This work introduces a limitation on the minimum value that can be assumed by the energy of a relativistic gas in the presence of a non-zero heat flux. Such a limitation arises from the non-negativity of the particle distribution function, and is found by solving the Hamburger moment problem. The resulting limitation is seen to recover the Taub inequality in the case of a zero heat flux, but is more strict if a non-zero heat flux is considered. These results imply that, in order for the distribution function to be non-negative, (i) the energy of a gas must be larger than a minimum threshold; (ii) the heat flux, on the other hand, has a maximum value determined by the energy and the pressure tensor; and (iii) there exists an upper limit for the the adiabatic index $\Gamma$ of the relativistic equation of state, and that limit decreases in the presence of a heat flux and pressure anisotropy, asymptoting to a value $\Gamma = 1$. The latter point implies that the Synge equation of state is formally incompatible with a relativistic gas showing a heat flux, except in certain gas states.

Following the first principles the analytic Born-Oppenheimer (B-O) potential curve for the ground state $X^1\Sigma^+$ of the molecule (H,D,T)Cl is constructed for whole range of internuclear distances $R \in [0,\infty)$ for the first time with accuracy 3-4-5 figures in comparison with experimental data where they are available. The procedure is based on matching the perturbation theory at small internuclear distances $R$ and the multipole expansion at large distances $R$ into a meromorphic function (two-point P\'ade approximant) which is fixed by fitting experimental data near the equilibrium configuration. With accuracy of 3-4 figures in the energies, it supports for HCl (DCl, TCl) the 836 (1625, 2366) B-O rovibrational bound states with maximal vibrational number $\nu_{max} = 20\, (29, 36)$ and maximal angular momentum $L_{max} = 64\, (90, 109)$ including 24 (46, 63) weakly-bound states (close to dissociation limit) with the energies $\lesssim 10^{-4}$\,Hartree. Insufficiency of available experimental data is indicated and the prediction of missing rovibrational states is made for all three molecules.

The production of waste as a consequence of human activities is one of the most fundamental challenges facing our society and global ecological systems. Waste generation is rapidly increasing, with corresponding shifts in the structure of our societies where almost all nations are moving from rural agrarian societies to urban and technological ones. However, the connections between these radical societal shifts and waste generation have not yet been described. Here we apply scaling theory to establish a new understanding of waste in urban systems. We identify universal scaling laws of waste generation across diverse urban systems worldwide for three forms of waste: wastewater, municipal solid waste, and greenhouse gasses. We show that wastewater generation scales superlinearly, municipal solid waste scales linearly, and greenhouse gasses scales sublinearly with city size. In specific cases production can be understood in terms of city size coupled with financial and natural resources. For example, wastewater generation can be understood in terms of the increased economic activity of larger cities, and the deviations around the scaling relationship - indicating relative efficiency - depend on GDP per person and local rainfall. We also show how the temporal evolution of these scaling relationships reveals a loss of economies of scale and the general increase in waste production, where sublinear scaling relationships become linear. Our findings suggest general mechanisms controlling waste generation across diverse cities and global urban systems. Our approach offers a systematic approach to uncover these underlying mechanisms that might be key to reducing waste and pursing a more sustainable future.

Liquid crystals (LCs) play a fundamental and significant role in modern technology. Recently, they have also been used in active switching, adaptive optics, and next-generation displays for augmented and virtual reality. This is due to the diverse properties of their various phases and the growing physical understanding of LCs. Our goal is to examine the applicability of a new method in determining these quantities for thermotropic uniaxial nematic liquid crystals (NLCs), even though nearly all theoretical and experimental efforts are focused on a deeper understanding of the temperature-dependent free energy behavior and other quantities related to it, especially in the vicinity of the first- and second-order phase transitions of LCs. The method that is being discussed is based on Fresnel diffraction (FD) from phase objects, which has found a wide range of precise metrological applications over the past two decades. Diffractometry is a very sensitive, accurate, and immune technique that can convert any change in the order of LCs as a function of temperature into a change in the optical phase and, as a result, a recordable change in the visibility of the light diffraction pattern from phase steps. This contrasts with interferometry, which is very sensitive to environmental changes. Theoretical investigations, numerical calculations, and comparisons of the results with experimental observations in turn demonstrate very high compliance with the output of other existing methods. As we will see, this method has the potential to not only strengthen existing approaches by addressing some of their flaws and shortcomings but also to take its place next to them.

Energy systems modellers often resort to simplified system representations and deterministic model formulations (i.e., not considering uncertainty) to preserve computational tractability. However, reduced levels of detail and neglected uncertainties can both lead to sub-optimal system designs. In this paper, we present a novel method that quantitatively compares the impact of detail and uncertainty to guide model development and help prioritisation of the limited computational resources. By considering modelling choices as an additional 'uncertain' parameter in a global sensitivity analysis, the method determines their qualitative ranking against conventional input parameters. As a case study, the method is applied to a peer-reviewed heat decarbonisation model for the United Kingdom with the objective of assessing the importance of spatial resolution. The results show that while for the optimal total system cost the impact of spatial resolution is negligible, it is the most important factor determining the capacities of electricity, gas and heat networks.

For nearly the past 30 years, Centroid Molecular Dynamics (CMD) has proven to be a viable classical-like phase space formulation for the calculation of quantum dynamical properties. However, calculation of the centroid effective force remains a significant computational cost and limits the ability of CMD to be an efficient approach to study condensed phase quantum dynamics. In this paper we introduce a neural network-based methodology for first learning the centroid effective force from path integral molecular dynamics data, which is subsequently used as an effective force field to evolve the centroids directly with the CMD algorithm. This method, called Machine-Learned Centroid Molecular Dynamics (ML-CMD) is faster and far less costly than both standard "on the fly" CMD and ring polymer molecular dynamics (RPMD). The training aspect of ML-CMD is also straightforwardly implemented utilizing the DeepMD software kit. ML-CMD is then applied to two model systems to illustrate the approach: liquid para-hydrogen and water. The results show comparable accuracy to both CMD and RPMD in the estimation of quantum dynamical properties, including the self-diffusion constant and velocity time correlation function, but for significantly reduced overall computational cost.

This study concerns a turbulent jet at Mach number $M_j=0.9$, subject to a uniform external flow stream at $M_f=0.15$. We assess the mechanisms that underpin the reduction in fluctuation energy that is known to occur when a jet is surrounded by a flight stream. The analysis combines experimental and numerical databases, spectral proper orthogonal decomposition (SPOD) and linear modelling. The experiments involve Time-Resolved, Stereo PIV measurements at different cross-sections of the jet. A companion large-eddy simulation was performed with the same operating conditions using the "CharLES" solver by Cascade Technologies in order to obtain a complete and highly resolved 3D database. We show that the energy reduction is spread over a broad region of the frequency-wavenumber space and involves, apart from the known stabilization of the modal Kelvin-Helmholtz (KH) instability, the attenuation of flow structures associated with the non-modal Orr and lift-up mechanisms. Streaky structures, associated with helical azimuthal wavenumbers and very slow time scales, are the most strongly affected by the flight stream, in terms of energy attenuation and spatial distortion. The energy reductions are accompanied by a weakening of the low-rank behaviour of the jet dynamics revealed by previous studies. These trends are found to be consistent with results of a local linear model based on the modified mean flow in the flight stream case.

