### Machine Learning Regularized Solution of the Lippmann-Schwinger Equation

Solution of the discretized Lippmann-Schwinger equation in the spatial frequency domain involves the inversion of a linear operator specified by the scattering potential. To regularize this inevitably ill-conditioned problem, we propose a machine learning approach: a recurrent neural network with long short-term memory (LSTM) and with the null space projection of the Lippmann-Schwinger kernel on the recurrence path. The learning method is trained using examples of typical scattering potentials and their corresponding scattered fields. We test the proposed method in two cases: electromagnetic scattering by dielectric objects, and electron scattering by multiple screened Coulomb potentials. In both cases the solutions to test examples, disjoint from the training set, were obtained with fewer iterations and were accurate compared to linear solvers. We also observed surprising generalization ability: in the electromagnetic case, an LSTM trained with random arrangements of dielectric spheres was able to obtain the correct solutions for general topologically similar objects, such as polygons. This suggests that the LSTM successfully incorporates the physics of scattering into the inversion algorithm.

### Diagnostic data integration using deep neural networks for real-time plasma analysis

Recent advances in acquisition equipment is providing experiments with growing amounts of precise yet affordable sensors. At the same time an improved computational power, coming from new hardware resources (GPU, FPGA, ACAP), has been made available at relatively low costs. This led us to explore the possibility of completely renewing the chain of acquisition for a fusion experiment, where many high-rate sources of data, coming from different diagnostics, can be combined in a wide framework of algorithms. If on one hand adding new data sources with different diagnostics enriches our knowledge about physical aspects, on the other hand the dimensions of the overall model grow, making relations among variables more and more opaque. A new approach for the integration of such heterogeneous diagnostics, based on composition of deep \textit{variational autoencoders}, could ease this problem, acting as a structural sparse regularizer. This has been applied to RFX-mod experiment data, integrating the soft X-ray linear images of plasma temperature with the magnetic state. However to ensure a real-time signal analysis, those algorithmic techniques must be adapted to run in well suited hardware. In particular it is shown that, attempting a quantization of neurons transfer functions, such models can be modified to create an embedded firmware. This firmware, approximating the deep inference model to a set of simple operations, fits well with the simple logic units that are largely abundant in FPGAs. This is the key factor that permits the use of affordable hardware with complex deep neural topology and operates them in real-time.

### Observation of an accidental bound state in the continuum in a chain of dielectric disks

Being a general wave phenomenon, bound states in the continuum (BICs) appear in acoustic, hydrodynamic, and photonic systems of various dimensionalities. Here, we report the first experimental observation of an accidental electromagnetic BIC in a one-dimensional periodic chain of coaxial ceramic disks. We show that the accidental BIC manifests itself as a narrow peak in the transmission spectra of the chain placed between two loop antennas. We demonstrate a linear growth of the radiative quality factor of the BICs with the number of disks that is well-described with a tight-binding model. We estimate the number of the disks when the radiation losses become negligible in comparison to material absorption and, therefore, the chain can be considered practically as infinite. The presented analysis is supported by near-field measurements of the BIC profile. The obtained results provide useful guidelines for practical implementations of structures with BICs opening new horizons for the development of radio-frequency and optical metadevices.

### Self-assembling kinetics: Accessing a new design space via differentiable statistical-physics models

The inverse problem of designing component interactions to target emergent structure is fundamental to numerous applications in biotechnology, materials science, and statistical physics. Equally important is the inverse problem of designing emergent kinetics, but this has received considerably less attention. Using recent advances in automatic differentiation, we show how kinetic pathways can be precisely designed by directly differentiating through statistical-physics models, namely free energy calculations and molecular dynamics simulations. We consider two systems that are crucial to our understanding of structural self-assembly: bulk crystallization and small nanoclusters. In each case we are able to assemble precise dynamical features. Using gradient information, we manipulate interactions among constituent particles to tune the rate at which these systems yield specific structures of interest. Moreover, we use this approach to learn non-trivial features about the high-dimensional design space, allowing us to accurately predict when multiple kinetic features can be simultaneously and independently controlled. These results provide a concrete and generalizable foundation for studying non-structural self-assembly, including kinetic properties as well as other complex emergent properties, in a vast array of systems.

### Extrapolation in an implicit many-body expansion: Protonated water neural network potential applied to the extended Zundel cation

A previously published neural network potential for the description of protonated water clusters up to the protonated water tetramer, H$^+$(H$_2$O)$_4$, at essentially converged coupled cluster accuracy (J. Chem. Theory Comput. 16, 88 (2020)) is applied to the protonated water hexamer, H$^+$(H$_2$O)$_6$, in its extended Zundel conformation -- a system that the neural network has never seen before. Although being in the extrapolation regime, it is shown that the potential not only allows for stable quantum simulations from ultra-low temperatures $\sim$1 K up to 100 K but that it is able to describe the new system very accurately compared to explicit coupled cluster calculations. Compared to the interpolation regime the quality of the model is reduced by roughly one order of magnitude, but most of the difference to the coupled cluster reference comes from global shifts of the potential energy surface, while local energy fluctuations are well recovered. These results suggest that the application of neural network potentials in extrapolation regimes can provide useful results and might be more general than usually thought.

### On the algebraic definition of total rotation in RSA

Total rotation is a quantity that has been used for years in RSA. However, its definition has no mathematical sense, since the Euler angles do not form a vector space, since angles cannot define a multiplication group. With this work I tried to give a mathematical definition of the total rotation connecting the Euler description of the rotations with the helical axis. The approximation for small angles was used to connect Euler's angles and helical angle. With this approximation Euler angles acquire the properties of a vector space and it is possible to justify the meaning of this parameter. Validation test showed that total rotation has an approximation error between 5\% and 7\% for angles in the range $\left[-\frac{\pi}{6}, \frac{\pi}{6} \right]$. Since usually RSA uses smaller angle ranges, the approximation is perfectly suitable for use in RSA.

