Final State Research Articles

Exploring correlated parking–charging behaviours in electric vehicles: a data-driven study

To enhance the management of parking–charging behaviours for electric vehicles (EVs) and promote the development of vehicle–grid interaction technology, the interrelation between parking and charging behaviours among EV users should be investigated further. This study, based in Changshu City, Suzhou, China, established a data linkage mechanism for parking–charging platforms and developed an EV parking–charging behaviour database, considering critical metrics like charging start time, initial and final state of charge, and charging duration. Employing the K–S test and K-means clustering methods, the diversity in parking–charging preferences between pure and plug-in hybrid EV users is explored. Results indicate that pure EVs’ parking–charging behaviours can be categorised into five distinct groups using a classification model, while those of plug-in hybrid EVs can be grouped into four categories. Both user groups include behaviours with low range anxiety, such as complete charging during special journeys, at the destination, or partial charging. Both groups also exhibit high-range-anxiety behaviours, with pure EV users favouring specific journey complete charging and plug-in hybrid EV users preferring complete charging. Notably, pure EV users also show a significant inclination towards nighttime complete charging. These insights are valuable for efficient planning and management of integrated EV facilities.

Vavilov-Cherenkov emission with twisted electrons: A study of the final entangled state

Vavilov-Cherenkov emission with twisted electrons: A study of the final entangled state

Particle Production in pA Collisions at Mid-Rapidity in the Color Glass Condensate

Particle correlations in small collisions systems, like proton–nucleus, lie at the core of the discussion about whether quark–gluon plasma is produced in small systems. Both initial and final state explanations have been essayed to describe such correlations. In this work, we focus on the initial state explanations provided by the quantum effects in the initial wave function of the incoming hadrons, in the framework of the Color Glass Condensate effective theory. We describe the formalism indicating the different inputs required for phenomenological applications. We compare the results from two different models, finding that the results for azimuthal harmonics agree qualitatively, but show quantitative differences, particularly at transverse momenta above the saturation scale.

Probing new physics with charge asymmetries in 2 same-sign leptons plus jets final states at the LHC

We study the impact of new physics models in the charge asymmetry defined for LHC final states consisting of two same-sign leptons (2SSl, with l = e, μ) plus jets (Njets ≥ 2), with a center-of-mass energy of s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s} $$\\end{document} = 13 TeV, where the main SM contribution is tt¯W\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ t\\overline{t}W $$\\end{document} production. Concretely, we consider three different new physics sources for the charge asymmetries: a heavy neutral scalar/pseudoscalar arising from the general two Higgs doublet model, an effective theory with dimension-6 four-quark operators, and a simplified R-parity-violating supersymmetric model with electroweakino production (higgsino-like or wino-like). We propose measuring the charge asymmetries differentially with respect to several kinematic observables, and inclusively/exclusively with the number of b-tagged jets in the final state (Nb ≥ {1, 2, 3}). Results are compared with the SM prediction using the χ2 criteria, expressing sensitivity in terms of the normal Gaussian significance. We show that some of the proposed new physics scenarios can be probed at the LHC even for the already recorded integrated luminosity of 139 fb−1. Finally, we also estimate the prospects for the potential LHC sensitivity to the considered new physics models in its high-luminosity phase.

Atomic-scale manipulation of polar domain boundaries in monolayer ferroelectric In2Se3

Domain boundaries have been intensively investigated in bulk ferroelectric materials and two-dimensional materials. Many methods such as electrical, mechanical and optical approaches have been utilized to probe and manipulate domain boundaries. So far most research focuses on the initial and final states of domain boundaries before and after manipulation, while the microscopic understanding of the evolution of domain boundaries remains elusive. In this paper, we report controllable manipulation of the domain boundaries in two-dimensional ferroelectric In2Se3 with atomic precision using scanning tunneling microscopy. We show that the movements of the domain boundaries can be driven by the electric field from a scanning tunneling microscope tip and proceed by the collective shifting of atoms at the domain boundaries. Our density functional theory calculations reveal the energy path and evolution of the domain boundary movement. The results provide deep insight into domain boundaries in two-dimensional ferroelectric materials and will inspire inventive applications of these materials.