The pharmaceutical success of atorvastatin (ATV), a widely employed drug against the "bad" cholesterol (LDL) and cardiovascular diseases, traces back to its ability to scavenge free radicals. Unfortunately, information on its antioxidant properties is missing or unreliable. Here, we report detailed quantum chemical results for ATV and its ortho- and para-hydroxy metabolites (o-ATV, p-ATV) in the methanolic phase. They comprise global reactivity indices, bond order indices, and spin densities as well as all relevant enthalpies of reaction (bond dissociation BDE, ionization IP and electron attachment EA, proton detachment PDE and proton affinity PA, and electron transfer ETE). With these properties in hand, we can provide the first theoretical explanation of the experimental finding that, due to their free radical scavenging activity, ATV hydroxy metabolites rather than the parent ATV, have substantial inhibitory effect on LDL and the like. Surprisingly (because it is contrary to the most cases currently known), we unambiguously found that HAT (direct hydrogen atom transfer) rather than SPLET (sequential proton loss electron transfer) or SET-PT (stepwise electron transfer proton transfer) is the thermodynamically preferred pathway by which o-ATV and p-ATV in methanolic phase can scavenge DPPH$^\bullet$ (1,1-diphenyl-2-picrylhydrazyl) radicals. From a quantum chemical perspective, the ATV's species investigated are surprising because of the nontrivial correlations between bond dissociation energies, bond lengths, bond order indices and pertaining stretching frequencies, which do not fit the framework of naive chemical intuition.

Based on the phenomenological extension of Darcy's law, two-fluid flow is dependent on a relative permeability function of saturation only that is process/path dependent with an underlying dependency on pore structure. For applications, fuel cells to underground $CO_2$ storage, it is imperative to determine the effective phase permeability relationships where the traditional approach is based on the inverse modelling of time-consuming experiments. The underlying reason is that the fundamental upscaling step from pore to Darcy scale, which links the pore structure of the porous medium to the continuum hydraulic conductivities, is not solved. Herein, we develop an Artificial Neural Network (ANN) that relies on fundamental geometrical relationships to determine the mechanical energy dissipation during creeping immiscible two-fluid flow. The developed ANN is based on a prescribed set of state variables based on physical insights that predicts the effective permeability of 4,500 unseen pore-scale geometrical states with $R^2 = 0.98$.

To include the bound electron effects in particle-in-cell (PIC) simulation, we propose a model in which the response of the dipole components of partially ionized ions to external electromagnetic fields can be included. Instead of treating the macro-ion particle as a single particle without an internal structure, the ions are considered to have a structure composed of a central nucleus and a bounded electron cloud in our model. The two parts experience the interactions of both the external electromagnetic fields and the internal Coulomb fields. In this way, the laser scattering effects by a partially ionized medium can be modeled properly in the PIC simulation. The laser propagation in a neutral medium and the Bragg scattering of the laser in crystal structure have been simulated with a PIC code modified based on our model as the benchmark. Our model may find applications to study some interesting problems, such as the x-ray laser-driven wakefield acceleration in crystals, the x-ray laser-driven high energy density physics, and intense laser propagation in partially ionized nonlinear optical materials, etc.

Microwave signal generation with fast frequency tuning underlies many applications including sensing, imaging, ranging, time keeping, wireless communication, and high-speed electronics. Soliton microcombs are a promising new approach for photonic-based microwave signal synthesis. To date, however, tuning rate has been limited in microcombs (and in frequency combs generally). Here, we demonstrate the first microwave-rate soliton microcomb whose repetition rate can be tuned at a high speed. By integrating an electro-optic tuning/modulation element into a lithium niobate comb microresonator, a modulation bandwidth up to 75 MHz and a continuous frequency modulation rate up to 5.0 * 10^14 Hz/s are achieved, several orders-of-magnitude faster than existing microcomb technology. These features are especially useful for disciplining an optical VCO to a long-term reference such as an optical clock or for tight phase lock in dual-microcomb clocks or synthesizers. Moreover, the microwave signal rate can be set to any X - W band rate. Besides its positive impact on microwave photonics, fast repetition rate control is generally important in all applications of frequency combs.

The self-trapping critical power of light propagation is one of the key physical quantities characterizing nonlinear-beam propagation. Above the critical power, the spatial and temporal profiles of the beam deviate from its original shapes. Therefore, the critical power is considered an important indicator in nonlinear optical phenomena, such as filamentation and laser processing. However, although the concept of the critical power has been established for fundamental waves, it remains unclear if the power-dependent phenomena can also be observed in harmonic generation because of the complex interplay of nonlinear-propagation effects and ionization-plasma effects. In this study, we find the critical power for the third-harmonic generation; the criterion for whether or not temporal-pulse collapse occurs in the third-harmonic generation is determined only by the incident power. Experiments show that a certain incident power exists, at which the third-harmonic power exerts a specific dependence, independent of the focusing conditions. This incident power is approximately six times lower than the self-trapping critical power of the fundamental pulse, which indicates that it is unique to the third-harmonic generation. Numerical calculations reveal that at this incident power, the third-harmonic pulse begins to collapse temporally. Furthermore, the numerical calculations reproduce the experimental results without the nonlinear effects of the fundamental pulse, dispersion effect, and ionization-plasma effects. This shows that the pulse collapse is due to the interference effects from the third-order nonlinear term, which disappears after long-distance propagation due to phase mismatch, and higher-order nonlinear terms. This study demonstrates the existence of the critical power for harmonic pulses and show that higher-order nonlinear effects on the harmonics can yield a universal phenomenon.

Experimental results, supported by precise modelling, demonstrate optimisation of a plasma-based injector with intermediate laser pulse energy ($<1$~J), corresponding to a normalised vector potential $a_0 = 2.15$, using ionisation injection in a tailored plasma density profile. An increase in electron bunch quality and energy is achieved experimentally with the extension of the density downramp at the plasma exit. Optimisation of the focal position of the laser pulse in the tailored plasma density profile is shown to efficiently reduce electron bunch angular deviation, leading to a better alignment of the electron bunch with the laser axis. Single peak electron spectra are produced in a previously unexplored regime by combining an early focal position and adaptive optic control of the laser wavefront through optimising the symmetry of the pre-focal laser energy distribution. Experimental results have been validated through particle-in-cell simulations using realistic laser energy, phase distribution, and temporal envelope, allowing for accurate predictions of difficult to model parameters, such as total charge and spatial properties of the electron bunches, opening the way for more accurate modelling for the design of plasma-based accelerators.

We study magneto-optical coupling in a ferrimagnetic sphere resonator made of Yttrium iron garnet. We find that the resonator can be operated in the telecom band as a polarization-selective optical modulator. Intermodulation gain can be employed in the nonlinear regime for amplification.