### Novel imaging technique for $α$-particles using a fast optical camera

A new imaging technique for $\alpha$-particles using a fast optical camera focused on a thin scintillator is presented. As $\alpha$-particles interact in a thin layer of LYSO fast scintillator, they produce a localized flash of light. The light is collected with a lens to an intensified optical camera, Tpx3Cam, with single photon sensitivity and excellent spatial & temporal resolutions. The interactions of photons with the camera is reconstructed by means of a custom algorithm, capable of discriminating single photons using time and spatial information.

### Wave-particle energy transfer directly observed in an ion cyclotron wave

Context. The first studies with Parker Solar Probe (PSP) data have made significant progress toward the understanding of the fundamental properties of ion cyclotron waves in the inner heliosphere. The survey mode particle measurements of PSP, however, did not make it possible to measure the coupling between electromagnetic fields and particles on the time scale of the wave periods. Aims. We present a novel approach to study wave-particle energy exchange with PSP. Methods. We use the Flux Angle operation mode of the Solar Probe Cup in conjunction with the electric field measurements and present a case study when the Flux Angle mode measured the direct interaction of the proton velocity distribution with an ion cyclotron wave. Results. Our results suggest that the energy transfer from fields to particles on the timescale of a cyclotron period is equal to approximately 3-6% of the electromagnetic energy flux. This rate is consistent with the hypothesis that the ion cyclotron wave was locally generated in the solar wind.

### Identifying Entangled Physics Relationships through Sparse Matrix Decomposition to Inform Plasma Fusion Design

A sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulations codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g. yield, shape) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield such as picket power and laser energy, variables that represent a dramatic change of the ICF design such as number of pulse steps are also very important. The obtained sparse components are then used to train a random forest (RF) surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF surrogate trained using all design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulations results.

### Analysis of high-order velocity moments in a strained channel flow

In the current study, model expressions for fifth-order velocity moments obtained from the truncated Gram-Charlier series expansions model for a turbulent flow field probability density function are validated using data from direct numerical simulation (DNS) of a planar turbulent flow in a strained channel. Simplicity of the model expressions, the lack of unknown coefficients, and their applicability to non-Gaussian turbulent flows make this approach attractive to use for closing turbulent models based on the Reynolds-averaged Navier-Stokes equations. The study confirms validity of the model expressions. It also shows that the imposed flow strain improves agreement between the model and DNS profiles for the fifth-order moments in the flow buffer zone including when the flow separates. The results of investigation of this phenomenon reveal sensitivity of odd velocity moments to the grid resolution. A new length scale is proposed as a criterion for the grid generation near walls and other areas of high velocity gradients when higher-order statistics are collected from DNS.

### Uncertainty Relations in Hydrodynamics

The uncertainty relations in hydrodynamics are numerically studied. We first give a review for the formulation of the generalized uncertainty relations in the stochastic variational method (SVM), following the paper by two of the present authors [Phys. Lett. A382, 1472 (2018)]. In this approach, the origin of the finite minimum value of uncertainty is attributed to the non-differentiable (virtual) trajectory of a quantum particle and then both of the Kennard and Robertson-Schr\"{o}dinger inequalities in quantum mechanics are reproduced. The same non-differentiable trajectory is applied to the motion of fluid elements in hydrodynamics. By introducing the standard deviations of position and momentum for fluid elements, the uncertainty relations in hydrodynamics are derived. These are applicable even to the Gross-Pitaevskii equation and then the field-theoretical uncertainty relation is reproduced. We further investigate numerically the derived relations and find that the behaviors of the uncertainty relations for liquid and gas are qualitatively different. This suggests that the uncertainty relations in hydrodynamics are used as a criterion to classify liquid and gas in fluid.

### Simulation of detection and scattering of sound waves by the lateral line of a fish

An explicitly solvable model of sound sources detection and sound wave scattering by the lateral line of a fish or amphibian based on the theory of self-adjoint perturbations of the Laplace operator by arrays of additional boundary conditions at isolated points is proposed and discussed.

### Frequency comb generation in a pulse-pumped normal dispersion Kerr mini-resonator

Kerr microresonators driven in the normal dispersion regime typically require the presence of localized dispersion perturbations, such as those induced by avoided mode crossings, to initiate the formation of optical frequency combs. In this work, we experimentally demonstrate that this requirement can be lifted by driving the resonator with a pulsed pump source. We also show that controlling the desynchronization between the pump repetition rate and the cavity free-spectral range (FSR) provides a simple mechanism to tune the center frequency of the output comb. Using a fiber mini-resonator with a radius of only 6 cm we experimentally present spectrally flat combs with a bandwidth of 3 THz whose center frequency can be tuned by more than 2 THz. By driving the cavity at harmonics of its 0.54 GHz FSR, we are able to generate combs with line spacings selectable between 0.54 and 10.8 GHz. The ability to tune both the center frequency and frequency spacing of the output comb highlights the flexibility of this platform. Additionally, we demonstrate that under conditions of large pump-cavity desynchronization, the same cavity also supports a new form of Raman-assisted anomalous dispersion cavity soliton.

