Field Programmable Gate Arrays generate algorithmic specific architectures that improve the code's FLOP per watt ratio. Such devices are re-gaining interest due to the rise of new tools that facilitate their programming, such as OmpSs. The computational fluid dynamics community is always investigating new architectures that can improve its algorithm's performance. Commonly, those algorithms have a low arithmetic intensity and only reach a small percentage of the peak performance. The sparse matrix-vector multiplication is one of the most time-consuming operations on unstructured simulations. The matrix's sparsity pattern determines the indirect memory accesses of the multiplying vector. This data path is hard to predict, making traditional implementations fail. In this work, we present an FPGA architecture that maximizes the vector's re-usability by introducing a cache-like architecture. The cache is implemented as a circular list that maintains the BRAM vector components while needed. Following this strategy, up to 16 times of acceleration is obtained compared to a naive implementation of the algorithm.

Geometric deep learning (GDL), which is based on neural network architectures that incorporate and process symmetry information, has emerged as a recent paradigm in artificial intelligence. GDL bears particular promise in molecular modeling applications, in which various molecular representations with different symmetry properties and levels of abstraction exist. This review provides a structured and harmonized overview of molecular GDL, highlighting its applications in drug discovery, chemical synthesis prediction, and quantum chemistry. Emphasis is placed on the relevance of the learned molecular features and their complementarity to well-established molecular descriptors. This review provides an overview of current challenges and opportunities, and presents a forecast of the future of GDL for molecular sciences.

Within the framework of diffuse interface methods, we derive a pressure-based Baer-Nunziato type model well-suited to weakly compressible multiphase flows. The model can easily deal with different equation of states and it includes relaxation terms characterized by user-defined finite parameters, which drive the pressure and velocity of each phase toward the equilibrium. There is no clear notion of speed of sound, and thus, most of the classical low Mach approximation cannot easily be cast in this context. The proposed solution strategy consists of two operators: a semi-implicit finite-volume solver for the hyperbolic part and an ODE integrator for the relaxation processes. Being the acoustic terms in the hyperbolic part integrated implicitly, the stability condition on the time step is lessened. The discretization of non-conservative terms involving the gradient of the volume fraction fulfills by construction the non-disturbance condition on pressure and velocity to avoid oscillations across the multimaterial interfaces. The developed simulation tool is validated through one-dimensional simulations of shock-tube and Riemann-problems, involving water-aluminum and water-air mixtures, vapor-liquid mixture of water and of carbon dioxide, and almost pure flows. The numerical results match analytical and reference ones, except some expected discrepancies across shocks, which however remain acceptable (errors within some percentage points). All tests were performed with acoustic CFL numbers greater than one, and no stability issues arose, even for CFL greater than 10. The effects of different values of relaxation parameters and of different amount equations of state -- stiffened gas and Peng-Robinson -- were investigated.

Relative phases of atomic above-threshold ionization wavepackets have been investigated in a recent experiment [L. J. Zipp, A. Natan, and P. H. Bucksbaum, Optica \textbf{1}, 361-364 (2014)] exploiting interferences between different pathways in a weak probe field at half the frequency of the strong ionization pulse. In this work we theoretically explore the extraction of phase delays and time delays of attosecond wavepackets formed in strong-field ionization. We perform simulations solving the time-dependent Schr\"odinger equation and compare these results with the strong-field and Coulomb-Volkov approximations. In order to disentangle short- from long- ranged effects of the atomic potential we also perform simulations for atomic model potentials featuring a Yukawa-type short-range potential. We find significant deviations of the \textit{ab-initio} phase delays between different photoelectron pathways from the predictions by the strong-field approximation even at energies well above the ionization threshold. We identify similarities but also profound differences to the well-known interferometric extraction of phase- and time delays in one-photon ionization.

PyCharge is a computational electrodynamics Python simulator that can calculate the electromagnetic fields and potentials generated by moving point charges and can self-consistently simulate dipoles modeled as Lorentz oscillators. To calculate the total fields and potentials along a discretized spatial grid at a specified time, PyCharge computes the retarded time of the point charges at each grid point, which are subsequently used to compute the analytical solutions to Maxwell's equations for each point charge. The Lorentz oscillators are driven by the electric field in the system and PyCharge self-consistently determines the reaction of the radiation on the dipole moment at each time step. PyCharge treats the two opposite charges in the dipole as separate point charge sources and calculates their individual contributions to the total electromagnetic fields and potentials. The expected coupling that arises between dipoles is captured in the PyCharge simulation, and the modified radiative properties of the dipoles (radiative decay rate and frequency shift) can be extracted using the dipole's energy at each time step throughout the simulation. The modified radiative properties of two dipoles separated in the near-field, which requires a full dipole response to yield the correct physics, are calculated by PyCharge in excellent agreement with the analytical Green's function results ($< 0.2\%$ relative error, over a wide range of spatial separations). Moving dipoles can also be modeled by specifying the dipole's origin position as a function of time. PyCharge includes a parallelized version of the dipole simulation method to enable the parallel execution of computationally demanding simulations on high performance computing environments to significantly improve run time.

Long-lived excited states of atomic nuclei can act as energy traps. These states, known as nuclear isomers, can store a large amount of energy over long periods of time, with a very high energy-to-mass ratio. Under natural conditions, the trapped energy is only slowly released, limited by the long isomer lifetimes. Dynamical external control of nuclear state population has proven so far very challenging, despite ground-breaking incentives for a clean and efficient energy storage solution. Here, we describe a protocol to achieve the external control of the isomeric nuclear decay by using electrons whose wavefunction has been especially designed and reshaped on demand. Recombination of these electrons into the atomic shell around the isomer can lead to the controlled release of the stored nuclear energy. On the example of $^{93m}$Mo, we show that the use of tailored electron vortex beams increases the depletion by four orders of magnitude compared to the spontaneous nuclear decay of the isomer. Furthermore, specific orbitals can sustain an enhancement of the recombination cross section for vortex electron beams by as much as six orders of magnitude, providing a handle for manipulating the capture mechanism. These findings open new prospects for controlling the interplay between atomic and nuclear degrees of freedom, with potential energy-related and high-energy radiation sources applications.

Topological photonic edge states, protected by chiral symmetry, are attractive for guiding wave energy as they can allow for more robust guiding and greater control of light than alternatives; however, for photonics, chiral symmetry is often broken by long-range interactions. We look to overcome this difficulty by exploiting the topology of networks, consisting of voids and narrow connecting channels, formed by the spaces between closely spaced perfect conductors. In the limit of low frequencies and narrow channels, these void-channel systems have a direct mapping to analogous discrete mass-spring systems in an asymptotically rigorous manner and therefore only have short-range interactions. We demonstrate that the photonic analogues of topological tight-binding models that are protected by chiral symmetries, such as the SSH model and square-root semimetals, are reproduced for these void-channel networks with appropriate boundary conditions. We anticipate, moving forward, that this paper provides a basis from which to explore continuum photonic topological systems, in an asymptotically exact manner, through the lens of a simplified tight-binding model.

A theory for excitation of molecular resonances by a train of precursors is developed. Right at the vacuum-medium interface, a train of incident square waves interacts with light electrons and is converted into a train of precursors, which further excite molecular dipoles. Analytic calculations indicate that these excited dipoles generate radiation, including secondary precursors propagating in the backward direction. Encoded in this radiation are proper frequencies of excited molecular dipoles allowing for spectroscopic measurements. The frequency of the train of incident square pulses can be by several orders of magnitude smaller than the proper frequencies of molecular resonances.

The increasing availability of a variety of two-dimensional materials has generated enormous growth in the field of nanoengineering and nanomechanics. Recent developments in thin film synthesis have enabled the fabrication of freestanding functional oxide membranes that can be readily incorporated in nanomechanical devices. While many oxides are extremely brittle in bulk, recent studies have shown that, in thin membrane form, they can be much more robust to fracture as compared to their bulk counterparts. Here, we investigate the ultimate tensile strength of SrTiO$_3$ membranes by probing freestanding SrTiO$_3$ drumheads using an atomic force microscope. We demonstrate that SrTiO$_3$ membranes can withstand an elastic deformation with an average strain of ~6% in the sub-20 nm thickness regime, which is more than an order of magnitude beyond the bulk limit. We also show that these membranes are highly resilient upon a high cycle fatigue test, surviving up to a billion cycles of force modulation at 85% of their fracture strain, demonstrating their high potential for use in nanomechanical applications.