Probing dark sector fermions in Higgs precision studies and direct searches

In this paper, we investigate the discovery prospect of simplified fermionic dark sectors models through Higgs precision measurements at e+e− colliders and direct searches at hadron colliders. These models extend the Standard Model with two Majorana or Dirac fermions that are singlets, doublets or triplets under the weak SU(2) group. For all models, we consider two scenarios where the lightest new fermion is either stable, or where it decays into other visible final states. For the Higgs precision observables we primarily focus on σ(e+e− → ZH), which can deviate from the Standard Model through one-loop corrections involving the new fermions. Deviations of 0.5% or more, which could be observable at future e+e− colliders, are found for TeV-scale dark sector masses. By combining the constraints from the oblique parameters, Br(H → γγ), and direct production of the new fermions at the LHC, a comprehensive understanding of the discovery potential of these models can be achieved. In both scenarios, there exist some parameter regions where the Higgs precision measurements can provide complementary information to direct LHC searches.

AMY Lorentz invariant parton cascade: the thermal equilibrium case

We introduce the parton cascade Alpaca, which evolves parton ensembles corresponding to single events according to the effective kinetic theory of QCD at high temperature formulated by Arnold, Moore and Yaffe by explicitly simulating elastic scattering, splitting and merging. By taking the ensemble average over many events the phase space density (as evolved by the Boltzmann equation) is recovered, but the parton cascade can go beyond the evolution of the mean because it can be turned into a complete event generator that produces fully exclusive final states including fluctuations and correlations. The parton cascade does not require the phase space density as input (except for the initial condition at the starting time). Rather, effective masses and temperature, which are functions of time and are defined as integrals over expressions involving the distribution function, are estimated in each event from just the parton ensemble of that event. We validate the framework by showing that ensembles sampled from a thermal distribution stay in thermal equilibrium even after running the simulation for a long time. This is a non-trivial result, because it requires all parts of the simulation to intertwine correctly.

Sub-GeV dark matter annihilation: limits from Milky Way observations with INTEGRAL

ABSTRACT From 16 years of INTEGRAL/SPI γ-ray observations, we derive bounds on annihilating light dark matter particles in the halo of the Milky Way up to masses of about 300 MeV. We test four different spatial templates for the dark matter halo, including a Navarro–Frenk–White (NFW), Einasto, Burkert, and isothermal sphere profile, as well as three different models for the underlying diffuse inverse compton emission. We find that the bounds on the s-wave velocity-averaged annihilation cross sections for both the electron-positron and the photon–photon final states are the strongest to date from γ-ray observations alone in the mass range ≲6 MeV. We provide fitting formulae for the upper limits and discuss their dependences on the halo profile. The bounds on the two-photon final state are superseding the limits from the cosmic microwave background in the range of 50 keV up to ∼3 MeV, showing the great potential future MeV mission will have in probing light dark matter.

Beneficial and detrimental entanglement for quantum battery charging

We establish a general implementation-independent approach to assess the potential advantage of using highly entangled quantum states between the initial and final states of the charging protocol to enhance the maximum charging power of quantum batteries. It is shown that the impact of entanglement on power can be separated from both the global quantum speed limit associated with an optimal choice of driving Hamiltonian and the energy gap of the batteries. We then demonstrate that the quantum state advantage of battery charging, defined as the power obtainable for given quantum speed limit and battery energy gap, is not an entanglement monotone. A striking example we provide is that, counterintuitively, independent thermalization of the local batteries, completely destroying any entanglement, can lead to larger charging power than that of the initial maximally entangled state. Highly entangled states can thus also be potentially disadvantageous when compared to product states. We also demonstrate that taking the considerable effort of producing highly entangled states, such as W or k-locally entangled states, is not sufficient to obtain quantum-enhanced scaling behavior with the number of battery cells. Finally, we perform an explicit computation for a Sachdev–Ye–Kitaev battery charger to demonstrate that the quantum state advantage allows the instantaneous power to exceed its classical bound.

