • Calculates density profiles as a fn of time and space • Calculates temperature structure as a fn of time and space • Calculates chemical rates for all relevant reactions • Calculates fractional abudances (gas-phase and solid by taking into account feeze out and desorption)

  8. Inside a chemical model: examples of output parameters • Chemical abundances as a fn of time and space • How the density varies with time and space • Thermal balance • Visual Extinction • Radiation field as a fn of time and space

  9. s p a c e S p a c e Time

  10. What needs to be done • Form the dense clumps (gradient of densities) • This involves: depletion, surface reactions • Account for the UV field from the source (time and space dependent) • Account for X-ray emission

  11. Example of output HCO+ abundance as a fn of time at Av ~ 3 mags

  12. Its ‘beauties’ • Very flexible because “ab initio” • Free to include as many species and reactions as we want/need • Time-dependent • Fast

  13. Its ‘horrors’ (too many to list all) • Degree of freedom may be as many as the no of reactions • Many rate coefficients are not experimental and/or have a large error bar • Rates for surface reactions missing • Surface reactions missing! • … • …

  14. What we still need: • Experimentally: • Branching ratios • Sticking probabilites • Mobilities of adsorbed species • Hydrogenation on grain surfaces • Desorption

  15. Laboratory Data  Time and depth dependentChemical Models Observations (high spectral and spatial resolution)

  16. Conclusions • Close interaction between models, observations and chemical data • Full coupling of chemistry with hydrodynamics and radiative transfer Investigate a larger parameter space

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