Urban rail transit is an efficient and environmentally friendly mode of transport, which is an important means of transportation for passengers. From a holistic point of view, this paper constructs an urban rail transit interchange topology (URTIT) network based on the interchange relationships among lines. We investigate a unique influence propagation mechanism to explore the impact of applying new technologies on the passenger travel behavior of urban rail transit. We analyze the influence from three aspects: the influence range, the influence propagation path, and the influence intensity. Based on the Dijkstra algorithm, the influence propagation paths are found according to the shortest transfer time. The improved path−based gravity model is applied to measure the influence intensity. The case study on urban rail transit in Beijing, China is carried out. The influence propagation mechanism of a single line in the Beijing URTIT network is analyzed, considering that Beijing Subway Line S1 is equipped with magnetic levitation technology. We not only quantify the impact of technologies on passenger travel behavior of urban rail transit, but also perform the sensitivity analysis. To avoid randomness, the influence propagation mechanisms of all lines are explored in this paper. The research results correspond to the situation in reality, which can provide certain references for urban rail transit operation and planning.
In this paper, we investigate the integrable fractional coupled Gerdjikov–Ivanov equation and derive its explicit form by employing the completeness relation of squared eigenfunctions. Based on the Riemann–Hilbert method, we construct the fractional N-soliton solutions. We find that as the power ε of the Riesz fractional derivative increases, the amplitudes of the fractional soliton solutions remain invariant, while their widths decrease and the absolute values of the wave velocity, group velocity, and phase velocity increase. Additionally, we examine the long-time asymptotic behavior of the fractional N-soliton solution. The results show that as t →±∞, the solution can be approximated by the sum of N fractional one-soliton solutions, with each soliton's amplitude and velocity remaining constant, whereas both position and phase shifts are observed.
To improve the decoding performance of quantum error-correcting codes in asymmetric noise channels, a neural network-based decoding algorithm for bias-tailored quantum codes is proposed. The algorithm consists of a biased noise model, a neural belief propagation decoder, a convolutional optimization layer, and a multi-objective loss function. The biased noise model simulates asymmetric error generation, providing a training dataset for decoding. The neural network, leveraging dynamic weight learning and a multi-objective loss function, mitigates error degeneracy. Additionally, the convolutional optimization layer enhances early-stage convergence efficiency. Numerical results show that for bias-tailored quantum codes, our decoder performs much better than the belief propagation (BP) with ordered statistics decoding (BP + OSD). Our decoder achieves an order of magnitude improvement in the error suppression compared to higher-order BP + OSD. Furthermore, the decoding threshold of our decoder for surface codes reaches a high threshold of 20%.
We present error-rejecting entanglement concentration protocols (ECPs) for partially entangled electron spins in quantum dots (QDs) with unknown and known parameters using quantum electrodynamics of QDs coupled with optical cavities, which can recover the partially entangled state to the maximally entangled state with unit fidelity even in the non-ideal experimental condition. The error-rejecting ECP for a partially entangled state utilizes parity check operations on electron spins within QDs. Furthermore, for a partially entangled state with known parameters, the ECP is devised through a parameter-splitting approach. The success probabilities of these two error-rejecting ECPs can be further improved by using the resource recycling method and iteration method. On account of their unit fidelity and considerable success probability, the error-rejecting ECPs have promising application value in improving the fidelity of quantum communication.
We investigate phase estimation in a lossy interferometer using entangled coherent states, with a particular focus on a scenario where no reference beam is employed. By calculating the quantum Fisher information, we reveal two key results: (1) the metrological equivalence between scenarios with and without a reference beam, established under ideal lossless conditions for the two-phase-shifting configuration, breaks down in the presence of photon loss, and (2) the pronounced inferior performance of ECSs relative to NOON states, observed in the presence of a reference beam, disappears in its absence.
This work theoretically studies the Bose–Hubbard (BH) model in a ring geometry in a rotating frame. We obtain an effective Hamiltonian by using unitary transformation, where the effect of the rotating reference frame is introducing additional phases to the hopping constant. Within the mean-field theory, the phase transition edge depends not only on the particle number and ring radius, but also on rotation velocity. Therefore, we propose a sensing method of the rotation velocity using the phase transition edge of the Bose–Hubbard model. At the exact phase transition edge where this sensing method is most sensitive, the resolution depends on the rotation velocity, the particle number and the ring radius, while it is independent of the parameters in the Bose–Hubbard model such as the hopping constant and the on-site interaction.