The melanins are a ubiquitous class of pigments found throughout nature from lower organisms to humans. It is one of the few biopolymers with fascinating functions in biology, medicine, chemistry, physics and engineering due to its relation to neurological diseases, skin disorders and melanoma, and, in the last couple of decades, its applications in biocompatible and biodegradable devices for organic electronic and bioelectronics. In this review, we present the major advances in physicochemical, biochemical and photochemical properties as well as some melanin-based technological application. Keywords: Melanin; physical-chemical properties; biochemistry; photochemistry technological applications.

We demonstrate strong negative electrothermal feedback accelerating and linearizing the response of a thermal kinetic inductance detector (TKID). TKIDs are a proposed highly multiplexable replacement to transition-edge sensors and measure power through the temperature-dependent resonant frequency of a superconducting microresonator bolometer. At high readout probe power and probe frequency detuned from the TKID resonant frequency, we observe electrothermal feedback loop gain up to $\mathcal L$ $\approx$ 16 through measuring the reduction of settling time. We also show that the detector response has no detectable non-linearity over a 38% range of incident power and that the noise-equivalent power is below the design photon noise.

In many social networks it is a useful assumption that, regarding a given quality, an underlying hierarchy of the connected individuals exists, and that the outcome of interactions is to some extent determined by the relative positions in the hierarchy. We consider a simple and broadly applicable method of estimating individual positions in a linear hierarchy, and the corresponding uncertainties. The method relies on solving a linear system characterized by a modified Laplacian matrix of the underlying network of interactions, and is equivalent to finding the equilibrium configuration of a system of directed linear springs. We provide a simple first-order approximation to the exact solution, which can be evaluated in linear time. The uncertainty of the hierarchy estimate is determined by the network structure and the potantial energy of the corresponding spring system in equilibrium. The method generalizes straightforwardly to multidimensional hierarchies and higher-order, non-pairwise interactions.

Temporal interfaces introduced by abrupt switching of the constitutive parameters of unbounded media enable unusual wave phenomena. So far, their explorations have been mostly limited to lossless media. Yet, non-Hermitian phenomena leveraging material loss and gain, and their balanced combination in parity-time (PT)-symmetric systems, have been opening new vistas in photonics. Here, we unveil the role that temporal interfaces offer in non-Hermitian physics, introducing the dual of PT symmetry for temporal boundaries. Our findings reveal unexplored interference mechanisms enabling extreme energy manipulation, and open new scenarios for time-switched metamaterials, connecting them with the broad opportunities offered by non-Hermitian phenomena.

The study of naturally occurring turbulent flows requires ability to collect empirical data down to the fine scales. While hotwire anemometry offers such ability, the open field studies are uncommon due to the cumbersome calibration procedure and operational requirements of hotwire anemometry, e.g., constant ambient properties and steady flow conditions. The combo probe-the combined sonic-hotfilm anemometer developed and tested over the last decade-has demonstrated its ability to overcome this hurdle. The old-er generation had a limited wind alignment range of 120 degrees and the in-situ calibration procedure was human decision based. This study presents the next generation of the combo probe design, and the new fully automated in-situ calibration procedure implementing deep learning. The elegant new design now enables measurements of the incoming wind flow in a 360-degree range. The improved calibration procedure is shown to have the robustness necessary for operation in everchanging open field flow and environmental conditions. This is especially useful with diurnally changing environments or non-stationary measuring stations, i.e., probes placed on moving platforms like boats, drones, and weather balloons. Together, the updated design and the new calibration procedure, allow for continuous field measurements with minimal to no human interaction, enabling near real-time monitoring of fine-scale turbulent fluctuations. Integration of these probes will contribute toward generation of a large pool of field data to be collected to unravel the intricacies of all scales of turbulent flows occurring in natural setups.

Discretizing a distribution function in a phase space for an efficient quantum dynamics simulation is a non-trivial challenge, in particular for a case that a system is further coupled to environmental degrees of freedom. Such open quantum dynamics is described by a reduced equation of motion (REOM) most notably by a quantum Fokker-Planck equation (QFPE) for a Wigner distribution function (WDF). To develop a discretization scheme that is stable for numerical simulations from the REOM approach, we employ a two-dimensional (2D) periodically invariant system-bath (PISB) model with two heat baths. This model is an ideal platform not only for a periodic system but also for a non-periodic system confined by a potential. We then derive the numerically ''exact'' hierarchical equations of motion (HEOM) for a discrete WDF in terms of periodically invariant operators in both coordinate and momentum spaces. The obtained equations can treat non-Markovian heat-bath in a non-perturbative manner at finite temperatures regardless of the mesh size. As demonstrations, we numerically integrate the discrete QFPE for a 2D free rotor and harmonic potential systems in a high-temperature Markovian case using a coarse mesh with initial conditions that involve singularity.

Several calorimetric measurements have shown that 1-ethyl-3-methylimidazolium dicyanamide, [C2C1im][N(CN)2], is a glass-forming liquid, even though it is a low-viscous liquid at room temperature. Here we found slow crystallization during cooling of [C2C1im][N(CN)2] along Raman spectroscopy measurements. The low-frequency range of the Raman spectrum shows that the same crystalline phase is obtained at 210 K either by cooling or by reheating the glass (cold-crystallization). Another crystalline phase is formed at ca. 260 K just prior the melting at 270 K. X-ray diffraction and calorimetric measurements confirm that there are two crystalline phases of [C2C1im][N(CN)2]. The Raman spectra indicate that polymorphism is related to [C2C1im]+ with the ethyl chain on the plane of the imidazolium ring (the low-temperature crystal) or non-planar (the high-temperature crystal). The structural reason for the glass-forming ability of [C2C1im][N(CN)2], despite of the relatively simple molecular structures of the ions, was pursued by quantum chemistry calculations and molecular dynamics (MD) simulations. Density functional theory (DFT) calculations were performed for ionic pairs in order to draw free energy surfaces of the anion around the cation. The MD simulations using a polarizable model provided maps of occurrence of anions around cations. Both the quantum and classical calculations suggest that the delocalization of preferred positions of the anion around the cation, which adopts different conformations of the ethyl chain, is on the origin of the crystallization being hampered during cooling and the resulting glass-forming ability of [C2C1im][N(CN)2].

With the advent of new technologies and the growing conviction in favor of renewable energy, a marked importance has been placed on utilizing renewable energy sources for long-term use. Coming into play with NASA's objective to establish a long-term extraterrestrial colony on Earth's moon as part of its ongoing Artemis program, there is a marked need to utilize advanced technology to sustain the operations of lunar processes. Thermoelectric generators are a form of renewable energy source that converts heat into power. Simulations and experiments were conducted to test the use of a helical anchor-based device relying on such generators. This study aims to determine the feasibility of using thermoelectric technology for the Artemis Base Camp as a way to both dissipate heat away from working processes and to generate power while doing so.

In this article, we propose a traffic rule inspired from nature, that facilitates an elite agent to move efficiently through a crowd of inert agents. When an object swims in a fluid medium or an intruder is forced through granular matter, characteristic flow-fields are created around them. We show that if inert agents, made small movements based on a traffic rule derived from these characteristic flow-fields, they efficiently reorganize and transport enough space for the elite to pass through. The traffic rule used in the article is a dipole-field which satisfactorily captures the features of the flow-fields around a moving intruder. We study the effectiveness of this dipole traffic rule using numerical simulations in a 2D periodic domain, where one self-propelled elite agent tries to move through a crowd of inert agents that prefer to stay in a state of rest. Simulations are carried out for a wide range of strengths of the traffic rule and packing density of the crowd. We characterize and analyze four regions in the parameter space, free-flow, motion due to cooperation, frozen and collective drift regions, and discuss the consequence of the traffic rule in light of the collective behavior observed. We believe that the proposed method can be of use in a swarm of robots working in constrained environments.

A feasibility demonstration of three-dimensional (3D) muon tomography was performed for infrastructure equivalent targets using the proposed portable muography detector. For the target, we used two sets of lead blocks placed at different heights. The detector consists of two muon position-sensitive detectors, made of plastic scintillating fibers (PSFs) and multi-pixel photon counters (MPPCs) with an angular resolution of 8 msr. The maximum likelihood-expectation maximization (ML-EM) method was used for the 3D imaging reconstruction of the muography simulation and measurement. For both simulation and experiment, the reconstructed positions of the blocks produce consistent results with prior knowledge of the blocks' arrangement. This result demonstrates the potential of the 3D tomographic imaging of infrastructure by using eleven detection positions for portable muography detectors to image infrastructure scale targets.