### Simulating Plasmon Resonances of Gold Nanoparticles with Bipyramidal Shapes by Boundary Element Methods

Computational modeling and accurate simulations of localized surface plasmon resonance (LSPR) absorption properties are reported for gold nanobipyramids (GNBs), a class of metal nanoparticle that features highly tunable, geometrydependent optical properties. GNB bicone models with spherical tips performed best in reproducing experimental LSPR spectra while the comparison with other geometrical models provided a fundamental understanding of base shapes and tip effects on the optical properties of GNBs. Our results demonstrated the importance of averaging all geometrical parameters determined from transmission electron microscopy images to build representative models of GNBs. By assessing the performances of LSPR absorption spectra simulations based on a quasi-static approximation, we provided an applicability range of this approach as a function of the nanoparticle size, paving the way to the theoretical study of the coupling between molecular electron densities and metal nanoparticles in GNB-based nanohybrid systems, with potential applications in the design of nanomaterials for bioimaging, optics and photocatalysis.

### Machine learning assisted non-destructive transverse beam profile imaging

We present a non-destructive beam profile imaging concept that utilizes machine learning tools, namely genetic algorithm with a gradient descent-like minimization. Electromagnetic fields around a charged beam carry information about its transverse profile. The electrodes of a stripline-type beam position monitor (with eight probes in this study) can pick up that information for visualization of the beam profile. We use a genetic algorithm to transform an arbitrary Gaussian beam in such a way that it eventually reconstructs the transverse position and the shape of the original beam. The algorithm requires a signal that is picked up by the stripline electrodes, and a (precise or approximate) knowledge of the beam size. It can visualize the profile of fairly distorted beams as well.

### Compact transportable 171Yb+ single-ion optical fully automated clock with 4.9E-16 relative instability

The paper describes the results achieved in the development of the compact transportable fully automated optical clock based on a single 171Yb+ ion in a radiofrequency (RF) quadrupole trap. The resulted measurements demonstrated the 4.9E-16 output RF signal relative instability on 1000 s integration time with 298.1 kg weight, 0.921 volume, and 2.766 kW input power consumption of the device. A transformation of the ultrastable optical signal into the RF range was performed via the optical frequency comb with a supercontinuum fiber laser generator. The transformation was conducted without loss of initial stability and accuracy characteristics of the signal.

### A marine radioisotope gamma-ray spectrum analysis method based on Monte Carlo simulation and MLP neural network

A multilayer perceptron (MLP) neural network is built to analyze the Cs-137 concentration in seawater via gamma-ray spectrums measured by a LaBr3 detector. The MLP is trained and tested by a large data set generated by combining measured and Monte Carlo simulated spectrums under the assumption that all the measured spectrums have 0 Cs-137 concentration. And the performance of MLP is evaluated and compared with the traditional net-peak area method. The results show an improvement of 7% in accuracy and 0.036 in the ROC-curve area compared to those of the net peak area method. And the influence of the assumption of Cs-137 concentration in the training data set on the classifying performance of MLP is evaluated.

### The Raspberry Pi Auto-aligner: Machine Learning for Automated Alignment of Laser Beams

We present a novel solution to automated beam alignment optimization. This device is based on a Raspberry Pi computer, stepper motors, commercial optomechanics and electronic devices, and the open source machine learning algorithm M-LOOP. We provide schematic drawings for the custom hardware necessary to operate the device and discuss diagnostic techniques to determine the performance. The beam auto-aligning device has been used to improve the alignment of a laser beam into a single-mode optical fiber from manually optimized fiber alignment with an iteration time of typically 20~minutes. We present example data of one such measurement to illustrate device performance.

### Fast Rossi-alpha Measurements of Plutonium using Organic Scintillators

In this work, Rossi-alpha measurements were simultaneously performed with a $^3$He-based detection system and an organic scintillator-based detection system. The assembly is 15 kg of plutonium (93 wt$\%$ $^{239}$Pu) reflected by copper and moderated by lead. The goal of Rossi-alpha measurements is to estimate the prompt neutron decay constant, alpha. Simulations estimate $k_\text{eff}$ = 0.624 and $\alpha$ = 52.3 $\pm$ 2.5 ns for the measured assembly. The organic scintillator system estimated $\alpha$ = 47.4 $\pm$ 2.0 ns, having a 9.37$\%$ error (though the 1.09 standard deviation confidence intervals overlapped). The $^3$He system estimated $\alpha$ = 37 $\mu$s. The known slowing down time of the $^3$He system is 35-40 $\mu$s, which means the slowing down time dominates and obscures the prompt neutron decay constant. Subsequently, the organic scintillator system should be used for assemblies with alpha much less than 35 $\mu$s.

### Historical Context, Scientific Context, and Translation of Haidinger's (1844) Discovery of Naked-Eye Visibility of the Polarization of Light

In 1844, the Austrian mineralogist Wilhelm von Haidinger reported he could see the polarization of light with the naked eye. It appears as a faint, blurry, transient, yellow hourglass shape superimposed on whatever one looks at. It is now commonly called Haidinger's brushes. To our surprise, even though the paper is well cited, we were unable to find a translation of it from its difficult, nineteenth-century German into English. We provide one, with annotations to set the paper into its scientific and historical context.

### [21] 2010.15259

As radiation detector arrays in nuclear physics applications become larger and physically more separated, the time synchronization and trigger distribution between many channels of detector readout electronics become more challenging. Clocks and triggers are traditionally distributed through dedicated cabling, but newer methods such as the IEEE 1588 Precision Time Protocol and White Rabbit allow clock synchronization through the exchange of timing messages over Ethernet. Consequently, we report here the use of White Rabbit in a new detector readout module, the Pixie-Net XL. The White Rabbit core, data capture from multiple digitizing channels, and subsequent pulse processing for pulse height and constant fraction timing are implemented in a Kintex 7 FPGA. The detector data records include White Rabbit time stamps and are transmitted to storage through the White Rabbit core's gigabit Ethernet data path or a slower diagnostic/control link using an embedded Zynq processor. The performance is characterized by time-of-flight style measurements and by time correlation of high energy background events from cosmic showers in detectors separated by longer distances. Software for the Zynq processor can implement "software triggering", for example to limit recording of data to events where a minimum number of channels from multiple modules detect radiation at the same time.

