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Abstract

Highly dynamic solar eruptive activities occurring over the corona and transition region, triggered off by magnetic field reconnection, are the driving source of disastrous space weather, and the space imaging and spectroscopic measurements of solar eruptive activities are a key data source for accurate space weather forecasting. The He II 30.4 nm resonance line comes from the Lyman αtransition of singly ionized helium, which has an anomalous intensity, an order of magnitude higher than the intensities of other transition region lines. In this paper, we propose and design a two-dimensional spectroscopic tomographic imaging instrument operating at He II 30.4 nm wavelength to make up for the shortcomings of conventional solar extreme ultraviolet imager and imaging spectrometer, and adopt a slitless three-order (–1, 0, +1) simultaneous diffraction imaging configuration with a single snapshot to achieve two-dimensional spectroscopy instantaneous imaging with a large field of view. Owing to the confusion of spatial and spectral information of the three orders of images, the three-dimensional data cube I( x, y, λ) of the observed target is reconstructed using a spectral data inversion algorithm with a limited tomographic projection angle.

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Authors and contacts

Corresponding author:Li Lin,bit421@bit.edu.cn; Liu Yue,liuyue@bit.edu.cn

Funds:Project supported by the Strategic Pioneer Science and Technology Program of the Chinese Academy of Sciences (Grant No. XDA15018300)

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	参数	取值
Specifications	Spectral range/nm	29.4 — 31.4
	FOV/arcmin²	10 arcmin × 10 arcmin
	Spectral resolution/nm	0.003
	Spatial resolution/arcsec	0.42
	Line-of-sight velocity/(km·s^–1)	> 29.61
	System focal length/mm	6500
	Pixel size/μm	13
	Optical volume/mm³	1050 mm× 330 mm×60 mm
Telescope design	R_T/mm	1888.190
	Conic	–1
	Δ/mm	80
Spectral imaging system design	1/d₀/mm^–1	3200
	r_A/mm	150
	β	6.87^×
	i/(°)	5.56
	R/mm	263.514
	ρ/mm	259.940
	b₂	0.0938
	Ruling area/mm²	20 mm × 20 mm

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Smooth multiplicative algebraic reconstruction technique
1. Initial guess: $G(x, \lambda ) = {I_0}(x){I_\infty }(\lambda )/N$
2. Projection: $[{I'_{ - 1}}, {I'_0}, {I'_{ + 1}}, {I'_\infty }] = P[G]$
3. Correction: $\begin{aligned} G = G{\left[ {\frac{ { {I_{ - 1} }(x - \lambda )} }{ { { {I'}_{ - 1} }(x - \lambda )} } } \right]^\gamma }{\left[ {\frac{ { {I_0}(x)} }{ { { {I'}_0}(x)} } } \right]^\gamma }\\ \times{\left[ {\frac{ { {I_{ + 1} }(x + \lambda )} }{ { { {I'}_{ + 1} }(x + \lambda )} } } \right]^\gamma }{\left[ {\frac{ { {I_\infty }(\lambda )} }{ { { {I'}_\infty }(\lambda )} } } \right]^\gamma }\end{aligned}$
4. Smoothing: $G = G \otimes \displaystyle\frac{1}{ {1 + 2 t + 2 s} }\left[ {\begin{array}{*{20}{c} } 0& t & 0 \\ s& 1 & s \\ 0& t & 0 \end{array} } \right]$
5. Reprojection: $[{I'_{ - 1}}, {I'_0}, {I'_{ + 1}}, {I'_\infty }] = P[G]$
6. Evaluate goodness of fit: $\chi _m^2 = 1 + \displaystyle\sum\limits_{x, y} \dfrac{(I'_m - I_m)^2}{N}$
7. Adjust smoothing parameters: $t = \dfrac{t}{\chi _{ - 1}^2\chi _{ + 1}^2},~~ s = \dfrac{s}{\chi _0^2}$
8. Loop to step 3

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Quantized indicators	τ	k	δ_RMS
Parametric inversion	0.862	0.668	0.294

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Vol. 71, Issue 15 - 2022-08-05

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