Emotion generation method in online physical education teaching based on data mining of teacher-student interactions.

Different from conventional educational paradigms, online education lacks the direct interplay between instructors and learners, particularly in the sphere of virtual physical education. Regrettably, extant research seldom directs its focus toward the intricacies of emotional arousal within the teacher-student course dynamic. The formulation of an emotion generation model exhibits constraints necessitating refinement tailored to distinct educational cohorts, disciplines, and instructional contexts. This study proffers an emotion generation model rooted in data mining of teacher-student course interactions to refine emotional discourse and enhance learning outcomes in the realm of online physical education. This model includes techniques for data preprocessing and augmentation, a multimodal dialogue text emotion recognition model, and a topic-expanding emotional dialogue generation model based on joint decoding. The encoder assimilates the input sentence into a fixed-length vector, culminating in the final state, wherein the vector produced by the context recurrent neural network is conjoined with the preceding word's vector and employed as the decoder's input. Leveraging the long-short-term memory neural network facilitates the modeling of emotional fluctuations across multiple rounds of dialogue, thus fulfilling the mandate of emotion prediction. The evaluation of the model against the DailyDialog dataset demonstrates its superiority over the conventional end-to-end model in terms of loss and confusion values. Achieving an accuracy rate of 84.4%, the model substantiates that embedding emotional cues within dialogues augments response generation. The proposed emotion generation model augments emotional discourse and learning efficacy within online physical education, offering fresh avenues for refining and advancing emotion generation models.

Logical states for fault-tolerant quantum computation with propagating light.

To harness the potential of a quantum computer, quantum information must be protected against error by encoding it into a logical state that is suitable for quantum error correction. The Gottesman-Kitaev-Preskill (GKP) qubit is a promising candidate because the required multiqubit operations are readily available at optical frequency. To date, however, GKP qubits have been demonstrated only at mechanical and microwave frequencies. We realized a GKP state in propagating light at telecommunication wavelength and verified it through homodyne measurements without loss corrections. The generation is based on interference of cat states, followed by homodyne measurements. Our final states exhibit nonclassicality and non-Gaussianity, including the trident shape of faint instances of GKP states. Improvements toward brighter, multipeaked GKP qubits will be the basis for quantum computation with light.

Directed propaganda in the majority-rule model

Advertisement and propaganda have changed continuously in the past decades, mainly due to the people’s interactions at online platforms and social networks, and operate nowadays reaching a highly specific online audience instead targeting the masses. The impacts of this new media effect, oriented directly for a specific audience, are investigated on this study, in which we focus on the opinion evolution of agents in the majority-rule model, considering the presence of directed propaganda. We introduce p as the probability of a “positive” external propaganda and q as the probability to the agents follow the external propaganda. Our results show that the usual majority-rule model stationary state is reached, with a full consensus, only for two cases, namely when the external propaganda is absent or when the media favors only one of the two opinions. However, even for a small influence of external propaganda, the final state is reached with a majority opinion dominating the population. For the case in which the propaganda influence is strong enough among the agents, we show that the consensus cannot be reached at all, and we observe the polarization of opinions. In addition, we show through analytical and numerical results that the system undergoes an order–disorder phase transition that occurs at [Formula: see text] for the case [Formula: see text].

Impact of structural distortion on electronic and magnetic properties of La[formula omitted]MnVO[formula omitted] double perovskite: An ab initio approach

We have studied the detailed structural, electronic, and magnetic properties of La2MnVO6 double perovskite considering both ab initio and semiempirical parameters within the density functional formalism. We have also considered the strong electron correlation (density functional theory plus the Hubbard potential U) in our calculations to determine the ground state of the compound. Investigation of detailed structural properties with both ab initio and semiempirical parameters reveals that the structure obtained with the semiempirical parameters is more distorted, having more distorted octahedra than the theoretically optimized structure obtained with the variable-cell relaxation method. The stable magnetic phase of the compound is obtained as ferromagnetic with use of the energy minimization principle with the Hubbard potential. Study of the electronic properties shows that the compound is a half-metal with the ab initio parameters, whereas it behaves as a semimetal with the semiempirical parameters. The final ground state of the compound is concluded to be a ferromagnetic metal.

