The European Physical Journal Plus最新文献

We show that the five (alpha ) cluster states recently observed in (^{20})Ne, slightly above the five (alpha ) threshold energy, are Bose–Einstein condensates of five (alpha ) clusters. The states are described well using a superfluid cluster model, where the order parameter is defined. We suggest that the five (alpha ) states are fragmented. Theory predicts the emergence of a five (alpha ) rotational roton band characterized by a large moment of inertia. This band is formed through roton excitations of the five (alpha ) BEC vacuum and possesses dual properties of superfluidity and crystallinity, a property of supersolidity. The persistent existence of such a roton band is discussed and confirmed for the four (alpha ) condensate above the four (alpha ) threshold in (^{16})O and the three (alpha ) condensate above the three (alpha ) threshold in (^{12})C.

We investigate quantum metrology in a degenerate down-conversion system composed of a pump mode and two degenerate signal modes. In the conventional parametric approximation, the pump mode is assumed to be constant, not a quantum operator. We obtain the measurement precision of the coupling strength beyond the parametric approximation. Without a dissipation, the super-Heisenberg limit can be obtained when the initial state is the direct product of classical state and quantum state. When the pump mode suffers from a single-photon dissipation, the measurement uncertainty of the coupling strength is close to 0 as the coupling strength approaches 0 with a coherent driving. The direct photon detection is proved to be the optimal measurement. This result has not been changed when the signal modes suffer from the two-photon dissipation. When the signal modes also suffer from the single-mode dissipation, the information of the coupling strength can still be obtained in the steady state. In addition, the measurement uncertainty of the coupling strength can also be close to 0 and become independent of noise temperature as a critical point approaches. Finally, we show that a driven-dissipation down-conversion system can be used as a precise quantum sensor to measure the driving strength.

The van der Pol-Duffing oscillator is widely used in various linear motion mechanisms due to the nonlinear effects of spring force and friction, and is accompanied by self-excited oscillation. Continuous self-excited oscillation can cause serious damage to equipment and production life, so it is extremely necessary to suppress its self-excited oscillation. This article focuses on the vibration control problem of van der Pol-Duffing oscillators at different scales, and innovatively uses a coupled nonlinear energy sink (NES) to suppress unexpected oscillations of external excitation and self-excited systems to reduce oscillation amplitude. Apply the complex variable averaging method to approximate the analytical solution of the coupled system and compare it with the numerical solution of the fourth-order Runge Kutta method. In the primary resonance region, different scale coupling characteristics are exhibited based on the difference in structural mass scale. Using the fast-slow analysis method, the slow invariant manifold is explored to determine the excitation amplitude range that causes the strongly modulated response, and it is found that the vibration reduction effect is optimal at this time. In the non-primary resonance region, there are also coupling phenomena of different scales based on frequency level differences. The fast-slow analysis method is used to evaluate the vibration reduction effect of the coupled NES system and explain the vibration reduction mechanism, clarifying that the change in the balance point type of the autonomous system is the key factor in the vibration reduction of the non-autonomous system.

To resolve the tough issue of strong vibration of the secondary suspension system of the heavy construction machinery cab, a novel liquid-filled isolator is designed. Considering the flow-solid coupling effect between liquid and rubber element, a new parallel combination model with nonlinear coupling relationship is proposed, and the influences of different structural parameters on the amplitude-frequency characteristics and the absolute displacement transmissibility of the suspension system are studied respectively. The low frequency dynamic characteristics of the liquid-filled isolator are investigated and analyzed experimentally. The results show that the transmissibility curves for the measured system keep good agreement with the analytical solutions of the nonlinear dynamics equation, which verifies the validity of the mathematical model. Moreover, the results in the random test show that the novel liquid-filled isolator has obvious vibration isolation effect in both low and high frequency bands, especially the amplitude’s decay rate at high frequency also reaches nearly 90%. This study provides meaningful reference value for the optimized design of the future novel liquid-filled isolator.

This work compares simulated and measured neutron time-of-flight spectra for a cold neutron moderator with varying para-hydrogen concentrations (25%, 50%, 90% and 99.9%) embedded in a polyethylene thermal moderator. The primary neutrons are generated from the interaction of 45MeV protons with a tantalum target. The simulations were performed using several Monte Carlo codes (MCNP, PHITS, McStas, VITESS, and KDSource) together with nuclear data from the ENDF/B-VII.1 and JENDL(-)5.0 libraries. The simulated primary neutron yields had deviations from experimental measurements ranging from 0.3 to 16% depending on the code and the nuclear data used. The neutron moderation in the para-hydrogen moderator coupled with a neutron guide was then modeled. The neutron time distribution was measured by a (^3)He detector at the end of the guide. Comparison with experimental data showed good agreement, with relative differences of less than 15%. For the 99.9% para-hydrogen concentration, simulations with JENDL(-)5.0 were in better agreement with the experimental data, while ENDF-B/VII.1 showed better agreement for the 25% para-hydrogen case. The analysis of the results obtained provides insights into the strengths and limitations of each Monte Carlo code and nuclear data library combination. The observed discrepancies were analyzed, and possible sources of error were also identified. The analytical procedure followed in this work will help to improve the accuracy and reliability of neutron cold moderator design.

