Transport Approach Research Articles

Prospects for the (Hyper)Nuclei Study in the Nica Energy Range

The production of nuclei and hypernuclei is of interest for experimental and theoretical studies: it is a big question how such weakly bound objects survive in a hot, dense environment and which new insights on the heavy-ion collisions dynamics they can bring us. We present the results on the hypernuclei feasibility study for the flagship Nuclotron-based Ion Collider fAcility (NICA)/Multi-Purpose Detector (MPD) experiment at the Joint Institute for Nuclear Research (JINR) in Dubna using the Parton-Hadron-Quantum-Molecular Dynamics (PHQMD) transport approach and a realistic reconstruction chain.

Wigner distribution function approach to analyze MIMO communication within a waveguide

Multiple-input-multiple-output (MIMO) communication is a technology to create high capacity wireless links. The main aim of this paper is to provide a foundation to mathematically model wireless chip to chip communication within complex enclosures. This paper mainly concentrates on modelling wave propagation between transmit and receive antennas through a phase space approach which exploits the relationship between the field-field correlation function (CF) and the Wigner distribution function (WDF). A reliable model of wireless chip-to-chip (C2C) communication helps mitigate the information bottleneck caused due to the wired connections between chips, thus, help improve the efficiency of electronic devices of the future. Placing complex sources such as printed circuit board (PCB) inside a cavity or enclosure results in multi-path interference and hence makes the prediction of signal propagation more difficult. Thus, the CFs can be propagated based on a ray transport approach that predicts the average radiated density, but not the significant fluctuations that occur about it. Hence, the WDF approach can be extended to problems in finite cavities that incorporates reflections as well. Phase space propagators based on classical multi-reflection ray dynamics can be obtained by considering the high-frequency asymptotics.

Modeling Excited States of Molecular Organic Aggregates for Optoelectronics.

Light-driven phenomena in organic molecular aggregates underpin several mechanisms relevant to optoelectronic applications. Modeling these processes is essential for aiding the design of new materials and optimizing optoelectronic devices. In this review, we cover the use of different atomistic models, excited-state dynamics, and transport approaches for understanding light-activated phenomena in molecular aggregates, including radiative and nonradiative decay pathways. We consider both intra- and intermolecular mechanisms and focus on the role of conical intersections as facilitators of internal conversion. We explore the use of the exciton models for Frenkel and charge transfer states and the electronic structure methods and algorithms commonly applied for excited-state dynamics. Throughout the review, we analyze the approximations employed for the simulation of internal conversion, intersystem crossing, and reverse intersystem crossing rates and analyze the molecular processes behind single fission, triplet-triplet annihilation, Dexter energy transfer, and Förster energy transfer.

Rank-based testing for semiparametric VAR models: A measure transportation approach

We develop a class of tests for semiparametric vector autoregressive (VAR) models with unspecified innovation densities, based on the recent measure-transportation-based concepts of multivariate {\it center-outward ranks} and {\it signs}. We show that these concepts, combined with Le Cam's asymptotic theory of statistical experiments, yield novel testing procedures, which (a)~are valid under a broad class of innovation densities (possibly non-elliptical, skewed, and/or with infinite moments), (b)~are optimal (locally asymptotically maximin or most stringent) at selected ones, and (c) are robust against additive outliers. In order to do so, we establish a H\' ajek asymptotic representation result, of independent interest, for a general class of center-outward rank-based serial statistics. As an illustration, we consider the problems of testing the absence of serial correlation in multiple-output and possibly non-linear regression (an extension of the classical Durbin-Watson problem) and the sequential identification of the order $p$ of a vector autoregressive (VAR($p$)) model. A Monte Carlo comparative study of our tests and their routinely-applied Gaussian competitors demonstrates the benefits (in terms of size, power, and robustness) of our methodology; these benefits are particularly significant in the presence of asymmetric and leptokurtic innovation densities. A real data application concludes the paper.