A thorough understanding of biological species and of emerging nanomaterials requires, among others, their in-depth characterization with optical techniques capable of nano-resolution. Nanoscopy techniques based on tip-enhanced optical effects have gained over the past years tremendous interest given their potential to probe various optical properties with resolutions depending on the size of a sharp probe interacting with focused light, irrespective of the illumination wavelength. Although their popularity and number of applications is rising, tip-enhanced nanoscopy techniques (TEN) still largely rely on probes that are not specifically developed for such applications, but for Atomic Force Microscopy. This cages their potential in many regards, e.g. in terms of signal-to-noise ratio, attainable image quality, or extent of applications. In this article we place first steps towards next-gen TEN, demonstrating the fabrication and modelling of specialized TEN probes with known optical properties. The proposed framework is highly flexible and can be easily adjusted to be of o benefit to various types of TEN techniques, for which probes with known optical properties could potentially enable faster and more accurate imaging via different routes, such as direct signal enhancement or novel signal modulation strategies. We consider that the reported development can pave the way for a vast number of novel TEN imaging protocols and applications, given the many advantages that it offers.

In dilute turbulent particle-laden flows, such as atmospheric dispersion of pollutants or virus particles, the dynamics of tracer-like to low inertial particles are significantly altered by the fluctuating motion of the carrier fluid phase. Neglecting the effects of fluid velocity fluctuations on particle dynamics causes poor prediction of particle transport and dispersion. To account for the effects of fluid phase fluctuating velocity on the particle transport, stochastic differential equations coupled with large-eddy simulation are proposed to model the fluid velocity seen by the particle. The drift and diffusion terms in the stochastic differential equation are modelled using neural networks ('neural stochastic differential equations'). The neural networks are trained with direct numerical simulations (DNS) of decaying homogeneous isotropic turbulence at low and moderate Reynolds numbers. The predictability of the proposed models are assessed against DNS results through a priori analyses and a posteriori simulations of decaying homogeneous isotropic turbulence at low-to-high Reynolds numbers. Total particle fluctuating kinetic energy is under-predicted by 40% with no model, compared to the DNS data. In contrast, the proposed model predictions match total particle fluctuating kinetic energy to within 5% of the DNS data for low to high-inertia particles. For inertial particles, the model matches the variance of uncorrelated particle velocity to within 10% of DNS results, compared to 60-70% under-prediction with no model. It is concluded that the proposed model is applicable for flow configurations involving tracer and inertial particles, such as transport and dispersion of pollutants or virus particles.

In this paper, we have designed and investigated the performance of radial GaAs/AlGaAs pin junction nanocone array solar cells by performing coupled optoelectronic simulations to obtain the most optimal design configuration based on its photovoltaic properties. Each model has been compared with its GaAs shell counterparts for different levels of surface passivations. It has been observed that the nanocones with the AlGaAs shell has a much better performance compared to those having GaAs shell. AlGaAs shell acts as a strong barrier restricting most of the photogeneration to the inner GaAs regions and it also acts as a strong passivation layer, reducing the recombination losses due to surface effects. Further, it is observed that the nanocones achieve their highest photoconversion efficiency when they are sparsely packed, with a constant i-shell thickness of 7-9 nm and have an angle of tilt of 5 degrees. This enhanced performance is attributed to a more effective and extended photogeneration throughout the nanowire length, a strong overlapping built-in electric field, and lower recombination losses.

We develop a general framework to describe the cubically nonlinear interaction of a unidirectional degenerate quartet of deep-water gravity waves. Starting from the discretised Zakharov equation, and thus without restriction on spectral bandwidth, we derive a planar Hamiltonian system in terms of the dynamic phase and a modal amplitude. This is characterised by two free parameters: the wave action and the mode separation between the carrier and the side-bands. The mode separation serves as a bifurcation parameter, which allows us to fully classify the dynamics. Centres of our system correspond to non-trivial, steady-state nearly-resonant degenerate quartets. The existence of saddle-points is connected to the instability of uniform and bichromatic wave trains, generalising the classical picture of the Benjamin-Feir instability. Moreover, heteroclinic orbits are found to correspond to primitive, three-mode breather solutions, including an analogue of the famed Akhmediev breather solution of the nonlinear Schr\"odinger equation.

Spherical-cap-shaped interfacial nanobubbles (NBs) forming on hydrophobic surfaces in aqueous solutions have extensively been studied both from a fundamental point of view and due to their relevance for various practical applications. In this study, the nucleation mechanism of spontaneously generated NBs at solid-liquid interfaces of immersed nanostructured hydrophobic surfaces is studied. Depending on the size and density of the surface nanostructures, NBs with different size and density were reproducibly and deterministically obtained. A two-step process can explain the NB nucleation, based on the crevice model, i.e., entrapped air pockets in surface cavities which grow by diffusion. The results show direct evidence for the spontaneous formation of NBs on a surface at its immersion. Next, the influence of size and shape of the nanostructures on the nucleated NBs are revealed. In particular, on non-circular nanopits we obtain NBs with a non-circular footprint, demonstrating the strong pinning forces at the three-phase contact line.

The Quaternary geodynamics of the Central Mediterranean region is controlled by the migration of narrow orogenic belts within the slow Nubia-Eurasia plate convergence. As testified by the occurrence of major volcanic and seismic events, the Eastern Sicilian Margin is presently one of the most active regions. Using a Permanent-Scatterer approach, we process Sentinel-1 satellite images acquired from 2015 to 2020 to provide an island-wide quantification of surface displacements at a high spatiotemporal resolution. We then convert the calculated mean surface velocities along the ascending and descending satellite line of sight into the ITRF2014 reference frame by using GNSS velocity data derived from regional stations. The resulting pseudo-3D velocity field mainly highlights a general uplift of about $1.5 \pm 0.5$ mm/yr of the Nebrodi-Peloritani range and its differential motion with respect to mainland Sicily along the Cefal\`u-Etna seismic zone. Permanent/Persistent-Scatterer (PS) vertical velocities in the Eastern Hyblean region reveal a long wavelength eastward down-bending of the margin, including the inferred epicentral area of the 1693 Noto earthquake. Compared to Quaternary coastal uplift rates, these results confirm the relative low activity of Western Sicily, a potential slow uplift of South-Central Sicily and a significant discrepancy along the Eastern Hyblean margin were PS-derived vertical velocities that appear 2-3 mm/yr lower than the Quaternary rates. Over the 2015--2020 timespan, transient processes are also captured, notably on Mount Etna, showing both magmatic pressurization uplift and collapse of the eastern flank, but also all over Sicily where numerous gravitational mass movements and anthropogenic ground subsidence are detected.

In our study, we determine the alignment of magnetic domains in a CoFeB layer using THz radiation. We generate THz-pulses by fs-laser-pulses in magnetized CoFeB/Pt heterostructures, based on spin currents. An LT-GaAs Auston switch detects the radiation phase-sensitively and allows to determine the magnetization alignment. Our scanning technique with motorized stages with step sizes in the sub-micrometer range, allows to image two dimensional magnetic structures. Theoretically the resolution is restricted to half of the wavelength if focusing optics in the far-field limit are used. By applying near-field imaging, the spatial resolution is enhanced to the single digit micrometer range. For this purpose, spintronic emitters in diverse geometric shapes, e.g. circles, triangles, squares, and sizes are prepared to observe the formation of magnetization patterns. The alignment of the emitted THz radiation can be influenced by applying unidirectional external magnetic fields. We demonstrate how magnetic domains with opposite alignment and different shapes divided by domain walls are created by demagnetizing the patterns using minor loops and imaged using phase sensitive THz radiation detection. For analysis, the data is compared to Kerr microscope images. The possibility to combine this method with THz range spectroscopic information of magnetic texture or antiferromagnets in direct vicinity to the spintronic emitter, makes this detection method interesting for much wider applications probing THz excitation in spin systems with high resolution beyond the Abbe diffraction limit, limited solely by the laser excitation area.

