rhessi10.wordpress/

1. http://rhessi10.wordpress.com/ Mon AM: opening plenary session Mon PM – Tue AM & Wed: working groups 1-6 Thu AM: concluding panel discussion Thu PM – Fri AM: Planning a New Flare/CME/SEP Mission

2. http://sprg.ssl.berkeley.edu/RHESSI/rhessiws_book/ - inspired and initiated from the 2007 RHESSI VII workshop in Santa Cruz, CA - contents being updated - will be published in 2011

3. Opening Plenary Session: OVERVIEW (Bob Lin)- operational > 8 yrs- Resolution and sensitivity restored to state in 2005 (via annealing the detector)- front segments even better than before lunch- April 2010 abnormally (shutdown)New Theory Questions:- simple thick-target model is inadequate (Brown)- Multi-island reconnection model (Drake)- Stochastic acceleration model (Petrosian & Chen; 2010 ApJL,712,L131)- Flare-CME connection (Temmer et al. 2010, ApJ,712,1410 on CME acc. and flare particle acc.) Microflares (cannot be source of corona heating outside AR) Quiet & Non-flaring Sun (Hannah et al.) Gamma-ray spectra (modeled up to 150 MeV; new line production code by Murphy 2009) RHESSI solar oblateness (total ~10.8; EUV excluded ~8; theory ~7.8) RHESSI+Hinode/SOT (Krucker 2010); RHESSI+Hinode/EIS (Milligan 2010)RHESSI+STEREO (Milligan 2010); RHESSI+FERMI/GBM & LAT

4. FUTURE:- 2013 NRC/NASA Decadal Survey (flares/CMEs/SEPs mission for 2023 maximum?)- ESA medium class mission proposal (2022 launch)- ESA/NASA Solar Obiter 2017-2018 launch- Solar Probe Plus (2018 launch) Plenary: Anneal & Radiation Damage (Smith)better image than before launch; detector 2 fixed; another anneal in ~1.5 years Plenary: Imaging and Software Status (Gordon Hurford)- Anna Massone / Michele Piana / Macro Prato:electron imaging inversion, uv_smoothing, deconvolution- Imaging: 1. regression provision in CLEAN; 2. electron mapping available; 3. visibility improvement- RHESSI calibration is time-dependent depending on radiation damage- risk: can only measure the first three moments of source distribution (flux, location, RMS size)- New directions: Bayesian statistics; tools for hypothesis rejection; visibility-based PIXON, CLEAN; Hybrid algorithm- Laszlo Etesi & Brian Dennis: Cloudy software (RHESSI Nugget 131)

5. How does everything come together? 5 TRACE 171 Å 14-Dec-2007 14:14:42 with RHESSI contours RHESSI 20-25keV clean image 14-Dec-2007 14:14:28 Hinode/EIS FE XV 284 Å 14-Dec-2007 14:13:41 with RHESSI contours László I. Etesi (1,5), Brian R. Dennis (2), Kim Tolbert (3), Dominic Zarro (4), Richard A. Schwartz (1), André Csillaghy (5) (1) The Catholic University of America; (2) NASA Goddard Space Flight Center(3) Wyle Information Systems, Inc.; (4) ADNET Systems, Inc.(5) University of Applied Sciences North-Western Switzerland PLOTMAN SHOW_SYNOP

6. High Energy Solar Physics data in Europe (HESPE) PI: Michele Piana- improved ancillary data (STEREO, Hinode, SDO, FERMI, radio [ELUA, CSRH, LoFAR, OVSA upgrade])- better understanding of calibration (time-dependent) UNEXPLORED:- high spatial resolution (grid 1 data)- high time-resolution (< 4s; e.g., two footpoints excited simultaneously?)- occultation for coronal source- comparison w/ microwave data (e.g., spatial location of small spikes)- question-motivated as opposed to event-initiated analysis Plenary: SDO (Prestel)- spectrum leakage between dopplergram (p-mode) & magnetogram turns out to be small- internal alignement registration: 1/10 pixel- SSW interface fetching data is recommended (AIA branch)- RHESSI synoptic interface Plenary: Radio & HXR signatures of electron acc. during solar flares (G. Mann) Plenary: A Multi-island Mechanism for Particle Acc. (J.F. Drake & M. Swisdak)