On-chip manipulation of single resonance over broad background comb spectra of microring resonators is indispensable, ranging from tailoring laser emission, optical signal processing to non-classical light generation, yet challenging without scarifying the quality factor or inducing additional dispersive effects. Here, we propose an experimentally feasible platform to realize on-chip selective depletion of single resonance in microring with decoupled dispersion and dissipation, which are usually entangled by Kramer-Kroning relation. Thanks to the existence of non-Hermitian singularity, unsplit but significantly increased dissipation of the selected resonance is achieved due to the simultaneous collapse of eigenvalues and eigenvectors, fitting elegantly the requirement of pure single-mode depletion. With delicate yet experimentally feasible parameters, we show explicit evidence of modulation instability as well as deterministic single soliton generation in microresonators induced by depletion in normal and anomalous dispersion regime, respectively. Our findings connect non-Hermitian singularities to wide range of applications associated with selective single mode manipulation in microwave photonics, quantum optics, ultrafast optics and beyond.

Organic semiconductors have enough molecular versatility to feature chemo-specific electrical sensitivity to large families of chemical substituents via different intermolecular bonding modes. This study demonstrates that one single conducting polymer can be tuned to either discriminate water-, ethanol- or acetone-vapors, on demand, by changing the nature of its dopant. Seven triflate salts differ from mild to strong p-dopant on poly(3hexylthiophene) sensing micro-arrays. Each material shows a pattern of conductance modulation for the polymer which is reversible, reproducible, and distinctive of other gas exposures. Based on principal component analysis, an array doped with only two different triflates can be trained to reliably discriminate gases, which re-motivates using conducting polymers as a class of materials for integrated electronic noses. More importantly, this method points out the existence of tripartite donor-acceptor charge-transfer complexes responsible for chemospecific molecular sensing. By showing that molecular acceptors can have duality to p-dope semiconductors and to coordinate donor gases, such behavior can be used to understand the role of frontier orbital overlapping in organic semiconductors, the formation of charge-transfer complexes via Lewis acid-base adducts in molecular semiconductors.

INTPIX4NA is an integration-type silicon-on-insulator pixel detector. This detector has a 14.1 x 8.7 mm^2 sensitive area, 425,984 (832 column x 512 row matrix) pixels and the pixel size is 17 x 17 um^2. This detector was developed for residual stress measurement using X-rays (the cos alpha method). The performance of INTPIX4NA was tested with the synchrotron beamlines of the Photon Factory (KEK), and the following results were obtained. The modulation transfer function, the index of the spatial resolution, was more than 50% at the Nyquist frequency (29.4 cycle/mm). The energy resolution analyzed from the collected charge counts is 35.3%--46.2% at 5.415 keV, 21.7%--35.6% at 8 keV, and 15.7%--19.4% at 12 keV. The X-ray signal can be separated from the noise even at a low energy of 5.415 keV at room temperature (approximately 25--27 degree Celsius). The maximum frame rate at which the signal quality can be maintained is 153 fps in the current measurement system. These results satisfy the required performance in the air and at room temperature (approximately 25--27 degree Celsius) condition that is assumed for the environment of the residual stress measurement.

This paper presents a review of the recent Machine Learning activities carried out on beam measurements performed at the CERN Large Hadron Collider. This paper has been accepted for publication in IEEE Instrumentation and Measurement Magazine and in the published version no abstract is provided.

We study the SIR ("susceptible, infected, removed/recovered") model on directed graphs with heterogeneous transmission probabilities within the message-passing approximation. We characterize the percolation transition, predict cluster size distributions and suggest vaccination strategies. All predictions are compared to numerical simulations on real networks. The percolation threshold which we predict is a rigorous lower bound to the threshold on real networks. For large, locally tree-like networks, our predictions agree very well with the numerical data.

The extreme nonlinear optical process of high-harmonic generation (HHG) makes it possible to map the properties of a laser beam onto a radiating electron wavefunction, and in turn, onto the emitted x-ray light. Bright HHG beams typically emerge from a longitudinal phased distribution of atomic-scale quantum antennae. Here, we form a transverse necklace-shaped phased array of HHG emitters, where orbital angular momentum conservation allows us to tune the line spacing and divergence properties of extreme-ultraviolet and soft X-ray high harmonic combs. The on-axis HHG emission has extremely low divergence, well below that obtained when using Gaussian driving beams, which further decreases with harmonic order. This work provides a new degree of freedom for the design of harmonic combs, particularly in the soft X-ray regime, where very limited options are available. Such harmonic beams can enable more sensitive probes of the fastest correlated charge and spin dynamics in molecules, nanoparticles and materials.

Microrobots hold promise for applications ranging from targeted delivery to enhanced mixing at the microscale. However, current fabrication techniques suffer from limited throughput and material selection. Here, we demonstrate a versatile route enabling the synthesis of microrobots from off-the-shelf micro- and nano-particles. Our protocol hinges on the toposelective attachment of photocatalytic nanoparticles onto microparticles, exploiting a multi-functional polymer and a Pickering-wax emulsification step, to yield large quantities of photo-responsive active Janus particles. The polymer presents both silane and nitrocatechol groups, binding silica microspheres to a range of metal oxide nanoparticles. The Pickering-wax emulsions protect part of the microspheres' surface, enabling asymmetric functionalization, as required for self-propulsion. The resulting photocatalytic microrobots display a characteristic orientation-dependent 3D active motion upon UV illumination, different to that conventionally described in the literature. By connecting the extensive library of heterogeneous nanoparticle photocatalysts with the nascent field of active matter, this versatile material platform lays the groundwork towards designer microrobots, which can swim by catalysing a broad range of chemical reactions with potential for future applications.

We study urban public transport systems by means of multiplex networks in which stops are represented as nodes and each line is represented by a layer. We determine and visualize public transport network orientations and compare them with street network orientations of the $36$ largest German as well as $18$ selected major European cities. We find that German urban public transport networks are mainly oriented in a direction close to the cardinal east-west axis, which usually coincides with one of two orthogonal preferential directions of the corresponding street network. While this behavior is present in only a subset of the considered European cities it remains true that none but one considered public transport network has a distinct north-south-like preferential orientation. Furthermore, we study the applicability of the class of matrix function-based centrality measures, which has recently been generalized from single-layer networks to layer-coupled multiplex networks, to our more general urban multiplex framework. Numerical experiments based on highly efficient and scalable methods from numerical linear algebra show promising results, which are in line with previous studies. We comment on advantages over existing methodology, elaborate on the comparison of different measures and weight models, and present detailed hyper-parameter studies. All results are illustrated by demonstrative graphical representations.

Detection of nascent O($^3P_j$, $j=2,1,0$) atoms using one-photon resonant excitation to the $3s\,^3S^o_1$ state at $\sim 130$ nm followed by near-threshold ionization, i. e., 1 + 1' resonance enhanced multi-photon ionization (REMPI), has been investigated. The aim was to achieve low ion recoil, improved sensitivity, and reliable angular momentum polarization information, with an as simple as possible laser setup. An efficient 1 + 1' scheme has been found where the VUV light for the first step 1 is generated by difference frequency ($2\omega_1 - \omega_2$) VUV generation by four wave mixing in Kr gas, and the ionization step 1' uses 2$\omega_2$ at 289 nm. The presented scheme induces 9 m/s recoil of the O$^+$ ion using a two-dye laser system, and zero recoil should be possible by generating 302 nm radiation with a third dye laser. While this approach is much more sensitive than a previous 1 + 1' scheme using 212.6 nm for the 1' step, we found that the relatively intense 289 nm radiation does not saturate the 1' step. In order to test the ability of this scheme to accurately determine branching ratios, fine structure yields, and angular distributions including polarization information, it has been applied to O$_2$ photodissociation around 130 nm with subsequent O($^3P_j$) fragment detection.

