1. 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

2. 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

3. 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.

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

5. 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.

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

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

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

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

11. 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

12. 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

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

14. 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

15. 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