### Designing of strongly confined short-wave Brillouin phonons in silicon waveguide periodic lattices

We propose a feasible waveguide design optimized for harnessing Stimulated Brillouin Scattering with long-lived phonons. The design consists of a fully suspended ridge waveguide surrounded by a 1D phononic crystal that mitigates losses to the substrate while providing the needed homogeneity for the build-up of the optomechanical interaction. The coupling factor of these structures was calculated to be 0.54 (W.m)$^{-1}$ for intramodal backward Brillouin scattering with its fundamental TE-like mode and 4.5(W.m)$^{-1}$ for intramodal forward Brillouin scattering. The addition of the phononic crystal provides a 30 dB attenuation of the mechanical displacement after only five unitary cells, possibly leading to a regime where the acoustic losses are only limited by fabrication. As a result, the total Brillouin gain, which is proportional to the product of the coupling and acoustic quality factors, is nominally equal to the idealized fully suspended waveguide.

### A globally convergent modified Newton method for the direct minimization of the Ohta-Kawasaki energy with application to the directed self-assembly of diblock copolymers

We propose a fast and robust scheme for the direct minimization of the Ohta-Kawasaki energy that characterizes the microphase separation of diblock copolymer melts. The scheme employs a globally convergent modified Newton method with line search which is shown to be mass-conservative, energy-descending, asymptotically quadratically convergent, and three orders of magnitude more efficient than the commonly-used gradient flow approach. The regularity and the first-order condition of minimizers are analyzed. A numerical study of the chemical substrate guided directed self-assembly of diblock copolymer melts, based on a novel polymer-substrate interaction model and the proposed scheme, is provided.

### Optical soliton formation controlled by angle twisting in photonic moiré lattices

Exploration of the impact of synthetic material landscapes featuring tunable geometrical properties on physical processes is a research direction that is currently of great interest because of the outstanding phenomena that are continually being uncovered. Twistronics and the properties of wave excitations in moir\'e lattices are salient examples. Moir\'e patterns bridge the gap between aperiodic structures and perfect crystals, thus opening the door to the exploration of effects accompanying the transition from commensurate to incommensurate phases. Moir\'e patterns have revealed profound effects in graphene-based systems1,2,3,4,5, they are used to manipulate ultracold atoms6,7 and to create gauge potentials8, and are observed in colloidal clusters9. Recently, it was shown that photonic moir\'e lattices enable observation of the two-dimensional localization-to-delocalization transition of light in purely linear systems10,11. Here, we employ moir\'e lattices optically induced in photorefractive nonlinear media12,13,14 to elucidate the formation of optical solitons under different geometrical conditions controlled by the twisting angle between the constitutive sublattices. We observe the formation of solitons in lattices that smoothly transition from fully periodic geometries to aperiodic ones, with threshold properties that are a pristine direct manifestation of flat-band physics11.

### Grid point and time step requirements for wall-resolved large-eddy simulation and direct numerical simulation of a developing turbulent boundary layer

The grid point requirements of Chapman [AIAA J., 17, 1293, (1979)] and Choi and Moin [Phys. Fluid, 24, 011702 (2012)] are refined. We show that the grid requirement for DNS is $N\sim Re_{L_x}^{2.05}$ rather than $N\sim Re_{L_x}^{2.64}$ as suggested by Choi and Moin, where $L_x$ is the length of the plate. In addition, we estimate the time step requirement for DNS, WRLES, and WMLES. Requiring that the convective CFL$\leq 1$ and the diffusive CFL$\leq 1$, the time steps required for converged statistics is $n_t\sim Re_{L_x}/Re_{x_0}^{6/7}$ for WMLES, $n_t\sim Re_{L_x}/Re_{x_0}^{1/7}$ for WRLES and DNS (with different prefactors), where $Re_{x_0}$ is the inlet Reynolds number.

### Improvement of EAST Data Acquisition Configuration Management

The data acquisition console is an important component of the EAST data acquisition system which provides unified data acquisition and long-term data storage for diagnostics. The data acquisition console is used to manage the data acquisition configuration information and control the data acquisition workflow. The data acquisition console has been developed many years, and with increasing of data acquisition nodes and emergence of new control nodes, the function of configuration management has become inadequate. It is going to update the configuration management function of data acquisition console. The upgraded data acquisition console based on LabVIEW should be oriented to the data acquisition administrator, with the functions of managing data acquisition nodes, managing control nodes, setting and publishing configuration parameters, batch management, database backup, monitoring the status of data acquisition nodes, controlling the data acquisition workflow, and shot simulation data acquisition test. The upgraded data acquisition console has been designed and under testing recently.

### High-resolution for IAXO: MMC-based X-ray Detectors

Axion helioscopes like the International Axion Observatory (IAXO) search for evidence of axions and axion-like particles (ALPs) from the Sun. A strong magnetic field is used to convert ALPs into photons via the generic ALP-photon coupling. To observe the resulting photons, X-ray detectors with low background and high efficiency are necessary. In addition, good energy resolution and low energy threshold would allow for investigating the ALP properties by studying the X-ray spectrum after their discovery. We propose to use low temperature metallic magnetic calorimeters (MMCs). Here we present the first detector system based on MMCs developed for IAXO and discuss the results of the characterization. The detector consists of a two-dimensional 64-pixel array covering an active area of 16 mm$^2$ with a filling factor of 93 %. We achieve an average energy resolution of 6.1 eV FWHM allowing for energy thresholds below 100 eV. This detector is the first step towards a larger 1 cm$^2$ array matching the IAXO X-ray optics. We determine the background rate in the energy range between 1 keV and 10 keV to be $3.2(1) \times 10^{-4}$ keV$^{-1}$ cm$^{-2}$ s$^{-1}$ from events acquired over 30 days. During this measurement the detector system was unshielded. In the future, active and passive shields will significantly reduce the background rate. Our results demonstrate that MMCs are a promising technology to discover and study ALPs in helioscopes.

