Based on the cosmological space-time background, the correction of space curvature and cosmological torsion to the neutrino-scattering-matrix element is calculated under the lowest-order approximation of perturbation theory. The result shows that a non-flat spatial curvature and cosmological torsion field can shift the peak position energy of the background radiation spectrum of cosmological neutrinos. Based on astronomical observation data and three types of Padé parameterizations, the magnitude of the effects of spatial curvature and cosmological torsion on the peak position shift of neutrinos is calculated. The result shows that positive and negative spatial curvatures cause the peak position of the neutrino background radiation spectrum to shift to the right and left, respectively. Cosmological torsion causes the peak position of the background radiation spectrum of the neutrinos to shift to the right, and because of the different coupling of Dirac and Majorana neutrinos with vector torsion, the right-shift degrees of their peak positions are different. This provides a solution for distinguishing the fermion types of neutrinos, eliminating the parameter degeneracy of dark energy and spatial curvature, and for determining the essence of dark energy.

Bandos-Lechner-Sorokin-Townsend electrodynamics is a two-parameter extension of Maxwell electrodynamics. It unifies Born-Infeld and ModMax theories and satisfies electromagnetic duality. In this new electrodynamic theory, the dispersion relation of electromagnetic waves is examined in the presence of a strong magnetic background field. Based on this, thermodynamic quantities, such as the energy density and pressure of the photon gas, are calculated. It is discovered that the BLST theory provides a modification to the blackbody radiation spectrum, particularly to Stefan-Boltzmann law. As the dispersion relations are dependent on the direction of the background magnetic field, the blackbody radiation power is a function of the angle between the area element direction and background magnetic field direction.

In quantum precision metrology, simultaneously weakening two types of noise based on quantum mechanisms, i.e., shot noise and measurement back-action noise, is challenging. Thus, the measurement precision is limited by the standard quantum limit(SQL). Two commonly used methods for surpassing this limit are to employ quantum squeezed light fields or quantum non-demolition(QND) measurements. This paper proposes an approach that combines these two methods within a typical cavity optomechanical weak-force-detection system. Compared with solely performing QND measurements, this integrated method surpasses the SQL significantly, thereby achieving superior measurement precision.

In this study, light propagation and electromagnetically induced transparency(EIT) in cold Rydberg atomic gas were theoretically investigated, using an inhomogeneous coupling beam. By virtue of EIT, the strong long-range atom-atom interactions in Rydberg states are mapped to light fields, resulting in strong photonic interaction. In previous studies, the coupled optical field was considered as spatially uniform and constant, with the interaction of the optical field possessing potential energy with spatial translation invariance. In the case of repulsive atomic interactions, when the intensity of the probe light field exceeds a critical threshold, the system undergoes a first-order phase transition because of the instability of the roton mode in momentum space, leading to self-organization of the system into optical patterns. However, in recent experiments, the spatial distribution of coupled light has often been nonuniform, and this nonuniformity can destroy the spatial translation invariance of the system. Our calculations show that when considering a large beam waist with coupling, the system can still self-organize into optical pattern structures at low atomic densities. However, as the atomic density increases, the edges of the patterns can be disrupted due to an increase in nonuniform excitation. The results of this study not only contribute to the development of Rydberg nonlinear optics but also have potential applications in the design of novel nonlinear optical devices in many-body systems.

Laser-induced solid-state anti-Stokes fluorescence cooling has important application value in the fields of all-solid-state cryogenic optical coolers and radiation balance lasers. Among many fluorides and oxide crystal materials, Yb³⁺-doped LiYF₄ (YLF) and Y₃Al₅O₁₂ (YAG) crystals stand out for their excellent laser cooling performance. Accordingly, in this study, the spectral properties and anti-Stokes fluorescence cooling properties of Yb³⁺ and YAG crystals with 7.5% doping concentration were compared and analyzed in detail under the same conditions. The results show that compared with YAG crystal, YLF crystal has a smaller minimum achievable temperature, and hence, a more feasible candidate for use in cryogenic coolers. In addition, under the condition of 1030 nm laser pumping, the net cooling effect cannot be observed in 7.5% Yb³⁺:YAG crystal. Therefore, for the radiation balance laser designed with Yb³⁺:YAG crystal as the gain medium, the doping concentration of Yb³⁺ should not exceed 7.5%.