Climate change impact of food distribution: The case of reverse logistics for bread in Sweden

Efficient and purposeful transport of food, from primary production to waste management, is essential to drive the necessary transition towards sustainable production and consumption of food within planetary boundaries. This is particularly the case for bread, one of the most frequently wasted food items in Europe. In Sweden, bread is often sold under a take-back agreement where bakeries are responsible for transportation up to the supermarket shelf and for the collection of unsold products. This provides an opportunity for reverse logistics, but creates a risk of inefficient transport that could reduce the environmental benefits of prevention and valorization of surplus bread. This study assessed the climate change impact of bread transport in Sweden and evaluated the impact of alternative food transport pathways. Life cycle assessment revealed the climate change impact of conventional bread transport, from bakery gate to waste management, to be on average 49.0 g CO2e per kg bread with 68 % deriving from long-distance transport, 26 % from short-distance delivery, and 6 % from waste transport. Evaluation of alternative bread transport pathways showed the highest climate savings with a collaborative transport approach that also reduced the need for small vehicles and decreased transport distances. The overall contribution of waste transport to the total climate impact of food transport was low for all scenario routes analyzed, suggesting that food waste management facilitating high-value recovery and valorization could be prioritized without increasing the climate impact due to longer transport. It has been claimed that conventional take-back agreements are responsible for most of the climate change impact related to bread transport, but we identified long distances between bakeries and retailers as the main contributor to transport climate impacts.

Drag reduction performance and mechanism of flexible conical microstructure film inspired by pufferfish epidermis

Flexible bionic drag reduction surfaces have attracted increasing attention in recent years owing to its potential to address the daunting energy crisis. Inspired by the skin of pufferfish, a flexible conical microstructure film with effective drag reduction is designed. The film has the advantages of cost-effective and tensile-bending resistance to meet commercial applications. The low price of raw materials and rapid solidification at room temperature are the core of cost reduction, and the manufactured film can withstand a maximum tensile force of 70 N and a strain of 484%. The practical application effect of the film has been confirmed by model ship tests, and it still has stable drag reduction ability after multiple stretching and bending. The water tunnel experiment results show that the drag-reducing efficiency of the flexible conical microstructure film is 10.65%–12.04% compared to the rigid plane, in which the conical topography suppresses turbulence burst, whereas the flexible surface has the effect of absorbing turbulent energy to buffer the near-wall fluid. The coupling effect enhances drag-reducing efficiency. Therefore, the flexible conical microstructure film in this work provides a practical and commercialized fluid drag reduction approach for ships, underwater vehicles, and pipeline transportation.

Limitations of Variational Quantum Algorithms: A Quantum Optimal Transport Approach

The impressive progress in quantum hardware in the last years has raised the interest of the quantum computing community in harvesting the computational power of such devices. However, in the absence of error correction, these devices can only reliably implement very shallow circuits or comparatively deeper circuits at the expense of a nontrivial density of errors. In this work, we obtain extremely tight limitation bounds for standard NISQ proposals in both the noisy and noiseless regimes, with or without error-mitigation tools. The bounds limit the performance of both circuit model algorithms, such as QAOA, and also continuous-time algorithms, such as quantum annealing. In the noisy regime with local depolarizing noise $p$, we prove that at depths $L=\mathcal{O}(p^{-1})$ it is exponentially unlikely that the outcome of a noisy quantum circuit outperforms efficient classical algorithms for combinatorial optimization problems like Max-Cut. Although previous results already showed that classical algorithms outperform noisy quantum circuits at constant depth, these results only held for the expectation value of the output. Our results are based on newly developed quantum entropic and concentration inequalities, which constitute a homogeneous toolkit of theoretical methods from the quantum theory of optimal mass transport whose potential usefulness goes beyond the study of variational quantum algorithms.