### Inverse centrifugal effect induced by collective motion of vortices in rotating turbulent convection

When a fluid system is subject to strong rotation, centrifugal fluid motion is expected, i.e., denser (lighter) fluid moves outward (inward) from (toward) the axis of rotation. Here we demonstrate, both experimentally and numerically, the existence of an unexpected outward motion of warm and lighter vortices in rotating turbulent convection. This anomalous vortex motion occurs under rapid rotations when the centrifugal buoyancy is sufficiently strong to induce a symmetry-breaking in the vorticity field, i.e., the vorticity of the cold anticyclones overrides that of the warm cyclones. We show that through hydrodynamic interactions the densely populated vortices can self-aggregate into coherent clusters and exhibit collective motion in this flow regime. Interestingly, the correlation of the vortex velocity fluctuations within a cluster is scale-free, with the correlation length being about 30% of the cluster length. Such long-range correlation leads to the collective outward motion of cyclones. Our study provides new understanding of vortex dynamics that are widely present in nature.

### FPGA Based Real-Time Image Manipulation and Advanced Data Acquisition For 2D-XRAY Detectors

Scientific experiments rely on some type of measurements that provides the required data to extract aimed information or conclusions. Data production and analysis are therefore essential components at the heart of any scientific experimental application. Traditionally, efforts on detector development for photon sources have focused on the properties and performance of the detection front-ends. In many cases, the data acquisition chain as well as data processing, are treated as a complementary component of the detector system and added at a late stage of the project. In most of the cases, data processing tasks are entrusted to CPUs; achieving thus the minimum bandwidth requirements and kept hardware relatively simple in term of functionalities. This also minimizes design effort, complexity and implementation cost. This approach is changing in the last years as it does not fit new high-performance detectors; FPGA and GPUs are now used to perform complex image manipulation tasks such as image reconstruction, image rotation, accumulation, filtering, data analysis and many others. This frees up CPUs for simpler tasks. The objective of this paper is to present both the implementation of real time FPGA-based image manipulation techniques, as well as, the performance of the ESRF data acquisition platform called RASHPA, into the back-end board of the SMARTPIX photon-counting detector developed at the ESRF.

### Modeling ionic reactions at interstellar temperatures: the case of NH2- + H2 <--> NH3 + H-

We present in this paper the main structural features and enthalpy details for the energy profiles of the title reactions, both for the exothermic (forward) path to NH$_{3}$ formation and for the endothermic (reverse) reaction to NH$_{2}^{-}$ formation. Both systems have relevance for the nitrogen chemistry in the interstellar medium (ISM). They are also helpful to document the possible role of H$^{-}$ in molecular clouds at temperatures well below room temperature. The structural calculations are carried out using ab initio methods and are further employed to obtain the reaction rates down to the interstellar temperatures detected in earlier experiments. The reaction rates are obtained from the computed Minimum Energy Path (MEP) using the Variational Transition State Theory (VTST) approach. The results indicate very good accord with the experiments at room temperature, while the measured low temperature data down to 8 K are well described once we analyse in detail the physics of the reactions and modify accordingly the VTST approach. This is done by employing a T-dependent scaling, from room temperature conditions down to the lower ISM temperatures, which acknowledges the non-canonical behavior of the fast, barrierless exothermic reaction. This feature was also suggested in the earlier work discussed below in our main text. The physical reasons for the experimental behavior, and the need for improving on the VTST method when used away from room temperatures, are discussed in detail.

### An optically-heated atomic source for compact ion trap vacuum systems

We present a design for an atomic oven suitable for loading ion traps, which is operated via optical heating with a continuous-wave multimode diode laser. The absence of the low-resistance electrical connections necessary for Joule heating allows the oven to be extremely well thermally isolated from the rest of the vacuum system, and for an oven filled with calcium we achieve a number density suitable for rapid ion loading in the target region with ~200 mW of laser power, limited by radiative losses. With simple feedforward to the laser power, the turn-on time for the oven is less than 20 s, while the oven contains enough calcium to operate continuously for many thousands of years without replenishment.

### The rotational influence on solar convection

This paper considers the dominant dynamical, thermal and rotational balances within the solar convection zone. The reasoning is such that: Coriolis forces balance pressure gradients. Background vortex stretching, baroclinic torques and nonlinear advection balance jointly. Turbulent fluxes convey what part of the solar luminosity that radiative diffusion cannot. These four relations determine estimates for the dominant length scales and dynamical amplitudes strictly in terms of known physical quantities. We predict that the dynamical Rossby number for convection is less than unity below the near-surface shear layer, indicating strong rotational constraint. We also predict a characteristic convection length scale of roughly 30 Mm throughout much of the convection zone. These inferences help explain recent observations that reveal weak flow amplitudes at 100-200 Mm scales.

