dataesr/scientific-paragraphs-categorization huggingface dataset:
85) ions of interest, with radiative transitions from n 2 assumed. To go beyond the aforementioned weak-and strong-field approximations, the atomic-physics code MASCB has been developed to generate B-field-dependent atomic-physics quantities. MASCB follows the usual approach in which the N-electron atomic Hamiltonian H is divided into two parts: a separable part in which electrons are supposed to be independent in a central potential, and a corrective part that is treated using perturbation theory. In this framework, multi-electron atomic states appear formally as a combination of Slater determinants. This means that the matrix elements of H, J 2 , and J z must be calculated, and the eigenvectors of these operators obtained after diagonalization are the eigenstates of the atomic system. After identifying the useful (i.
VI. CONCLUSION Atomic structure can be used to characterize magnetized plasmas because hydrogen and multi-ionized-atom line emissions broaden and become polarized under strong B-fields. In this paper, the main features of the SZ line-shape code PPPB were presented through various applications related to strongly magnetized plasmas encountered in either astrophysics or the laboratory. PPPB allows calculations over a wide range of plasma conditions and is sufficiently fast to provide line shapes for use in radiation transport codes. The Zeeman effect in intermediate coupling is accounted for by the atomic-physics code MASCB that generates B-field-dependent atomic-physics quantities. Investigations of hydrogen line series in highly magnetized astrophysical plasmas have shown that the quadratic Zeeman terms give rise to additional structures and to a global shift that increases with the PQN.
Moreover, all these analyses assume a dependence of the effects on redshift which was conjectured in the pioneering paper by  [39] ; however as theorists acquire the ability to test the Jacob-Piran conjecture in explicit models it is often found that other forms of redshift dependence apply (see e. g. [62] ). In our opinion, given the importance of the question, a direct robust measurement cannot be based on the analysis of a single object and a robust statistical analysis of a rich sample of data is required, in which the natural direct timescale of the LIV-induced delays in the gamma-ray band (one microsecond) is thoroughly searched. None of the experiments discussed above had the right combination of time resolution and collecting area to effectively scrutinise this regime.
Alternatively, Silicon Drift Detectors (SDDs) can be used to read out the scintillation light with timing capabilities of the order of tens of nanoseconds. Despite their relatively lower response to light pulses, SDDs have several advantages with respect to Si-PM, namely their greater robustness against radiation environment and higher efficiency (90% vs. 20-30%). Both types of devices, when optically coupled to the above mentioned scintillators, allow efficient detection of X-rays down to ∼ 10 keV and even below. The criteria for the choice of the photodetector can take into account the dimensions and robustness of the device, its ageing in the space radiation environment, and the availability for mass production. The architecture of each GrailQuest detector sub-unit is modular, with modules of a few square centimeters of geometric area each.
The whole detector is then assembled to the necessary size by adding modules, which will also ease the processing of intense impulsive events by reducing the pile-up of signals in any given module. The planning of the ESA Science Programme Voyage 2050 relies on the public discussion of open scientific questions of paramount importance for advancing our understanding of the Laws of Nature, that can be addressed by a scientific space mission within the Voyage 2050 planning cycle, covering the period from 2035 to 2050. As a part of the ESA Science Programme Voyage 2050, a new high-energy mission concept named GrailQuest (Gamma Ray Astronomy International Laboratory for QUantum Exploration of Space-Time) has been presented in this paper. The main scientific objectives that the mission aims to address are the following: i) to localise GRB prompt emission with an accuracy of a few arcseconds.
The HERMES pathfinder experiment will test fast timing techniques that are at the core of the GrailQuest project. The design performance of the HER-MES pathfinder detectors guarantee a temporal resolution of 300 nanoseconds, 5-10 times better than most current and past GRB experiments. The HERMES pathfinder is funded by the Italian Space Agency and by the European Community through the HERMES-SP H2020 SPACE grant. More information on the HERMES pathfinder can be found at www. hermes-sp. eu and hermes. dsf. unica. it.