Experts on Resistance to Reorganization of Structure and Technologies of Urban Mobility Provision in Russia: Challenges, Reasons, Solutions and Prospects

In 2022 a lot has changed in the Russian transport system. Today the urban transport systems of Russian cities are staying at the bifurcation point – they are awaiting serious changes. Therefore, it was interesting to investigate expert opinions of specialists on the prospects of the development of urban mobility provision technologies in Russia and possible changes in the current structure of citizens’ transportation approaches. The paper gives results of the research of opinions of transport market specialists on the issues of the probability of the shift of the current paradigm of transport services in Tyumen (a large Russian city with a population of 828.5 thousand people) and the necessity of reorganization of the structure and technologies of urban mobility provision due to the withdrawal of foreign automakers from the Russian market. The article presents the comparison of opinions between Tyumen professionals in the transport market and ordinary Russian citizens. The main conclusion of the research considers the serious resistance of the public environment to the expected reorganization of the structure and technologies of urban mobility provision in Russia.

On the Origin of Interfacial Resistance in Ideal Nanomaterials

Interfacial resistance significantly hinders transport in nanomaterials and membranes, limiting efficiency improvement as system size is reduced. While slow transport of fluids in finite-sized materials, found in experiment and simulation, has been imputed to interfacial resistance, the underlying mechanism is unclear, and no theory exists for its prediction. A kinetic theory-based approach for low-density transport in finite nanopores is developed here, which demonstrates interfacial resistance to arise from an entry region of developing flow, in which the transport coefficient is nonuniform. The origin of interfacial resistance is shown to lie in the enhanced influence of short molecular trajectories in the entry region, with increased frequency of wall collision, which reduces the local transport coefficient. It is shown that the relative interfacial resistance is a universal function of a parameter related to length and surface momentum accommodation factor for a given fluid–solid interaction potential. While interfacial resistance is system size-dependent, it approaches a limiting value in long nanopores that is readily determined. Application of the approach to H2 transport in carbon nanotubes using molecular dynamics simulation results shows the apparent interfacial resistance to increase with decrease in nanotube diameter and with increase in fluid–solid interaction strength.

A combined multi-objective multi criteria approach for blockchain-based synchromodal transportation

Despite our planet’s serious environmental challenges, road transportation remains the most important mode of freight shipment, with the broadest coverage and the greatest influence on global economic development. Intermodal transportation may be a more environmentally friendly alternative to heavy road use. However, such a solution is still limited in terms of scalability, service quality, and interoperability. In this context, synchromodal transportation combined with block chain technology may play a critical role in achieving transportation system efficiency and sustainability. In this paper, we study the use of blockchain technology for synchromodal transportation. We build a multi-objective mathematical model for the optimization of transportation cost, transportation time, CO2 emissions and the blockchain cost. Then, we use several variants of the well-known weighting method and epsilon constraints method to get compromise solutions. We rank the obtained compromise solutions using a variety of multi-criteria decision methods. Then a metaranking method is used to obtain an aggregated ranking. Results show that the proposed methodology may help to ensure the security, the efficiency and the sustainability of synchromodal transportation.

Topological Speed Limit.

Any physical system evolves at a finite speed that is constrained not only by the energetic cost but also by the topological structure of the underlying dynamics. In this Letter, by considering such structural information, we derive a unified topological speed limit for the evolution of physical states using an optimal transport approach. We prove that the minimum time required for changing states is lower bounded by the discrete Wasserstein distance, which encodes the topological information of the system, and the time-averaged velocity. The bound obtained is tight and applicable to a wide range of dynamics, from deterministic to stochastic, and classical to quantum systems. In addition, the bound provides insight into the design principles of the optimal process that attains the maximum speed. We demonstrate the application of our results to chemical reaction networks and interacting many-body quantum systems.

Exploration of the phase diagram within a transport approach

We study equilibrium as well as out-of-equilibrium properties of the strongly interacting QGP medium under extreme conditions of high temperature T and high baryon densities or baryon chemical potentials μB within a kinetic approach. We present the thermodynamic and transport properties of the QGP close to equilibrium in the framework of effective models with Nf=3 active quark flavours such as the Polyakov extended Nambu-Jona Lasinio (PNJL) and dynamical quasiparticle model with the CEP (DQPM-CP). Considering the transport coefficients and the EoS of the QGP phase, we compare our results with various results from the literature. Furthermore, out-of equilibrium properties of the QGP medium and in particular, the effect of a μB- dependence of thermodynamic and transport properties of the QGP are studied within the Parton-Hadron-String-Dynamics (PHSD) transport approach, which covers the full evolution of the system during HICs. We find that bulk observables and flow coefficients for strange hadrons as well as for antiprotons are more sensitive to the properties of the QGP, in particular to the μB - dependence of the QGP interactions.

