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12 results for “chromosphere”
Supporting Information for Publication "Multi-band study of a bi-directional jet occurred in the upper chromosphere"
<p>This supporting information provides three observational movies from SDO/AIA, SDO/HMI, and IRIS. The evolution of the jet and the evolution of the line-of-sight magnetograms in the corresponding region can be tracked in these movies. The caption of each movie is included in 'AGUSupporting-Information_Movie.pdf'.</p>
Stellar chromospheric activity database of solar-like stars based on the Ca II H and K lines of LAMOST Low-Resolution Spectroscopic Survey: the bolometric and photospheric calibration
<p>This database contains the stellar chromospheric activity parameters of solar-like stars based on the Ca II H and K lines from the spectra of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). We extract 1,122,495 LRS spectra of solar-like stars from the LAMOST Data Release 8 v2.0 and provide the chromospheric activity parameters $S_{\rm tri}$, $S_{\rm MWO}$, $R_{\rm HK}$ and $R'_{\rm HK}$, as well as their uncertainties in the database. $R_{\rm HK}$ and $R'_{\rm HK}$ are derived from the method in the classic literature (denoted with classic) and the method based on the PHOENIX model (denoted with PHOENIX). These stellar chromospheric activity indexes and their uncertainties, along with the relevant spectroscopic parameters from the LAMOST catalogs, are saved in a CSV-format file (name: CaIIHK_Activity_Indexes_LAMOST_DR8_LRS.csv).</p> <p> </p> <p>Columns in the catalog of the database:</p> <p>obsid - Unique observation identifier of LAMOST LRS spectrum</p> <p>obsdate-Spectral observation date</p> <p>fitsname - FITS file name of LAMOST LRS spectrum</p> <p>snrg - Signal-to-noise ratio in the $g$ band ($\mathrm{S/N}_g$) of LAMOST LRS spectrum</p> <p>snrr - Signal-to-noise ratio in the $r$ band ($\mathrm{S/N}_r$) of LAMOST LRS spectrum</p> <p>teff - Effective temperature ($T_\mathrm{eff}$) derived from the LASP (unit: K)</p> <p>teff_err - Uncertainty of $T_\mathrm{eff}$ derived from the LASP (unit: K)</p> <p>logg - Surface gravity ($\log\,g$) derived from the LASP (unit: dex)</p> <p>logg_err - Uncertainty of $\log\,g$ derived from the LASP (unit: dex)</p> <p>feh - Metallicity ([Fe/H]) derived from the LASP (unit: dex)</p> <p>feh_err - Uncertainty of [Fe/H] derived from the LASP (unit: dex)</p> <p>rv - Radial velocity ($V_r$) derived from the LASP (unit: km/s)</p> <p>rv_err - Uncertainty of $V_r$ derived from the LASP (unit: km/s)</p> <p>ra_obs - Right ascension (RA) of fiber pointing (unit: degree)</p> <p>dec_obs - Declination (DEC) of fiber pointing (unit: degree) </p> <p>gaia_source_id - Source identifier in Gaia DR3 catalog</p> <p>gaia_g_mean_mag - $G$ magnitude in Gaia DR3 catalog</p> <p>S_tri* - $S_{\rm tri}$ index of LAMOST LRS </p> <p>S_tri_err* - Uncertainty of $S_{\rm tri}$ </p> <p>S_MWO* - $S_{\rm MWO}$ </p> <p>S_MWO_err* - Uncertainty of $S_{\rm MWO}$ </p> <p>log_R_HK_classic* - $\log\,R_{\rm HK,classic}$ </p> <p>log_R_HK_classic_err* - Uncertainty of $\log\,R_{\rm HK,classic}$ </p> <p>log_R_p_HK_classic* - $\log\,R'_{\rm HK,classic}$ </p> <p>log_R_p_HK_classic_err* - Uncertainty of $\log\,R'_{\rm HK,classic}$ </p> <p>log_R_HK_PHOENIX* - $\log\,R_{\rm HK,PHOENIX}$ </p> <p>log_R_HK_PHOENIX_err* - Uncertainty of $\log\,R_{\rm HK,PHOENIX}$ </p> <p>log_R_p_HK_PHOENIX* - $\log\,R'_{\rm HK,PHOENIX}$ </p> <p>log_R_p_HK_PHOENIX_err* - Uncertainty of $\log\,R'_{\rm HK,PHOENIX}$ </p> <p>(Note: The columns denoted by an asterisk represent the parameters provided by this database, and the remaining columns are collected from the data release of LAMOST DR8 V2.0. If the values are not available, they will be filled with '-9999' in this database.)</p>
Dataset of hydrogen Balmer line indexes for stellar chromospheric activity of solar-like stars based on the LAMOST spectroscopic surveys