Acknowledgements Some of the authors wish to thank  ASI  and  INAF  (agreements  ASI-UNI-Ca 2016-13-U. O  and  ASI-INAF 2018-10-hh. 0 ), MIUR, Italy  ( HERMES-TP  project) and  EU (HERMES-SP Horizon 2020 Research and Innovation Project  under grant agreement  821896 ) for financial support within the  HERMES  project.
Also, the rigorous theoretical approach of the SSCHA yields a clear distinction between auxiliary phonons of the theory and the phonon spectra probed experimentally, which can be accessed from a rigorous dynamical extension of the theory  [23, 38, 39]. Lastly, the code provides non-perturbative third-and fourth-order phonon-phonon scattering matrices that can be fed in any external thermal transport code to compute thermal conductivity and lattice transport properties. Here, we present an implementation of the full SSCHA theory in a modular Python software that can be easily and efficiently interfaced with any total-energy-force engine, e. g. , density-functional-theory (DFT) first-principles codes. This paper is organized to introduce the reader to the SSCHA algorithm and to review the recent developments in the SSCHA theory that lead to the SSCHA code, following the typical usage of the final user.
In Sec. II we give a simple overview of the method, presenting a simple picture of how it works with a model calculation on a highly anharmonic system with one particle in one dimension. Then, we review the full theory of the SSCHA in details, starting from the free energy calculation and structure optimization in Sec. III. Then, we describe, in Sec. IV, the post-processing features of the code, which include calculations of the free energy Hessian for secondorder phase transitions, as well as phonon spectral function and linewidth calculations. Each section is introduced by an overview of the theory to understand what the code is doing and, then, reports the details of the implementation, together with a guide for setting up a typical run. In Sec. V, specific details of the Python code are provided, including the different execution modes and installation tips.
V. THE PYTHON CODE Two different Python libraries are provided with the SSCHA code: CellConstructor and Python-sscha. The latter is the library that performs the SSCHA minimization itself, while the former is a library that deals with the dynamical matrix, the crystal structure, the symmetrization, and performs the calculation of phonon spectral functions and linewidths as a post-processing tool. The SSCHA code allows to set up the calculations with a simple Python script. In the standard calculation, the script loads the starting dynamical matrices; sets up the ensemble and the parameters for the SSCHA run; performs the calculations of the Born-Oppenheimer energies, forces, and stress tensors on the configurations in the ensemble by calling to a external total-energy-force engine; and starts the minimization of the free energy.
A simple input script that performs all these steps requires less than 20 lines. Examples are provided within the code, as well as step-by-step tutorials to perform a full SSCHA calculation starting just with the structure in a cif file. Python scripting the SSCHA run makes it versatile, as it can be interfaced with other Python libraries to facilitate the analysis of the results. As an alternative, it is also possible to write an input file and run the SSCHA code as a stand-alone command-line program.
A. Code structure Most of the program is written in python with an object-oriented style. The system status (density matrix) is described by a class defined in CellConstructor (Phonons), that contains all the information about the system, including lattice parameters, atomic positions, and the auxiliary force-constant matrix (plus eventual extra data, as effective charges used for post-processing purposes). Methods of this class allow the user to impose symmetries on the system, constrain the auxiliary force to be positive definite (Eq. 32), extract auxiliary phonon frequencies and polarization vectors, or interpolate them to other points in the Brillouin zone. All the calculations related to the SSCHA averages are performed by the Ensemble class (inside Python-sscha). This class generates and stores all the randomly displaced ionic configurations, and can submit or load the results of the energy, forces, and stress tensors calculations.
