Author name code: gafeira
ADS astronomy entries on 2022-09-14
author:"Gafeira, Ricardo"
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Title: Magnetic properties of short-lived penumbral microjets
Authors: Tapia, Azaymi Siu; Bellot Rubio, L. R.; Gafeira, Ricardo;
Orozco Suárez, David
Bibcode: 2022cosp...44.2520T
Altcode:
Penumbral microjets (PMJs) are fast elongated brightenings above
sunspots penumbrae. They are presumed to be related to photospheric
magnetic reconnection processes and contribute to the heating of the
plasma in the higher atmospheric layers. Studying the spectral and
polarization properties of the shortest-living microjets requires
the fastest temporal cadence possible and is currently a challenging
task. In this work, we use fast spectropolarimetric measurements of
the Ca II 8542 A line made with the CRISP instrument at the Swedish
1 m Solar Telescope, and exploit the diagnostic capabilities of this
line to retrieve the magnetic field configuration and its evolution
at different atmospheric heights during PMJs. Our findings show that
short-lived PMJs are associated with a transient perturbation in
the photospheric magnetic field and sometimes they show clear but
weaker changes in the chromospheric field as well. We will describe
the different types of evolution that were identified. These results
support the idea that PMJs may be the result of magnetic reconnection
at low altitudes in sunspot penumbra.
Title: Exploring dynamic, small-scale quiet Sun magnetism at high
S/N with the GREGOR/GRIS-IFU
Authors: Campbell, Ryan; Collados, Manuel; Quintero Noda, Carlos;
Mathioudakis, Mihalis; Gafeira, Ricardo
Bibcode: 2022cosp...44.2510C
Altcode:
We have taken advantage of the improvements to GREGOR (Kleint et
al. 2020, A&A, 641, A27), Europe's largest solar telescope,
to reveal small-scale magnetism at the solar internetwork (IN) in
unprecedented detail. The observations were carried out at solar disk
centre with the highly magnetically sensitive Fe I line at 1565nm. Our
observations suggest that GREGOR's overhaul has helped achieve a
higher effective spatial resolution while our synthetic profiles
produced from MHD simulations suggests this data have been obtained
at the telescope diffraction limit in the near infrared. By observing
with high signal-to-noise (S/N), and exceptional seeing conditions, we
reveal that as much as 35% of the IN shows linear polarisation signal
at the 5$\sigma$ level, the highest fraction of linear polarization
ever recorded in the quiet Sun IN, while as much as 70% shows circular
polarization. We use the Stokes inversion based on response functions
(SIR) inversion code to retrieve the thermodynamic, kinematic and
magnetic properties of the atmosphere. We statistically compare our
results to previous GRIS-IFU observations (Campbell et al. 2021,
647, A182) obtained in 2019, prior to GREGOR's overhaul, focusing on
controversies surrounding the impact of noise on the retrieval of the
magnetic inclination angle. We employ the new open-source SIR Explorer
(SIRE) application to easily and efficiently study several dynamic,
small-scale magnetic features. We see evidence for weak transverse
and complex small-scale 'loop-like' structures, with transverse fields
flanked between opposite polarity longitudinal fields. In the last part
of the presentation, SIRE will be demonstrated live for the audience.
Title: DeSIRe: Departure coefficient aided Stokes Inversion based
on Response functions
Authors: Ruiz Cobo, B.; Quintero Noda, C.; Gafeira, R.; Uitenbroek,
H.; Orozco Suárez, D.; Páez Mañá, E.