We report the simulation results for angular resolution of an electromagnetic (EM) sampling calorimeter with photons in the range of 100 MeV to 2 GeV. The simulation model of the EM calorimeter consists of alternating layers of an 1-mm-thick Pb plate and a 5-mm-thick plastic scintillator plate. The scintillator plates are alternately segmented into horizontal and vertical strips. In this study, we obtained energy deposits in individual strips using Geant4 simulations and reconstructed the incident photon angles using XGBoost with gradient-boosted decision trees. The performance of the angle reconstruction depends on both the detector configuration and accuracy of machine learning. The angular resolution so obtained can be expressed as $0.24 \oplus 1.24/\sqrt{E_{\gamma}}$, where $E_{\gamma}$ is the incident photon energy in GeV. This energy dependence is consistent for different incident angles in the range of 15$^{\circ}$ to 40$^{\circ}$.

Machine learning assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality electronic structure data, a model that can be pretrained on all available data and finetuned on downstream tasks with a small additional effort would bring the field to a new stage. Here we propose DPA-1, a Deep Potential model with a novel attention mechanism, which is highly effective for representing the conformation and chemical spaces of atomic systems and learning the PES. We tested DPA-1 on a number of systems and observed superior performance compared with existing benchmarks. When pretrained on large-scale datasets containing 56 elements, DPA-1 can be successfully applied to various downstream tasks with a great improvement of sample efficiency. Surprisingly, for different elements, the learned type embedding parameters form a $spiral$ in the latent space and have a natural correspondence with their positions on the periodic table, showing interesting interpretability of the pretrained DPA-1 model.

With the increasing industrial relevance of new quantum technologies, a well educated quantum workforce becomes increasingly crucial and raises important questions. What are the expectations regarding the future relevance of second generation quantum technologies? And what are the requirements for the workforce in the coming quantum industry? What competences, knowledge and skills should the future employees have? In this paper, we report the results of our Delphi study that was aimed at mapping requirements and forecasts for the future quantum workforce. Our Delphi study consisted of three consecutive survey rounds. In total, we gathered 188 responses from industry and academic experts across Europe. Our study results served as an input for the development of the European Competence Framework for Quantum Technologies, delivered by the project QTEdu CSA for the European Quantum Flagship. In addition, we will discuss predictions from experts related to the future quantum workforce, including the expected industrial relevance of the main areas of quantum technologies, the need for educational efforts, and the expected influence of quantum technologies on everyday life.

Backflow, or retro-propagation, is a counterintuitive phenomenon where for a forward-propagating wave the energy or probability density locally propagates backward. In this study the energy backflow has been examined in connection with relatively simple causal unidirectional finite-energy solutions of the wave equation which are derived from a factorization of the so-called basic splash mode. Specific results are given for the energy backflow arising in known azimuthally symmetric unidirectional wavepackets, as well as in novel azimuthally asymmetric extensions. Using the Bateman-Whittaker technique, a novel finite-energy unidirectional null localized wave has been constructed that is devoid of energy backflow and has some of the topological properties of the basic Hopfion.

The Jiangmen underground neutrino observatory (JUNO) is a neutrino project with a 20-kton liquid scintillator detector located at 700-m underground. The large 20-inch PMTs are one of the crucial components of the JUNO experiment aiming to precision neutrino measurements with better than 3% energy resolution at 1 MeV. The excellent energy resolution and a large fiducial volume provide many exciting opportunities for addressing important topics in neutrino and astro-particle physics. With the container #D at JUNO Pan-Asia PMT testing and potting station, the features of waterproof potted 20-inch PMTs were measured with JUNO 1F3 electronics prototype in waveform and charge, which are valuable for better understanding on the performance of the waterproof potted PMTs and the JUNO 1F3 electronics. In this paper, basic features of JUNO 1F3 electronics prototype run at Pan-Asia will be introduced, followed by an analysis of the waterproof potted 20-inch PMTs and a comparison with the results from commercial electronics used by the container #A and #B.

Climate projection uncertainty can be partitioned into model uncertainty, scenario uncertainty and internal variability. Here, we investigate the different sources of uncertainty in the projected frequencies of daily maximum temperature and precipitation extremes, which are defined as events that exceed the 99.97th percentile. This is done globally using initial-condition large ensembles. For maximum temperature extremes, internal variability dominates in the next two decades. Around the middle of the 21st century model and scenario uncertainty become the dominant contribution in the tropics but internal variability remains dominant in the extra-tropics. Towards the end of the century, model and scenario uncertainty increase to near equal contributions of ~40% each globally with large regional fluctuations. For precipitation extremes, internal variability dominates throughout the 21st century, except for some tropical regions, for example, West Africa. In regions where internal variability constitutes the major source of uncertainty, the potential impact of reducing model uncertainty on the signal-to-noise ratio of the climate projection is estimated to be small. We discuss the caveats of the methodology used and impact of our findings for the design of future climate models. The importance of internal variability found here emphasizes that large ensembles are a vital tool for understanding climate projections.

Frequency-domain simulation of seismic waves plays an important role in seismic inversion, but it remains challenging in large models. The recently proposed physics-informed neural network (PINN), as an effective deep learning method, has achieved successful applications in solving a wide range of partial differential equations (PDEs), and there is still room for improvement on this front. For example, PINN can lead to inaccurate solutions when PDE coefficients are non-smooth and describe structurally-complex media. In this paper, we solve the acoustic and visco-acoustic scattered-field wave equation in the frequency domain with PINN instead of the wave equation to remove source singularity. We first illustrate that non-smooth velocity models lead to inaccurate wavefields when no boundary conditions are implemented in the loss function. Then, we add the perfectly matched layer (PML) conditions in the loss function of PINN and design a quadratic neural network to overcome the detrimental effects of non-smooth models in PINN. We show that PML and quadratic neurons improve the results as well as attenuation and discuss the reason for this improvement. We also illustrate that a network trained during a wavefield simulation can be used to pre-train the neural network of another wavefield simulation after PDE-coefficient alteration and improve the convergence speed accordingly. This pre-training strategy should find application in iterative full waveform inversion (FWI) and time-lag target-oriented imaging when the model perturbation between two consecutive iterations or two consecutive experiments can be small.

The polarization plane stimulated rotation angle of probe signal in the intense laser field in plasma is calculated. The estimates of the residual gas local density in a cesium plasma based on the effects of Faraday, Cotton-Mouton and stimulated rotation of probe signal in the intense laser field have been found. A brief theory of resonant change in the plane of polarization of a probe signal under the action of an intense pulse is presented. It is shown, that the rotation in the medium has a complex structure.

