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Explore magnetic effects, phase changes, and more in helioseismic data processing for in-depth solar analysis. Discover new science using HMI and vector magnetograph combo with high-resolution flow maps. Develop innovative techniques like point spread function proxy for data deconvolution.
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Some Thoughts on HMI Data Products & Processing F. Hill Jan. 27, 2005
A personal view • Developed over last 2 days during sessions, lunches, chats, etc. • Synthesis of conversations with several attendees. • NSO/GONG has experience in several areas of helioseismology but they will not be evenly covered here. • Will mainly focus on rings, but not exclusively.
Magnetic effects on spectral line characteristics Shape changes Phase changes Travel times Non-simultaneous λ sampling Remapping, projections, tracking Large set of choices, all bad Adaptive strategy? Abandon altogether? Interpolation Vary with ρ? Recent work of de Forest Fitting Rings, peaks, ridges, etc. V & I? Leaks Background & asymmetry Inversions Which for rings? 1D, 2D, 3D, RLS, OLA? Better error estimates – correlated Depth-dependent trade-off parameter Display Q(x,y,z,t) VRML Just about every helioseismic processing step needs work!
Where’s the new science? • HMI is first helioseismology + vector magnetograph combination. • Subsurface flows and magnetic field geometry unexplored. • GONG + SOLIS provide good test bed. • Want continual synoptic flow maps and vector B maps
More new science • HMI resolution will allow study of subsurface flows closer to poles than before. • New highly-detailed flow maps will challenge AFD & dynamo theory. • Ultimate goals of activity prediction and now-casting. • Want on-demand custom tracking origin and extent. • VSO integration will leverage SDO return.
An idea from the half-bakery • Create the “Best” flow map by combining results from different techniques (global, rings, TD, holography). • Construct a “point spread function” proxy (PSFP) for each analysis. • PSFP is function of x, y, z, t, Δx, Δy, Δz, Δt. • “Deconvolve” PSFP from data – it’s the same sun. • Blind deconvolution assumes no a-priori knowledge. • Average results with some weights.
Develop using rings • Same analysis method, but different horizontal resolution as function of depth. • Use 3-D resolution kernels as first guess to PSFP. • Specter of mode beating may rise again for small-area short-time span patches. • Need resolution kernels as standard data product.
Another semi-pastry • Return of full raw data enables 4-D power spectra of solar atmosphere. • λ is a proxy for height in the atmosphere. • P(kx,ky,kz,ω) allows estimate of slowness surface, useful for MHD mode studies. • Major challenges: • Calibration from λ to z (RT) • Only 5 or 6 z points (limits accuracy) • Non-simultaneous sampling in λ (Fourier shift theorem)
Needed data products • Synoptic maps of subsurface flow • Quick-look available 24 hours after acquisition • Updated daily • sf (surface focusing) and ar (active region) products are OK as specified • Synoptic maps of B with identical specifications • Resolution kernels
Tentative Co-I Plans • Systematic projection comparison for rings • Attempt to combine rings with different resolutions • Extend study of magnetic field effects on observables • Improve fitting and inversions