It also computes the quantities related to averages on the ensemble, as the free energy, the gradients, the stress tensor, and the free energy Hessian. Finally there are other classes, which employ the ensemble and perform the minimization of the free energy, take care of communicating with a remote cluster to run the calculation of forces and energies (see next section), and manage the post-processing to compute the spectral function (the full description of them is provided within the documentation of the code). Most of the code is written in Python, however, the heaviest CPU-intensive calculation is written in Fortran and interfaced with python through the f2py utility provided by numpy  [56]. In particular, the calculation of the free energy gradient, the free energy hessian, the spectral functions, the interpolation, and the symmetrization are performed by a Fortran module compiled with the code.
For this reason, it is possible to exploit the efficient parallelization already implemented by the chosen software. For example, the widely used Quantum ESPRESSO package recently implemented also a hybrid parallelization that exploits together multithreading (OpenMP), multiprocessing (MPI), and GPU (CUDA) parallelization  [57]. In this way the SSCHA code stands on the shoulders of giants, exploiting the most efficient parallelization available today. All other steps of the code are generally computationally very cheap compared to the energy and force calculation, especially when an ab initio approach is followed. The SSCHA minimization cannot exploit so well the possibilities offered by parallelization, since each step of the main cycle depends on the previous one. Most of the computations executed in the cycle are linear algebra calculations carried out with the numpy library  [56] , some of them speeded up with an explicit Fortran implementation.
Thanks to the numpy implementation  [58] , if this library is correctly compiled, the linear algebra calculations will exploit multi-threading. For this reason, the best performances of the SSCHA are obtained by executing the ab initio calculations on an HPC facility, while the SSCHA minimization on a commercial workstation in which the minimization can take few seconds. Post-processing calculations, like the free energy Hessian and the phonon dynamical spectral functions, may be executed with additional Python scripts after the end of the SSCHA run. The calculation of the free energy Hessian has been parallelized with OpenMP (multi-threading), while the calculation of the spectral functions, which may require a dense k-point grid for the interpolation, exploits multiprocessor parallelization through MPI (both mpi4py and pypar can be used  [59] [60] [61] ).
After, it is up to the user to decide whether to start a new population or not. In this sense, the manual mode does not require direct interaction between the SSCHA code and any other external software, and consequently this execution mode does not require the installation of the SSCHA code on an HPC facility. In the local automatic mode that can be scripted in Python, the code has to be supplied with an interface to an external code that is able to compute atomic forces and energies. This can be done through the Atomic Simulation Environment (ASE) library  [62] , which already implements interfaces with most common ab initio codes like Quantum ESPRESSO  [63, 64] , VASP  [65] , SIESTA  [66] , CP2K  [67] , and many more. Force-field codes like LAMMPS  [68]  may also be used. In this execution mode, the code will proceed automatically to perform the calculations locally, and the full flowchart in Figure  2  is executed without requiring any direct interaction with the user.
D. Distribution The packages is distributed as a standard Python application, and can be installed with a setup. py script. Since parts of the code are written in Fortran and C, it requires the appropriate compilers with LAPACK and BLAS libraries to be installed. Part of the Fortran subroutines are modified versions of Quantum ESPRESSO subroutines from the PHonon package, especially those regarding the symmetries. Together with the github page, we also provide the stable release in the pip repository, to facilitate installation. A different setup. py script is provided to facilitate the installation of the package on clusters to fully exploit MPI parallelization for the post-processing. The code is documented with Sphinx. We release the package and the source code under the GPLv3 license.
7  we illustrate the convergence for a phonon linewidth 2Γ µ (q) with respect to the δ se parameter and the k-mesh summation grid in Eq. (75). All the data of this simulation has been obtained in less than one hour, using a single on a laptop, proving the high-efficiency of the SSCHA package, which is beyond standard molecular dynamics software. We provide in the additional materials the Python scripts to run and analyze all the simulations here reported in this example.
