dataesr/scientific-paragraphs-categorization huggingface dataset:
Withers (2014)  analyzed Mars Global Surveyor radio-occultation and Mars Express radar data and confirmed the expected trend that the ionospheric peak electron density increases smoothly with increasing solar activity represented by the F10. 7 space weather proxy, named from the solar radio flux at 10. 7 cm (2800 MHz). This trend is not obviously identified in the Mars Express radio-occultation data alone  (Peter et al. 2014). What is more evident in this dataset is the increase of the peak altitude with solar activity, especially at high solar zenith angle. Girazian and Withers (2013)  propose an empirical relationship, with the maximum electron density varying as the square of F10. 7. Sanchez-Cano et al. (2015)  used Mars Express radar data covering almost one solar cycle and analyzed differences in the shape of the topside electron density profiles.
Finally, ionospheric layers meteoritic in origin appear sporadically below 100 km altitude  (Molina-Cuberos et al. 2003). So far, 89 events have been identified in the Mariner 7/Mariner 9/Mars Global Surveyor/Mars Express datasets  (Withers et al. 2013; Pätzold et al. 2005). One of the proposed causes of temporal variations in the occurrence rate of meteoric layers is meteor showers. Regarding spatial variability, the upper atmosphere is also affected by the crustal magnetic field, discovered by Mars Global Surveyor  (Acuna et al. 1999). Elevated ionospheric densities and localized spatial structures are seen above magnetic anomalies  (Andrews et al. 2014 (Andrews et al. , 2015;; Matta et al. 2015; Ma et al. 2014; Dubinin et al. 2012; Safaeinili et al. 2007) , and can be explained to first order by a larger ionization due to higher energetic particle fluxes spiraling along the magnetic field lines  (Lillis and Fang 2015).
2008). In some cases, the Mars Express/ASPERA measurements show the existence of long-lived and active aurora-type magnetic flux tubes with a width of 20-150 km. This aurora activity has an influence on the atmospheric escape  (Dubinin et al. 2009 ). The analysis of MAVEN data  (Schneider et al. 2015)  has shown a new kind of martian aurora, called diffuse aurora, observed at low altitudes, over areas not characterized by a crustal fields, and likely due to the penetration in the atmosphere of very energetic particles of ∼200 keV energy.
2008). The lower section of the north polar plateau consists of a distinct, complex, layered unit commonly called the basal unit that can be fully mapped by MARSIS. The total volumes of the polar deposits and the basal unit are estimated to be 7. 8 × 10 5 and 4. 5 × 10 5 cubic Fig. 17  Top bright lower echo from Mars' south-polar layered deposits  (Plaut et al. 2009 ). The upper image of this composite is a 'radargram' from the MARSIS radar on board Mars Express. The lower image shows the position of the ground track of the spacecraft (indicated by a white line) on an topographic map of the area based on data from the MOLA Laser Altimeter on board Mars Global Surveyor. The images are 1250 km wide. The MARSIS radar echo trace splits into two traces on the left side of the image, at the point where the ground track crosses from the surrounding plains onto elevated layered deposits.
The late veneer As for the Earth mantle, the depletion of HSE appears to be not as marked as one would expect from their respective metal-silicate partition coefficient  (Jones et al. 2003; Walker 2009; Brandon et al. 2012 ). In addition, their respective concentration follows a near chondritic signature suggesting that they have not been fractionated from each other. Several hypotheses have been explored to explain this apparent excess of HSE on the Earth, including inefficient core formation, metal-silicate equilibration at high pressures and temperatures, and the addition of material with chondritic bulk compositions (late veneer) (e. g. ,  Rubie et al. 2007 ). Synthesis of the large database now available for HSE in the terrestrial mantle (including also lunar samples) reveals that each of the main hypotheses has flaws.
Although the last volcanic phases are recent and indicate a warm interior, the thickness of the present lithosphere (100-300 km) and the existence of felsic crustal components may represent a significant obstacle for the ascent of partial melts. Systematic evolution of surface concentrations of K, Th, and Fe with time was noticed in global analyses of Gamma Ray Spectrometer data  (Hahn et al. 2007; Karunatillake et al. 2009) , but these studies fail to decipher the respective role of primary and secondary processes in explaining these variations. Baratoux et al. (2011)  revisited this dataset and have provided evidence that systematic variations with time on Si, Fe, and Th concentrations on volcanic provinces were compatible with globally evolving conditions of partial melting related to the cooling of the mantle and to the thickening of the lithosphere.