<p><span>This dataset consists of three catalogs of the data of the hydrogen Balmer line indexes of solar-like stars for stellar chromospheric activity based on the LAMOST Low-Resolution Spectroscopic Survey (LRS) and Medium-Resolution Spectroscopic Survey (MRS): (1) LRS spectral catalog, (2) MRS spectral catalog, and (3) stellar source catalog. These catalogs are stored as three CSV-format data files. The columns contained in the catalogs are described below. The observational and spectroscopic parameters of the spectral samples in the dataset are from LAMOST DR9 v2.0. Unavailable values in the dataset are marked as −9999.0.</span></p> <p><span> </span></p> <p><span>(1) LRS spectral catalog (Balmer_line_indexes_LRS_spectral_catalog_LAMOST_DR9.csv)</span></p> <p><span>obsid - unique LAMOST observation identifier of LRS</span></p> <p><span>obsdate - date of LRS observation (UTC)</span></p> <p><span>uid - unique LAMOST source identifier</span></p> <p><span>ra - right ascension of stellar source in LRS catalog (unit: degree)</span></p> <p><span>dec - declination of stellar source in LRS catalog (unit: degree)</span></p> <p><span>sn_g - LRS g-band signal-to-noise ratio</span></p> <p><span>sn_r - LRS r-band signal-to-noise ratio</span></p> <p><span>teff - stellar effective temperature determined from LRS data (unit: K)</span></p> <p><span>teff_err - uncertainty of teff (unit: K)</span></p> <p><span>logg - stellar surface gravity determined from LRS data (unit: dex)</span></p> <p><span>logg_err - uncertainty of logg (unit: dex)</span></p> <p><span>feh - stellar metallicity determined from LRS data (unit: dex)</span></p> <p><span>feh_err - uncertainty of feh (unit: dex)</span></p> <p><span>rv - radial velocity determined from LRS data (unit: km/s)</span></p> <p><span>rv_err - uncertainty of rv (unit: km/s)</span></p> <p><span>L_halpha - Hα activity index of LRS data</span></p> <p><span>L_halpha_err - uncertainty of L_halpha</span></p> <p><span>L_hbeta - Hβ activity index of LRS data</span></p> <p><span>L_hbeta_err - uncertainty of L_hbeta</span></p> <p><span>L_hgamma - Hγ activity index of LRS data</span></p> <p><span>L_hgamma_err - uncertainty of L_hgamma</span></p> <p><span>L_hdelta - Hδ activity index of LRS data</span></p> <p><span>L_hdelta_err - uncertainty of L_hdelta</span></p> <p><span> </span></p> <p><span>(2) MRS spectral catalog (Balmer_line_indexes_MRS_spectral_catalog_LAMOST_DR9.csv)</span></p> <p><span>obsid - unique LAMOST observation identifier of MRS</span></p> <p><span>obsdate - date of MRS observation (UTC)</span></p> <p><span>uid - unique LAMOST source identifier</span></p> <p><span>ra - right ascension of stellar source in MRS catalog (unit: degree)</span></p> <p><span>dec - declination of stellar source in MRS catalog (unit: degree)</span></p> <p><span>sn_B - MRS blue-band signal-to-noise ratio</span></p> <p><span>sn_R - MRS red-band signal-to-noise ratio</span></p> <p><span>teff - stellar effective temperature determined from MRS data (unit: K)</span></p> <p><span>teff_err - uncertainty of teff (unit: K)</span></p> <p><span>logg - stellar surface gravity determined from MRS data (unit: dex)</span></p> <p><span>logg_err - uncertainty of logg (unit: dex)</span></p> <p><span>feh - stellar metallicity determined from MRS data (unit: dex)</span></p> <p><span>feh_err - uncertainty of feh (unit: dex)</span></p> <p><span>rv_r0 - radial velocity determined from the red band data of MRS (unit: km/s)</span></p> <p><span>rv_r0_err - uncertainty of rv_r0 (unit: km/s)</span></p> <p><span>M_halpha – Hα activity index of MRS data</span></p> <p><span>M_halpha_err - uncertainty of M_halpha</span></p> <p><span> </span></p> <p><span>(3) stellar source catalog (Balmer_line_indexes_stellar_source_catalog_LAMOST_DR9.csv)</span></p> <p><span>uid - unique LAMOST source identifier</span></p> <p><span>ra - right ascension of stellar source from LRS catalog (unit: degree)</span></p> <p><span>dec - declination of stellar source from LRS catalog (unit: degree)</span></p> <p><span>teff - stellar effective temperature from LRS catalog (unit: K)</span></p> <p><span>teff_err - uncertainty of teff (unit: K)</span></p> <p><span>logg - stellar surface gravity from LRS catalog (unit: dex)</span></p> <p><span>logg_err - uncertainty of logg (unit: dex)</span></p> <p><span>feh - stellar metallicity from LRS catalog (unit: dex)</span></p> <p><span>feh_err - uncertainty of feh (unit: dex)</span></p> <p><span>L_halpha - Hα activity