VIII. CONCLUSIONS We present here the implementation of the SSCHA theory into an efficient modular Python code, which can be run in conjunction with other Python modules and interfaced with HPC clusters for the Born-Oppenheimer total energy, force, and stress tensor calculations needed. The SSCHA provides an efficient way of calculating the effect of ionic quantum and/or thermal fluctuations on the free energy, as well as their impact on the atomic positions. It is a unique feature of the SSCHA to optimize the atomic positions, including the lattice degrees of freedom, by considering quantum and finite temperature fluctuations and without any approximation on the Born-Oppenheimer energy landscape. As a postprocessing, it calculates the free energy Hessian, which allows to infer the thermodynamic conditions at which second-order phase transitions occur.
These matrices are reported in Refs. [87] [88] [89]. To find the symmetries given the structure, we wrapped into the SSCHA the symmetry module of Quantum ESPRESSO  [63, 64]. This operation is performed also on the gradient of the dynamical matrix each time it is computed. Since the dynamical matrices satisfying the symmetries define a linear subspace, if both the gradient and the original dynamical matrix belong to this subspace, any linear combination of them will also satisfy the symmetry constrains. Thus, it is necessary to symmetrize the dynamical matrix once at the beginning, and then apply the symmetry constrains only to the gradient to preserve the symmetries in the whole simulation. The symmetry module from Quantum ESPRESSO only recognizes symmetries when the unit cell is the primitive one.
Sometimes, it could be convenient to choose a different unit cell. Therefore, we also interfaced the SSCHA code with the spglib package  [90]  to improve the identification of symmetries. Instead of working in the unit cell in q space, spglib provides the symmetry operations in real space. In this case, the SSCHA code divides the symmetry matrices identified by spglib into pure translations and point group operations. Then, symmetries are enforced in real space by first imposing pure translations, followed by point group operations as Φ = 1 N S N S i=1 T Ŝi ΦT † Ŝi. (D2) Then, the permutation symmetry on the indices is imposed. Finally, the code transforms back the real space dynamical matrix (or the gradient) in q space. This operation takes more time than the symmetrization in q space, as it is performed in the supercell.
ACKNOWLEDGEMENTS R. B. and I. E. acknowledge funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant no. 802533 ). M. C. acknowledges support from  Agence Nationale de la Recherche  (Grant No. ANR-19-CE24-0028 ). R. B. thanks  L. Paulatto  for illuminating discussions.
The experimental design of EUREC 4 A involved 85 dropsonde circles from aircraft flights combined with regular around-the-clock upper-air observations from surface-launched radiosondes. The regular sampling from surface-launched radiosondes complemented the mesoscale vertical velocity measurements from dropsonde circles by continuously measuring timeheight profiles of the atmosphere, synoptic variability for an extended time period, and diurnal variability. Radiosondes sampled when research aircraft were not flying, notably at night. This article introduces the radiosonde observations and their resulting data sets. Other measurements, including the dropsonde data, are described in the overview paper by  Stevens et al. (2021)  and the references therein. Between 8 January and 19 February 2020, 811 radiosondes were launched from Barbados and the northwestern tropical Atlantic Ocean east of Barbados.
, 2016). Four research vessels launched radiosondes over the northwestern tropical Atlantic east of Barbados (6-16 • N, 51-60 • W) during EUREC 4 A: two German research vessels, Maria S. Merian (hereafter Merian) and Meteor; a French research vessel, L'Atalante (hereafter Atalante); and a United States research vessel, Ronald H. Brown (hereafter Brown). The BCO and the research vessels all measured surface meteorology and deployed various other measurements for remote sensing of clouds and the atmospheric boundary layer. In Sect. 2 we describe the measurement strategy for the coordinated EUREC 4 A radiosonde network, the data collection procedures for each platform, and the post-processing steps that were applied to create the final data set. Section 3 shows an overview and some characteristics of the data and is followed by a summary in Sect.