2016). In summary, the most recent and fresh examples of deltas may not be representative of the most intense period of fluvial activity, whereas the sedimentary deposits from the ancient valleys are poorly preserved. Therefore, using deltaic deposits on As observed in orbital data, sedimentary rocks often do not have an obvious depositional context, as the so-called light-toned deposits observed mostly in Noachian and Hesperian terrains  (Nedell et al. 1987; Malin and Edgett 2000a; Stack et al. 2013). While the sedimentary facies can be assessed locally with rovers (see Sects. 4. 1. 4 and 4. 3. 2), facies can usually not be interpreted from orbital data  (Grotzinger and Milliken 2012; Stack et al. 2013). In this case, layered deposits can be interpreted as aeolian, glacial, fluvial, and lacustrine of even pyroclastic deposits, leaving a large range of possible implications in terms of climatic implications.
Then, the challenging exercise of extrapolating previous estimations over a few billion years, from a current larger time dataset, may be improved. It is also necessary to link these results with the D/H measurements and interpretation (e. g. ,  Chassefiere and Leblanc 2004; Mahaffy et al. 2015)  for consistency. Certainly, MAVEN  (Jakosky et al. 2015a, b)  will bring much more information and constraints to the atmospheric escape, and thus on the evolution of the red planet. MAVEN observations have recently shown a major impact of interplanetary coronal mass ejections on atmospheric erosion  (Jakosky et al. 2015a, b). The effects through the entire upper atmosphere system produced substantially disturbed conditions and appeared to have a major impact on the instantaneous rates of loss of ions to space.
Fortunately, most of the data of this experience were collected on time; they will enable scientists to improve atmospheric models. The ExoMars rover mission is planned to be launched in August 2020 on a Proton rocket, with a landing on Mars in April 2021. The rover will carry a comprehensive suite of instruments dedicated to exobiology and geology research named after Louis Pasteur. It will be able to travel several kilometers searching for traces of past and present signs of life. The rover will collect and analyze samples from within rocky outcrops, and from the sub-surface, down to 2-m depth. The very powerful combination of mobility with the ability to access locations where organic molecules can be well preserved is unique to this mission. It is also planned to include instruments on the landing platform with the goal to study the surface environment.
Acknowledgements We greatly appreciated detailed reviews from  Mike Carr  and anonymous reviewer. We wish to warmly thank  Eliott Sefton-Nash  for his detailed comments. Authors are funded by the  Centre National d'Etudes Spatiales (CNES). Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://creativecommons. org/licenses/by/4. 0/),which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
(2010 Simon et al. ( , 2013)). On the contrary, all of the considered nightside flybys (T55-T59) were associated with an SLT of ∼22 hr and occurred within Saturnʼs oscillating current sheet  (Simon et al. 2010 (Simon et al. , 2013)). to the CAPS/ELS-derived electron-impact ionization frequencies (electron energies up to 10 keV considered), (b) electron-impact ionization frequencies when limited to electrons with energies <60 eV, and (c) electron-impact ionization frequencies when limited to electrons with energies <10 keV. The nightside points (shown by magenta triangles) are taken from the study by  Vigren et al. (2015)  and are associated with the T55-T59 flybys. In order to look for dependencies of, e. g. , the solar zenith angle, the SLT, and the magnetic environment on the fluxes of high-energy electrons in Titanʼs upper atmosphere (at locations with similar neutral number densities), we are planning to conduct a study making use of CAPS/ELS and INMS/CSN data from an extended set of Titan flybys.
As concluding words, the main motivation of this study was to investigate further whether overestimated plasma production is a contributing reason as to why models predict nearly a factor of 2 higher electron number densities than observed in Titanʼs sunlit and main ionosphere. While the finding that the modeled electron fluxes at typical photoelectron energies are markedly higher than measured by the CAPS/ELS (anode 2) is indicative of such an overestimation in plasma production, we wish to keep several possibilities open and therefore refrain from drawing (possibly too) strong conclusions. E. V. is grateful for funding from the Swedish National Space Board (DNR 14/166). M. G. is partially funded by the Science & Technology Facilities Council (STFC) of UK under grant ST/K001051/1. N. J. T.
