Can Reconnection Heat the Solar Corona?

Can Reconnection Heat the Solar Corona?

Nanoflare Properties in the Solar Corona Nicholeen Viall, (NASA/GSFC) With thanks to Stephen Bradshaw (Rice University), James Klimchuk (NASA/GSFC), ISSI Coronal Heating Team, Coronal Loops Workshops We thank the SDO/AIA team for the use of these data. This research was supported by a NASA Heliophysics GI. What are the Properties of Coronal Heating on the Sun? Nanoflare Impulsive burst of energy (Klimchuk 2006)

We can get information on the recurrence time of energy release from the thermal evolution in SDO/AIA emission We find that the observations are best reproduced with heating that recurs every ~ 2000s per flux tube, where there is a distribution of energies and recurrence times We address question with SDO/AIA timelag technique can be applied to any multi-wavelength data

The details of the timing of energy release on a given flux tube have observable thermal consequences Coronal Plasma Evolution Temperature SDO/AIA Light Curves 335 , ~ 3 MK 211 , ~ 2 MK 335 211 193 94 171 131 131 , ~0.5 MK Density

Viall & Klimchuk 2011 Impulsive heating: only see cooling phase Cross Correlation = Cooling Time t, Time Lag between t, Time Lag between 335 and 211 Viall & Klimchuk 2011 SDO/AIA light curves predicted with nanoflare model (EBTEL)

Cooling time from 335 (~3 MK) to 211 (~2 MK) -1000 -500 0 500 1000 Time Offset (s) Automatically detect post-nanoflare cooling (and other heating forms) Cross correlate two wavelengths (temperatures) at different temporal offsets: peak cross correlation = time lag between light curves

Time Lag Map Shows Post-nanoflare Cooling SDO/AIA 171 (~3 MK-~2 MK) 0.8 MK Apply test on pixel-by-pixel basis to 12-hr timeseries AR core is almost exclusively positive time lags AR outside core has zero time lag in moss/transition region (Viall & Klimchuk 2014) Positive time and in fan loop due to flows (Viall & Klimchuk Negative time

zero time delay: lags: post2016) lags: slow transition nanoflare cooling Not just at a few discrete loops ; rather, entire AR heating region/moss core nanoflares, including the diffuse emission Partial cooling between loops Self consistent picture in other 14 pairs of Viall & Klimchuk 2012 channels (6 channels 15 pairs) We Test Four Simple Models for Nanoflare Recurrence Time on a Given Flux Tube:

1) >10,000 s recurrence time for energy release on a given flux tube (aka low frequency heating) 2) ~2000 s recurrence time for energy release on a single flux tube; power law distribution (Hudson 1991), recurrence time energy (Cargill 2014) 3) ~500 s recurrence time for energy release on a single flux tube; power law distribution (Hudson 1991), recurrence time energy (Cargill 2014) 4) <500 s regular and continuous (aka steady heating) Reep et al. 2013

Cooling times longer than 500 seconds are typically observed (~3 MK-~2 MK) Viall & Klimchuk 2012 Cooling times of greater than 500s are observed, precluding such rapid energy bursts. 1) >10,000 s recurrence time for energy release on a single flux tube 2) ~2000 s recurrence time for energy release on a single flux tube; power law distribution (Hudson 1991), recurrence time energy (Cargill 2014)

3) ~500 s recurrence time for energy release on a single flux tube; power law distribution (Hudson 1991), recurrence time energy (Cargill 2014) 4) <500 s regular and continuous (aka steady heating) Reep et al. 2013 Hydrad Model of an Active Region Bradshaw & Viall 2016 PFSS to get distribution of flux tube lengths Build model of AR populating each of 400 field lines with a

unique Hydrad flux tube result Hydrad is a 1-D hydrodynamic model of plasma evolution Built 3 different ARs to test nanoflare recurrence times AR model; distribution of nanoflares ~2000s avg 335 211 171 131 Time lag maps of all three experiments show

post-nanoflare cooling 10000 s 2000 s 500 s 2-hr 12-hr Bradshaw & Viall 2016 Observed timelag maps show only full cooling in some

flux tubes, unlike the 10,000s model 10000 s Bradshaw & Viall 2016 2000 s 500 s 2-hr 12-hr Full cooling observed only occasionally (DEM analyses also provide evidence against #1)

1) >10,000 s recurrence time for energy release on a single flux tube 2) ~2000 s recurrence time for energy release on a single flux tube; power law distribution (Hudson 1991), recurrence time energy (Cargill 2014) 3) ~500 s recurrence time for energy release on a single flux tube; power law distribution (Hudson 1991), recurrence time energy (Cargill 2014) 4) <500 s regular and continuous (aka steady heating) Reep et al. 2013

Time lag maps allow statistical comparison; 2000 s distribution matches closest Bradshaw & Viall 2016 1) >10,000 s recurrence time for energy release on a single flux tube 2) ~2000 s recurrence time for energy release on a single flux tube; power law distribution (Hudson 1991), recurrence time energy (Cargill 2014) 3) ~500 s recurrence time for energy release on a single flux tube; power

law distribution (Hudson 1991), recurrence time energy (Cargill 2014) 4) <500 s regular and continuous (aka steady heating) Reep et al. 2013 Bursts of Energy Recur Every ~2000s in AR; Distribution is Required Burst of energy We can rule out regular/continuous steady heating, i.e. recurrence times of <500s. We can rule out low frequency heating, i.e. recurrence times >10,000s. Power law distribution of recurrence times, and recurrence times dependent on energy deposition (consistent with DEM observations, Cargill 2014) with an average

recurrence time of ~2000s on a flux tube best reproduces time lag AR maps Distribution is key to simultaneously explaining presence of both partial and full cooling that is observed: sometimes full cooling between energy bursts followed by short intervals of steady Remaining Questions Distribution with ~2000 s is typical for this AR; we need to compare the model with our measurements of other ARs; we need to model QS and compare to our QS measurements We have narrowed parameter space substantially, but still havent determined precise physics of coronal heating

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