Elucidating photochemical reactions is vital to understand various biochemical phenomena and develop functional materials such as artificial photosynthesis and organic solar cells, albeit its notorious difficulty by both experiments and theories. The best theoretical way so far to analyze photochemical reactions at the level of ab initio electronic structure is the state-averaged multi-configurational self-consistent field (SA-MCSCF) method. However, the exponential computational cost of classical computers with the increasing number of molecular orbitals hinders applications of SA-MCSCF for large systems we are interested in. Utilizing quantum computers was recently proposed as a promising approach to overcome such computational cost, dubbed as SA orbital-optimized variational quantum eigensolver (SA-OO-VQE). Here we extend a theory of SA-OO-VQE so that analytical gradients of energy can be evaluated by standard techniques that are feasible with near-term quantum computers. The analytical gradients, known only for the state-specific OO-VQE in previous studies, allow us to determine various characteristics of photochemical reactions such as the minimal energy (ME) points and the conical intersection (CI) points. We perform a proof-of-principle calculation of our methods by applying it to the photochemical {\it cis-trans} isomerization of 1,3,3,3-tetrafluoropropene. Numerical simulations of quantum circuits and measurements can correctly capture the photochemical reaction pathway of this model system, including the ME and CI points. Our results illustrate the possibility of leveraging quantum computers for studying photochemical reactions.

In this paper, size-dependent dynamic responses of small-size frames are modelled by stress-driven nonlocal elasticity and assessed by a consistent finite-element methodology. Starting from uncoupled axial and bending differential equations, the exact dynamic stiffness matrix of a two-node stress-driven nonlocal beam element is evaluated in a closed form. The relevant global dynamic stiffness matrix of an arbitrarily-shaped small-size frame, where every member is made of a single element, is built by a standard finite-element assembly procedure. The Wittrick-Williams algorithm is applied to calculate natural frequencies and modes. The developed methodology, exploiting the one conceived for straight beams in [International Journal of Engineering Science 115, 14-27 (2017)], is suitable for investigating size-dependent free vibrations of small-size systems of current applicative interest in Nano-Engineering, such as carbon nanotube networks and polymer-metal micro-trusses.

In this paper, the bending behaviour of small-scale Bernoulli-Euler beams is investigated by Eringen's two-phase local/nonlocal theory of elasticity. Bending moments are expressed in terms of elastic curvatures by a convex combination of local and nonlocal contributions, that is a combination with non-negative scalar coefficients summing to unity. The nonlocal contribution is the convolution integral of the elastic curvature field with a suitable averaging kernel characterized by a scale parameter. The relevant structural problem, well-posed for non-vanishing local phases, is preliminarily formulated and exact elastic solutions of some simple beam problems are recalled. Limit behaviours of the obtained elastic solutions, analytically evaluated, studied and diagrammed, do not fulfill equilibrium requirements and kinematic boundary conditions. Accordingly, unlike alleged claims in literature, such asymptotic fields cannot be assumed as solutions of the purely nonlocal theory of beam elasticity. This conclusion agrees with the known result which the elastic equilibrium problem of beams of engineering interest formulated by Eringen's purely nonlocal theory admits no solution.

In this research, the size-dependent static behaviour of elastic curved stubby beams is investigated by Timoshenko kinematics. Stress-driven two-phase integral elasticity is adopted to model size effects which soften or stiffen classical local responses. The corresponding governing equations of nonlocal elasticity are established and discussed, non-classical boundary conditions are detected and an effective coordinate-free solution procedure is proposed. The presented mixture approach is elucidated by solving simple curved small-scale beams of current interest in Nanotechnology. The contributed results could be useful for design and optimization of modern sensors and actuators.

However, their electrocatalytic activity is still poorly understood. This work deciphers the origin of the catalytic activity of counter-electrodes (CEs)/current collectors made of self-standing carbon nanotubes fibers (CNTfs) using Co$^(+2)$/Co$^(+3)$ redox couple electrolytes. This is based on comprehensive electrochemical and spectroscopic characterizations of fresh and used electrodes applied to symmetric electrochemical cells using platinum-based CEs as a reference. As the most relevant findings, two straight relationships were established: i) the limiting current and stability increase rapidly with surface concentration of oxygen-containing functional groups, and ii) the catalytic potential is inversily related to the amount of residual metallic Fe catalyst nanoparticles interspersed in the CNTf network. Finally, the fine tune of the metallic nanoparticle content and the degree of functionalization enabled fabrication of efficient and stable dye-sensitized solar cells with cobalt electrolytes and CNTf-CE outperforming those with reference Pt-CEs.

We perform a parametric study of the newly developed time-of-flight (TOF) image reconstruction algorithm, proposed for the real-time imaging in total-body Jagiellonian PET (J-PET) scanners. The asymmetric 3D filtering kernel is applied at each most likely position of electron-positron annihilation, estimated from the emissions of back-to-back $\gamma$-photons. The optimisation of its parameters is studied using Monte Carlo simulations of a 1-mm spherical source, NEMA IEC and XCAT phantoms inside the ideal J-PET scanner. The combination of high-pass filters which included the TOF filtered back-projection (FBP), resulted in spatial resolution, 1.5 $\times$ higher in the axial direction than for the conventional 3D FBP. For realistic $10$-minute scans of NEMA IEC and XCAT, which require a trade-off between the noise and spatial resolution, the need for Gaussian TOF kernel components, coupled with median post-filtering, is demonstrated. The best sets of 3D filter parameters were obtained by the Nelder-Mead minimisation of the mean squared error between the resulting and reference images. The approach allows training the reconstruction algorithm for custom scans, using the IEC phantom, when the temporal resolution is below 50 ps. The image quality parameters, estimated for the best outcomes, were systematically better than for the non-TOF FBP.

In this article, eigenfrequencies of nano-beams under axial loads are assessed by making recourse to the well-posed stress-driven nonlocal model (SDM) and strain-driven two-phase local/nonlocal formulation (NstrainG) of elasticity and Bernoulli-Euler kinematics. The developed nonlocal methodology is applicable to a wide variety of nano-engineered materials, such as carbon nanotubes, and modern small-scale beam-like devices of nanotechnological interest. Eigenfrequencies calculated using SDM, are compared with NstrainG and other pertinent results in literature obtained by other nonlocal strategies. Influence of nonlocal thermoelastic effects and initial axial force (tension and compression) on dynamic responses are analyzed and discussed. Model hardening size effects from stress-driven approach is compared to model softening size effects from strain-driven two-phase local/nonlocal approach for increasing nonlocal parameters.

Modelling hydrodynamic lubrication is crucial in the design of engineering components as well as for a fundamental understanding of friction mechanisms. The cornerstone of thin-film flow modelling is the Reynolds equation -- a lower-dimensional representation of the Stokes equation. However, the derivation of the Reynolds equation is based on assumptions and fixed form constitutive relations, that may not generally be valid, especially when studying systems under extreme conditions. Furthermore, these explicit assumptions about the constitutive behaviour of the fluid prohibit applications in a multiscale scenario based on measured or atomistically simulated data. Here, we present a method that considers the full compressible Navier-Stokes equation in a height-averaged sense for arbitrary constitutive relations. We perform numerical tests by using a reformulation of the viscous stress tensor for laminar flow to validate the presented method comparing to results from conventional Reynolds solutions. The versatility of the method is shown by incorporating models for mass-conserving cavitation, wall slip and non-Newtonian fluids. This allows testing of new constitutive relations that not necessarily need to take a fixed form, and may be obtained from experimental or simulation data.

In optical devices like diffraction gratings and Fresnel lenses, light wavefront is engineered through the structuring of device surface morphology, within thicknesses comparable to the light wavelength. Fabrication of such diffractive optical elements involves highly accurate multi-step lithographic processes that in fact set into stone both the device morphology and optical functionality. In this work, we introduce shapeshifting diffractive optical elements directly written on an erasable photoresist. We first develop a lithographic configuration that allows writing/erasing cycles of aligned optical elements directly in the light path. Then, we show the realization of complex diffractive gratings with arbitrary combinations of grating vectors. Finally, we demonstrate a shapeshifting diffractive lens that is reconfigured in the light-path in order to change the imaging parameters of an optical system.