### Quantum gas microscopy for single atom and spin detection

A particular strength of ultracold quantum gases are the versatile detection methods available. Since they are based on atom-light interactions, the whole quantum optics toolbox can be used to tailor the detection process to the specific scientific question to be explored in the experiment. Common methods include time-of-flight measurements to access the momentum distribution of the gas, the use of cavities to monitor global properties of the quantum gas with minimal disturbance and phase-contrast or high-intensity absorption imaging to obtain local real space information in high-density settings. Even the ultimate limit of detecting each and every atom locally has been realized in two-dimensions using so-called quantum gas microscopes. In fact, these microscopes not only revolutionized the detection, but also the control of lattice gases. Here we provide a short overview of this technique, highlighting new observables as well as key experiments that have been enabled by quantum gas microscopy.

### Determination of Young's modulus of active pharmaceutical ingredients by relaxation dynamics at elevated pressures

A new approach is theoretically proposed to study the glass transition of active pharmaceutical ingredients and a glass-forming anisotropic molecular liquid at high pressures. We describe amorphous materials as a fluid of hard spheres. Effects of nearest-neighbor interactions and cooperative motions of particles on glassy dynamics are quantified through a local and collective elastic barrier calculated using the Elastically Collective Nonlinear Langevin Equation theory. Inserting two barriers into Kramer's theory gives structural relaxation time. Then, we formulate a new mapping based on the thermal expansion process under pressure to intercorrelate particle density, temperature, and pressure. This analysis allows us to determine the pressure and temperature dependence of alpha relaxation. From this, we estimate an effective elastic modulus of amorphous materials and capture effects of conformation on the relaxation process. Remarkably, our theoretical results agree well with experiments.

### Dynamical field inference and supersymmetry

Knowledge on evolving physical fields is of paramount importance in science, technology, and economics. Dynamical field inference (DFI) addresses the problem of reconstructing a stochastically driven, dynamically evolving field from finite data. It relies on information field theory (IFT), the information theory for fields. Here, the relations of DFI, IFT, and the recently developed supersymmetric theory of stochastics (STS) are established in a pedagogical discussion. In IFT, field expectation values can be calculated from the partition function of the full space-time inference problem. The partition function of the inference problem invokes a functional Dirac function to guarantee the dynamics, as well as a field-dependent functional determinant, to establish proper normalization, both impeding the necessary evaluation of the path integral over all field configurations. STS replaces these problematic expressions via the introduction of fermionic ghost and bosonic Lagrange fields, respectively. The action of these fields has a supersymmetry, which means there exist an exchange operation between bosons and fermions that leaves the system invariant. In contrast to this, measurements of the dynamical fields do not adhere to this supersymmetry. The supersymmetry can also be broken spontaneously, in which case the system evolves chaotically. This will affect the predictability of the system and thereby make DFI more challenging.

### Excitons in bulk black phosphorus evidenced by photoluminescence at low temperature

Atomic layers of Black Phosphorus (BP) present unique opto-electronic properties dominated by a direct tunable bandgap in a wide spectral range from visible to mid-infrared. In this work, we investigate the infrared photoluminescence of BP single crystals at very low temperature. Near-bandedge recombinations are observed at 2 K, including dominant excitonic transitions at 0.276 eV and a weaker one at 0.278 eV. The free-exciton binding energy is calculated with an anisotropic Wannier-Mott model and found equal to 9.1 meV. On the contrary, the PL intensity quenching of the 0.276 eV peak at high temperature is found with a much smaller activation energy, attributed to the localization of free excitons on a shallow impurity. This analysis leads us to attribute respectively the 0.276 eV and 0.278 eV PL lines to bound excitons and free excitons in BP. As a result, the value of bulk BP bandgap is refined to 0.287 eV at 2K.

### Artificial coherent states of light by multi-photon interference in a single-photon stream

Coherent optical states consist of a quantum superposition of different photon number (Fock) states, but because they do not form an orthogonal basis, no photon number states can be obtained from it by linear optics. Here we demonstrate the reverse, by manipulating a random continuous single-photon stream using quantum interference in an optical Sagnac loop, we create engineered quantum states of light with tunable photon statistics, including approximately coherent states. We demonstrate this experimentally using a true single-photon stream produced by a semiconductor quantum dot in an optical microcavity, and show that we can obtain light with g2(0)->1 in agreement with our theory, which can only be explained by quantum interference of at least 3 photons. The produced artificial light states are, however, much more complex than coherent states, containing quantum entanglement of photons, making them a resource for multi-photon entanglement.

### Learned infinite elements

We study the numerical solution of scalar time-harmonic wave equations on unbounded domains which can be split into a bounded interior domain of primary interest and an exterior domain with separable geometry. To compute the solution in the interior domain, approximations to the Dirichlet-to-Neumann (DtN) map of the exterior domain have to be imposed as transparent boundary conditions on the artificial coupling boundary. Although the DtN map can be computed by separation of variables, it is a nonlocal operator with dense matrix representations, and hence computationally inefficient. Therefore, approximations of DtN maps by sparse matrices, usually involving additional degrees of freedom, have been studied intensively in the literature using a variety of approaches including different types of infinite elements, local non-reflecting boundary conditions, and perfectly matched layers. The entries of these sparse matrices are derived analytically, e.g. from transformations or asymptotic expansions of solutions to the differential equation in the exterior domain. In contrast, in this paper we propose to `learn' the matrix entries from the DtN map in its separated form by solving an optimization problem as a preprocessing step. Theoretical considerations suggest that the approximation quality of learned infinite elements improves exponentially with increasing number of infinite element degrees of freedom, which is confirmed in numerical experiments. These numerical studies also show that learned infinite elements outperform state-of-the-art methods for the Helmholtz equation. At the same time, learned infinite elements are much more flexible than traditional methods as they, e.g., work similarly well for exterior domains involving strong reflections, for example, for the atmosphere of the Sun, which is strongly inhomogeneous and exhibits reflections at the corona.