index of LRS data</span></p> <p><span>L_halpha_err - uncertainty of L_halpha</span></p> <p><span>L_hbeta - Hβ activity index of LRS data</span></p> <p><span>L_hbeta_err - uncertainty of L_hbeta</span></p> <p><span>L_hgamma - Hγ activity index of LRS data</span></p> <p><span>L_hgamma_err - uncertainty of L_hgamma</span></p> <p><span>L_hdelta - Hδ activity index of LRS data</span></p> <p><span>L_hdelta_err - uncertainty of L_hdelta</span></p> <p><span>M_halpha - Hα activity index of MRS data</span></p> <p><span>M_halpha_err - uncertainty of M_halpha</span></p> <p><span>l_halpha - Hα absolute flux index of LRS data (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>l_halpha_err - uncertainty of l_halpha (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>l_hbeta - Hβ absolute flux index of LRS data (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>l_hbeta_err - uncertainty of l_hbeta (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>l_hgamma - Hγ absolute flux index of LRS data (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>l_hgamma_err - uncertainty of l_hgamma (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>l_hdelta - Hδ absolute flux index of LRS data (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>l_hdelta_err - uncertainty of l_hdelta (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>m_halpha</span><span> - Hα absolute flux index of MRS data (unit: 1/</span><span>Å</span><span>)</span></p> <p><span>m_halpha_err - uncertainty of m_halpha (unit: 1/</span><span>Å</span><span>)</span></p> <p><span> </span></p> <p><span> </span></p>
Stellar chromospheric activity spectral database of solar-type stars based on the LAMOST Low-Resolution Spectroscopic Survey(disused)
<p>A stellar chromospheric activity spectral database of solar-type stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains 1,330,654 high-quality LRS spectra of solar-type stars with <em>T</em><sub>eff</sub> ranging from 4800 K to 6800 K. We measure the mean fluxes at line cores of the Ca II H&K lines using a 1 Å rectangular bandpass as well as a 1.09 Å full width at half maximum (FWHM) triangular bandpass, and the mean fluxes of two 20 Å pseudo-continuum bands on the two sides of the lines. Three chromospheric activity indexes, <em>S</em><sub>rec</sub> using the rectangular bandpass, and <em>S</em><sub>tri</sub> and <em>S</em><sub>MWL</sub> using the triangular bandpass, are evaluated based on the measured fluxes. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H&K lines for all the spectra in the database. This database with more than one million high-quality LAMOST LRS spectra and basal chromospheric activity parameters can be further used for investigating activity characteristics of solar-type stars and solar-stellar connection.</p> <p> </p> <p>The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams.</p> <p>(1) Catalog of Spectral Sample and Activity Parameters<br> CaIIHK_Sindex_LAMOST_DR7_LRS.csv</p> <p>(2) Library of Spectrum Diagrams<br> spectrum_diagrams_000-049.zip (46 subfolders)<br> spectrum_diagrams_050-099.zip (40 subfolders)<br> spectrum_diagrams_100-149.zip (47 subfolders)<br> spectrum_diagrams_150-199.zip (49 subfolders)<br> spectrum_diagrams_200-249.zip (47 subfolders)<br> spectrum_diagrams_250-299.zip (45 subfolders)<br> spectrum_diagrams_300-349.zip (41 subfolders)<br> spectrum_diagrams_350-399.zip (39 subfolders)<br> spectrum_diagrams_400-449.zip (45 subfolders)<br> spectrum_diagrams_450-499.zip (35 subfolders)<br> spectrum_diagrams_500-549.zip (27 subfolders)<br> spectrum_diagrams_550-599.zip (38 subfolders)<br> spectrum_diagrams_600-649.zip (32 subfolders)<br> spectrum_diagrams_650-699.zip (26 subfolders)<br> spectrum_diagrams_700-749.zip (28 subfolders)</p> <p> </p>
Stellar chromospheric activity spectral database of solar-type stars based on the LAMOST Low-Resolution Spectroscopic Survey (disused)