Bibcode: 2022A&A...660A..37R
Altcode: 2022arXiv220202226R
Future ground-based telescopes, such as the 4-metre class facilities
DKIST and EST, will dramatically improve on current capabilities for
simultaneous multi-line polarimetric observations in a wide range of
wavelength bands, from the near-ultraviolet to the near-infrared. As a
result, there will be an increasing demand for fast diagnostic tools,
i.e., inversion codes, that can infer the physical properties of the
solar atmosphere from the vast amount of data these observatories
will produce. The advent of substantially larger apertures,
with the concomitant increase in polarimetric sensitivity, will
drive an increased interest in observing chromospheric spectral
lines. Accordingly, pertinent inversion codes will need to take
account of line formation under general non-local thermodynamic
equilibrium (NLTE) conditions. Several currently available codes can
already accomplish this, but they have a common practical limitation
that impairs the speed at which they can invert polarised spectra,
namely that they employ numerical evaluation of the so-called response
functions to changes in the atmospheric parameters, which makes them
less suitable for the analysis of very large data volumes. Here we
present DeSIRe (Departure coefficient aided Stokes Inversion based on
Response functions), an inversion code that integrates the well-known
inversion code SIR with the NLTE radiative transfer solver RH. The
DeSIRe runtime benefits from employing analytical response functions
computed in local thermodynamic equilibrium (through SIR), modified
with fixed departure coefficients to incorporate NLTE effects in
chromospheric spectral lines. This publication describes the operating
fundamentals of DeSIRe and describes its behaviour, robustness,
stability, and speed. The code is ready to be used by the solar
community and is being made publicly available.
Title: Testing the Accuracy of Coimbra Astronomical Observatory
Solar Filament Historical Series (1929-1941)
Authors: Lourenço, Ana; Gafeira, Ricardo; Bonifácio, Vitor; Barata,
Teresa; Fernandes, João; Silva, Eva
Bibcode: 2021SoPh..296..155L
Altcode: 2021arXiv210805978L
The present work aims to validate the positions of solar filaments
published in the Annals of Coimbra University Astronomical Observatory,
currently the Geophysical and Astronomical Observatory of the
University of Coimbra, corresponding to years 1929 to 1941. The
published Stonyhurst positions were obtained by an original method
devised in the early 20th century that used a spherical calculator
instrument, a wood-made model of the Sun. We used the digital images
of the original spectroheliograms to measure the positions of the
filaments, and heliographic coordinates were determined with the
routines implemented in the Python package Sunpy. The correlation
coefficients between both sets of coordinates are positive and highly
significant. The results validate the method used at the Coimbra
observatory and the published data. We conclude that the Coimbra solar
filament catalogues are reliable and can therefore be considered for
future solar activity studies.
Title: Diagnostic capabilities of spectropolarimetric observations for
understanding solar phenomena. I. Zeeman-sensitive photospheric lines
Authors: Quintero Noda, C.; Barklem, P. S.; Gafeira, R.; Ruiz Cobo,
B.; Collados, M.; Carlsson, M.; Martínez Pillet, V.; Orozco Suárez,
D.; Uitenbroek, H.; Katsukawa, Y.
Bibcode: 2021A&A...652A.161Q
Altcode: 2021arXiv210605084Q
Future ground-based telescopes will expand our capabilities for
simultaneous multi-line polarimetric observations in a wide range of
wavelengths, from the near-ultraviolet to the near-infrared. This
creates a strong demand to compare candidate spectral lines to
establish a guideline of the lines that are most appropriate for each
observation target. We focused in this first work on Zeeman-sensitive
photospheric lines in the visible and infrared. We first examined their
polarisation signals and response functions using a 1D semi-empirical
atmosphere. Then we studied the spatial distribution of the line core
intensity and linear and circular polarisation signals using a realistic
3D numerical simulation. We ran inversions of synthetic profiles, and
we compared the heights at which we obtain a high correlation between
the input and the inferred atmosphere. We also used this opportunity
to revisit the atomic information we have on these lines and computed
the broadening cross-sections due to collisions with neutral hydrogen
atoms for all the studied spectral lines. The results reveal that
four spectral lines stand out from the rest for quiet-Sun and network
conditions: Fe I 5250.2, 6302, 8468, and 15 648 Å. The first three
form higher in the atmosphere, and the last line is mainly sensitive to
the atmospheric parameters at the bottom of the photosphere. However,
as they reach different heights, we strongly recommend using at least
one of the first three candidates together with the Fe I 15 648 Å line
to optimise our capabilities for inferring the thermal and magnetic
properties of the lower atmosphere.
