Generic Setup Research Articles

Spin-polarized thermoelectrical currents induced in Aharonov-Bohm rings

We propose an interferometric device that generates spin-polarized electric currents based on an Aharonov-Bohm ring geometry. The device is driven by a temperature gradient and a magnetic flux without any voltage bias. Remarkably, no ferromagnetic contact is necessary once the two-path interference effects are present combined with a spin-orbit interaction. A large amplitude of spin current signal occurs where the charge current is small or even vanishing, thus easily creating pure spin currents by applying a magnetic field. Our proposal provides an ingredient of information processing devices in a generic caloritronic setup. Published by the American Physical Society 2024

Convergence of the numerical approximations and well-posedness: Nonlocal conservation laws with rough flux

We study a class of nonlinear nonlocal conservation laws with discontinuous flux, modeling crowd dynamics and traffic flow. The discontinuous coefficient of the flux function is assumed to be of bounded variation (BV) and bounded away from zero, and hence the spatial discontinuities of the flux function can be infinitely many with possible accumulation points. Strong compactness of the Godunov and Lax-Friedrichs type approximations is proved, providing the existence of entropy solutions. A proof of the uniqueness of the adapted entropy solutions is provided, establishing the convergence of the entire sequence of finite volume approximations to the adapted entropy solution. As per the current literature, this is the first well-posedness result for the aforesaid class and connects the theory of nonlocal conservation laws (with discontinuous flux), with its local counterpart in a generic setup. Some numerical examples are presented to display the performance of the schemes and explore the limiting behavior of these nonlocal conservation laws to their local counterparts.

Numerical simulation of droplet dispersion within meso-porous membranes

Analysis of membrane processes in fluid processing, and their main influencing operating conditions are relevant in a variety of industrial applications. Increasing regulatory scrutiny and environmental considerations are forcing industries across all sectors, from food and pharma to oil and gas, to further understand and optimise the handling and formulation of liquid systems for efficient process design. In a generic setup for emulsification and liquid formulation the flow and dispersion behaviour of a liquid oil droplet on its way through a porous water filled membrane is analysed. A set of high-resolution numerical simulations of a single oil droplet dispersed in water through a porous membrane structure with varying contact angles is performed. In this work cluster analysis of volume-of-fluid simulation results to obtain statistical droplet size distributions is conducted and further analysed to highlight the effect of the contact angle as well as pressure drop on the dynamics of the system. It is observed that based on the membrane surface activity the droplet behaviour changes from filtration with coalescence when the membrane is lipophilic to emulsification with droplet break-up when the membrane is lipophobic. Furthermore, the pressure drop is identified as a key factor for the dynamics of the droplet process and the frame in which it occurs. These results highlight that the membrane wettability is a determining factor for the emulsification or filtration effectiveness of a membrane for various applications.

Existence of bounded solutions to multiplicative poisson equations under mixing property

We study the problem of Multiplicative Poisson Equation (MPE) bounded solution existence in a generic probabilistic discrete-time setup with preimposed mixing. In particular, we consolidate results based on the span-contraction framework and derive an explicit sharp bound that must be imposed on the cost function to guarantee the existence of a bounded MPE solution under mixing. Also, we study properties that the probability kernel must satisfy to ensure the existence of an MPE solution for any generic risk-reward function and characterise process behaviour in the complement of the invariant measure support. Finally, we present numerous examples and stochastic dominance based arguments that help to better understand the problems that arise when the mean is replaced by the entropy in the ergodic setup.

Universality of loop corrected soft theorems in 4d

In [1], logarithmic correction to subleading soft photon and soft graviton theorems have been derived in four spacetime dimensions from the ratio of IR-finite S-matrices. This has been achieved after factoring out IR-divergent components from the traditional electromagnetic and gravitational S-matrices using Grammer-Yennie prescription. Although the loop corrected subleading soft theorems are derived from one-loop scattering amplitudes involving scalar particles in a minimally coupled theory with scalar contact interaction, it has been conjectured that the soft factors are universal (theory independent) and one-loop exact (don’t receive corrections from higher loops).This paper extends the analysis conducted in [1] to encompass general spinning particle scattering with non-minimal couplings permitted by gauge invariance and general coordinate invariance. By re-deriving the ln ω soft factors in this generic setup, we establish their universal nature. Furthermore, we summarize the results of loop corrected soft photon and graviton theorems up to sub-subleading order, which follows from the analysis of one and two loop QED and quantum gravity S-matrices. While the classical versions of these soft factors have already been derived in the literature, we put forth conjectures regarding the quantum soft factors and outline potential strategies for their derivation.