<p>A stellar chromospheric activity spectral database of solar-type stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains 1,330,654 high-quality LRS spectra of solar-type stars with effective temperature ranging from 4800 K to 6800 K. We measure the mean fluxes at line cores of the Ca II H&K lines using a 1 Å rectangular bandpass as well as a 1.09 Å full width at half maximum (FWHM) triangular bandpass, and the mean fluxes of two 20 Å pseudo-continuum bands on the two sides of the lines. Three chromospheric activity indexes, <em>S</em><sub>rec</sub> based on the 1 Å rectangular bandpass, and <em>S</em><sub>tri</sub> and <em>S</em><sub>MWL</sub> based on the 1.09 Å FWHM triangular bandpass, are evaluated from the measured fluxes. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H&K lines for all the spectra in the database. This database with more than one million high-quality LAMOST LRS spectra and basal chromospheric activity parameters can be further used for investigating activity characteristics of solar-type stars and solar-stellar connection.</p> <p> </p> <p>The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams.</p> <p>(1) Catalog of Spectral Sample and Activity Parameters<br> CaIIHK_Sindex_LAMOST_DR7_LRS.csv</p> <p>(2) Library of Spectrum Diagrams<br> spectrum_diagrams_000-049.zip (46 subfolders)<br> spectrum_diagrams_050-099.zip (40 subfolders)<br> spectrum_diagrams_100-149.zip (47 subfolders)<br> spectrum_diagrams_150-199.zip (49 subfolders)<br> spectrum_diagrams_200-249.zip (47 subfolders)<br> spectrum_diagrams_250-299.zip (45 subfolders)<br> spectrum_diagrams_300-349.zip (41 subfolders)<br> spectrum_diagrams_350-399.zip (39 subfolders)<br> spectrum_diagrams_400-449.zip (45 subfolders)<br> spectrum_diagrams_450-499.zip (35 subfolders)<br> spectrum_diagrams_500-549.zip (27 subfolders)<br> spectrum_diagrams_550-599.zip (38 subfolders)<br> spectrum_diagrams_600-649.zip (32 subfolders)<br> spectrum_diagrams_650-699.zip (26 subfolders)<br> spectrum_diagrams_700-749.zip (28 subfolders)</p>
Stellar chromospheric activity spectral database of solar-type stars based on the LAMOST Low-Resolution Spectroscopic Survey(disused)
<p>A stellar chromospheric activity spectral database of solar-type stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains 1,330,654 high-quality LRS spectra of solar-type stars with effective temperature ranging from 4800 K to 6800 K. We measure the mean fluxes at line cores of the Ca II H&K lines using a 1 Å rectangular bandpass as well as a 1.09 Å full width at half maximum (FWHM) triangular bandpass, and the mean fluxes of two 20 Å pseudo-continuum bands on the two sides of the lines. Three chromospheric activity indexes, <em>S</em><sub>rec</sub> based on the 1 Å rectangular bandpass, and <em>S</em><sub>tri</sub> and <em>S</em><sub>MWL</sub> based on the 1.09 Å FWHM triangular bandpass, are evaluated from the measured fluxes. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H&K lines for all the spectra in the database. This database with more than one million high-quality LAMOST LRS spectra and basal chromospheric activity parameters can be further used for investigating activity characteristics of solar-type stars and solar-stellar connection.</p> <p> </p> <p>The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams.</p> <p>(1) Catalog of Spectral Sample and Activity Parameters<br> CaIIHK_Sindex_LAMOST_DR7_LRS.csv</p> <p>(2) Library of Spectrum Diagrams<br> spectrum_diagrams_000-049.zip (46 subfolders)<br> spectrum_diagrams_050-099.zip (40 subfolders)<br> spectrum_diagrams_100-149.zip (47 subfolders)<br> spectrum_diagrams_150-199.zip (49 subfolders)<br> spectrum_diagrams_200-249.zip (47 subfolders)<br> spectrum_diagrams_250-299.zip (45 subfolders)<br> spectrum_diagrams_300-349.zip (41 subfolders)<br> spectrum_diagrams_350-399.zip (39 subfolders)<br> spectrum_diagrams_400-449.zip (45 subfolders)<br> spectrum_diagrams_450-499.zip (35 subfolders)<br> spectrum_diagrams_500-549.zip (27 subfolders)<br> spectrum_diagrams_550-599.zip (38 subfolders)<br> spectrum_diagrams_600-649.zip (32 subfolders)<br> spectrum_diagrams_650-699.zip (26 subfolders)<br> spectrum_diagrams_700-749.zip (28 subfolders)</p>
FUMES III: Ultraviolet and Optical Variability of M Dwarf Chromospheres