Resistive Silicon Detectors (RSDs) are based on the LGAD technology, characterized by a continuous gain layer, and by the innovative introduction of resistive read-out. Thanks to a novel electrode design aimed at maximizing signal sharing, the second FBK production of RSD sensors, RSD2, achieves a position resolution on the whole pixel surface of about 8 $\mu m$ for 200-$\mu m$ pitch. RSD2 arrays have been tested in the Laboratory for Innovative Silicon Sensors in Torino using a Transient Current Technique setup equipped with a 16-channel digitizer, and results on spatial resolution have been obtained with machine learning algorithms.

X-ray photoemission spectroscopy (XPS) provides direct information on the atomic composition and stoichiometry by measuring core electron binding energies. Moreover, according to the shift of the binding energy, so-called chemical shift, the precise chemical type of bonds can be inferred, which brings additional information on the local structure. In this work, we present a theoretical study of the chemical shift firstly by comparing different theories, from Hartree-Fock (HF) and density-functional theory (DFT) to many-body perturbation theory (MBPT) approaches like the GW approximation and its static version (COHSEX). The accuracy of each theory is assessed by benchmarking against the experiment on the chemical shift of the carbon 1s electron in a set of molecules. More importantly, by decomposing the chemical shift into different contributions according to terms in the total Hamiltonian, the physical origin of the chemical shift is identified as classical electrostatics.

Uncertainty quantification (UQ) is important to machine learning (ML) force fields to assess the level of confidence during prediction, as ML models are not inherently physical and can therefore yield catastrophically incorrect predictions. Established a-posteriori UQ methods, including ensemble methods, the dropout method, the delta method, and various heuristic distance metrics, have limitations such as being computationally challenging for large models due to model re-training. In addition, the uncertainty estimates are often not rigorously calibrated. In this work, we propose combining the distribution-free UQ method, known as conformal prediction (CP), with the distances in the neural network's latent space to estimate the uncertainty of energies predicted by neural network force fields. We evaluate this method (CP+latent) along with other UQ methods on two essential aspects, calibration, and sharpness, and find this method to be both calibrated and sharp under the assumption of independent and identically-distributed (i.i.d.) data. We show that the method is relatively insensitive to hyperparameters selected, and test the limitations of the method when the i.i.d. assumption is violated. Finally, we demonstrate that this method can be readily applied to trained neural network force fields with traditional and graph neural network architectures to obtain estimates of uncertainty with low computational costs on a training dataset of 1 million images to showcase its scalability and portability. Incorporating the CP method with latent distances offers a calibrated, sharp and efficient strategy to estimate the uncertainty of neural network force fields. In addition, the CP approach can also function as a promising strategy for calibrating uncertainty estimated by other approaches.

We present the advantages of supercontinuum generation in chiral, therefore circularly birefringent, all-normal dispersion fibers. Due to the absence of nonlinear power transfer between the polarization eigenstates of the fiber, chiral all-normal dispersion fibers do not exhibit any polarization instabilities and thus are an ideal platform for low-noise supercontinuum generation. By pumping a chiral all-normal dispersion fiber at 802 nm, we obtained an octave-spanning, robustly circularly polarized supercontinuum with low-noise.

This paper provides an analytical solution for the deformation of an elastic half-space caused by a cylindrical roller. The roller is considered rigid, and is forced into the half space and rolls across its surface, with contact modelled by Coulomb friction. In general, portions of the surface of the roller in contact with the half space may slip across the surface of the half space, or may stick to it. In this paper, we consider only the regime where all of the rollers contact surface is slipping. This results in a mixed boundary value problem, which is formulated as a $2\times 2$ matrix Wiener-Hopf problem. The exponential factors in the Wiener-Hopf matrix allows a solution by following the iterative method of Priddin, Kisil, and Ayton (Phil. Trans. Roy. Soc. A 378, p. 20190241, 2020) which is implemented numerically by computing Cauchy transforms using a spectral method following Slevinsky and Olver (J. Comput. Phys. 332, pp. 290-315, 2017). The limits of the contact region are located a posteriori by applying an optimisation method. The solution is illustrated with several examples, and numerical code to compute the solutions in general is included in the supplementary material.

Most ultrasound (US) imaging techniques use spatially-constant speed-of-sound (SoS) values for beamforming. Having a discrepancy between the actual and used SoS value leads to aberration artifacts, e.g., reducing the image resolution, which may affect diagnostic usability. Accuracy and quality of different US imaging modalities, such as tomographic reconstruction of local SoS maps, also depend on a good initial beamforming SoS. In this work, we develop an analytical method for estimating mean SoS in an imaged medium. We show that the relative shifts between beamformed frames depend on the SoS offset and the geometric disparities in transmission paths. Using this relation, we estimate a correction factor and hence a corrected mean SoS in the medium. We evaluated our proposed method on a set of numerical simulations, demonstrating its utility both for global SoS prediction and for local SoS tomographic reconstruction. For our evaluation dataset, for an initial SoS under- and over-assumption of 5% the medium SoS, our method is able to predict the actual mean SoS within 0.3% accuracy. For the tomographic reconstruction of local SoS maps, the reconstruction accuracy is improved on average by 78.5% and 87%, respectively, compared to an initial SoS under- and over-assumption of 5%.

We propose a variation of the classical Szilard engine that uses a porous piston. Such an engine requires neither information about the position of the particle, nor the removal and subsequent insertion of the piston when resetting the engine to continue doing work by lifting a mass against a gravitational field. Though the engine operates in contact with a single thermal reservoir, the reset mechanism acts as a second reservoir, dissipating energy when a mass that has been lifted by the engine is removed to initiate a new operation cycle.

We present octave-wide bandpass filters in the terahertz (THz) region based on bilayer-metamaterial (BLMM) structures. The passband region has a super-Gaussian shape with a maximum transmittance approaching 70% and a typical stopband rejection of 20 dB. The design is based on a metasurface consisting of a metallic square-hole array deposited on a transparent polymer, which is stacked on top of an identical metasurface with a sub-wavelength separation. The superimposed metasurface structures were designed using finite-difference time-domain (FDTD) simulations and fabricated using a photolithography process. Experimental characterization of these structures between 0.3 to 5.8 THz is performed with a time-domain THz spectroscopy system. Good agreement between experiment and simulation results is observed. We also demonstrate that two superimposed BLMM (2BLMM) devices increase the steepness of the roll-offs to more than 85 dB/octave and enable a superior stopband rejection approaching 40 dB while the maximum transmittance remains above 64%. This work paves the way toward new THz applications, including the detection of THz pulses centered at specific frequencies, and an enhanced time-resolved detection sensitivity towards molecular vibrations that are noise dominated by a strong, off-resonant, driving field.

Zhuang and Shapiro have recently discussed how quantum illumination can be used to increase the mean value range delay. In this paper it is shown how multiple entangled photon quantum illumination helps to reduce the integration time when evaluating range delay. The analysis is conveyed in the setting of three entangled photon states discrete quantum illumination models, but it is argued the extension of the main result to the setting of continuous quantum illumination models.