Metric-Affine Cosmologies: kinematics of Perfect (Ideal) Cosmological Hyperfluids and first integrals

We consider a generic Metric-Affine Cosmological setup and classify some particularly interesting specific cases of Perfect Hyperfluids. In particular, we present the form of conservation laws for the cases of pure spin, pure dilation and pure shear fluids. We also develop the concept of an incompressible hyperfluid and pay special attention to the case of a hypermomentum preserving hyperfluid. We also give a specific example on the emergence of the spin, dilation and shear currents through matter-connection couplings. In addition, starting from the generalized acceleration equation for the scale factor including torsion and non-metricity we provide a first integral of motion relating the latter with the rest of the hyperfluid variables. These results then formalize the analysis of the non-Riemannian effects in Cosmology.

Can We Observe Nonperturbative Vacuum Shifts in Cavity QED?

We address the fundamental question of whether or not it is possible to achieve conditions under which the coupling of a single dipole to a strongly confined electromagnetic vacuum can result in nonperturbative corrections to the dipole's ground state. To do so we consider two simplified, but otherwise rather generic cavity QED setups, which allow us to derive analytic expressions for the total ground-state energy and to distinguish explicitly between purely electrostatic and genuine vacuum-induced contributions. Importantly, this derivation takes the full electromagnetic spectrum into account while avoiding any ambiguities arising from an adhoc mode truncation. Our findings show that while the effect of confinement perse is not enough to result in substantial vacuum-induced corrections, the presence of high-impedance modes, such as plasmons or engineered LC resonances, can drastically increase these effects. Therefore, we conclude that with appropriately designed experiments it is at least in principle possible to access a regime where light-matter interactions become nonperturbative.

Application of a hybrid multiphase CFD approach to the simulation of gas–liquid flow at a trapezoid fixed valve for distillation trays

In the present contribution, we demonstrate the application of a hybrid multiphase CFD approach, which allows for simulating dispersed phases as well as resolved interfaces within an Eulerian framework, for the flow on distillation trays for the first time. The morphology adaptive multifield two–fluid model is exemplified for continuous gas–liquid flow on a generic tray setup with a single trapezoid fixed valve. Instead of fully resolving its geometry in the computational grid, the gas inlets are emulated by implementing mass and momentum sources that are applied to local cell zones. Different zone types in terms of volume and curtain area are tested and compared. The simulation results are verified with experimental data from a lab–scale test rig with air–water flow. Local phase fractions were measured using a conductivity sensor array. The comparison of simulated and experimental results reveals that the relevant time–averaged and transient flow characteristics can be predicted satisfactorily if at least an approximate representation of the valve’s geometry in the computational grid is given. However, local differences are observed among the simulated phase distributions due to the varying cell zone volume and hence maximum intensity of the injected momentum.

Information flows in macroscopic Maxwell's demons.

A CMOS-based implementation of an autonomous Maxwell's demon was recently proposed [Phys. Rev. Lett. 129, 120602 (2022)0031-900710.1103/PhysRevLett.129.120602] to demonstrate that a Maxwell demon can still work at macroscopic scales, provided that its power supply is scaled appropriately. Here we first provide a full analytical characterization of the nonautonomous version of that model. We then study system-demon information flows within generic autonomous bipartite setups displaying a macroscopic limit. By doing so, we can study the thermodynamic efficiency of both the measurement and the feedback process performed by the demon. We find that the information flow is an intensive quantity and that, as a consequence, any Maxwell's demon is bound to stop working above a finite scale if all parameters but the scale are fixed. However, this can be prevented by appropriately scaling the thermodynamic forces. These general results are applied to the autonomous CMOS-based demon.