Title: Machine learning initialization to accelerate Stokes profile
inversions
Authors: Gafeira, R.; Orozco Suárez, D.; Milić, I.; Quintero Noda,
C.; Ruiz Cobo, B.; Uitenbroek, H.
Bibcode: 2021A&A...651A..31G
Altcode: 2021arXiv210309651G
Context. At present, an exponential growth in scientific data
from current and upcoming solar observatories is expected. Most of
the data consist of high spatial and temporal resolution cubes of
Stokes profiles taken in both local thermodynamic equilibrium (LTE)
and non-LTE spectral lines. The analysis of such solar observations
requires complex inversion codes. Hence, it is necessary to develop
new tools to boost the speed and efficiency of inversions and reduce
computation times and costs.
Aims: In this work we discuss
the application of convolutional neural networks (CNNs) as a tool to
advantageously initialize Stokes profile inversions.
Methods:
To demonstrate the usefulness of CNNs, we concentrate in this paper on
the inversion of LTE Stokes profiles. We use observations taken with
the spectropolarimeter on board the Hinode spacecraft as a test bench
mark. First, we carefully analyse the data with the SIR inversion code
using a given initial atmospheric model. The code provides a set of
atmospheric models that reproduce the observations well. These models
are then used to train a CNN. Afterwards, the same data are again
inverted with SIR but using the trained CNN to provide the initial
guess atmospheric models for SIR.
Results: The CNNs allow us
to significantly reduce the number of inversion cycles when used to
compute initial guess model atmospheres (`assisted inversions'),
therefore decreasing the computational time for LTE inversions by
a factor of two to four. CNNs alone are much faster than assisted
inversions, but the latter are more robust and accurate. CNNs also
help to automatically cluster pixels with similar physical properties,
allowing the association with different solar features on the solar
surface, which is useful when inverting huge datasets where completely
different regimes are present. The advantages and limitations of machine
learning techniques for estimating optimum initial atmospheric models
for spectral line inversions are discussed. Finally, we describe a
python wrapper for the SIR and DeSIRe codes that allows for the easy
setup of parallel inversions. The tool implements the assisted inversion
method described in this paper. The parallel wrapper can also be used
to synthesize Stokes profiles with the RH code.
Conclusions:
The assisted inversions can speed up the inversion process, but the
efficiency and accuracy of the inversion results depend strongly on
the solar scene and the data used for the CNN training. This method
(assisted inversions) will not obviate the need for analysing individual
events with the utmost care but will provide solar scientists with
a much better opportunity to sample large amounts of inverted data,
which will undoubtedly broaden the physical discovery space.
Title: 3D Solar Coronal Loop Reconstructions with Machine Learning
Authors: Chifu, Iulia; Gafeira, Ricardo
Bibcode: 2021ApJ...910L..10C
Altcode: 2021arXiv210309960C
The magnetic field plays an essential role in the initiation and
evolution of different solar phenomena in the corona. The structure
and evolution of the 3D coronal magnetic field are still not very
well known. A way to ascertain the 3D structure of the coronal
magnetic field is by performing magnetic field extrapolations from
the photosphere to the corona. In previous work, it was shown that by
prescribing the 3D-reconstructed loops' geometry, the magnetic field
extrapolation produces a solution with a better agreement between
the modeled field and the reconstructed loops. This also improves
the quality of the field extrapolation. Stereoscopy, which uses at
least two view directions, is the traditional method for performing
3D coronal loop reconstruction. When only one vantage point of the
coronal loops is available, other 3D reconstruction methods must
be applied. Within this work, we present a method for the 3D loop
reconstruction based on machine learning. Our purpose for developing
this method is to use as many observed coronal loops in space and time
for the modeling of the coronal magnetic field. Our results show that
we can build machine-learning models that can retrieve 3D loops based
only on their projection information. Ultimately, the neural network
model will be able to use only 2D information of the coronal loops,
identified, traced, and extracted from the extreme-ultraviolet images,
for the calculation of their 3D geometry.