To provide optimal depth resolution with a coded-aperture Laue diffraction microscope, an accurate position of the coded-aperture and its scanning geometry need to be known. However, finding the geometry by trial and error is a time-consuming and often challenging process because of the large number of parameters involved. In this paper, we propose an optimization approach to automate the focusing process after data is collected. We demonstrate the robustness and efficiency of the proposed approach with experimental data taken at a synchrotron facility.

A set of programs for the numerical simulation of the diffusion decomposition processes was developed by using simulation methods, kinetic and particle method. The complex has been validated on the model system Ni-Al by the growth of -phase separations. The results on the evolution of the distribution function and other characteristics of the ensemble, which in the zero volume fraction approximation are asymptotically in good agreement with the theory and the experiment, have been obtained. The peculiarity of the created program complex is the possibility of its adaptation to the description of the decomposition of multicomponent multiphase systems

C-H bond activation enables the facile synthesis of new chemicals. While C-H activation in short-chain alkanes has been widely investigated, it remains largely unexplored for long-chain organic molecules. Here, we report light-driven C-H activation in complex organic materials mediated by 2D transition metal dichalcogenides (TMDCs) and the resultant solid-state synthesis of luminescent carbon dots in a spatially resolved fashion. Through the first-principle calculations, we unravel that the defects and oxidized states in 2D TMDCs lead to efficient C-H activation and chemical reaction. Furthermore, we exploit the light-controlled point-and-shoot chemical reaction for versatile carbon dot patterning and optical encoding of encrypted information. Our results will shed light on 2D materials for C-H activation in a variety of organic compounds for applications in organic chemistry, photonic materials, and environmental remediation.

Decay rates of the positronium hydride PsH, a bound state of a proton, a positron, and two electrons, are determined for two rare channels, PsH $\to p^+ e^- \gamma$ and PsH $\to p^+ e^-$. Previous studies overestimated these rates by factors of about 2 and 700, respectively. We explain the physics underlying these wrong predictions. We confirm a range of static PsH properties, including the non-relativistic ground state energy, expectation values of inter-particle distances and their powers, and the three and four particle coalescence probabilities, using a variational method in the Gaussian basis.

This is a personal perspective on data sharing in the context of public data releases suitable for generic analysis. These open data can be a powerful tool for expanding the science of high energy physics, but care must be taken in when, where, and how they are utilized. I argue that data preservation even within collaborations needs additional support in order to maximize our science potential. Additionally, it should also be easier for non-collaboration members to engage with collaborations. Finally, I advocate that we recognize a new type of high energy physicist: the 'data physicist', who would be optimally suited to analyze open data as well as develop and deploy new advanced data science tools so that we can use our precious data to their fullest potential. This document has been coordinated with a white paper on open data commissioned by the American Physical Society's (APS) Division of Particles and Field (DPS) Community Planning Exercise ('Snowmass') Theory Frontier [1] and relevant also for the Computational Frontier.

We report on experimentally measured drag force experienced by a solid cylinder penetrating a granular bed of glass beads including, specifically, a highly polydisperse sample with grain sizes in the range 1-100 {\mu}m. We consider both cases of lateral and axial intrusion in which the long axis of the cylinder is held horizontally and vertically, respectively. We explore different regimes of behavior for the drag force as a function of the penetration depth. In lateral intrusion, where the motion is effectively quasi-two-dimensional, we establish quantitative comparisons with existing theoretical predictions across the whole range of depths. In axial intrusion, we observe peculiar undulations in the force-depth profiles in a wide range of intrusion speeds and for different cylinder diameters. We argue that these undulations reflect general shear failure in the highly polydisperse sample and can be understood based on the ultimate bearing capacity theory on a semiquantitative level.

The fast solar wind that fills the heliosphere originates from deep within regions of open magnetic field on the Sun called coronal holes. However the energy source responsible for accelerating the outflowing plasma to such high speeds is still widely debated, although there is broad evidence that it is ultimately magnetic in nature with candidate mechanisms including Alfven wave heating and interchange reconnection. The magnetic field near the solar surface within coronal holes is structured on spatial scales associated with the boundaries of meso-scale supergranulation convection cells, where descending flows create intense bundles of magnetic field. The energy density in these network magnetic field bundles is a likely candidate as an energy source of the wind. Here we report measurements of two fast solar wind streams from the Parker Solar Probe (PSP) spacecraft near its 10th perihelion which provides strong evidence for the interchange reconnection mechanism. Specifically, we show that supergranulation structure at the coronal hole base remains imprinted in the near-Sun solar wind resulting in asymmetric patches of magnetic 'switchbacks' and bursty solar wind streams with corresponding energetic ions with power law-like distributions extending to beyond 100 keV. Particle-in-cell simulations of interchange reconnection between open and closed magnetic structures support key features of the observations, including the energetic ion spectra. Important characteristics of interchange reconnection in the low corona are inferred from the PSP data including that the reconnection is collisionless and that the rate of energy release is sufficient to heat the ambient plasma and drive the fast wind.

Membrane viscosity is usually assumed to only affect short-wavelength undulations of lipid bilayers. Here, we show that fluctuation dynamics about a curved shape such as a quasi-spherical vesicle is sensitive to the membrane viscosity even at long wavelengths, if the Saffman-Debr\"uck length is larger than the radius of curvature. The theory predicts a relaxation rate of $\sim \ell^4$ for a spherical harmonic mode $\ell$, a drastic change from the classic result $\sim \ell^3$. Accordingly, the anomalous diffusion exponent governing the Dynamic Structure Factor (DSF) becomes 1/2 instead of the commonly used 2/3 [Zilman and Granek, Phys. Rev. Lett. (1996)]. Flickering spectroscopy of the shape fluctuations of giant vesicles made of phospholipid/cholesterol mixtures confirm the theoretical results and, for the first time, demonstrate the effect of membrane viscosity in the bilayer thermal undulations. The new DSF scaling implies that the data analysis in methods that utilize DSF of liposomes, e.g., neutron spin echo, need to be reassessed.

Molecular hydrogen (H$_2$) production by electrochemical hydrogen evolution reaction (HER) is being actively explored for non-precious-metal based electrocatalysts that are earth-abundant and low cost like MoS$_2$. Although it is acid-stable, its applicability is limited by catalytically inactive basal plane, poor electrical transport and inefficient charge transfer at the interface. Therefore, the present work examines its bilayer van der Waals heterostructure (vdW HTS). The second constituent monolayer Boron Phosphide (BP) is advantageous as an electrode material owing to its chemical stability in both oxygen and water environments. Here, we have performed first-principles based calculations under the framework of density functional theory (DFT) for HER in an electrochemical double layer model with the BP monolayer, MoS$_2$/BP and MoSSe/BP vdW HTSs. The climbing image nudged elastic band method (CI-NEB) has been employed to determine the minimum energy pathways for Tafel and Heyrovsky reactions. The calculations yield that Tafel reaction shows no reaction barrier. Thereafter, for Heyrovsky reaction, we have obtained low reaction barrier in the vdW HTSs as compared to that in the BP monolayer. Subsequently, we have observed no significant difference in the reaction profile of MoS$_2$/BP and MoSSe/BP vdW HTSs in case of high coverage (25 %) and 1/3 H$^+$ concentration (conc.). However, in the case of small coverage (11 %) and 1/3 H$^+$ conc., MoSSe/BP shows feasible Heyrovsky reaction with no reaction barrier. Finally, on comparing the coverages with 1/4 H$^+$ conc., we deduce high coverage with low conc. and low coverage with high conc. to be apt for HER via Heyrovsky reaction path.