Generation of time-frequency entangled photon pairs propagating in separate waveguides in circuit QED setup

Time-frequency entangled photons constitute an important resource for a plethora of applications across the diverse quantum technology landscape. Thus, efficient and tunable setups for the generation of entangled photons are requisite for modern quantum technologies. In this work, we propose a generic cavity QED setup designed for on-demand generation of time-frequency entangled photon pairs, with each photon propagating in a separate waveguide. We outline a potential incarnation of this setup in the microwave superconducting circuit QED architecture. We derive and numerically solve the set of equations of motion governing the evolution of the quantum state of the system, allowing us to examine the photon emission dynamics. Using the Schmidt decomposition of the joint spectral amplitude of the emitted photon pair, we compute the entanglement entropy analyzing its dependence on the system parameters. We outline the potential extension of the proposed scheme for the generation of multiphoton time-frequency entangled states.

Optical tractor beam for a cluster of plasmonic and dielectric and chiral Mie objects

A light beam pushes any object towards the direction of its propagation as light or quantum of light, photon, carries momentum. However, a light beam can also pull a particle backward towards the source — regarded as an optical tractor beam. Despite a series of phenomenal works being done in the field of optical manipulation using optical tractor beams, optical setup that can enable the optical pulling of all objects (i.e., dielectric, plasmonic and chiral) is still extremely rare. This work stands as the very first proposal of a simple and generic all-optical setup, where attaining optical tractor beam effect over all objects within a cluster is facilitated. Such optical pulling effect is observed only over a dielectric substrate (but not over plasmonic substrate) when two simple plane waves superimpose appropriately maintaining certain conditions. The emergence of such counterintuitive force has been explained based on distinct physical phenomena. For instance, in case of the dielectric and chiral nanoparticles, origin of the pulling force has been explained based on the field induced multipole radiation; whereas, in case of the plasmonic scatterer, the pulling has been explained based on the reversal of induced current density within the object.

Machine learning‐based predictive modeling for failure management of optical spatial mode division multiplexing system

SummaryThe bit error rate (BER) in optical communication systems is often get degraded due to various factors like launch power, dispersion, modal noise, and so on. Finding the most optimal launch power for a signal to provide acceptable BER is usually difficult on an installed link. Therefore, in this paper, an attempt has been made to use machine learning‐based linear regression technique for predicting the optimal signal quality for spatial division multiplexed (SDM)‐based fiber optical transmission system for a fixed distance. This technique helps in predicting the optimal value of continuous launch power. Therefore, to demonstrate the given concept in this research work, the generic setup of an SDM optical long‐haul system of 20 km in length has been designed and simulated in Optisystem‐14.0. The light sources in our experiments are two spatial optical transmitters with an emission wavelength of around 1550 nm. Abiding to the first step for the regression analysis, that is the data preparation, normality and correlation checks were performed. After this, a linear regression model is developed which was validated through a summary report, coefficients and diagnostic plots. Furthermore, the accuracy of the model is improved by employing Cook's distance. These tests help in dealing with the influence points that hinders the prediction ability of the proposed model. The results show that the R‐squared value is 0.9366, and value of adjusted R2 comes out to be around 0.9344; we therefore came to infer that the model explains nearly 94% variations in the dependent variables.

Causal structures and nonlocality in double holography

Double holography plays a crucial role in recent studies of Hawking radiation and information paradox by relating an intermediate picture, in which a dynamical gravity living on an end-of-the-world brane is coupled to a non-gravitational heat bath, to a much better-understood BCFT picture as well as a bulk picture. In this paper, causal structures in generic double holographic setups are studied. We find that the causal structure in the bulk picture is compatible with causality in the BCFT picture, thanks to a generalization of the Gao-Wald theorem. On the other hand, consistency with the bulk causal structure requires the effective theory in the intermediate picture to contain a special type of super-luminal and nonlocal effect which is significant at long range or IR. These are confirmed by both geometrical analysis and commutators of microscopic fields. Subregion correspondences in double holography are discussed with the knowledge of this nonlocality. Possible fundamental origins of this nonlocality and its difference with other types of nonlocality will also be discussed.