Title: Revisiting the mass- and radius-luminosity relations for FGK
main-sequence stars
Authors: Fernandes, João; Gafeira, Ricardo; Andersen, Johannes
Bibcode: 2021A&A...647A..90F
Altcode: 2021arXiv210311044F
Context. Scaling relations are very useful tools for estimating
unknown stellar quantities. Within this framework, eclipsing binaries
are ideal for this goal because their mass and radius are known with
a very good level of accuracy, leading to improved constraints on
the models.
Aims: We aim to provide empirical relations for
the mass and radius as function of luminosity, metallicity, and
age. We investigate, in particular, the impact of metallicity and
age on those relations.
Methods: We used a multi-dimensional
fit approach based on the data from DEBCat, an updated catalogue
of eclipsing binary observations such as mass, radius, luminosity,
effective temperature, gravity, and metallicity. We used the PARAM
web interface for the Bayesian estimation of stellar parameters,
along with the stellar evolutionary code MESA to estimate the binary
age, assuming a coeval hypothesis for both members.
Results:
We derived the mass and radius-luminosity-metallicity-age relations
using 56 stars, with metallicity and mass in the range −0.34 <
[Fe/H] < 0.27 and 0.66 < M/M⊙ < 1.8. With that,
the observed mass and radius are reproduced with an accuracy of 3.5%
and 5.9%, respectively, which is consistent with the other results
in literature.
Conclusions: We conclude that including the
age in such relations increases the quality of the fit, particularly
in terms of the mass, as compared to the radius. On the other hand,
as otherss authors have noted, we observed an higher dispersion on the
mass relation than in that of the radius. We propose that this is due
to a stellar age effect.
Title: Mimicking spectropolarimetric inversions using convolutional
neural networks
Authors: Milić, I.; Gafeira, R.
Bibcode: 2020A&A...644A.129M
Altcode: 2020arXiv200602005M
Context. Interpreting spectropolarimetric observations of the solar
atmosphere takes much longer than the acquiring the data. The most
important reason for this is that the model fitting, or "inversion",
used to infer physical quantities from the observations is extremely
slow, because the underlying models are numerically demanding.
Aims: We aim to improve the speed of the inference by using a neural
network that relates input polarized spectra to the output physical
parameters.
Methods: We first select a subset of the data
to be interpreted and infer physical quantities from corresponding
spectra using a standard minimization-based inversion code. Taking
these results as reliable and representative of the whole data set, we
train a convolutional neural network to connect the input polarized
spectra to the output physical parameters (nodes, in context of
spectropolarimetric inversion). We then apply the neural network to
the various other data, previously unseen to the network. As a check,
we apply the referent inversion code to the unseen data and compare
the fit quality and the maps of the inferred parameters between the
two inversions.
Results: The physical parameters inferred by
the neural network show excellent agreement with the results from
the inversion, and are obtained in a factor of 105 less
time. Additionally, substituting the results of the neural network back
in the forward model, shows excellent agreement between inferred and
original spectra.
Conclusions: The method we present here is
very simple for implementation and extremely fast. It only requires a
training data set, which can be obtained by inverting a representative
subset of the observed data. Applying these (and similar) machine
learning techniques will yield orders of magnitude acceleration in
the routine interpretation of spectropolarimetric data.
Title: Temporal evolution of short-lived penumbral microjets
Authors: Siu-Tapia, A. L.; Bellot Rubio, L. R.; Orozco Suárez, D.;
Gafeira, R.
Bibcode: 2020A&A...642A.128S
Altcode: 2020arXiv200715926S
Context. Penumbral microjets (PMJs) is the name given to elongated
jet-like brightenings observed in the chromosphere above sunspot
penumbrae. They are transient events that last from a few seconds
to several minutes, and their origin is presumed to be related to
magnetic reconnection processes. Previous studies have mainly focused
on their morphological and spectral characteristics, and more recently
on their spectropolarimetric signals during the maximum brightness
stage. Studies addressing the temporal evolution of PMJs have also
been carried out, but they are based on spatial and spectral time
variations only.