7. Concluding discussion: WG2 & WG5: Polarization, Albedo, Instrumental - testing datagap algorithm vs. count rate- standardizing pileup para. (forward-folding technique); influence on imgs; currently use Richard’s correction in OSPEX- Matching response matrix across attenuator state changes problem: low-energy excess (< 6 keV in A1&A3) measure resolution improvement with attenuator in- detector vs. detector area calibration for imging- rear grid scattering for imging- detector response with dead volume (front + rear)- improve line shape for severe tailing- implement offset (channel vs. energy) dependence on orbit & rate- pileup occurs most severely at twice the energy in count space- pile up img appears close to the thermal imgs (1) hessi_pileup_test.pro (2) OSPEX to see whether pileup switch makes diff.- Spectral signature of Albedo, peaks near 40-50 keV 6.5 keV  albedo iron line emission 6.7 keV  coronal iron line emission- Kontar: spatial signature of Albedo: brodens FP distribution; shifts FP location etc, but obs are not sensitive

8. Polarimetry:- provides measurement of angular distribution of HXR emitting electrons- can distinguish thermal & nonthermal component- ………………. Direct and albedo emission (Kontar)- ………………. Bremsstrahlung and inverse compton emissionsDirectivity:- direct measurement of the angular distribution of the emitted photon- longitudinal distribution of flares

10. I. Investigation the Neupert effect in the various intervals of solar flares II.Thermal and nonthermal energies in solar flares NING Zongjun Purple Mountain Observatory

11. Open question: 1. Does a Neupert-type (electron-beam heating) flare follow this effect during its lifetime? 2. How many nonthermal energies could efficiently transfer into the thermal energies which can be traced by observations?

12. Nuepert-type flare From the Neupert effect (SXR & HXR or MW), the thermal energy is expected to increase with time during the nonthermal energy input. Based on this concept, we explore the relation between thermal and nonthermal energies to test the Neupert effect at various intervals of flare.

13. Method Eth: thermal energy (erg) Pnth: nonthermal energy input (ergs-1) is the energy transfer rate

14. Thermal component: • parameters from HXR & SXR spectral fits: • - emission measure • - temperature • parameters from HXR imaging: • - thermal source area  thermal volume (direct) • - footpoint area • - footpoint separation • thermal energy: thermal volume (indirect) • Nonthermal component: • parameters from HXR spectral fits: • - total injected electron flux above low-energy cutoff • nonthermal energy:

15. 2003-11-13 flare TemperatureEMEthPnth Phase1 2 3

16. Correlation 右图单位有问题 2 3 Phase 1

17. 2004-11-04 flare TemperatureEMEthPnth Phase1 2 3

18. Corr. for other three flares

19. Three phases Phase 1: Neupert effect (heating dominant) Phase 2: Neupert effect(heating gt cooling) Phase 3: No (cooling dominant)

20. Summary 1 Ignoring the uncertainties to estimate the thermal and nonthermal energies: • 1. The Neupert-type flare does not hold this effect during its lifetime. (in Phases 1 and 2, not in phase 3). • 2. In Neupert-type flare,about 2-20% nonthermal energy can be efficiently transfered into thermal energy which is traced by the observations. (Ning & Cao 2010) Question: If the cooling effects (radiation + conduction) would be considered, does the Nuepert-type flare hold this effect in phase 3 as well?