3 • N, -57. 7 • E (Fig. 2c ). Dropsondes were deployed along the circle to estimate the area-averaged mass divergence, as described in  Bony and Stevens (2019). To sample larger scales than represented by this circle, we aimed at 4-hourly soundings from all five stations while platforms were separated by more than 200 km. The launch frequency was reduced when such a sep- aration could not be maintained or when vessels left the key region of the network, i. e. , moved south of 12 • N. These scenarios occurred from time to time in order to support other measurements. Figure  4  shows that the network sampled large scales for 30 consecutive days. To increase the number of vertical profiles, we recorded the ascent as well as the descent of the radiosondes. For descending soundings the raw data near the surface are missing as the signal is lost due to Earth's curvature at 300-800 m above mean sea level.
The median of the lowest descent measurement is 340 m. Except for Brown, balloons were equipped with parachutes, which nearly match fall speeds in the middle and lower troposphere to balloon ascent speeds. Given that a typical ascent takes about 90 min, a radiosonde was sampling the air somewhere close to each platform nearly continuously during regular operation. The horizontal drift of the sondes is shown in Fig. 3  for the example of the BCO. All platforms deployed Vaisala RS41-SGP radiosondes -which measure wind, temperature, relative humidity, and pressure -and used Vaisala MW41 ground station software to record and process the sounding data. The software versions of the MW41 system are given in Table  1  for each platform. Basic algorithms and data processing did not change between these versions.
R/V Meteor Meteor launched 203 sondes and collected data for 167 descents during the EUREC 4 A core period (8 January to 19 February). Eight additional ascents and descents were recorded after 20 February. Radiosondes were prepared inside a laboratory on the top deck of the ship with the antenna placed on the roof. Before 9 February the soundings were launched from the container of the German Weather Service (DWD) on the port side at the stern of the ship (Fig. 5b ). This container had a marker to indicate the optimum fill level of the balloons. On 9 February the DWD launcher broke, and a launcher of the type shown in Fig. 5a  was used, located at the stern of the ship. An awning over the balloon indicated the fill level. Ground data were obtained from onboard instruments of the DWD. In addition to sondes launched by the EUREC 4 A science crew, the DWD launched one radiosonde per day.
The 31 ascending DWD sondes launched during the EUREC 4 A core period, plus an additional eight after 20 February, are included in the Level 1 and Level 2 data sets, described in Sect. 2. 3. By mistake, the heights of the pressure sensor, the GPS antenna, and the launching altitude were incorrectly entered at the beginning of the cruise. In addition, we noticed large delays between the time at which surface measurements were entered and the launch. Therefore, we reprocessed the raw data using the MW41 software, after correcting the sensor heights and surface data in the raw files. This post-processing is lossless, and the reprocessed data have the same quality standard as the data from the other platforms. We included both the original and reprocessed Level 0 data in the data set. Table  1.
R/V Ronald H. Brown (Brown) Brown released 169 sondes and collected data for 158 descents. The radiosondes were initialized and ground-checked inside an air-conditioned laboratory. Near-surface measurements were recorded from the ship's meteorological sensors via the ship computer system display. The ground station antenna was located on the aft 02 deck railing above the staging bay. Initialized radiosonde sensor packages were placed for 1-5 min on the main deck to equilibrate to ambient environmental conditions and check GPS reception and telemetry. The balloons were filled by hand in the staging bay (Fig. 5d ), which was mostly sheltered. Operators avoided unnecessary contact with the balloon body but restrained it by hand if the wind was strong. On leg 1 (8-24 January) at night, less helium was used to reduce the buoyancy of the balloons in order to achieve lower ascent rates and better resolve the fine-scale vertical structure of the atmosphere.
5c ). The helium fill level was decided by inflating the balloon until it reached the upper edge of the launch container. During the day, temperatures in the container rose considerably higher than ambient, but the container was well ventilated as the launch was prepared, such that the instruments experienced typical temperatures of 28-31 • C during synchronization, with only few exceptions. Nonetheless, the residual warming could be a source of bias relative to the surface meteorology observations and persist for tens of meters after the launch. Near-surface data were taken from ship measurements.