Aims: Here we investigate, for the first
time, the temporal evolution of the polarization signals produced by
short-lived PMJs (lifetimes < 2 min) to infer how the magnetic field
vector evolves in the upper photosphere and mid-chromosphere.
Methods: We use fast-cadence spectropolarimetric observations of the
Ca II 854.2 nm line taken with the CRisp Imaging Spectropolarimeter
at the Swedish 1 m Solar Telescope. The weak-field approximation (WFA)
is used to estimate the strength and inclination of the magnetic field
vector. By separating the Ca II 854.2 nm line into two different
wavelength domains to account for the chromospheric origin of the
line core and the photospheric contribution to the wings, we infer
the height variation of the magnetic field vector.
Results:
The WFA reveals larger magnetic field changes in the upper photosphere
than in the chromosphere during the PMJ maximum brightness stage. In
the photosphere, the magnetic field inclination and strength undergo
a transient increase for most PMJs, but in 25% of the cases the field
strength decreases during the brightening. In the chromosphere, the
magnetic field tends to be slightly stronger during the PMJs.
Conclusions: The propagation of compressive perturbation fronts
followed by a rarefaction phase in the aftershock region may explain
the observed behavior of the magnetic field vector. The fact that such
behavior varies among the analyzed PMJs could be a consequence of the
limited temporal resolution of the observations and the fast-evolving
nature of the PMJs.
Title: Analysis of full-disc Ca II K spectroheliograms. III. Plage
area composite series covering 1892-2019
Authors: Chatzistergos, Theodosios; Ermolli, Ilaria; Krivova,
Natalie A.; Solanki, Sami K.; Banerjee, Dipankar; Barata, Teresa;
Belik, Marcel; Gafeira, Ricardo; Garcia, Adriana; Hanaoka, Yoichiro;
Hegde, Manjunath; Klimeš, Jan; Korokhin, Viktor V.; Lourenço, Ana;
Malherbe, Jean-Marie; Marchenko, Gennady P.; Peixinho, Nuno; Sakurai,
Takashi; Tlatov, Andrey G.
Bibcode: 2020A&A...639A..88C
Altcode: 2020arXiv200501435C
Context. Studies of long-term solar activity and variability require
knowledge of the past evolution of the solar surface magnetism. The
archives of full-disc Ca II K observations that have been performed
more or less regularly at various sites since 1892 can serve as an
important source of such information.
Aims: We derive the plage
area evolution over the last 12 solar cycles by employing data from all
Ca II K archives that are publicly available in digital form, including
several as-yet-unexplored Ca II K archives.
Methods: We analysed
more than 290 000 full-disc Ca II K observations from 43 datasets
spanning the period between 1892-2019. All images were consistently
processed with an automatic procedure that performs the photometric
calibration (if needed) and the limb-darkening compensation. The
processing also accounts for artefacts affecting many of the images,
including some very specific artefacts, such as bright arcs found
in Kyoto and Yerkes data. Our employed methods have previously been
tested and evaluated on synthetic data and found to be more accurate
than other methods used in the literature to treat a subset of the data
analysed here.
Results: We produced a plage area time-series
from each analysed dataset. We found that the differences between the
plage areas derived from individual archives are mainly due to the
differences in the central wavelength and the bandpass used to acquire
the data at the various sites. We empirically cross-calibrated and
combined the results obtained from each dataset to produce a composite
series of plage areas. The 'backbone' approach was used to bridge
the series together. We have also shown that the selection of the
backbone series has little effect on the final composite of the plage
area. We quantified the uncertainty of determining the plage areas
with our processing due to shifts in the central wavelength and found
it to be less than 0.01 in fraction of the solar disc for the average
conditions found on historical data. We also found the variable seeing
conditions during the observations to slightly increase the plage
areas during the activity maxima.
Conclusions: We provide the
most complete so far time series of plage areas based on corrected
and calibrated historical and modern Ca II K images. Consistent
plage areas are now available on 88% of all days from 1892 onwards
and on 98% from 1907 onwards.