Probing hyperon CP violation with charmed baryon decays

CP violation (CPV) in the baryon sectors has not yet been established experimentally. In this work, we propose to search for the hyperon CPV through the Cabibbo-favored charm-baryon decaying processes involving a hyperon in the final states, such as Λc+→Λ0π+ with Λ0→pπ−. The CPV of the hyperon decays is accessed exclusively in these chain processes, since the CPV in the Cabibbo-favored charm decays is vanishing in the Standard Model (SM). The hyperons are polarized in the weak charm decays, so that we can measure the Lee-Yang asymmetric parameter α by analyzing the angular distributions, and then measure the α-induced CPV. We expect that it is accessible for Belle II and LHCb to reach the SM prediction of the hyperon CPV in the near future.

Impact of Non‐Stoichiometric Phases and Grain Boundaries on the Nanoscale Forming and Switching of HfOx Thin Films

AbstractHfO2 is one of the most common memristive materials and it is widely accepted that oxygen vacancies are prerequisite to reduce the forming voltage of the respective memristive devices. Here, a series of six oxygen engineered substoichiometric HfO2 − x thin films with varying oxygen deficiency is investigated by conductive atomic force microscopy (c‐AFM) and the switching process of substoichiometric films is observed on the nanoscale. X‐ray diffractometry (XRD) exhibits a phase transition from stoichiometric, monoclinic HfO2 toward oxygen deficient, rhombohedral HfO1.7. The conductance of HfO2 − x is increasing with increasing oxygen deficiency, which is consistent with the increasing prevalence of the highly conductive rhombohedral phase. Simultaneously, c‐AFM reveals significant local conductivity differences between grains and grain boundaries, regardless of the level of oxygen deficiency. Single grains of highly oxygen deficient samples are formed at significant lower voltages. The mean forming voltage is reduced from (7.0 ± 0.6) V for HfO2 to (1.9 ± 0.8) V for HfO1.7. Resistive switching on the nanoscale is established for single grains for the highest deficient thin film samples. The final resistance state is thereby dependent on the initial conductivity of the grains. These studies offer valuable insights into the switching behavior of memristive polycrystalline HfO2.

Microscopic mechanisms of pressure-induced amorphous-amorphous transitions and crystallisation in silicon

Some low-coordination materials, including water, silica, and silicon, exhibit polyamorphism, having multiple amorphous forms. However, the microscopic mechanism and kinetic pathway of amorphous-amorphous transition (AAT) remain largely unknown. Here, we use a state-of-the-art machine-learning potential and local structural analysis to investigate the microscopic kinetics of AAT in silicon after a rapid pressure change. We find that the transition from low-density-amorphous (LDA) to high-density-amorphous (HDA) occurs through nucleation and growth, resulting in non-spherical interfaces that underscore the mechanical nature of AAT. In contrast, the reverse transition occurs through spinodal decomposition. Further pressurisation transforms LDA into very-high-density amorphous (VHDA), with HDA serving as an intermediate state. Notably, the final amorphous states are inherently unstable, transitioning into crystals. Our findings demonstrate that AAT and crystallisation are driven by joint thermodynamic and mechanical instabilities, assisted by preordering, occurring without diffusion. This unique mechanical and diffusion-less nature distinguishes AAT from liquid-liquid transitions.