<p>We obtained ultraviolet and optical spectra for 9 M dwarfs across a range of rotation periods to determine whether they showed stochastic intrinsic variability distinguishable from flares. The ultraviolet spectra were observed during the Far Ultraviolet M Dwarf Evolution Survey <em>Hubble Space Telescope</em> program using the Space Telescope Imaging Spectrograph. The optical observations were taken from the Apache Point Observatory 3.5-meter telescope using the Dual Imaging Spectrograph and from the Gemini South Observatory using the Gemini Multi-Object Spectrograph. We used the optical spectra to measure multiple chromospheric lines: the Balmer series from H$\alpha$ to H$10$ and the Ca II H and K lines. We find that after excising flares, these lines vary on the order of $1-20\%$ at minute-cadence over the course of an hour. The absolute amplitude of variability was greater for the faster rotating M dwarfs in our sample. Among the 5 stars for which measured the weaker Balmer lines, we note a tentative trend that the fractional amplitude of the variability increases for higher order Balmer lines. We measured the integrated flux of multiple ultraviolet emission features formed in the transition region: the N V, Si IV, and C IV resonance line doublets, and the C II and He II multiplets. The signal-to-noise (S/N) ratio of the UV data was too low for us to detect non-flare variability at the same scale and time cadence as the optical. We consider multiple mechanisms for the observed stochastic variability and propose both observational and theoretical avenues of investigation to determine the physical causes of intrinsic variability in the chromospheres of M dwarfs.</p> <p>All code associated with the analysis and plots for this paper are included in .py scripts. All raw data for the optical spectra are its files compressed into a tar.gzip archive while all reduced spectra are in fits files. All tables are provided in the astropy ASCII text ecsv file format.</p> <ul> <li><strong>Optical Reduction Code</strong>: The reduction code is divided into two folders, one labelled "pydis" and another labelled "pygemini".</li> <li><strong>Equivalent Width Measurements:</strong> The equivalent widths are measured using a combination of two tables for each exposure: one ending with the suffix "ew_windows.ecsv" that lists the boundaries of the blue and red continua windows and the continuum flux density value, and another ending with the suffix "ew_lines.ecsv" that lists the boundaries of the wavelength window, the integrated line flux with its error, and the equivalent width with its error. These tables are in a subdirectory named "fit_tables".</li> <li><strong>spectralPhoton:</strong> The version of spectralPhoton code and the scripts we use to split the <em>Hubble</em> x1d spectra are in a directory named "uv".</li> <li><strong>Line-fitting Tables:</strong> The parameter values and associated errors are recorded in tables structured similarly to the equivalent width tables, ending with suffixes "windows.ecsv" and "lines.ecsv".</li> <li><strong>Time Series Tables:</strong> The equivalent widths and integrated line fluxes are collated into time series tables in the subdirectory "time_series". Entries with cosmic ray hits in the middle of the line or other spectral defects have been commented out using a # symbol.</li> <li><strong>Posterior Distributions:</strong> All posterior samples and their log-likelihood values are recorded in numpy binary .npy files that can be read using the numpy.load() function. These files are divided into two subdirectories named ``abs" and ``frac" for the absolute and fractional flux fits respectively.</li> </ul>
Stellar chromospheric activity database of solar-like stars based on the LAMOST Low-Resolution Spectroscopic Survey
<p>A stellar chromospheric activity database of solar-like stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains spectral bandpass fluxes and indexes of Ca II H and K lines derived from 1,330,654 high-quality LRS spectra of solar-like stars. We measure the mean fluxes at line cores of the Ca II H and K lines using a 1 Å rectangular bandpass and a 1.09 Å FWHM triangular bandpass, as well as the mean fluxes of two 20 Å wide pseudocontinuum bands on the two sides of the lines. Three activity indexes of Ca II H and K lines, <em>S</em><sub>rec</sub> based on the 1 Å rectangular bandpass and <em>S</em><sub>tri</sub> and <em>S<sub>L</sub></em> based on the 1.09 Å FWHM triangular bandpass, are evaluated from the measured fluxes to quantitatively indicate the chromospheric activity level. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H and K lines for all the spectra in the database. This database, with more than one million high-quality LAMOST LRS spectra of Ca II H and K lines and basal chromospheric activity parameters, can be further used for investigating activity characteristics of solar-like stars and solar-stellar connection.</p> <p> </p> <p>The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams of Ca II H and K lines.</p> <p>(1) Catalog of Spectral Sample and Activity Parameters<br> CaIIHK_Sindex_LAMOST_DR7_LRS.csv<br> (see Table3 in the paper 2022_ApJS_263_12 for description of the columns)</p> <p>(2) Library of Spectrum Diagrams of Ca II H and K lines<br> spectrum_diagrams_000-049.zip (46 subfolders)<br> spectrum_diagrams_050-099.zip (40 subfolders)<br> spectrum_diagrams_100-149.zip (47 subfolders)<br> spectrum_diagrams_150-174.zip (25 subfolders)<br> spectrum_diagrams_175-199.zip (24 subfolders)<br> spectrum_diagrams_200-224.zip (24 subfolders)<br> spectrum_diagrams_225-249.zip (23 subfolders)<br> spectrum_diagrams_250-259.zip (10 subfolders)<br> spectrum_diagrams_260-274.zip (12 subfolders)<br> spectrum_diagrams_275-299.zip (23 subfolders)<br> spectrum_diagrams_300-349.zip (41 subfolders)<br> spectrum_diagrams_350-374.zip (20 subfolders)<br> spectrum_diagrams_375-399.zip (19 subfolders)<br> spectrum_diagrams_400-424.zip (23 subfolders)<br> spectrum_diagrams_425-449.zip (22 subfolders)<br> spectrum_diagrams_450-499.zip (35 subfolders)<br> spectrum_diagrams_500-549.zip (27 subfolders)<br> spectrum_diagrams_550-599.zip (38 subfolders)<br> spectrum_diagrams_600-649.zip (32 subfolders)<br> spectrum_diagrams_650-699.zip (26 subfolders)<br> spectrum_diagrams_700-749.zip (28 subfolders)</p>
How stable are solar-type cycles over half a century? Chromospheric S-indices Mt. Wilson vs. TIGRE
<p> <br>by Klaus-Peter Schröder (1); Jürgen Schmitt (2); Marco Mittag (2)<br>Departamento de Astronomia, Universidad de Guanajuato, Mexico; Hamburger<br>Sternwarte, University of Hamburg, Germany</p> <p>Since autumn 2013, the robotic 1.2m telescope TIGRE (formerly the Hamburg Robotic<br>Telescope) is operating in Guanajuato (Mexico, and see poster by Gonzalez et al.). Regularly<br>using the same calibration stars for S-indices as did the Mount Wilson project (see Baliunas et<br>al. 1995), our R=20,000 HEROS echelle spectra have provided a decade of chromospheric<br>activity monitoring of the same ca. 100 solar-type stars, including a smaller number with<br>pronounced cycles (see Schröder et al. 2013) of periods of o(10yrs), which were already<br>observed at Mount Wilson since the 1970ies. Hence, on a timescale of half a century, we can<br>now use those same stars, first shown by Olin C. Wilson and his group to perform solar-type<br>activity cycles, to probe the stability of these cycles. This is motivated by the solar cycle<br>variability, which is evident, when comparing the last two, relatively weak maxima monitored by<br>TIGRE, with the Mount Wilson data from the 1970ies and 1980ies. Hence, we here show that<br>this is not a singular behavior. Strong cycles seem to be less variable, while weaker cycles like<br>the solar are natural to change between stronger and weaker performance. In the case of the<br>Sun this behavior is consistent with an o(century)-period as of the semi-regular Gleissberg<br>cycle, as well as with the occurrence of grand-minima.</p> <p><br>Theme(s): The Sun and Cool Stars in the Time Domain, Cool Stars as Stellar Systems</p>
Driven two-fluid slow magnetoacoustic waves in the solar chromosphere with a realistic ionisation profile
<p>An animation showing log(Ti) overlaid by magnetic field lines. The initial atmosphere (at t = 0 s) is described by a hydrostatic equilibrium supplemented by the Saha equation and embedded in a fanning magnetic field. This initial equilibrium is perturbed by a monochromatic driver which operates in the chromosphere on the vertical components of the ion and neutral velocities with period P = 5 s.</p>