Far-from-equilibrium Attractors in a 3+1D Transport Approach at Fixed \(\eta /s\)

Far-from-equilibrium Attractors in a 3+1D Transport Approach at Fixed \(\eta /s\)

Heavy-flavor anisotropic flow at RHIC and LHC energies within a full transport approach

The propagation of heavy quarks (HQs) in the quark-gluon plasma (QGP) is described by means of a full Boltzmann transport approach. The nonperturbative dynamics and the interaction between HQs and the bulk is taken into account by means of a Quasi-Particle Model. Including the intense electromagnetic and vortical fields, we discuss their impact on the directed flow of neutral D mesons at RHIC energy, clarifying the role of this observable in giving information on QGP transport properties. We also show a novel study of the correlations between different flow coefficients of D mesons and soft hadrons at LHC energy within a coalescence plus fragmentation hadronization scheme and including event-by-event initial state fluctuations. This investigations can put further constraints on HQ transport coefficients towards a solid determination in comparison to the lattice QCD calculations.

In-medium effects on hidden strangeness production in heavy-ion collisions

We study ϕ meson production in heavy-ion collisions from subthreshold energies of 1.23 A GeV up to RHIC energies within the microscopic Parton-Hadron-String Dynamics (PHSD) transport approach where novel production channels for ϕ mesons based on a coupled channel T-matrix approach are implemented along with the collisional broadening of the ϕ meson spectral width in medium. Since ϕ meson production is closely related to the production of kaons and antikaons, antikaon properties are described via the self-consistent coupled-channel unitarized scheme within a SU(3) chiral Lagrangian (G-matrix) which incorporates explicitly the s− and p− waves of the kaon-nucleon interaction, while the in-medium modifications of kaons are accounted for via a kaon-nuclear potential, which is assumed to be proportional to the local baryon density.

Midrapidity cluster formation in heavy-ion collisions

We study the production of clusters and hypernuclei at midrapidity employing the Parton-Hadron- Quantum-Molecular-Dynamics (PHQMD) approach, a microscopic n-body transport model based on the QMD propagation of the baryonic degrees of freedom with density dependent 2-body potential interactions. In PHQMD the cluster formation occurs dynamically, caused by the interactions. The clusters are recognized by the Minimum Spanning Tree (MST) algorithm. We present the PHQMD results for cluster and hypernuclei formation in comparison with the available experimental data at relativistic energies. PHQMD allows to study the time evolution of formed clusters and the origin of their production, which helps to understand how such weakly bound objects are formed and survive in the rather dense and hot environment created in heavy-ion collisions. It offers therefore an explanation of the ’ice in the fire’ puzzle. To investigate whether this explanation of the ’ice in the fire’ puzzle applies only to the MST results we study also the deuterons production by coalescence. We embed MST and coalescence in the PHQMD and UrQMD transport approaches in order to obtain model independent results. We find that both clustering procedures give very similar results for the deuteron observables in the UrQMD as well as in the PHQMD environment. This confirms that our solution for the ’ice in the fire’ puzzle is common to MST and coalescence and independent of the transport approach.

Electromagnetic simulation and microwave circuit approach of heat transport in superconducting qubits

The study of quantum heat transport in superconducting circuits is significant for further understanding the connection between quantum mechanics and thermodynamics, and for possible applications for quantum information. The first experimental realisations of devices demonstrating photonic heat transport mediated by a qubit have already been designed and measured. Motivated by the analysis of such experimental results, and for future experimental designs, we numerically evaluate the photonic heat transport of qubit-resonator devices in the linear circuit regime through electromagnetic simulations using Sonnet software, and compare with microwave circuit theory. We show that the method is a powerful tool to calculate heat transport and predict unwanted parasitic resonances and background.