Variational quantum eigensolver (VQE) is a hybrid quantum-classical technique that leverages noisy intermediate scale quantum (NISQ) hardware to obtain the minimum eigenvalue of a model Hamiltonian. VQE has so far been used to simulate condensed matter systems as well as quantum chemistry of small molecules. In this work, we employ VQE methods to obtain the ground-state energy of LiCoO$_2$, a candidate transition metal oxide used for battery cathodes. We simulate Li$_2$Co$_2$O$_4$ and Co$_2$O$_4$ gas-phase models, which represent the lithiated and delithiated states during the discharge and the charge of the Li-ion battery, respectively. Computations are performed using a statevector simulator with a single reference state for three different trial wavefunctions: unitary coupled-cluster singles and doubles (UCCSD), unitary coupled-cluster generalized singles and doubles (UCCGSD) and k-unitary pair coupled-cluster generalized singles and doubles (k-UpCCGSD). The resources in terms of circuit depth, two-qubit entangling gates and wavefunction parameters are analyzed. We find that the k-UpCCGSD with k=5 produces results similar to UCCSD but at a lower cost. Finally, the performance of VQE methods is benchmarked against the classical wavefunction-based methods, such as coupled-cluster singles and doubles (CCSD) and complete active space configuration interaction (CASCI). Our results show that VQE methods quantitatively agree with the results obtained from CCSD. However, the comparison against the CASCI results clearly suggests that advanced trial wavefunctions are likely necessary to capture the multi-reference characteristics as well as the correlations emerging from high-level electronic excitations.

Interferometry is a prime technique for modern precision measurements. Atoms, unlike light, have significant interactions with electric, magnetic, and gravitational fields, making their use in interferometric applications particularly versatile. Here, we demonstrate atom interferometry to image optical and magnetic potential landscapes over an area exceeding $240 \mu m \times 600 \mu m$. The differential potentials employed in our experiments generate phase imprints in an atom laser that are made visible through a Ramsey pulse sequence. We further demonstrate how advanced pulse sequences can enhance desired imaging features, e.g. to image steep potential gradients. A theoretical discussion is presented that provides a semiclassical analysis and matching numerics.

We propose a theoretical framework for the dynamics of bulk isotropic hard-sphere systems in the presence of randomly pinned particles and apply this theory to supercooled water to validate it. Structural relaxation is mainly governed by local and non-local activated process. As the pinned fraction grows, a local caging constraint becomes stronger and the long range collective aspect of relaxation is screened by immobile obstacles. Different responses of the local and cooperative motions results in subtle predictions for how the alpha relaxation time varies with pinning and density. Our theoretical analysis for the relaxation time of water with pinned molecules quantitatively well describe previous simulations. In addition, the thermal dependence of relaxation for unpinned bulk water is also consistent with prior computational and experimental data.

Owing to the limitation of traditional analytical methods, the coloration mechanism of copper red glaze has been disputed in the academic field for a long time, which mainly focuses on whether the color agent is metallic copper nanoparticles or cuprous oxide (Cu2O) nanoparticles. Based on Mie scattering theory, this work calculated the reflection spectra of nanoparticles uniformly dispersed in transparent glaze with different types, diameters and volume fractions, then discussed the differences between the reflection spectra of metallic copper and cuprous oxide as scatters, calculated the corresponding L*a*b* values, and compared them with the experimental results. This work provides a feasible and convenient method to distinguish these two coloration mechanisms.

Isolated, micro-meter sized diamonds are grown by micro-wave plasma chemical vapour deposition technique on Si(001) substrates. Each diamond is uniquely identified by markers milled in the Si substrate by Ga+ focused ion beam. The morphology and micrograin structure analysis indicates that the diamonds are icosahedral or bi-crystals. Icosahedral diamonds have higher (up to $\sigma_\mathrm{h}$ = 2.3 GPa), and wider distribution ($\Delta\sigma_\mathrm{h}$ = 4.47 GPa) of hydrostatic stress built up at the microcrystal grain boundaries, compared to the other crystals. The number and spectral shape of SiV- color centers incorporated in the micro-diamonds is analysed, and estimated by means of temperature dependent photoluminescence measurements, and Montecarlo simulations. The Montecarlo simulations indicate that the number of SiV- color centers is a few thousand per micro-diamond.

Swarms are examples of collective behavior of insects, which are singular among manifestations of flocking. Swarms possess strong correlations but no global order and exhibit finite-size scaling with a dynamic critical exponent $z \approx 1$. We have discovered a phase transition of the three-dimensional harmonically confined Vicsek model that exists for appropriate noise and small confinement strength. On the critical line of confinement versus noise, swarms are in a state of scale-free chaos that can be characterized by minimal correlation time, correlation length proportional to swarm size and topological data analysis. The critical line separates dispersed single clusters from confined multicluster swarms. Susceptibility, correlation length, dynamic correlation function and largest Lyapunov exponent obey power laws. Their critical exponents agree with those observed in natural midge swarms, unlike values obtained from the order-disorder transition of the standard Vicsek model which confines particles by artificial periodic boundary conditions.

In the chemotactic motion of Escherichia coli, the switching of transmembrane chemoreceptors between active and inactive states is one of the most important steps of the signaling pathway. We study the effect of this switching time-scale on the chemotactic performance of the cell. We quantify performance by the chemotactic drift velocity of the cell. Our extensive numerical simulations on a detailed theoretical model show that as the activity switching rate increases, the drift velocity increases and then saturates. Our data also show the mean duration of a downhill run decreases strongly with the switching rate, while that of an uphill run decreases relatively slowly. We explain this effect from temporal variation of activity along uphill and downhill trajectories. We show that for large and small switching rates the nature of activity variation show qualitatively different behaviors along a downhill run but similar behavior along an uphill run. This results in a stronger dependence of downhill run duration on the switching rate and relatively milder dependence for uphill run duration.

Active droplets are artificial microswimmers built from a liquid dispersion by microfluidic tools and showing self-propelled motion. These systems hold particular interest for mimicking biological phenomena, such as some aspects of cell locomotion and collective behaviors of bacterial colonies, as well as for the design of droplet-based biologically inspired materials, such as engineered tissues. Growing evidence suggests that geometrical confinement crucially affects their morphology and motility, but the driving physical mechanisms are still poorly understood. Here we study the effect of activity on a droplet containing a contractile fluid confined within microfluidic channels of various sizes. We find a surprising wealth of shapes and dynamic regimes, whose mechanics is regulated by a subtle interplay between contractile stress, droplet elasticity and microchannel width. They range from worm-like and fish-like shaped droplets displaying an oscillating behavior within wider channels to bullet-shaped droplets exhibiting rectilinear motion in narrower slits. Our findings support the view that geometrical confinement can provide a viable strategy to control and predict the propulsion direction of active droplets. It would be of interest to look for analogues of these motility modes in biological cells or in synthetic active matter.