This study presents the preparation of PbF radicals via the reaction of Pb plasma, generated by the laser ablation of lead, with SF₆/Ar gas mixture. Moreover, the vibrational-rotational bands of the ${\rm{A}}^2{\text{∑}}^{ +}$–X²Π_1/2 transition of PbF molecule were measured using laser induced fluorescence spectroscopy. The molecular constants $ {T}_{0} $, $ B $, $ D $, $ \gamma $ and $ p $ for the vibrational levels $ v $ = 0 and $ v $ = 1 of the PbF molecule in the ${\rm{A}}^2{\text{∑}}^{ +}$ state. The data provide effective information for electronic electric dipole moment(eEDM) measurement. Additionally, the fluorescence lifetime of the PbF molecule in the $v=0$ vibrational state of the ${\rm{A}}^2{\text{∑}}^{ +}$ state was measured. Finally, the Franck-Condon factors for the ${\rm{A}}^2{\text{∑}}^{ +}$–X²Π_1/2 transition were calculated using the Morse potential and Rydberg-Klein-Rees inversion(RKR)/LEVEL methods, indicating that PbF molecules are unsuitable for laser cooling research. The above results enrich the understanding of PbF molecular spectrum and provide key references for future studies on precise eEDM measurements.

In this study, a high-resolution fractional hybrid vortex beam is proposed. The hybrid scaling parameter $n $ used to generate the fractional hybrid vortex beam provides new degrees of freedom, extending the bandwidth of orbital angular momentum. The convolutional neural network from deep learning was adopted to accurately recognize the fractional hybrid vortex beam with an orbital angular momentum resolution $\Delta l $ of 0.1 and hybrid scaling parameter resolution $\Delta n $ of 0.01 under atmospheric turbulence conditions. The study investigated the effects of turbulence intensity and transmission distance on recognition accuracy. The results indicate that at a transmission distance of 150 m, the recognition accuracy reaches 82.09%, even under strong turbulence ($C_n^2 $ = 5×10^–14 m^–2/3). The recognition accuracy exceeded 99% under the conditions of medium and weak turbulence ($C_n^2 $ = 1×10^–14 m^–2/3 and 5×10^–15 m^–2/3, respectively). This scheme provides a reference for the accurate identification of fractional orbital angular momentum in turbulent environments.

Optical tweezers provide an effective non-contact and non-damaging method for precise manipulation of microscopic particles, which is of great significance in the development and application of optical micromanipulation technology. In this paper, a scheme is proposed for generating a one-dimensional movable optical potential trap(optical tweezers) using a spatial light modulator, thereby demonstrating it and discussing its application in particle trapping. The phase holograms of the two beams loaded on a space light modulator were dynamically tuned continuously to produce focused Gaussian and vortex hollow beams. The propagation characteristics of the two kinds of beams in free space, the relationship to the maximum intensity of the beam, size of the spot, and focal length were further studied. The optical potential, gradient force, and scattering force of particles in focused Gaussian and vortex hollow optical tweezers were calculated. The feasibility of constructing tunable one-dimensional moving optical tweezers is further discussed. This scheme has important application prospects in laser trapping and manipulation of microscopic particles.

As a novel cryocooler, a cryogenic optical refrigerator utilizing an anti-Stokes fluorescence process provides cooling power to a payload. Cryogenic optical refrigerators exhibit a compact structure, wide temperature range, and non-vibration. Hence, they are promising for applications in space technology, defense, and precision measurement. In this study, the principle prototype of a cryogenic optical refrigerator is introduced based on a cooling-grade Yb³⁺:LuLiF₄ crystal. Furthermore, the fluorescence escape coefficient and thermal loads of a heat link in an optical refrigerator is analyzed. Various heat link structures are designed, the fluorescence transmission process in these heat links is simulated using an optical simulation software, and the fluorescence escape coefficients of the different structures are determined based on the ray tracing results. The thermal loads of the heat link in the optical refrigerator are analyzed, and the thermal loads of the refrigerator with different angles of D-type bending structure heat links at low temperatures are calculated. The most suitable heat-link structure for cryogenic optical refrigerators is identified by optimizing the fluorescence escape coefficient and thermal loads of the heat link. The heat link design proposed in this study provides a good solution for high-efficiency cryogenic optical coolers.