Macroscopic ensembles of nanocarbons, such as fibres of carbon nanotubes (CNT), are characterised by a complex hierarchical structure combining coherent crystalline regions with a large porosity arising from imperfect packing of the large rigid building blocks. Such structure is at the centre of a wide range of charge storage and transfer processes when CNT fibres are used as electrodes and/or current collectors. This work introduces a method based on wide and small-angle X-ray scattering (WAXS/SAXS) to obtain structural descriptors of CNT fibres and which enables in situ characterisation during electrochemical processes. It enables accurate determination of parameters such as specific surface area, average pore size and average bundle size from SAXS data after correction for scattering from density fluctuations arising from imperfect packing of graphitic planes. In situ and ex situ WAXS/SAXS measurements during electrochemical swelling of CNT fibre electrodes in ionic liquid provide continuous monitoring of the increase in effective surface area caused by electrostatic separation of CNT bundles in remarkable agreement with capacitance changes measured independently. Relative contributions from quantum and Helmholtz capacitance to total capacitance remaining fairly constant. The WAXS/SAXS analysis is demonstrated for fibres of either multi- and single-walled CNTs, and is expected to be generally applicable to operando studies on nanocarbon-based electrodes used in batteries, actuators and other applications

A plethora of metalenses and diffractive lenses (flat lenses) have been demonstrated over the years. Recently, attempts have been made to stretch their performance envelope, particularly in the direction of wide-band achromatic performance. While achromatic behavior has been demonstrated, an actual improvement in imaging performance relative to conventional (non-chromatically corrected) flat lenses has not. The reasons for this are use of inappropriate performance metrics, lack of comparison to a baseline conventional design, and lack of a performance metric that combines signal-to-noise ratio and resolution. In this work we present a metric that will allow comparison of different types of flat lenses, even if their first order optical parameters are not the same. We apply this metric to several published achromatic flat lens designs and compare them to the equivalent conventional flat lens, which we consider as the lower bound for achromatic flat lens performance. Use of this metric paves the way for future developments in the field of achromatic flat lenses, which will display proven progress.

For cross section measurements, an accurate knowledge of the integrated luminosity is required. The FCC-ee Z lineshape programme sets the ambitious precision goal of $10^{-4}$ on the \emph{absolute} luminosity measurement and one order of magnitude better on the \emph{relative} measurement between energy-scan points. The luminosity is determined from the rate of small-angle Bhabha scattering, $\mathrm{e^+e^- \to e^+e^-}$, where the final state electrons and positrons are detected in dedicated monitors covering small angles from the outgoing beam directions. The constraints on the luminosity monitors are multiple: \mbox{\emph{i}) they} are placed inside the main detector volume only about 1\,m from the interaction point; \mbox{\emph{ii})} they are centred around the outgoing beam lines and do not satisfy the normal axial detector symmetry; \mbox{\emph{iii})} their coverage is limited by the beam pipe, on the one hand, and the requirement to stay clear of the main detector acceptance, on the other; \mbox{\emph{iv})} the steep angular dependence of the Bhabha scattering process imposes a geometrical precision on the acceptance limits at about 1\,\textmugreek rad, corresponding to geometrical precisions of $\mathcal{O}(1\,\text{\textmugreek m})$; and \mbox{\emph{v})} the very high bunch crossing rate of 50\,MHz during the Z-pole operation calls for fast readout electronics. %Some constraints may be hard to satisfy simultaneously. As an example, the high readout rate may lead to an elevated level of heat dissipation rendering it difficult to maintain the required geometrical stability. Inspired by second-generation LEP luminosity monitors, a proposed ultra-compact solution is based on a sandwich of tungsten-silicon layers. A vigorous R\&D programme is needed in order to ensure that such a solution satisfies the more challenging FCC-ee requirements.

Biermann battery magnetic field generation driven by high power laser-solid interactions is explored in experiments performed with the OMEGA EP laser system. Proton deflectometry captures changes to the strength, spatial profile, and temporal dynamics of the self-generated magnetic fields as the target material or laser intensity is varied. Measurements of the magnetic flux during the interaction are used to help validate extended magnetohydrodynamic (MHD) simulations. Results suggest that kinetic effects cause suppression of the Biermann battery mechanism in laser-plasma interactions relevant to both direct and indirect-drive inertial confinement fusion. Experiments also find that more magnetic flux is generated as the target atomic number is increased, which is counter to a standard MHD understanding.

Competition between alternative states is an essential process in social and biological networks. Neutral competition can be represented by an unbiased random drift process in which the states of vertices (e.g., opinions, genotypes, or species) in a network are updated by repeatedly selecting two connected vertices. One of these vertices copies the state of the selected neighbor. Such updates are repeated until all vertices are in the same "consensus" state. There is no unique rule for selecting the vertex pair to be updated. Real-world processes comprise three limiting factors that can influence the selected edge and the direction of spread: (1) the rate at which a vertex sends a state to its neighbors, (2) the rate at which a state is received by a neighbor, and (3) the rate at which a state can be exchanged through a connecting edge. We investigate how these three limitations influence neutral competition in networks with two communities generated by a stochastic block model. By using Monte Carlo simulations, we show how the community structure and update rule determine the states' success probabilities and the time until a consensus is reached. We present a heterogeneous mean-field theory that agrees well with the Monte Carlo simulations. The effectiveness of the heterogeneous mean-field theory implies that quantitative predictions about the consensus are possible even if empirical data (e.g., from ecological fieldwork or observations of social interactions) do not allow a complete reconstruction of all edges in the network.

The volume of flight traffic gets increasing over the time, which makes the strategic traffic flow management become one of the challenging problems since it requires a lot of computational resources to model entire traffic data. On the other hand, Automatic Dependent Surveillance - Broadcast (ADS-B) technology has been considered as a promising data technology to provide both flight crews and ground control staff the necessary information safely and efficiently about the position and velocity of the airplanes in a specific area. In the attempt to tackle this problem, we presented in this paper a simplified framework that can support to detect the typical air routes between airports based on ADS-B data. Specifically, the flight traffic will be classified into major groups based on similarity measures, which helps to reduce the number of flight paths between airports. As a matter of fact, our framework can be taken into account to reduce practically the computational cost for air flow optimization and evaluate the operational performance. Finally, in order to illustrate the potential applications of our proposed framework, an experiment was performed using ADS-B traffic flight data of three different pairs of airports. The detected typical routes between each couple of airports show promising results by virtue of combining two indices for measuring the clustering performance and incorporating human judgment into the visual inspection.

The unsteady motion of a two-layer fluid induced by oscillatory motion of a flat plate along its length is mathematically analyzed. Two cases are considered: (i) the two-layer fluid is bounded only by the oscillating plate (Stokes' second problem), (ii) the two-layer fluid is confined between two parallel plates, one of which oscillates while the other is held stationary (oscillatory Couette flow). In each of the Stokes' and Couette cases, both cosine and sine oscillations of the plate are considered. It is assumed that the fluids are immiscible, and that the flat interface between the fluids remains flat for all times. Solutions to the initial-boundary value problems are obtained using the Laplace transform method. Steady periodic and transient velocity fields are explicitly presented. Transient and steady-state shear stresses at the boundaries of the flows are calculated. The results derived in this paper retrieve previously known results for corresponding single-layer flows. Further, illustrative example of each of the Stokes' problem and the Couette flow is presented and discussed. Again, the results obtained could also be applicable to a problem of heat conduction in a composite solid with sinusoidal temperature variation on the surface.

Although researchers accumulated knowledge about seismogenesis and decades-long earthquake data, predicting imminent individual earthquakes at a specific time and location remains a long-standing enigma. This study hypothesizes that the observed data conceal the hidden rules which may be unraveled by a novel glass-box (as opposed to black-box) physics rule learner (GPRL) framework. Without any predefined earthquake-related mechanisms or statistical laws, GPRL's two essentials, convolved information index and transparent link function, seek generic expressions of rules directly from data. GPRL's training with 10-years data appears to identify plausible rules, suggesting a combination of the pseudo power and the pseudo vorticity of released energy in the lithosphere. Independent feasibility test supports the promising role of the unraveled rules in predicting earthquakes' magnitudes and their specific locations. The identified rules and GPRL are in their infancy requiring substantial improvement. Still, this study hints at the existence of the data-guided hidden pathway to imminent individual earthquake prediction.

In relativistic magnetized plasmas, asymmetry in the number densities of left- and right-handed fermions, i.e., a non-zero chiral chemical potential mu_5, leads to an electric current along the magnetic field. This causes a chiral dynamo instability for a uniform mu_5, but our simulations reveal dynamos even for fluctuating mu_5 with zero mean. This generates small-scale magnetic helicity and turbulence. A large-scale mu_5 emerges due to chirality conservation. These effects amplify a mean magnetic field via the magnetic alpha effect and produce a universal scale-invariant mu_5 spectrum.

