Understanding the Origin of Bright Features Carrie Swift – University of Michigan - Dearborn Philip A. Hughes – University of Michigan - Ann Arbor Extragalactic Jets | Theory and Observation from Radio to Gamma Ray May 24, 2007

Typical data set: 4-5 gigabytes per epoch of physical data. Sophisticated simulations of relativistic flows lead to large, complex data sets. Typical data set: 4-5 gigabytes per epoch of physical data. For time resolution similar to spatial resolution would require on the order of a terabyte of data to generate a simulated radio flux map. We want to know where and when in the flow’s history the bright radio features form. How do we find the needle in this very large haystack? Alta Meadow Ranch - Montana

Methodology Perform a relativistic hydrodynamic simulation. Generate simulated radio flux maps. Select lines of sight corresponding to features of interest and examine the physical conditions that led to the formation of the radio features.

1. Perform a relativistic hydrodynamic simulation. Simulation CF7 Fully Relativistic Three Dimensional Precessing inlet that leads to filamentary structures over time. v = 0.9798c 6 epochs – last run at time = 2.502e+03 Resulting data set is 14 gigabytes Philip Hughes

Angle of view 9º from direction of flow (within 1/γ) 2. Generate simulated radio flux maps. Angle of view 9º from direction of flow (within 1/γ) Time-delay: 6 epochs Static: last epoch Emissivity Model: Assume that the radiating particles are the result of shock-Fermi acceleration of the high energy tail of the particle distribution. The acceleration takes place in the region where the pressure is highest, so using pressure to model emissivity gives us a way to trace these particles.

3. Select lines of sight corresponding to features of interest and examine the physical conditions that led to the formation of the radio feature.

Computational space of hydrodynamic simulation Computational space of hydrodynamic simulation. Rendered variable is momentum of flow

Computational space of hydrodynamic simulation Computational space of hydrodynamic simulation. Rendered variable is momentum of flow Boundary between epochs

Computational space of hydrodynamic simulation Computational space of hydrodynamic simulation. Rendered variable is momentum of flow Contours represent flux on plane of sky

Computational space of hydrodynamic simulation Computational space of hydrodynamic simulation. Rendered variable is momentum of flow Line of sight 7760 Color corresponds to total flux as function of retarded time Contours represent flux on plane of sky

The flux of the line increases when it encounters pressure enhancements due to instabilities in the flow. Having an increase in the boost in the region of the instabilities results in a very bright line. Flux range 0 to 1.2 Boost range 0 to 1.4 Pressure range 0 to 1.2

The Effect of Angle of View and Differential Beaming on the Radio Morphology Within 1/γ Outside of 1/γ Map 7005 – no inlet 10755 lines Map 7004 – no inlet 3375 lines

Once outside the critical angle relativistic effects no longer dominate the radio morphology. Line 2537 Flux range 0 to 0.7 Boost range 0 to 1.2 Pressure range 0 to 1.0

Conclusions: This method’s highly visual nature allows for a straight forward analysis of radio features arising from a complex flow, leading to a better understanding of the relationship between the physical flow and the radio morphology of relativistic jets. Anne-Marie Mineur What’s Next? Improved time resolution Apply to variety of simulations