To ensure that the Larmor precession frequency of noble gas nuclei is solely determined by the applied main magnetic field, one must eliminate the residual background magnetic field, thereby providing the foundation for achieving high-precision nuclear magnetic resonance gyroscopes (NMRGs). Hence, accurate measurement of the residual magnetic field is critical for realizing this objective. In this study, the three-axis residual magnetic field is measured using the alkali-metal atomic magnetometer embedded within the NMRG system. Under specific experimental conditions, the magnitudes of the residual magnetic field in the x, y, and z axes are determined, respectively, which create the conditions necessary for effective three-axis residual field compensation in the gyroscope. Furthermore, when the main magnetic field is applied along the z-axis, the noble gas atoms are polarized due to spin-exchange collisions with alkali-metal atoms, thus generating an equivalent magnetic field along the z-axis. This equivalent magnetic field can be measured by using the embedded atomic magnetometer. These findings provide essential insights into spin-exchange collisions between alkali-metal and noble gas atoms, thereby enabling an analysis of the Fermi-contact-interaction enhancement factor and other critical parameters within the cell.

A new scheme of plasma block acceleration driven by intense lasers ($I_0 $ ~ 10¹⁸ W/cm²) is proposed based upon asymmetric plasma implosion in density gradient targets, using a particle-in-cell (PIC) simulation technique. Taking the proton target as an example, first, we present the implosion characteristics when the target has a homogeneous density. The influence of target thickness, laser polarization, and pulse length upon implosion are discussed. Then by changing the density gradient of the target, the asymmetric implosion induced by the asymmetric ponderomotive is investigated. Compared with the results from those based upon a target with homogenous density, the accelerated protons have higher energy, which is increased from magnitude of 10 keV to hundreds of keV, and the beam quality is also improved. Because the improved proton energy is just in the energy range for proton-boron fusion reactions with high probability, the above investigations would have great potential application for laser-driven proton-boron fusion research.

In this study, we employed a density functional theory to perform self-consistent calculations on rutile-structured RuO₂. The results reveal that when electronic correlation effects are included, RuO₂ exhibits antiferromagnetic ordering with alternating magnetic characteristics; however, without these effects, RuO₂ remains nonmagnetic. A comparison between the results of the NMTO(Nth-order muffin-tin orbital) method and those obtained using the pseudopotential plane-wave method in VASP(Vienna ab-initio simulation package) indicated that the NMTO method can effectively describe the physical properties of the loosely packed rutile structure of RuO₂. Additionally, by combining the NMTO method with its unique downfolding technique, we successfully obtained tight-binding model parameters for Ru d-electronic orbitals. These parameters are highly consistent with those derived from VASP combined with maximally localized Wannier functions, showing minimal differences. This study demonstrates that the NMTO method can accurately describe the properties of RuO₂ and provide reliable tight-binding parameters via its downfolding technique, thereby providing a deeper understanding of the physical properties of the material.

We theoretically demonstrate a novel metasurface for graphene ballistic electrons, which is a one-dimensional gate-defined quantum-dot array comprising multiple complex unit cells arranged periodically. Each complex unit cell is composed of a set of quantum dots with gradient-varying radii. The same bias is applied to all the quantum dots. The rigorous Mie scattering theory and multiple scattering theory reveal that the metasurfaces comprising different complex unit cells can deflect the incident electron wave at different angles with almost 100% efficiency, thus demonstrating high control over the transport of graphene electrons. The ultracompactness of the metasurface enables it to shape the wavefront within a distance significantly smaller than the room-temperature ballistic-transport distance. Electron optics devices can be miniaturized considerably by adopting the metasurface, thus providing a solution for eliminating low-temperature conditions and developing room-temperature electron optics technologies with significant application potential in graphene.