Calculations Coupled-channels calculations using the code CCFULL  [29]  were performed for both the systems. In the case of 7 Li + 198 Pt system, a standard Woods-Saxon potential (WS) was used with V 0 =110 MeV, r 0 =1. 1 fm and a=0. 63 fm. These calculations included two phonon quadrupole excitation of 198 Pt in the vibrational and the first excited state of 7 Li in the rotational mode. The CC calculations reproduce the data well for energies around and well below the barrier as seen in Fig. 1(a). Fusion hindrance has not been observed in this system in the measured energy range with the cross-section as low as ≈ 180 nb. The threshold energy for observing fusion hindrance obtained from the systematics of Ref. [30]  and the adiabatic model  [8]  is 20. 4 MeV and 21. 1 MeV, respectively. However, from an extrapolation of the experimental data, this energy is found to be ≈19 MeV (Fig.
(  1 ) to be estimated by investigating the magnitude of the variations in the calculated parameters for different choices of isotope triads. Its main disadvantage is that it requires the relativistic configuration interaction calculations to be performed for a series of selected isotopes. We first adopt this approach by computing the wave functions for the 65 Cu isotope that we use in RCI calculations for a series of five copper isotopes for the upper and lower levels (with mass numbers A = 59, 61, 63, 65, 66) to get the total energies and deduce the corresponding transition IS. The NMS and SMS form together the total mass shift, M k = M k,NMS + M k,SMS , as it occurs in Eq. (  1 ). The NMS is estimated from the "scaling law" of the NMS approximation  [24, 25]  using the observed transition frequency, M k,NMS = (m e /m n ) ν k , while the SMS operator that is included in the Hamiltonian for the RCI calculations is limited to the standard mass polarization term 1 M i<j p i • p j , as described in the write-up of the SMS92 computer program  [26].
B. Large scale multireference calculations and relativistic corrections to the recoil operator We carry out complementary large scale MCDHF calculations with the last version of the GRASP2K package  [27]  and computing M k and F k as expectation values of the relevant operators  [28]  using the 65 Cu wave function. In this scheme, M k is the difference in the expectation values between the two levels of the recoil Hamiltonian containing both the oneand two-body terms constituting, respectively, of the NMS and SMS, as described in Ref. [28]. In the case of Cu I, F k can be reliably computed using the electron density at the nucleus  [29, 30]. A specificity of the present work is that we test the impact of relativistic corrections to the recoil operator as originally derived by Shabaev  [31, 32].
For this, we compare the results obtained with SMS92  [26]  (denoted M k ), based on the Dirac kinetic form of the NMS  [25]  and the mass polarization term 1 M i<j p i • p j for the SMS, with the values (denoted M k ) obtained with the more recent computer code RIS3  [28]  using the relativistically corrected recoil operator  [33]. Recalling that the two main configurations are of the type [Ar]3d 10 n , with (n ) = 4s/4p, we will distinguish three types of double excitations: (i) core-core (CC), involving n = 2,3 electrons; (ii) core-valence (CV), involving n = 3 and 4s/4p electrons, and (iii) inner-core-valence (ICV), involving 1s 2 and 4s/4p electrons. All calculations are performed with a common orbital basis for the 4s and 4p states, i. e. , "Extended Optimized Level" (EOL) type of calculations  [19]  on the two states.
V. SUMMARY Using collinear laser spectroscopy we have measured the optical isotope shifts for 17 Cu isotopes. State-of-the art large-scale MCDHF calculations including different types of configuration mixing calculations yielded values for the mass shift and field shift in agreement with the muonic atomic data δ r 2 c 65,63. In order to reproduce the overall trend in the charge radii in the trans-Ni region, we finally adopted the calculated field shift, but used the experimentally determined specific mass shift factor for extracting the change in mean-square charge radii from the measured isotope shifts. The charge radii obtained from these measurements, together with advanced atomic calculations, reveal a weak sub-shell effect at N = 40 in the Cu isotopes having just one proton more than the magic Ni chain.