Simplified flood evacuation simulation in outdoor built environments. Preliminary comparison between setup-based generic software and custom simulator

• We investigate evacuation simulation in flooded outdoor built environments. • We compare a generic and a custom simulation model based on a microscopic approach. • We set a generic simulator up to reproduce flood-related behaviors. • Simulators are applied to an idealized literature-based case study, including comparisons with real-world data. • Results seem to encourage the proposed generic simulator setup. Floods are among the most destructive sudden-onset disasters affecting worldwide communities and society. Pedestrians can be forced to evacuate affected areas thus being exposed to multiple risks. Outdoor built environment flood risks analyses should be performed through rapid, easy, and sustainable tools to speed up and support risk assessment and mitigations. Custom evacuation simulators have been developed, but are generally used in research, are not user-friendly, and need high-level training. On the contrary, generic (e.g. commercial) software tools seem to be more suitable for low-trained technicians but should be modified to include human behaviors effects, especially considering the evacuation, when people's peculiar choices depend on interactions with floodwaters and built environment layout/composing elements. This work provides preliminary setups of a generic software tool to perform quick and sustainable assessments of pedestrians’ flood safety in outdoor spaces, using an easy-to-apply no-code modification approach to include flood peculiar behaviors. Simulation outputs of the setup-based generic software are compared with a custom simulator relying on the same modelling approach, and with real-world observations, using an idealized literature-based outdoor scenario. Results provide the best setup of the generic software to reliably represent evacuation phenomena, thus encouraging its future application also by local authorities.

‘Grey-Box-Processing’: a novel validation method for use in vehicle safety applications

The ‘Grey-Box-Processing’ method, presented in this article, allows for the integration of simulated and experimental data sets with the overall objective of a comprehensive validation of simulation methods and models. This integration leads to so-called hybrid data sets. They allow for a spatially and temporally resolved identification and quantitative assessment of deviations between experimental observations and results of corresponding finite element simulations in the field of vehicle safety. This is achieved by the iterative generation of a synthetic, dynamic solution corridor in the finite element domain, which is deduced from experimental observations and restricts the freedom of movement of a virtually analyzed structure. The hybrid data sets thus contain physically based information about the interaction (e.g. acting forces) between the solution corridor and the virtually analyzed structure. An additional result of the ‘Grey-Box-Processing’ is the complemented three-dimensional reconstruction of the incomplete experimental observations (e.g. two-dimensional X-ray movies). The extensive data sets can be used not only for the assessment of the similarity between experiment and simulation, but also for the efficient derivation of improvement measures in order to increase the predictive power of the used model or method if necessary. In this study, the approach is presented in detail. Simulation-based investigations are conducted using generic test setups as well as realistic pedestrian safety test cases. These investigations show the general applicability of the method as well as the significant informative value and interpretability of generated hybrid data sets.

Signal voids of active cardiac implants at 3.0\xa0T CMR

Recent technical advancements allow cardiac MRI (CMR) examinations in the presence of so-called MRI conditional active cardiac implants at 3.0 T. However, the artifact burden caused by susceptibility effects remain an obstacle. All measurements were obtained at a clinical 3.0 T scanner using an in-house designed cubic phantom and optimized sequences for artifact evaluation (3D gradient echo sequence, multi-slice 2D turbo spin echo sequence). Reference sequences according to the American Society for Testing and Materials (ASTM) were additionally applied. Four representative active cardiac devices and a generic setup were analyzed regarding volume and shape of the signal void. For analysis, a threshold operation was applied to the grey value profile of each data set. The presented approach allows the evaluation of the signal void and shape even for larger implants such as ICDs. The void shape is influenced by the orientation of the B0-field and by the chosen sequence type. The distribution of ferromagnetic material within the implants also matters. The void volume depends both on the device itself, and on the sequence type. Disturbances in the B0 and B1 fields exceed the visual signal void. This work presents a reproducible and highly defined approach to characterize both signal void artifacts at 3.0 T and their influencing factors.