K2 observations of 95 Vir: δ Scuti pulsations in a chromospherically active star
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017MNRAS.468.2017P">K2 observations of 95 Vir: δ Scuti pulsations in a chromospherically active star</a></p>
Investigation of the Chromosphere-Corona Interface with the Upgraded Very high angular Resolution ULtraviolet Telescope (VAULT2.0) Project
<p> We propose a three-year effort to upgrade our existing sub-arcsecond Lyman-alpha telescope payload to improve the observing cadence by a factor of 2, increase the signal-to-ratio by a factor of 4, and launch the payload twice. With this upgraded performance, we will be able to investigate a number of scientific questions regarding the structure and heating of the solar atmosphere that address NASA&rsquo;s Strategic Goal to understand the Sun and its effects on Earth and the Solar System. Specifically, the ultra-high resolution and high-temporal cadence VAULT2.0 science program and associated launch campaigns will answer the following five questions:</p> <p> ? <em>What is the role of Type-II spicules in the transfer of energy and mass across the chromosphere-corona interface? </em></p> <p> ? <em>Does neutral plasma absorption of the EUV emission from active region moss explain the discrepancies in the models of coronal loop heating? </em></p> <p> ? <em>Where are the photospheric footpoints of coronal loops? </em></p> <p> ? <em>What is the structure of coronal holes in the Lyman-alpha temperature range? </em></p> <p> ? <em>What is the absolute abundance of H I at the base of the solar wind? </em></p> <p> Despite decades of ground-based observations, the chromosphere remains one of the least understood layers of the solar atmosphere because of our limited understanding of the physical processes that govern it. In the last few years, the chromosphere has been propelled to the forefront of solar physics research thanks to spectacular new observations from space (Hinode/SOT and VAULT), and ground (e.g., SOUP, IBIS, DOT, SST), and the advent of sophisticated numerical simulations which are beginning to address the complex physics of the optically thick chromospheric plasmas and are opening up the interpretation of the observations. With these new capabilities come exciting new ideas regarding the role of the chromosphere in supplying the mass and energy to heat the corona, the nature of filaments, and the contribution of chromospheric jets to the solar wind. These ideas are challenging our traditional views of coronal heating (a long-standing mystery of solar physics), the existence of the &lsquo;transition region&rsquo;, the role of neutral plasmas in coronal emission and even the dominance of magnetic fields at coronal heights. The recent SMEX selection of a chromosphere-oriented mission, IRIS, is further evidence for the renewed importance of chromospheric physics. Observational limitations, however, are impeding further development and validation of these ideas. <strong>Both theoretical and observational considerations point to the importance of tracing the mass and energy on <em>small spatial scales through the upper chromosphere and transition region </em></strong>(e.g., De Pontieu et al. 2007a, 2009, 2011; Vourlidas et al. 2010). This layer corresponds roughly to the temperature range from 10,000K (ground-based H&alpha;) to 80,000K (space-based HeI). The requirement for high spatial- and temporal-resolution observations in this temperature range cannot be met fully by current instrumentation. Narrow-band, high-resolution images from TRACE, Hinode, STEREO and SOHO have inadequate temperature coverage or poor resolution. The SDO/AIA observations are skewed towards higher temperature plasmas. The SOHO spectrometers CDS and SUMER have good temperature coverage and fidelity, but limited spatial and temporal resolution and more importantly, limited operational lifetime. Hinode/EIS observations are mostly confined to the upper solar atmosphere while SOT observations are confined to the lower chromosphere (&le; 10,000K). The forthcoming IRIS satellite will partially cover the gap between chromosphere and transition region by obtaini
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.