Versatile lipoprotein-inspired nanocomposites rescue Alzheimer's cognitive dysfunction by promoting Aβ degradation and lessening oxidative stress.

The accumulation of amyloid-β (Aβ) into senile plaques and the resulting continuous oxidative stress are major pathogenic mechanisms in Alzheimer's disease (AD). In this study, we designed a lipoprotein-inspired nanoparticle to facilitate Aβ clearance and alleviate oxidative stress for the treatment of AD. Lipoprotein-like nanocomposites (RLA-rHDL@ANG) were fabricated by assembling reconstituted high density lipoprotein (rHDL) with an apoE-derived peptide (RLA) with Aβ binding and clearance capabilities, and were subsequently camouflaged using reactive oxygen species (ROS)-sensitive DSPE-TK-mPEG2000 and DSPE-TK-PEG3400-ANG with brain penetration as well as ROS scavenging ability. Immunoelectron microscopy, fluorescence colocalization, and enzyme linked immunosorbent assay, together with a thioflavin-T (ThT) fluorescence quantitative test, showed that RLA-rHDL@ANG possessed the ability of high binding affinity to both Aβ monomers and oligomers, and disintegration of pre-formed Aβ aggregates. ROS level monitoring and transmission electron microscopy (TEM) showed that RLA-rHDL@ANG possessed ROS sensitivity and consumption properties. Transcellular assay and in vivo imaging showed that RLA-rHDL@ANG effectively facilitated blood-brain barrier (BBB) penetration and intracerebral accumulation. It promoted the efficient degradation of Aβ by microglia and neurons through lysosomal transport and elimination approaches. Four-week administration of RLA-rHDL@ANG effectively reduced Aβ deposition, decreased the ROS level and improved cognitive functions in AD mice. These findings indicate that multifunctional RLA-rHDL@ANG may serve as a promising and feasible candidate for managing the progression of AD.

Topics in robust statistical learning

Some recent contributions to robust inference are presented. Firstly, the classical problem of robust M-estimation of a location parameter is revisited using an optimal transport approach - with specifically designed Wasserstein-type distances - that reduces robustness to a continuity property. Secondly, a procedure of estimation of the distance function to a compact set is described, using union of balls. This methodology originates in the field of topological inference and offers as a byproduct a robust clustering method. Thirdly, a robust Lloyd-type algorithm for clustering is constructed, using a bootstrap variant of the median-of-means strategy. This algorithm comes with a robust initialization.

The device performance limit of in-plane monolayer VTe2/WTe2 heterojunction-based field-effect transistors.

To overcome the scaling restriction on silicon-based field-effect transistors (FETs), two-dimensional (2D) transition metal dichalcogenides (TMDs) have been strongly proposed as alternative materials. To explore the device performance limit of TMD-based FETs, in this work, the ab initio quantum transport approach is utilized to study the transport properties of monolayer VTe2/WTe2 heterojunction-based FETs possessing double gates (DGs) with a 5 nm gate length (Lg). Our theoretical simulations demonstrate that the DG-cold-source VTe2/WTe2 FETs with a 5 nm Lg and 2 or 3 nm proper underlap (UL) meet the basic requirements of the on-state current (Ion), power dissipation (PDP), and delay time (τ) for the 2028 needs of the International Technology Roadmap for Semiconductor (ITRS) 2013, which ensures their high-performance and low-power-dissipation device applications. Moreover, the DG-cold-source VTe2/WTe2-based FETs with a 3 nm Lg and 2 or 3 nm UL meet the high-performance requirements of Ion, τ, and PDP for the 2028 needs of ITRS 2013. Additionally, by further considering the negative capacitance technology in devices, the parameters τ, Ion, and PDP of the VTe2/WTe2-based FETs with a 1 nm Lg and 3 nm UL meet well with the 2028 needs for ITRS 2013 towards high-performance device applications. Our theoretical results uncover that the 2D DG-cold-source VTe2/WTe2 FETs can be used as a new kind of promising material candidate to drive the scaling of Moore's law down to 1 nm.