According to the four-energy level theoretical model, the background absorption of a cooled sample is a key parameter affecting laser cooling performance. To investigate the relationship between background absorption coefficient and the temperature of the cooled sample, such as Yb³⁺:LuLiF₄(LLF), a low-temperature laser-induced temperature modulation spectrum(LITMoS) experiment was designed to obtain the background absorption coefficient of the crystal at low temperatures. Based on the heat load theory, the experimental formula for the cooling efficiency under low-temperature conditions was derived, and the source of heat load was theoretically analyzed, demonstrating that contact conduction is the main source of heat load for low-temperature LITMoS experimental samples. In the experiments, a liquid nitrogen cryostat and a specially designed cold finger structure were used to control the temperature of the crystal, thereby obtaining the temperature drop of the crystal by non-contact temperature measurement using time-valve-differential fluorescence spectroscopy thermometry. A feasibility analysis was conducted on the experimental design scheme, and the sample cooling efficiency at the corresponding wavelength was calculated. The results show that the experimental design scheme can measure the functional relationship between the background absorption coefficient and temperature under low-temperature conditions. The test results of refrigeration efficiency were in accordance with the prediction of the theoretical model of optical refrigeration.

The non-Markov and Markov spreading models are two common infectious disease spreading models. The essential difference between them lies in whether the spreading process depends on the historical dynamic state. Although some studies have revealed that the two can be equivalent under certain conditions, the accuracy of this prediction in an actual epidemic is insufficient. Thus, based on the SHIJR(susceptible, hidden, infected, confirmed, removed) model, this paper compares and analyzes the predictive ability of the non-Markov and Markov spreading models for the COVID-19(coronavirus disease 2019) epidemic situation. Assuming that the system is in a uniform mixing mode, the time distribution of the state transition in the non-Markov model can be converted to the corresponding transition rate in the Markov model. Then, the optimal propagation parameters of the two modes can be simulated respectively. In the simulations that we performed, we found that the parameters simulated by the non-Markov model were more realistic, and both the short-term and long-term prediction effects were better than those for the Markov model. This work fills the gap for predictive comparisons between these two communication models and promotes a greater understanding of their predictive abilities and applicable conditions.

Chess, a symbolic game of human intellectual competition, provides valuable behavioral insights into players’ cognition, creativity, and strategic thinking, making it an ideal subject for studying human decision-making patterns. Leveraging the vast chess game dataset from Kaggle, this study conducts an empirical analysis of the scale-free characteristics (Zipf’s law) of the popularity of games across different skill levels and explores the underlying patterns of decision-making behavior. Our empirical results indicate that the popularity of chess games follows a multi-scaling law correlated with player ratings. Specifically, the Zipf exponent of highly rated players is lower than that of lower-rated players in the opening stage, whereas this trend reverses as the game proceeds to the mid-game stage, which suggests a starkly opposite decision-making diversity of the two types of players in cases of different complexity. This difference in behavior may stem from the heterogeneity in the capacities of strategic sets and the fuzziness of payoffs and identify two independent variables that can quantitatively express the Zipf exponent. Furthermore, we find that the similarity between chess games exhibits long-term correlations, with Hurst exponents increasing alongside player ratings, indicating a locally rapid growth in popularity dynamics. These findings establish a critical foundation for understanding and predicting individual decision-making behaviors in complex scenarios.

In the active driven network established in this study with link memory, nodes connect to their neighbors from previous time steps(a memory window) with a certain probability(memory connection preference). Delving into the susceptible-infected-recovery(SIR) epidemic dynamics of the model, the epidemic outbreak threshold is derived using the quenched mean-field method, demonstrating that memory reduces the network’s maximum degree but increases the maximum edge weight, a pattern commonly observed in real-world mobile phone network datasets. Furthermore, in epidemic dynamics, with the rise in connection preference and memory window, the outbreak threshold increases, whereas final outbreak size decreases.

In response to the 2019 novel coronavirus disease (COVID-19) pandemic, 197 countries have implemented various government control policies to achieve varying degrees of suppression. Many scholars have analyzed the impact of various non-pharmaceutical interventions and vaccination policies on COVID-19 using mathematical modeling. These studies have primarily focused on the quantitative assessment of the impact of interventions on the reproductive number of COVID-19 patients. This study establishes a two-layer Bayes model to quantitatively estimate the effectiveness of different policies on COVID-19 infection and recovery based on Bayesian inference. It categorizes intervention measures into two groups: public health intervention policies and control policies. The results show that both types of intervention policies can reduce the infection rate of COVID-19 and improve the recovery rate. However, each type of intervention policy has a distinct impact on the transmission and recovery processes. Specifically, public health intervention measures have a greater impact on COVID-19 recovery, while control policies and public health measures significantly affect the transmission of COVID-19.