Carbon macromolecules are intermediates between small gas-phase species and larger dust structures. I illustrate how observations and dedicated laboratory experiments support this picture.

The productivity of a common pool of resources may degrade when overly exploited by a number of selfish investors, a situation known as the tragedy of the commons (TOC). Without regulations, agents optimize the size of their individual investments into the commons by balancing incurring costs with the returns received. The resulting Nash equilibrium involves a self-consistency loop between individual investment decisions and the state of the commons. As a consequence, several non-trivial properties emerge. For $N$ investing actors we proof rigorously that typical payoffs do not scale as $1/N$, the expected result for cooperating agents, but as $(1/N)^2$. Payoffs are hence functionally reduced, a situation denoted catastrophic poverty. This occurs despite the fact that the cumulative investment remains finite when $N\to\infty$. Catastrophic poverty is instead a consequence of an increasingly fine-tuned balance between returns and costs. In addition, we point out that a finite number of oligarchs may be present. Oligarchs are characterized by payoffs that are finite and not decreasing when $N$ increases. Our results hold for generic classes of models, including convex and moderately concave cost functions. For strongly concave cost functions the Nash equilibrium undergoes a collective reorganization, being characterized instead by entry barriers and sudden death forced market exits.

Quantifying the optical chirality of a sample requires the precise measurement of the rotation of the plane of linear polarisation of the transmitted light. Central to this notion is that the sample needs to be exposed to light of a defined polarisation state. We show that by using a polarisation-entangled photon source we can measure optical activity whilst illuminating a sample with unpolarised light. This not only allows for low light measurement of optical activity but also allows for the analysis of samples that would otherwise be perturbed if subject to polarised light.

A precision luminosity measurement is essential for LHC cross-section measurements to determine fundamental parameters of the standard model and constrain or discover beyond-the-standard-model phenomena. The luminosity of the CMS detector has been measured at the LHC Interaction Point 5 using proton-proton collisions at $\sqrt{s}=13$ TeV during the Run 2 data-taking period (2015-2018). The absolute luminosity scale is obtained using beam-separation scans and the Van der Meer (VdM) method, and several systematic uncertainty sources are investigated, from the knowledge of the scale of beam separation provided by LHC magnets to the nonfactorizability of the spatial components of proton bunch density distributions in the transverse direction. When the VdM calibration is applied to the entire data-taking period, the detector linearity and stability measurements contribute significantly to the total uncertainty in the integrated luminosity. In 2016-2018, the reported integrated luminosity was among the most precise measurements at bunched-beam hadron colliders.

We extend the continuum theory of active nematic fluids to study cell flows and tissue dynamics inside multicellular spheroids, spherical, self-assembled aggregates of cells that are widely used as model systems to study tumour dynamics. Cells near the surface of spheroids have better access to nutrients and therefore proliferate more rapidly than those in the resource-depleted core. Using both analytical arguments and three-dimensional simulations, we find that the proliferation gradients result in flows and in gradients of activity both of which can align the orientation axis of cells inside the aggregates. Depending on environmental conditions and the intrinsic tissue properties, we identify three distinct alignment regimes: spheroids in which all the cells align either radially or tangentially to the surface throughout the aggregate and spheroids with angular cell orientation close to the surface and radial alignment in the core. The continuum description of tissue dynamics inside spheroids not only allows us to infer dynamic cell parameters from experimentally measured cell alignment profiles, but more generally motivates novel mechanisms for controlling the alignment of cells within aggregates which has been shown to influence the mechanical properties and invasive capabilities of tumors.

We present a publicly available software for exponential integrators that computes the $\varphi_l(z)$ functions using polynomial interpolation. The interpolation method at Leja points have recently been shown to be competitive with the traditionally-used Krylov subspace method. The developed framework facilitates easy adaptation into any Python software package for time integration.

We consider different Linear Combination of Unitaries (LCU) decompositions for molecular electronic structure Hamiltonians. Using these LCU decompositions for Hamiltonian simulation on a quantum computer, the main figure of merit is the 1-norm of their coefficients, which is associated with the quantum circuit complexity. It is derived that the lowest possible LCU 1-norm for a given Hamiltonian is half of its spectral range. This lowest norm decomposition is practically unattainable for general Hamiltonians; therefore, multiple practical techniques to generate LCU decompositions are proposed and assessed. A technique using symmetries to reduce the 1-norm further is also introduced. In addition to considering LCU in the Schr\"odinger picture, we extend it to the interaction picture, which substantially further reduces the 1-norm.

Salty water is the most abundant electrolyte aqueous mixture on Earth, however, very little is known about the NaCl-saturated solution interfacial free energy. Here, we provide the first direct estimation of this magnitude for several NaCl crystallographic planes by means of the Mold Integration technique, a highly efficient computational method to evaluate interfacial free energies with anisotropic crystal resolution. Making use of the JC-SPC/E model, one of the most benchmarked force fields for NaCl/water solutions, we measure the interfacial free energy of four different planes, (100), (110), (111), and (11-2) with the saturated solution at normal conditions. We find high anisotropy between the different crystal orientations with values oscillating from 100 to 150 mJ/m2, being the average value of the distinct planes 137(20) mJ/m2. This value for the coexistence interfacial free energy is in reasonable agreement with previous extrapolations from nucleation studies. Our work represents a milestone in the computational calculation of interfacial free energies between ionic crystals and aqueous solutions.

Interfaces between heavy metals (HMs) and antiferromagnetic insulators (AFIs) have recently become highly investigated and debated systems in the effort to create spintronic devices able to function at terahertz frequencies. Such heterostructures have great technological potential because AFIs can generate sub-picosecond spin currents which the HMs can convert into charge signals. In this work we demonstrate an optically induced picosecond spin transfer at the interface between AFIs and Pt using time-resolved THz emission spectroscopy. We select two antiferromagnets in the same family of fluoride cubic perovskites, KCoF3 and KNiF3, whose magnon frequencies at the centre of the Brillouin zone differ by an order of magnitude. By studying their behaviour with temperature we correlate changes in the spin transfer efficiency across the interface to the opening of a gap in the magnon density of states below the N\'eel temperature. Our observations are reproduced in a model based on the spin exchange between the localized electrons in the antiferromagnet and the free electrons in Pt. These results constitute an important step in the rigorous investigation and understanding of the physics of AFIs/HMs interfaces on the ultrafast timescale.

We present a hydrodynamic model of ultracold, but not yet quantum condensed, dipolar Bosonic gases. Such systems present both $s$-wave and dipolar scattering, the latter of which results in anisotropic transport tensors of thermal conductivity and viscosity. This work presents an analytic derivation of the viscosity tensor coefficients, utilizing the methods established in [Wang et al., arXiv:2205.10465], where the thermal conductivities were derived. Taken together, these transport tensors then permit a comprehensive description of hydrodynamics that is now embellished with dipolar anisotropy. An analysis of attenuation in linear waves illustrates the effect of this anisotropy in dipolar fluids, where we find a clear dependence on the dipole orientation relative to the direction of wave propagation.