ACKNOWLEDGMENTS This work has been supported by the  German Ministry for Education and Research (BMBF)  under Contract Nos. 05P12RDCIC  and  05P15RDCIA , the  UK Science and Technology Facilities Council (STFC) , the  FWO-Vlaanderen (Belgium) , the  EU Sixth Framework  through No. Eurons-506065 , the  BriX IAP Research  Programs No. P6/23  and  P7/12 (Belgium), the  Max-Planck Society. M. K. was supported by the  EU  ( MEIF-CT-2006-042114 ). We thank the  ISOLDE technical group  for their support and assistance during this project.
5±0. 1 and 2. 8 ± 0. 1-equivalent to an odds ratio of between approximately 1:4 and 1:16-depending of the component separation technique adopted. Prior to the analysis of Planck Collaboration XXVI (2014), numerous analyses of Bianchi models using COBE  (Bennett et al. 1996)  and WMAP  (Jarosik et al. 2011 ) data had been performed  (Bunn et al. 1996; Kogut et al. 1997; Jaffe et al. 2005 Jaffe et al. , 2006a,c,b;,c,b; Cayón et al. 2006; Land & Magueijo 2006; McEwen et al. 2006; Bridges et al. 2007; Ghosh et al. 2007; Pontzen & Challinor 2007; Bridges et al. 2008; McEwen et al. 2013) , and a similar Bianchi template was found in the WMAP data, first by  Jaffe et al. (2005)  and then subsequently by others  (Bridges et al. 2007; Bridges et al. 2008; McEwen et al. 2013). Pontzen & Challinor (2007)  discussed the CMB polarization signal from Bianchi models, and showed some incompatibility with WMAP data due to the large amplitude of both E-and B-mode components.
Hence, it enables us to probe the ability to tell if, on average, we can distinguish realizations of p 1 from a fixed p 2 without having to perform a brute-force Monte Carlo integration. Thus, the KL divergence is related to ensemble averages of the likelihood-ratio plots that we present for simulations (Sect. 4. 4. 1) and real data (Sect. 5. 1) but can be calculated from the covariance matrices alone. Note that with this definition, the KL divergence is minimized for cases with the best match (maximal likelihood). In Planck Collaboration XXVI (2014) we used the KL divergence to show that the likelihood is robust to differences in the cosmological model and small differences in the topology. In Fig. 1  we plot the KL divergence relative to an infinite universe for the slab topology as a function of resolution max (upper panel) and fundamental domain size (lower panel).
Our ability to detect a topology with a fundamental domain smaller than the distance to the last-scattering surface (approximately at the horizon distance χ rec = 3. 1H -1 0 , so with sides of length L = 2 χ rec = 6. 2H -1 0 ) grows significantly with the resolution even beyond the cases that we studied. For the noise levels of the 2015 lowP data considered here and defined in Planck Collaboration XIII (2016), polarization maps do not add much information beyond that contained in the temperature maps, although, as also shown in Sect. 4. 4. 1, the higher sensitivity achievable by the full Planck low-data over all frequencies should enable even stronger constraints on these small fundamental domains. If, however, the fundamental domain is larger than the horizon (as is the case for L = 6. 5H -1 0 ) then the relative information in the covariance matrix saturates quite early and a resolution of max 48 is actually sufficient.
cient conversion of E-mode polarization to B modes; evidence for a significant Bianchi component found in temperature data would therefore suggest a large B-mode signal (but not necessarily require it; see  Pontzen 2009). For examples of the temperature and polarization signatures of Bianchi VII h models we refer the reader to figure 1 of  Pontzen (2009). Despite the potential for CMB polarization to constrain the Bianchi sector, a full polarization analysis has not yet been carried out. The analysis of  Pontzen & Challinor (2007)  remains the state-of-the-art, where WMAP BB and EB power spectra were used to demonstrate (using a simple χ 2  analysis) that a Bianchi VII h model derived from temperature data was disfavoured compared to an isotropic model. The subdominant, deterministic CMB contributions of Bianchi VII h models can be characterized by seven parameters: the matter and dark energy densities, Ω m and Ω Λ , respectively; the present dimensionless vorticity, (ω/H) 0 ; the dimensionless length-scale parameter, x, which controls the "tightness" of the characteristic Bianchi spirals; and the Euler angles 2 , (α, β, γ), describing their orientation (i.