To understand the dynamics on complex networks, measurement of correlations is indispensable. In a motorway network, it is not sufficient to collect information on fluxes and velocities on all individual links, i.e. parts of the freeways between ramps and highway crosses. The interdependencies and mutual connections are also of considerable interest. We analyze correlations in the complete motorway network in North Rhine-Westphalia, the most populous state in Germany. We view the motorway network as a complex system consisting of road sections which interact via the motion of vehicles, implying structures in the corresponding correlation matrices. In particular, we focus on collective behavior, i.e. coherent motion in the whole network or in large parts of it. To this end, we study the eigenvalue and eigenvector statistics and identify significant sections in the motorway network. We find collective behavior in these significant sections and further explore its causes. We show that collectivity throughout the network cannot directly be related to the traffic states (free, synchronous and congested) in Kerner's three-phase theory. Hence, the degree of collectivity provides a new, complementary observable to characterize the motorway network.

Cauchy-elastic solids include hyper-elasticity and a subset of elastic materials for which the stress does not follow from a scalar strain potential. More in general, hypo-elastic materials are only defined incrementally and comprise Cauchy-elasticity. Infringement of the hyperelastic 'dogma' is so far unattempted and normally believed to be impossible, as it apparently violates thermodynamics, because energy may be produced in closed strain cycles. Contrary to this belief, we show that non-hyper-elastic behavior is possible and we indicate the way to a practical realization of this new concept. In particular, a design paradigm is established for artificial materials where follower forces, so far ignored in homogenization schemes, are introduced as loads prestressing an elastic two-dimensional grid made up of linear elastic rods (reacting to elongation, flexure and shear). A rigorous application of Floquet-Bloch wave asymptotics yields an unsymmetric acoustic tensor governing the incremental dynamics of the effective material. The latter is therefore the incremental response of a hypo-elastic solid, which does not follow from a strain potential and thus does not belong to hyper-elasticity. Through the externally applied follower forces (which could be originated via interaction with a fluid, or gas, or by application of Coulomb friction, or non-holonomic constraints), the artificial material may adsorb/release energy from/to the environment, and therefore produce energy in a closed strain loop, without violating any rule of thermodynamics. The solid is also shown to display flutter, a material instability corresponding to a Hopf bifurcation, which was advocated as possible in plastic solids, but never experimentally found and so far believed to be impossible in elasticity.

The local extremes (i.e., peaks and pits) of the landscape-elevation field play a critical role in energy, water, and nutrient distribution over the region, but the statistical distributions of these points in relation to landscape advancing towards maturity have received limited research attention. In this work, we first explain how the spatial correlation structure of the elevation field affects the counts and frequency distributions of local extremes. We then analyze local extremes statistics for 8 mountainous landscapes worldwide with diverse hydroclimatic forcings and geologic histories using 24 Digital Elevation Models (DEMs) and compare them with complex terrain of the Erythraeum Chaos region on Mars. The results reveal that the spherical covariance structure captures the observed spatial correlation in these cases with the peak frequency distribution agreeing well with the elevation frequency distribution. The ratio of the pit-over-peak (POP) count is linked to the degree to which the pit and peak frequency distributions match, and carries the mark of landscape aging. The relationship between the geomorphic development stage (quantified by the reduced fatness of the slope-distribution tail) and the deviation of POP values from unity in old mountainous landscapes confirms that the evolution towards smoother topographies is atypically accompanied by reduced pit counts typical of organized valley and ridge patterns.

Longitudinal Dispersion(LD) is the dominant process of scalar transport in natural streams. An accurate prediction on LD coefficient(Dl) can produce a performance leap in related simulation. The emerging machine learning(ML) techniques provide a self-adaptive tool for this problem. However, most of the existing studies utilize an unproved quaternion feature set, obtained through simple theoretical deduction. Few studies have put attention on its reliability and rationality. Besides, due to the lack of comparative comparison, the proper choice of ML models in different scenarios still remains unknown. In this study, the Feature Gradient selector was first adopted to distill the local optimal feature sets directly from multivariable data. Then, a global optimal feature set (the channel width, the flow velocity, the channel slope and the cross sectional area) was proposed through numerical comparison of the distilled local optimums in performance with representative ML models. The channel slope is identified to be the key parameter for the prediction of LDC. Further, we designed a weighted evaluation metric which enables comprehensive model comparison. With the simple linear model as the baseline, a benchmark of single and ensemble learning models was provided. Advantages and disadvantages of the methods involved were also discussed. Results show that the support vector machine has significantly better performance than other models. Decision tree is not suitable for this problem due to poor generalization ability. Notably, simple models show superiority over complicated model on this low-dimensional problem, for their better balance between regression and generalization.

Performance-based optimization of energy dissipation devices in structures necessitates massive and repetitive dynamic analyses. In the endurance time method known as a rather fast dynamic analysis procedure, structures are subjected to intensifying dynamic excitations and their response at multiple intensity levels is estimated by a minimal number of analyses. So, this method significantly reduces computational endeavors. In this paper, the endurance time method is employed to determine the optimal placement of viscous dampers in a weak structure to achieve the desired performance at various hazard levels, simultaneously. The viscous damper is one of the energy dissipation systems which can dissipate a large amount of seismic input energy to the structure. To this end, hysteretic energy compatible endurance time excitation functions are used and the validity of the results is investigated by comparing them with the results obtained from a suite of ground motions. To optimize the placement of the dampers, the genetic algorithm is used. The damping coefficients of the dampers are considered as design variables in the optimization procedure and determined in such a way that the sum of them has a minimum value. The behavior of the weak structure before and after rehabilitation is also investigated using endurance time and nonlinear time history analysis procedures in different hazard levels.

Errors in the Epperlein & Haines [PoF (1986)] transport coefficients were recently found at low electron magnetizations, with new magnetic transport coefficients proposed simultaneously by two teams [Sadler, Walsh & Li, PRL (2021) and Davies, Wen, Ji & Held, PoP (2021)]; these two separate sets of updated coefficients are shown in this paper to be in agreement. The importance of these new coefficients in laser-plasmas with either self-generated or applied magnetic fields is demonstrated. When an external magnetic field is applied, the cross-gradient-Nernst term twists the field structure; this twisting is reduced by the new coefficients in the low magnetization regime. For plasmas where only self-generated magnetic fields are present, the new coefficients are found to result in the magnetic field moving with the Righi-Leduc heat-flow, enhancing the impact of MHD. Simulations of Biermann Battery magnetic fields around ICF hot-spot perturbations are presented, with cross-gradient-Nernst transport increasing spike penetration.

The motion of the free surface of an incompressible fluid is a very active research area. Most of these works examine the case of an inviscid fluid. However, in several practical applications, there are instances where the viscous damping needs to be considered. In this paper we derive and study a new asymptotic model for the motion of unidirectional viscous water waves. In particular, we establish the global well-posedness in Sobolev spaces. Furthermore, we also establish the global well-posedness and decay of a fourth order PDE modelling bidirectional water waves with viscosity moving in deep water with or without surface tension effects.

The generation of large-scale magnetic fields ($\overline{\mathbf{B}}$) in astrophysical systems is driven by the mean turbulent electromotive force. This can depend non-locally on $\overline{\mathbf{B}}$ through a convolution kernel $K_{ij}$. In a new approach to find $K_{ij}$, we directly fit the data from a galactic dynamo simulation using singular value decomposition. We calculate the usual turbulent transport coefficients as moments of $K_{ij}$, show the importance of including non-locality over eddy length scales to fully capture their amplitudes and that their higher order corrections are small.

The non-pharmaceutical interventions (NPIs), aimed at reducing the diffusion of the COVID-19 pandemic, has dramatically influenced our behaviour in everyday life. In this work, we study how individuals adapted their daily movements and person-to-person contact patterns over time in response to the COVID-19 pandemic and the NPIs. We leverage longitudinal GPS mobility data of hundreds of thousands of anonymous individuals in four US states and empirically show the dramatic disruption in people's life. We find that local interventions did not just impact the number of visits to different venues but also how people experience them. Individuals spend less time in venues, preferring simpler and more predictable routines and reducing person-to-person contact activities. Moreover, we show that the stringency of interventions alone does explain the number and duration of visits to venues: individual patterns of visits seem to be influenced by the local severity of the pandemic and a risk adaptation factor, which increases the people's mobility regardless of the stringency of interventions.