Nonreciprocal light transmission via optomechanical parametric interactions.

Nonreciprocal transmission of optical or microwave signals is indispensable in various applications involving sensitive measurements. In this paper, we study optomechanically induced directional amplification and isolation in a generic setup including two cavities and two mechanical oscillators by exclusively using blue-sideband drive tones. The input and output ports defined by the two cavity modes are coupled through coherent and dissipative paths mediated by the two mechanical resonators, respectively. By choosing appropriate transfer phases and strengths of the driving fields, either a directional amplifier or an isolator can be implemented at low thermal temperature, and both of them show bi-directional nonreciprocity working at two mirrored frequencies. The nonreciprocal device can potentially be demonstrated by opto- and electromechanical setups in both optical and microwave domains.

Wideband Measurement Techniques for Extracting Accurate RCS of Single and Distributed Targets

This article discusses both test setup and signal processing techniques to achieve highly accurate radar cross section (RCS) measurements across a wide bandwidth. This high accuracy is achieved through both postprocessing algorithms and test setup hardware modifications. The postprocessing techniques include calibration, clutter cancellation, and time-gating, all of which are applicable to a generic anechoic chamber setup. Specialized RCS measurement equipment such as a vector network analyzer (VNA) capable of producing nanosecond-length pulses is not necessary. However, strategic, inexpensive hardware modifications further improve measurement quality. Experiments are conducted at the University of Oklahoma in the far-field anechoic chamber to evaluate the effects of the postprocessing and setup variations on the measurement accuracy. Parameters including object support pedestal geometry, VNA intermediate frequency (IF) bandwidth, and azimuthal angle rotation are studied. Trade-offs between time, cost, and accuracy are considered in the context of these variables. By upgrading the measurement setup hardware and applying optimized processing techniques, the RCS average error is reduced from 3.2 dBsm to only 0.21 dBsm across the 2-18-GHz frequency range. The versatility of these techniques is then demonstrated by measuring a distributed target with an average error of 0.94 dBsm from 2 to 8 GHz when compared with simulation.

Breakthrough Investigation of Advective and Diffusive Transport in a Porous Matrix with a Crack

Fluid flow and transport processes in fractured porous media are of particular interest for geologists and in the material sciences. Here a systematic investigation is presented, dealing with a generic geometric set-up of a porous matrix with a crack. In such a combined porous medium/free fluid system flow patterns have been examined frequently, while the resulting transport patterns have attracted less attention. Using numerical modeling with finite elements the problem is approached using a dimensionless formulation. With a reduced number of dimensionless parameter combinations (Darcy-, Peclet- and Reynolds-numbers) solution dependencies are examined in parametric sweeps. Breakthrough curves are fitted in comparison to those of 1D model approaches, yielding effective diffusivities and velocities. The computations reveal highest sensitivity concerning the angle between crack axis and flow direction, followed by the Peclet number and the crack axes ratio. As a dimensionless representation is used the results are scale independent. Thus, they deliver estimations concerning effective heat and solute transport parameters that can be relevant in all application fields.

Elastic AI: system support for adaptive machine learning in pervasive computing systems

Artificial intelligence (AI) is an important part of today’s pervasive computing systems. Still, there is no end-to-end system platform that allows to deploy, update, manage and execute AI models in pervasive systems. We propose such a system platform in this paper. Most importantly, we reuse concepts and techniques from twenty years of pervasive computing research on how to enable runtime adaptation and apply it to AI. This allows to specify adaptive AI models that are able to react to a multitude of dynamic changes, e.g. with respect to available devices, networking conditions, but also application requirements and sensor data sources. Developers can optimise their applications iteratively, starting with a generic setup and refining it step by step towards their specific pervasive computing scenario. To show the applicability of our platform, we apply it to two pervasive use cases and evaluate them, achieving up to four times faster inference and three times lower energy consumption compared to a classical AI deployment.