Data In this work we use data from the Planck 2015 release. This includes intensity maps from the full mission, along with a subset of polarization data. Specifically, for the likelihood calculations discussed below (Sect. 4. 3. 1 for application to topology and Sect. 4. 3. 3 for Bianchi models) which rely on HEALPix maps at N side = 16, we use the data designated "lowT,P", as defined for the low-Planck likelihood for isotropic models  (Planck Collaboration XI 2016; Planck Collaboration XIII 2016) : lowP polarization maps based on the LFI 70 GHz channel and lowT temperature maps created by the Commander component separation method, along with the appropriate mask and noise covariance matrix. As in Planck Collaboration XXVI (2014), the intensity noise contribution is negligible on these scales, and diagonal regularizing noise with variance σ 2 I = 4 µK 2 has therefore been added to the intensity portion of the noise covariance matrix.
More details on the numerical implementation of the algorithm can be found in  Bielewicz & Banday (2011)  and  Bielewicz et al. (2012). To draw any conclusions from an analysis based on the statistic S ± max (α), it is very important to correctly estimate the threshold for a statistically significant match of circle pairs. We used 300 Monte Carlo simulations of the Planck SMICA maps processed in the same way as the data to establish the threshold such that fewer than 1 % of simulations would yield a false event. Note that we perform the entire analysis, including the final statistical calibration, separately for temperature and polarization.
Topology For the likelihood analysis of the large angle intensity and polarization data we have generalized the method implemented in Planck Collaboration XXVI (2014) to include polarization. The likelihood, i. e. , the probability to find a combined temperature and polarization data map d with associated noise matrix N given a certain topological model T is then given by P(d|C[Θ C , Θ T , T ], A, ϕ) ∝ 1 √ |AC + N| exp - 1 2 d * (AC + N) -1 d , (6) where now d is a 3N pix -component data vector obtained by concatenation of the (I, Q, U) data sets while C and N are 3N pix × 3N pix theoretical signal and noise covariance matrices, arranged in the block form as C =         C II C IQ C IU C QI C QQ C QU C UI C UQ C UU         , N =         N II N IQ N IU N QI N QQ N QU N UI N UQ N UU        .
The choice of the basis modes and their number N m used for analysis is a compromise between robust invertibility of C + N and the amount of information retained. All the models for which likelihoods are compared must be expanded in the same set of modes. Thus, in Planck Collaboration XXVI (2014) we used the set of eigenmodes of the cut-sky covariance matrix of the fiducial best-fit simply-connected universe, C fid , as the analysis basis, limiting ourselves to the N m modes with the largest eigenvalues. For comparison with the numbers we use, a full-sky temperature map with maximum multipole max has ( max + 1) 2 -4 independent modes (four are removed to account for the unobserved monopole and dipole). The addition of polarization data, with much lower signalto-noise than the temperature, raises a new question: how is the temperature and polarization data mix reflected in the limited basis set we project onto? The most natural choice is the set of eigenmodes of the signal-to-noise matrix C fid N -1 for the fiducial model, and a restriction of the mode set based on signal-to-noise eigenvalues (see, e.
We note that, as discussed in Planck Collaboration XXVI (2014), the ability to detect or rule out a multiply connected topology is insensitive to the values of the cosmological parameters adopted for the calculation of the covariance matrices. In the setting described above, Eq. (  9 ) simplifies to  (10)  where the likelihood at each gridpoint in topological parameter space, Θ T,i , is equal to the probability of obtaining the data given fixed cosmological and topological parameters and a compactification (i. e. , fundamental domain shape and size), marginalized over orientation and amplitude. The calculation therefore reduces to evaluating the Bayesian evidence for a set of gridded topologies. As we focus on cubic torus and slab topologies in this work, we note that the sole topological parameter of interest is the size of the fundamental domain, L.
This test shows that the matched-circle method, contrary to the likelihood method, predominantly exploits the topological signal in the CMB anisotropies at moderate angular scales. We also checked robustness of detection with respect to noise level in order to account for small discrepancies between the noise level in the Planck FFP8 simulations and the 2015 data (Planck Collaboration XII 2016). We repeated the analysis for the high-pass filtered map with added noise with 5 % larger amplitude than for the original map. As we can see in Fig. 6 , the statistic changes negligibly. The intersection of the peaks in the matching statistic with the false detection level estimated for the CMB map corresponding to the simply-connected universe defines the minimum radius of the correlated circles that can be detected for this map.