### Multi-Constitutive Neural Network for Large Deformation Poromechanics Problem

In this paper, we study the problem of large-strain consolidation in poromechanics with deep neural networks. Given different material properties and different loading conditions, the goal is to predict pore pressure and settlement. We propose a novel method "multi-constitutive neural network" (MCNN) such that one model can solve several different constitutive laws. We introduce a one-hot encoding vector as an additional input vector, which is used to label the constitutive law we wish to solve. Then we build a DNN which takes as input (X, t) along with a constitutive model label and outputs the corresponding solution. It is the first time, to our knowledge, that we can evaluate multi-constitutive laws through only one training process while still obtaining good accuracies. We found that MCNN trained to solve multiple PDEs outperforms individual neural network solvers trained with PDE.

### Chiral edge currents in confined fibrosarcoma cells

During metastatic dissemination, streams of cells collectively migrate through a network of narrow channels within the extracellular matrix, before entering into the blood stream. This strategy is believed to outperform other migration modes, based on the observation that individual cancer cells can take advantage of confinement to switch to an adhesion-independent form of locomotion. Yet, the physical origin of this behaviour has remained elusive and the mechanisms behind the emergence of coherent flows in populations of invading cells under confinement are presently unknown. Here we demonstrate that human fibrosarcoma cells (HT1080) confined in narrow stripe-shaped regions undergo collective migration by virtue of a novel type of topological edge currents, resulting from the interplay between liquid crystalline (nematic) order, microscopic chirality and topological defects. Thanks to a combination of in vitro experiments and theory of active hydrodynamics, we show that, while heterogeneous and chaotic in the bulk of the channel, the spontaneous flow arising in confined populations of HT1080 cells is rectified along the edges, leading to long-ranged collective cell migration, with broken chiral symmetry. These edge currents are fuelled by layers of +1/2 topological defects, orthogonally anchored at the channel walls and acting as local sources of chiral active stress. Our work highlights the profound correlation between confinement and collective migration in multicellular systems and suggests a possible mechanism for the emergence of directed motion in metastatic cancer.

### Limitations of the recall capabilities in delay based reservoir computing systems

We analyze the memory capacity of a delay based reservoir computer with a Hopf normal form as nonlinearity and numerically compute the linear as well as the higher order recall capabilities. A possible physical realisation could be a laser with external cavity, for which the information is fed via electrical injection. A task independent quantification of the computational capability of the reservoir system is done via a complete orthonormal set of basis functions. Our results suggest that even for constant readout dimension the total memory capacity is dependent on the ratio between the information input period, also called the clock cycle, and the time delay in the system. Optimal performance is found for a time delay about 1.6 times the clock cycle

### Identification of complex mixtures for Raman spectroscopy using a novel scheme based on a new multi-label deep neural network

With noisy environment caused by fluoresence and additive white noise as well as complicated spectrum fingerprints, the identification of complex mixture materials remains a major challenge in Raman spectroscopy application. In this paper, we propose a new scheme based on a constant wavelet transform (CWT) and a deep network for classifying complex mixture. The scheme first transforms the noisy Raman spectrum to a two-dimensional scale map using CWT. A multi-label deep neural network model (MDNN) is then applied for classifying material. The proposed model accelerates the feature extraction and expands the feature graph using the global averaging pooling layer. The Sigmoid function is implemented in the last layer of the model. The MDNN model was trained, validated and tested with data collected from the samples prepared from substances in palm oil. During training and validating process, data augmentation is applied to overcome the imbalance of data and enrich the diversity of Raman spectra. From the test results, it is found that the MDNN model outperforms previously proposed deep neural network models in terms of Hamming loss, one error, coverage, ranking loss, average precision, F1 macro averaging and F1 micro averaging, respectively. The average detection time obtained from our model is 5.31 s, which is much faster than the detection time of the previously proposed models.

### Lie-Trotter Splitting for the Nonlinear Stochastic Manakov System

This article analyses the convergence of the Lie-Trotter splitting scheme for the stochastic Manakov equation, a system arising in the study of pulse propagation in randomly birefringent optical fibers. First, we prove that the strong order of the numerical approximation is 1/2 if the nonlinear term in the system is globally Lipschitz. Then, we show that the splitting scheme has convergence order 1/2 in probability and almost sure order 1/2- in the case of a cubic nonlinearity. We provide several numerical experiments illustrating the aforementioned results and the efficiency of the Lie-Trotter splitting scheme. Finally, we numerically investigate the possible blowup of solutions for some power-law nonlinearities.

### Are randomness of behavior and information flow important to opinion forming in organization?

We examine how the randomness of behavior and the flow of information between agents affect the formation of opinions. Our main research involves the process of opinion evolution, opinion clusters formation and studying the probability of sustaining opinion. The results show that opinion formation (clustering of opinion) is influenced by both flow of information between agents (interactions outside the closest neighbors) and randomness in adopting opinions.

### Investigation on a Doubly-Averaged Model for the Molniya Satellites Orbits

The aim of this work is to investigate the lunisolar perturbations affecting the long-term dynamics of a Molniya satellite. Some numerical experiments on the doubly-averaged model, including the expansion of the lunisolar disturbing functions up to the third order, are carried out in order to detect the terms dominating the long-term evolution. The analysis focuses on the following significant indicators: the amplitude of the harmonic coefficients, the periods of the arguments involved and, in particular, the ratio between the amplitudes and the corresponding frequency. The results show that the second-order lunisolar perturbation gives the dominant contribution to the long-term dynamics. The second part of this work aims to study the resonant regions associated to the dominant terms identified so far by using both the ideal resonance model and an alternative approach. The results obtained show when the standard method does not catch the main features of the dynamical structure of the resonant regions. Finally, the maximum overlapping region is identified in the proximity of the Molniya orbital environment.