Reducing the stability pressure and enhancing superconductivity are the current missions in the research on superconducting hydrides. Rare-earth borohydrides have attracted extensive attention in very recent years. Using CALYPSO methodology and first-principles calculations, we investigated pressure-dependent behaviors of YBH₈ borohydride compounds. P2₁/m-YBH₈ is stable at 100–160 GPa, transitioning to C2/c-YBH₈ stable at 160–300 GPa. Dual bonding in BH_n units and metallic nature of both structures were confirmed. C2/c-YBH₈ʼs superconducting transition temperature exceeds 70 K at 200 GPa and 72 K at 300 GPa, mainly due to BH₆ units. This research contributes to understanding ytterbium-based borohydrides and provides a reference for future experiments and superconductivity investigations.

Thallium-activated sodium iodide scintillation (NaI(Tl)) and high-purity germanium semiconductor (HPGe) detectors are two commonly employed gamma spectroscopy devices. NaI(Tl) detectors are preferred for their cost-effectiveness, efficiency, and ease of construction, while HPGe detectors have superior resolution but face challenges in temperature operation and they are expensive. This article investigates the application of machine learning algorithms, specifically K-Nearest Neighbors (KNN) and a Multi-Channel Output Regression based on Support Vector Regression (MCO-SVR), to enhance the performance of NaI(Tl) detectors by transforming its gamma spectrum into HPGe spectrum. The model was trained using datasets generated from a limited radioisotope library and demonstrated excellent performance across a diverse range of measured experimental test data. The evaluation included various scenarios, such as low-count spectra and background effects. The KNN model exhibited optimal performance, achieving an accuracy of 98.69% with a Manhattan distance metric. In contrast, the MCO-SVR model, employing both direct and chained approaches, exhibited varied results with different kernel types, with the polynomial kernel in the direct approach yielding the value 97.45% accuracy. Overall, the results indicate that machine learning algorithms have the potential to improve the performance of NaI(Tl) detectors and expand their applications in various fields of nuclear security.

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Recent observations of quark-gluon plasma (QGP) like signatures in high-multiplicity proton-proton (pp) collisions, have compelled the heavy-ion physics community to re-examine small collision systems for proper baseline studies. Event shape-based studies in pp collisions have succeeded to a certain extent in identifying the rare events mimicking such heavy-ion-like behavior. In this study, we incorporate PYTHIA8 and AMPT to study radial flow-like signatures in pp collisions at (sqrt{s} = 13) TeV as a function of transverse spherocity and pseudorapidity. The selection of softer events possibly carrying heavy-ion-like features is performed using the transverse spherocity event shape observable. As the particle production mechanism in midrapidity differs greatly from the forward rapidity, a pseudorapidity dependent study is meaningful. Keeping ALICE 3 upgrades at the LHC in mind, this study aims to demonstrate the transverse spherocity and pseudorapidity dependence of the mean transverse momentum, particle ratios, and kinetic freeze out parameters in pp collisions at (sqrt{s}) = 13 TeV using PYTHIA8. We observe that the isotropic events show enhanced radial flow effects in all multiplicity classes, however, the jetty events show signatures of the radial flow-like effects only in high-multiplicity events. For the first time, we show the transverse spherocity and pseudorapidity dependence of partonic modification factor in pp collisions, which clearly shows that by choosing transverse spherocity, one can directly probe the radial flow-like effects in pp collisions at the LHC.

Dynamics reconstruction of complex networks usually requires a large amount of resources; therefore, it is of great significance to find a fast and effective way to achieve this goal. In the study of synchronization dynamics in coupled oscillator networks, complex network structures may be simplified into a smaller-scale network called quotient networks through the external equitable partition. Reservoir computing has demonstrated the capability of rapidly reconstructing system dynamics. In this paper, we attempt to utilize the quotient system in parameter-aware reservoir computing to replace the original network system for training the computer’s neurons, in order to reconstruct the synchronization dynamics of the original network. The system reconstructed by the reservoir computing trained with the quotient network exhibits the same synchronization dynamics, bifurcation diagrams, and spatiotemporal structures as the original system, while the training time is also reduced. The results demonstrate the feasibility of using quotient networks to replace original large-scale networks when reconstructing synchronization dynamics with reservoir computing.

The frequent eolian processes in the northwest region of China pose a persistent threat to the conservation of earthen sites. Located in the “World Wind City” of Guazhou, Suoyang Ancient City experiences maximum wind velocities of 24 m/s, leading to severe sand accumulation and damage to its walls. This study focused on a typical 70-m-long section of the east wall of Suoyang Ancient City, featuring a gap, and utilized unmanned aerial vehicle (UAV)-assisted modeling technology to construct a three-dimensional model of the wall. Computational fluid dynamics (CFD) methods were employed to simulate the movement and accumulation processes of wind-blown sand. The research found that upward airflow at the upper part of the wall enables sand particles to surmount the wall's top, while downward airflow at the lower part accelerates the downward deposition of sand particles at the base of the wall. The wind field on the windward side is evenly distributed, resulting in relatively uniform sand deposition. Conversely, on the leeward side, a reflux zone forms after the airflow passes over the wall, causing sand particles to accumulate in an arc-shaped pattern behind the wall. The simulated results align with actual observations of sand accumulation at the gap in the east wall, providing valuable insights for sand prevention and control efforts at the Suoyang Ancient City.

Graphical Abstract