The three-body problem is a fundamental long-standing open problem, with applications in all branches of physics, including astrophysics, nuclear physics and particle physics. In general, conserved quantities allow to reduce the formulation of a mechanical problem to fewer degrees of freedom, a process known as dynamical reduction. However, extant reductions are either non-general, or hide the problem's symmetry or include unexplained definitions. This paper presents a dynamical reduction that avoids these issues, and hence is general and natural. Any three-body configuration defines a triangle, and its orientation in space. Accordingly, we decompose the dynamical variables into the geometry (shape + size) and orientation of the triangle. The geometry variables are shown to describe the motion of an abstract point in a curved 3d space, subject to a potential-derived force and a magnetic-like force with a monopole charge. The orientation variables are shown to obey a dynamics analogous to the Euler equations for a rotating rigid body, only here the moments of inertia depend on the geometry variables, rather than being constant. The reduction rests on a novel symmetric solution to the center of mass constraint inspired by Lagrange's solution to the cubic. The formulation of the orientation variables is novel and rests on a little known generalization of the Euler-Lagrange equations to non-coordinate velocities. Applications to special exact solutions and to the statistical solution are described or discussed. Moreover, a generalization to the four-body problem is presented.

We demonstrate non-classical cooling on the IBMq cloud quantum computer. We implement a recently proposed refrigeration protocol which relies upon indefinite causal order for its quantum advantage. We use quantum channels which, when used in a well-defined order, are useless for refrigeration. We are able to use them for refrigeration, however, by applying them in a superposition of different orders. Our protocol is by nature relatively robust to noise, and so can be implemented on this noisy platform. As far as the authors are aware, this is the first example of cloud quantum refrigeration.

We consider linear stability of steady states of 1(1/2) and 3D Vlasov-Maxwell systems for collisionless plasmas. The linearized systems can be written as separable Hamiltonian systems with constraints. By using a general theory for separable Hamiltonian systems, we recover the sharp linear stability criteria obtained previously by different approaches. Moreover, we obtain the exponential trichotomy estimates for the linearized Vlasov-Maxwell systems in both relativistic and nonrelativistic cases.

Design of microfluidic biochips has led to newer challenges to the EDA community due to the availability of various flow-based architectures and the need for catering to diverse applications such as sample preparation, personalized medicine, point-of-care diagnostics, and drug design. The ongoing Covid-19 pandemic has increased the demand for low-cost diagnostic lab-on-chips manifold. Sample preparation (dilution or mixing of biochemical fluids) is an indispensable step of any biochemical experiment including sensitive detection and successful assay execution downstream. Although for valve-based microfluidic biochips various design automation tools are currently available, they are expensive, and prone to various manufacturing and operational defects. Additionally, many problems are left open in the domain of free-flowing biochips, where only a single layer of flow-channels is used for fluid-flow devoid of any kind of control layer/valves. In this work, we present a methodology for designing a free-flowing biochip that is capable of performing fluid dilution according to users requirement. The proposed algorithm for sample preparation utilizes the Farey-sequence arithmetic of fractions that are used to represent the concentration factor of the target fluid. We also present the detailed layout design of a free-flowing microfluidic architecture that emulates the dilution algorithm. The network is simulated using COMSOL multi-physics software accounting for relevant hydrodynamic parameters. Experiments on various test-cases support the efficacy of the proposed design in terms of accuracy, convergence time, reactant cost, and simplicity of the fluidic network compared to prior art.

This is a tutorial and survey paper on Boltzmann Machine (BM), Restricted Boltzmann Machine (RBM), and Deep Belief Network (DBN). We start with the required background on probabilistic graphical models, Markov random field, Gibbs sampling, statistical physics, Ising model, and the Hopfield network. Then, we introduce the structures of BM and RBM. The conditional distributions of visible and hidden variables, Gibbs sampling in RBM for generating variables, training BM and RBM by maximum likelihood estimation, and contrastive divergence are explained. Then, we discuss different possible discrete and continuous distributions for the variables. We introduce conditional RBM and how it is trained. Finally, we explain deep belief network as a stack of RBM models. This paper on Boltzmann machines can be useful in various fields including data science, statistics, neural computation, and statistical physics.

With rapidly growing photoconversion efficiencies, hybrid perovskite solar cells have emerged as promising contenders for next generation, low-cost photovoltaic technologies. Yet, the presence of nanoscale defect clusters, that form during the fabrication process, remains critical to overall device operation, including efficiency and long-term stability. To successfully deploy hybrid perovskites, we must understand the nature of the different types of defects, assess their potentially varied roles in device performance, and understand how they respond to passivation strategies. Here, by correlating photoemission and synchrotron-based scanning probe X-ray microscopies, we unveil three different types of defect clusters in state-of-the-art triple cation mixed halide perovskite thin films. Incorporating ultrafast time-resolution into our photoemission measurements, we show that defect clusters originating at grain boundaries are the most detrimental for photocarrier trapping, while lead iodide defect clusters are relatively benign. Hexagonal polytype defect clusters are only mildly detrimental individually, but can have a significant impact overall if abundant in occurrence. We also show that passivating defects with oxygen in the presence of light, a previously used approach to improve efficiency, has a varied impact on the different types of defects. Even with just mild oxygen treatment, the grain boundary defects are completely healed, while the lead iodide defects begin to show signs of chemical alteration. Our findings highlight the need for multi-pronged strategies tailored to selectively address the detrimental impact of the different defect types in hybrid perovskite solar cells.

This work studies the dynamics of a one dimensional elastic bar with random elastic modulus and prescribed boundary conditions, say, fixed at one end, and attached to a lumped mass and two springs (one linear and another nonlinear) on the other extreme. The system analysis assumes that the elastic modulus has gamma probability distribution and uses Monte Carlo simulations to compute the propagation of uncertainty in this continuous--discrete system. After describing the deterministic and the stochastic modeling of the system, some configurations of the model are analyzed in order to characterize the effect of the lumped mass in the overall behavior of this dynamical system.

We experimentally study intrusion into fluid-saturated granular beds by a free-falling sphere, varying particle size and fluid viscosity. We test our results against Darcy-Reynolds theory, where the deceleration of the sphere is controlled by Reynolds dilatancy and the Darcy flow resistance. We find the observed intruder dynamics are consistent with Darcy-Reynolds theory for varied particle size. We also find that our experimental results for varied viscosity are consistent with Darcy-Reynolds theory, but only for a limited range of the viscosity. For large viscosities, observed forces begin to decrease with increasing viscosity, in contrast with the theoretical prediction.

Fifty years of evolution of the transportation field is revisited at a macro scale using scientometric analysis of all publications in all 39 journals indexed in the category of Transportation by the Web of Science. The size of the literature is estimated to have reached 50,000 documents. At the highest level of aggregation, four major divisions of the literature are differentiated through these analyses, namely (i) network analysis and traffic flow, (ii) economics of transportation and logistics, (iii) travel behaviour, and (iv) road safety. Influential and emerging authors of each division are identified. Temporal trends in transportation research are also investigated via document co-citation analysis. This analysis identifies various major streams of transportation research while determining their approximate time of emergence and duration of activity. It documents topics that have been most trendy at any period of time during the last fifty years. Three clusters associated with the travel behaviour division (collectively embodying topics of land-use, active transportation, residential self-selection, traveller experience/satisfaction, social exclusion and transport/spatial equity), one cluster of statistical modelling of road accidents, and a cluster of network modelling linked predominantly to the notion of macroscopic fundamental diagram demonstrate characteristics of being current hot topics of the field. Three smaller clusters linked predominantly to electric mobility and autonomous/automated vehicles show characteristics of being emerging hot topics. A cluster labelled shared mobility is the youngest emerging cluster. Influential articles within each cluster of references are identified. Additional outcomes are the determination the influential outsiders of the transportation field.

We present an application of anomaly detection techniques based on deep recurrent autoencoders to the problem of detecting gravitational wave signals in laser interferometers. Trained on noise data, this class of algorithms could detect signals using an unsupervised strategy, i.e., without targeting a specific kind of source. We develop a custom architecture to analyze the data from two interferometers. We compare the obtained performance to that obtained with other autoencoder architectures and with a convolutional classifier. The unsupervised nature of the proposed strategy comes with a cost in terms of accuracy, when compared to more traditional supervised techniques. On the other hand, there is a qualitative gain in generalizing the experimental sensitivity beyond the ensemble of pre-computed signal templates. The recurrent autoencoder outperforms other autoencoders based on different architectures. The class of recurrent autoencoders presented in this paper could complement the search strategy employed for gravitational wave detection and extend the reach of the ongoing detection campaigns.

Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction characteristics, and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer and optimize complex propagation environments. Evaluating the performance and optimizing the deployment of RISs in wireless networks need physically sound frameworks that account for the actual electromagnetic and physical characteristics of engineered metasurfaces. In this paper, we introduce a general macroscopic model for the realistic evaluation of RIS scattering, based on its decomposition into multiple scattering mechanisms. Since state-of-the-art ray models can already efficiently simulate specular interactions (reflection, diffraction) and diffuse scattering, but not anomalous reradiation, we complement them with a Huygens principle approach implemented using either an integral formulation, or a simpler antenna-array-like formulation. The different scattering mechanisms are combined through a generalization of the Effective Roughness model using a suitable power conservation equation. Notably, multiple reradiation modes can be modeled through the proposed approach. In addition, we validate the overall model accuracy by benchmarking it against several case studies available in the literature, either based on analytical models, full-wave simulations, or experimental measurements.

In the present paper, we study the robustness of two-dimensional random lattices (Delaunay triangulations) under attacks based on betweenness centrality. Together with the standard definition of this centrality measure, we employ a range-limited approximation known as $\ell$-betweenness, where paths having more than $\ell$ steps are ignored. For finite $\ell$, the attacks produce continuous percolation transitions that belong to the universality class of random percolation. On the other hand, the attack under the full range betweenness induces a discontinuous transition that, in the thermodynamic limit, occurs after removing a sub-extensive amount of nodes. This behavior is recovered for $\ell$-betweenness if the cutoff is allowed to scale with the linear length of the network faster than $\ell\sim L^{0.91}$. Our results suggest that betweenness centrality encodes information on network robustness at all scales, and thus cannot be approximated using finite-ranged calculations without losing attack efficiency.

We have investigated the dynamics of water confined in mesostructured porous silicas (SBA-15, MCM-41) and four periodic mesoporous organosilicas (PMOs) by dielectric relaxation spectroscopy. The influence of water-surface interaction has been controlled by the carefully designed surface chemistry of PMOs that involved organic bridges connecting silica moieties with different repetition lengths, hydrophilicity and H-bonding capability. Relaxation processes attributed to the rotational motions of non-freezable water located in the vicinity of the pore surface were studied in the temperature range from 140 K to 225 K. Two distinct situations were achieved depending on the hydration level: at low relative humidity (33% RH), water formed a non-freezable layer adsorbed on the pore surface. At 75% RH, water formed an interfacial liquid layer sandwiched between the pore surface and the ice crystallized in the pore center. In the two cases, the study revealed different water dynamics and different dependence on the surface chemistry. We infer that these findings illustrate the respective importance of water-water and water-surface interactions in determining the dynamics of the interfacial liquid-like water and the adsorbed water molecules, as well as the nature of the different H-bonding sites present on the pore surface.

Recently, using conditioning approaches on the high-harmonic generation process induced by intense laser-atom interactions, we have developed a new method for the generation of optical Schr\"odinger cat states (M. Lewenstein et al., arXiv:2008.10221 (2020)). These quantum optical states have been proven to be very manageable as, by modifying the conditions under which harmonics are generated, one can interplay between $\textit{kitten}$ and $\textit{genuine cat}$ states. Here, we demonstrate that this method can also be used for the development of new schemes towards the creation of optical Schr\"odinger cat states, consisting of the superposition of three distinct coherent states. Apart from the interest these kind of states have on their own, we additionally propose a scheme for using them towards the generation of large cat states involving the sum of two different coherent states. The quantum properties of the obtained superpositions aim to significantly increase the applicability of optical Schr\"odinger cat states for quantum technology and quantum information processing.

Graphane is a layered material consisting of a sheet of hydrogenated graphene, with a C:H ratio of 1:1. We study isotopic effects in the properties of chair graphane, where H atoms alternate in a chairlike arrangement on both sides of the carbon layer. We use path-integral molecular dynamics simulations, which allows one to analyze the influence of nuclear quantum effects on equilibrium variables of materials. Finite-temperature properties of graphane are studied in the range 50--1500~K as functions of the isotopic mass of the constituent atoms, using an efficient tight-bonding potential. Results are presented for kinetic and internal energy, atomic mean-square displacements, fluctuations in the C--H bond direction, plus interatomic distances and layer area. At low temperature, substituting $^{13}$C for $^{12}$C gives a fractional change of $-2.6 \times 10^{-4}$ in C--C distance and $-3.9 \times 10^{-4}$ in the graphane layer area. Replacing $^2$H for $^1$H causes a larger fractional change in the C--H bond of $-5.7 \times 10^{-3}$. The isotopic effect in C--C bond distance increases (decreases) by applying a tensile (compressive) in-plane stress. These results are interpreted in terms of a quasiharmonic approximation for the vibrational modes. Similarities and differences with isotopic effects in graphene are discussed.

Differential flows among different ion species are often observed in the solar wind, and such ion differential flows can provide the free energy to drive Alfv\'en/ion-cyclotron and fast-magnetosonic/whistler instabilities. Previous works mainly focused on the ion beam instability under the parameters representative of the solar wind nearby 1 au. In this paper we further study the proton beam instability using the radial models of the magnetic field and plasma parameters in the inner heliosphere. We explore a comprehensive distribution of the proton beam instability as functions of the heliocentric distance and the beam speed. We also perform a detailed analysis of the energy transfer between unstable waves and particles and quantify how much the free energy of the proton beam flows into unstable waves and other kinds of particle species (i.e., proton core, alpha particle and electron). This work clarifies that both parallel and perpendicular electric field are responsible for the excitation of oblique Alfv\'en/ion-cyclotron and oblique fast-magnetosonic/whistler instabilities. Moreover, this work proposes an effective growth length to estimate whether the instability is efficiently excited or not. It shows that the oblique Alfv\'en/ion-cyclotron instability, oblique fast-magnetosonic/whistler instability and oblique Alfv\'en/ion-beam instability can be efficiently driven by proton beams drifting at the speed $\sim 600-1300$ km/s in the solar atmosphere. In particular, oblique Alfv\'en/ion-cyclotron waves driven in the solar atmosphere can be significantly damped therein, leading to the solar corona heating. These results are helpful for understanding the proton beam dynamics in the inner heliosphere and can be verified through in situ satellite measurements.

We present a theoretical demonstration on the generation of entangled coherent states and of coherent state superpositions, with photon numbers and energies orders of magnitude higher than those provided by the current technology. This is achieved by utilizing a quantum mechanical multimode description of the single- and two-color intense laser field driven process of high harmonic generation in atoms. It is found that all field modes involved in the high harmonic generation process are entangled, and upon performing a quantum operation, leads to the generation of high photon number non-classical coherent state superpositions spanning from the far infrared to the extreme-ultraviolet spectral region. These states can be considered as a new resource for fundamental tests of quantum theory and quantum information processing.

In the paper, we study the thermodynamic and electromagnetic properties of the Penson--Kolb (PK) model, i.e., the tight--binding model for fermionic particles with the pair-hopping interaction $J$. We focus on the case of repulsive $J$ (i.e., $J<0$), which can stabilize the eta-pairing superconductivity with Cooper-pair center-of-mass momentum $\vec{q}=\vec{Q}$, $\vec{Q}=(\pi/a$,$\pi/a$,\ldots). Numerical calculations are performed for several $d$-dimensional hypercubic lattices: $d=2$ (the square lattice, SQ), $d=3$ (the simple cubic lattice) and $d=\infty$ hypercubic lattice (for arbitrary particle concentration $0<n<2$ and temperature $T$). The ground state $J$ versus $n$ phase diagrams and the crossover to the Bose--Einstein condensation regime are analyzed and the evolution of the superfluid characteristics are examined within the (broken symmetry) Hartree--Fock approximation (HFA). The critical fields, the coherence length, the London penetration depth, and the Ginzburg ratio are determined at $T=0$ and $T>0$ as a function of $n$ and pairing strength. The analysis of the effects of the Fock term on the ground state phase boundaries and on selected PK model characteristics is performed as well as the influence of the phase fluctuations on the eta-pairing superconductivity is investigated. Within the Kosterlitz--Thouless scenario, the critical temperatures $T_{KT} $ are estimated for $d=2$ SQ lattice and compared with the critical temperature $T_c$ obtained from HFA. We also determine the temperature $T_m$ at which minimal gap between two quasiparticle bands vanishes in the eta-phase. Our results for repulsive $J$ are contrasted with those found earlier for the PK model with attractive $J$ (i.e., with $J>0$).