### A colloquium on the variational method applied to excitons in 2D materials

In this colloquium, we review the research on excitons in van der Waals heterostructures from the point of view of variational calculations. We first make a presentation of the current and past literature, followed by a discussion on the connections between experimental and theoretical results. In particular, we focus our review of the literature on the absorption spectrum and polarizability, as well as the Stark shift and the dissociation rate. Afterwards, we begin the discussion of the use of variational methods in the study of excitons. We initially model the electron-hole interaction as a soft-Coulomb potential, which can be used to describe interlayer excitons. Using an \emph{ansatz}, based on the solution for the two-dimensional quantum harmonic oscillator, we study the Rytova-Keldysh potential, which is appropriate to describe intralayer excitons in two-dimensional (2D) materials. These variational energies are then recalculated with a different \emph{ansatz}, based on the exact wavefunction of the 2D hydrogen atom, and the obtained energy curves are compared. Afterwards, we discuss the Wannier-Mott exciton model, reviewing it briefly before focusing on an application of this model to obtain both the exciton absorption spectrum and the binding energies for certain values of the physical parameters of the materials. Finally, we briefly discuss an approximation of the electron-hole interaction in interlayer excitons as an harmonic potential and the comparison of the obtained results with the existing values from both first--principles calculations and experimental measurements.

### The intensity and evolution of the extreme storms in January 1938

Major solar eruptions occasionally direct interplanetary coronal mass ejections (ICMEs) to Earth and cause significant geomagnetic storms and low-latitude aurorae. While single extreme storms are of significant threats to the modern civilization, storms occasionally appear in sequence and, acting synergistically, cause 'perfect storms' at Earth. The stormy interval in January 1938 was one of such cases. Here, we analyze the contemporary records to reveal its time series on their source active regions, solar eruptions, ICMEs, geomagnetic storms, low-latitude aurorae, and cosmic-ray (CR) variations. Geomagnetic records show that three storms occurred successively on 17/18 January (Dcx ~ -171 nT) on 21/22 January (Dcx ~ -328 nT) and on 25/26 January (Dcx ~ -336 nT). The amplitudes of the cosmic-ray variations and sudden storm commencements show the impact of the first ICME as the largest (~ 6% decrease in CR and 72 nT in SSC) and the ICME associated with the storms that followed as more moderate (~ 3% decrease in CR and 63 nT in SSC; ~ 2% decrease in CR and 63 nT in SSC). Interestingly, a significant solar proton event occurred on 16/17 January and the Cheltenham ionization chamber showed a possible ground level enhancement. During the first storm, aurorae were less visible at mid-latitudes, whereas during the second and third storms, the equatorward boundaries of the auroral oval were extended down to 40.3{\deg} and 40.0{\deg} in invariant latitude. This contrast shows that the initial ICME was probably faster, with a higher total magnitude but a smaller southward component.

### A computational periporomechanics model for localized failure in unsaturated porous media

We implement a computational periporomechanics model for simulating localized failure in unsaturated porous media. The coupled periporomechanics model is based on the peridynamic state concept and the effective force state concept. The coupled governing equations are integral-differential equations without assuming the continuity of solid displacement and fluid pressures. The fluid flow and effective force states are determined by nonlocal fluid pressure and deformation gradients through the recently formulated multiphase constitutive correspondence principle. The coupled peri-poromechanics is implemented numerically for high-performance computing by an implicit multiphase meshfree method utilizing the message passing interface. The numerical implementation is validated by simulating classical poromechanics problems and comparing the numerical results with analytical solutions and experimental data. Numerical examples are presented to demonstrate the robustness of the fully coupled peri-poromechanics in modeling localized failures in unsaturated porous media.

### Momentum Entanglement for Atom Interferometry

The Standard Quantum Limit (SQL) restricts the sensitivity of atom interferometers employing unentangled ensembles. Inertially sensitive light-pulse atom interferometry beyond the SQL requires the preparation of entangled atoms in different momentum states. So far, such a source of entangled atoms that is compatible with state-of-the-art interferometers has not been demonstrated. Here, we report the transfer of entanglement from the spin degree of freedom of a Bose-Einstein condensate to well-separated momentum modes. A measurement of number and phase correlations between the two momentum modes yields a squeezing parameter of -3.1(8) dB. The method is directly applicable for a future generation of entanglement-enhanced atom interferometers as desired for tests of the Einstein Equivalence Principle and the detection of gravitational waves.

### A data processing system for balloon-borne telescopes

The JEM-EUSO Collaboration aims at studying Ultra High Energy Cosmic Rays (UHECR) from space. To reach this goal, a series of pathfinder missions has been developed to prove the observation principle and to raise the technological readiness level of the instrument. Among these, the EUSO-SPB2 (Extreme Universe Space Observatory on a Super Pressure Balloon, mission two) foresees the launch of two telescopes on an ultra-long duration balloon. One is a fluorescence telescope designed to detect UHECR via the UV fluorescence emission of the showers in the atmosphere. The other one measures direct Cherenkov light emission from lower energy cosmic rays and other optical backgrounds for cosmogenic tau neutrino detection. In this paper, we describe the data processing system which has been designed to perform data management and instrument control for the two telescopes. It is a complex which controls front-end electronics, tags events with arrival time and payload position through a GPS system, provides signals for time synchronization of the event and measures live and dead time of the telescope. In addition, the data processing system manages mass memory for data storage, performs housekeeping monitor, and controls power on and power off sequences. The target flight duration for the NASA super pressure program is 100 days, consequently, the requirements on the electronics and the data handling are quite severe. The system operates at high altitude in unpressurised environment, which introduces a technological challenge for heat dissipation.