21. 2005-09-13 flare T EM Eth Volume Pradiation Pconduction Index Lower Cutoff Pnth

22. How to estimate the cooling? T: temperatureEM: emission measureL: temperature scale length (~10-6 cm-1)(Fisher et al. 1990; Cargill et al .1995; Veronig et al. 2005; Aschwanden 2007)

23. Thermal energies • Eth:observational thermal energy • Erad:radiation loss energy • Econd:conduction loss energy • Etot = Eobs+Erad+Econd

24. Phase 3 Derivative of Etot Nonthermal input ResultsEtot =Eth+ Erad+ Econd Derivative of Eth

25. correlation

26. Summary 2 Consideration the radiation and conduction loss energies, 1, a high correlation is obtained between the derivative of total thermal energies (Eobs+Econd+Erad) and nonthermal energy input (Pnth) from start to end, indicating the Neupert effect in phase 3. • ~ 12% fraction of the known energy is efficiently and stable transferred into the thermal energy from start to end. (Ning et al. 2010, submitted)

27. Thanks! Welcome to Nanjing for 11th REHSSI workshop (2011)!

28. Energy partition in solar flares: Relationship with flare importance and consequences for particle acceleration Alexander Warmuth Astrophysikalisches Institut Potsdam

29. Thermal vs. nonthermal energy content • What is the energy partition (thermal vs. nonthermal) in solar flares? • How do these quantities change with flare importance? • Sources of errors, loss processes • Consequences of energy partition for • particle acceleration: • is it consistent with the standard flare picture?

30. Method • 23 flares (from C4.8 to X17.2) • time series of HXR spectral fits: 2028 spectral fits • - VTH + THICK • - corrected for albedo, gain offset & pile-up • spectral parameters • GOES fluxes: • EM & T of SXR-emitting plasma • time series of HXR images: 1521 images • - images at thermal energies: thermal areas • - images at nonthermal energies: • footpoint areas & separation • geometric parameters

31. Geometric parameters • imaging algorithms used: • CLEAN uniform weighting • CLEAN natural weighting • MEM_NJIT • VIS_FWD • area measurements: • CLEAN: gaussian fit to sources, FWHM, • quadratic subtraction of CLEAN beam • MEM_NJIT: gaussian fit to sources • VIS_FWD: area directly obtained from fit • volumes: • direct: • indirect:

32. Nonthermal component:duration vs. GOES peak flux

33. Dependence on GOES peak flux (direct, HXR)

34. Thermal vs. nonthermal total energies(ELC=20 keV)

35. Caveats: nonthermal component • masked low-energy cutoff: • flux & power only lower estimates •  study influence of varying ELC • validity of thick-target model: • keep track of consequences of improved • particle transport/interaction and radiation models • (may reduce power in nontherm. electrons) • contribution of nonthermal ions: • - poor constraints on low-energy ions • - in large events: energy in ions >2 MeV comparable to energy in nontherm. electrons

36. Caveats: thermal component • non-isothermality • abundances (Fe): • can be fitted • systematic errors in volume estimations • filling factor ( ) • kinetic & potential energy of plasma: •  conservative estimate: equipartition • radiative and conductive losses •  can be calculated/estimated

37. Energy losses of the thermal plasma • radiative losses: • after Cox & Tucker (1969) • conductive losses: • approximation by Veronig et al. (2005)

38. Radiative & conductive losses vs. nonthermal energy (ELC=20 keV)

39. Radiative & conductive losses vs. peak thermal energy (dir)

40. Energy losses of thermal plasma:results • radiative losses (hot plasma) comparable to • peak thermal energy • very high conductive losses • (~10 times peak thermal) • but: • simple model may not be applicable •  compare with total radiated energy

41. Observational evidence for high values of total radiated energy • SORCE TSI: Erad,tot=4x1032 erg in 2003 Oct 28 • (Kopp et al. 2004, Woods et al. 2004) •  Erad,tot~ 100 x Erad,SXR(Emslie et al. 2005) • SOHO/VIRGO: Erad,tot~ 100 x Erad,SXR (Kretzschmar et al. 2010)

42. High conductive losses consistent with total radiated energy

43. Conclusions • good correlation between thermal & nontherm. energies • strong radiative and conductive losses • consistent with total radiated energy (bolometric) • conduction could heat dense lower atmosphere • which then radiates primarily in UV & WL • possible consequences for energy release and particle acceleration: • - lower cutoff energy of nonthermal electrons • (down to 10 keV required) • - strong contribution of ions • - additional non-beam heating mechanism

44. Open questions / Things to do • contribution of (low-energy) ions • modifications to thick-target • consider multithermality • better treatment of conductive losses • consider time evolution