Joint condition monitoring framework of wind turbines based on multi-task learning with poor-quality data

Effective condition monitoring can improve the reliability of the turbine and reduce its downtime. However, due to the complexity of the operating conditions, the monitoring data is always mixed with poor-quality data. Poor-quality data mixed in monitoring tasks disrupts long-term dependency on data, which challenges traditional condition monitoring methods to work. To solve it, a joint reparameterization feature pyramid network (JRFPN) is proposed. Firstly, three different reparameterization tricks are designed to reform temporal information and exchange cross-temporal information, to alleviate the damage of long-term dependency. Secondly, a joint condition monitoring framework is designed, aiming to suppress feature confounding between poor-quality data and faulty data. The auxiliary task is trained to extract the degradation trend. The main task fights against feature confounding and dynamically delineates the failure threshold. The degradation trend and failure threshold decisions are corrected for each other to make the final joint state inference. Besides, considering the different quality of the monitoring variables, a channel weighting mechanism is designed to strengthen the ability of JRFPN. The measured data proved that JRFPN is more effective than other methods.

Commitment vs. noncommitment behaviors in natural resource conflicts: A case study of groundwater resources

We examine the problem of natural resource exploitation when an exceptional extraction of a resource (groundwater) is needed and devoted to a different use than its regular use. The study applies a two-stage Stackelberg game to examine the strategic behavior of players who compete for water. The leader, with varying weights assigned to the different uses and environmental concern, is the manager of the new (nonregular) resource use, who only intervenes in the second stage of the game. The follower is a regular (agricultural) resource user. We examine the crucial resource of groundwater, introducing two types of Stackelberg equilibria (open-loop and feedback) that can arise depending on agents’ commitment behavior. We compare the extraction behaviors of the leader and the follower for the two equilibria and the effects on the final state of the resource and agents’ profits. Unexpectedly, we demonstrate that situations can occur in which noncommitment strategies could be more favorable than commitment strategies in terms of the final aquifer stock and the regular user’s profits. To avoid that noncommitment strategies are implemented in these circumstances, the weights assigned by the leader to the different uses will play an important role.

Study on Inverse Analysis Technique Considering Influence of Construction Procedure on Performance of Large-Span Steel Latticed Arch

In this paper, the influence of the construction process of large-span steel latticed arch on the geometric configuration and bearing capacity performance of the large-span steel latticed arch is calculated and analyzed by using the inverse analysis technique. By comparing the calculation results of single pre-deformation adjustment of the node co-ordinates in zero state of the whole structure and the dynamic adjustment of the node co-ordinates of the unconstructed part of the structure, it is found that the inverse analysis method of dynamic node co-ordinate adjustment is used to achieve the unification of the geometric configuration of the final structure and the bearing capacity performance of the structure. The results show that the inverse analysis method of dynamic node co-ordinate adjustment proposed in this paper can simulate and track the dynamic changes of structural geometry and stable bearing capacity performance in the actual construction process, which can not only consider the influence of the installed part of the structure on the co-ordinate adjustment value of the uninstalled part of the structure but also consider the deformation influence of the subsequent uninstalled structure on the installed structure and can realize the optimal approximation of the final state structure to the geometric configuration of the zero state structure and the accurate calculation of the bearing capacity performance with the progress of the construction process.

Towards Autonomous Firefighting UAVs: Online Planners for Obstacle Avoidance and Payload Delivery

Drone technology is advancing rapidly and represents significant benefits during firefighting operations. This paper presents a novel approach for autonomous firefighting missions for Unmanned Aerial Vehicles (UAVs). The proposed UAV framework consists of a local planner module that finds an obstacle-free path to guide the vehicle toward a target zone. After detecting the target point, the UAV plans an optimal trajectory to perform a precision ballistic launch of an extinguishing ball, exploiting its kinematics. The generated trajectory minimises the overall traversal time and the final state error while respecting UAV dynamic limits. The performance of the proposed system is evaluated both in simulations and real tests with randomly positioned obstacles and target locations. The proposed framework has been employed in the 2022 UAV Competition of the International Conference on Unmanned Aircraft Systems (ICUAS), where it successfully completed the mission in several runs of increasing difficulty, both in simulation and in real scenarios, achieving third place overall. A video attachment to this paper is available on the website https://www.youtube.com/watch?v=_hdxX2xXkVQ.