We argue that the hypothesis that positive-parity charm meson resonances exhibit a compact tetraquark structure has some clear tension with recent lattice results for the S-wave πD system for an SU(3) flavor symmetric setting. In particular, we show that such a diquark–anti-diquark tetraquark scenario would call for the presence of a state in the flavor $[\overline{{\bf{15}}}]$ representation, not seen in the lattice analysis. Moreover, we show that analogous lattice data in the axial-vector channel are even more sensitive to the internal structure of these very interesting states.
White dwarfs, one of the compact objects in the Universe, play a crucial role in astrophysical research and provide a platform for exploring nuclear physics. In this work, we extend the relativistic mean field approach by using a Walecka-type quantum hadrodynamics model to capture the intricate structure of white dwarfs. We calculate nuclear properties, Coulomb energy, and photon energy within white dwarfs in a unified framework. By carefully calibrating the model parameters to align with nuclear matter properties, we successfully reproduce the structures of several elements in white dwarfs, such as the isotopes of C and 16O, except for the unnaturally deeply bound state 4He. Furthermore, we predict the characteristics of white dwarfs composed of atom-like units and the gravitational waves stemming from binary white dwarf inspirals incorporating tidal deformability contributions up to the 2.5 post-Newtonian order. These results shed light on the structure of white dwarfs and provide valuable information for future gravitational wave detection. This methodological advancement allows for a cohesive analysis of white dwarfs, neutron stars, and the nuclear pasta within a unified theoretical framework.
Using the Melnikov method, the phenomenon of thermal chaos under periodic perturbation in the extended phase space of the modified thermodynamics of Kerr-AdS black holes is investigated. On the (P, v) section in the extended phase space, it is shown that temporal chaos will appear in the unstable spinodal region when the perturbation amplitude is larger than critical value ${\delta }_{c}^{Pv}$. We find ${\delta }_{c}^{Pv}$ is monotonically decreasing with respect to the angular momentum parameter a, which implies a large a leads to chaotic behavior more easily under time-periodic thermal perturbation. Similarly, on the $({\widehat{{\rm{\Omega }}}}_{H},J)$ section, we show there exists a critical value ${\delta }_{c}^{{\rm{\Omega }}J}$ which depends on the cosmological parameter $l=\sqrt{-3/{\rm{\Lambda }}}$. When the perturbation amplitude exceeds ${\delta }_{c}^{{\rm{\Omega }}J}$, temporal chaos occurs. As l increases, chaos becomes easier. For spatial perturbation, chaos always exists irrespective of perturbation amplitude in both the (P, v) section and $({\widehat{{\rm{\Omega }}}}_{H},J)$ section.
In the framework of general relativity (GR), gravitational waves (GWs) travel at the speed of light across all frequencies. However, massive gravity and weak equivalence principle (WEP) violation may lead to frequency-dependent variations in the propagation speed of GWs, which can be examined by comparing the theoretical and observed discrepancies in the arrival times of GW signals at various frequencies. This provides us with an opportunity to test these theories. For massive gravity, we consider that gravitons may have a nonzero rest mass. For WEP violations, we hypothesize that different massless particles exposed to the same gravitational source should exhibit varying gravitational time delays. The gravitational time delay induced by massive gravitational sources is proportional to γ + 1, where the parameter γ = 1 in GR. Therefore, we can quantify these two deviations using phenomenological parameters mg and ∣Δγ∣, respectively. In this study, we use selected GW data from binary black hole coalescences in the LIGO-Virgo catalogs GWTC-2.1 and GWTC-3 to place constraints on the parameters mg and ∣Δγ∣. We also compute Bayes factors for models that assume the existence of graviton mass and WEP violation compared to the standard GW model, respectively. The absolute value of the natural logarithm of the Bayes factor is generally less than two. Our analysis reveals no significant preference for either model. Additionally, the Bayes factors between these two models do not provide obvious evidence in favor of either one.
Cosmic inflation is one of the most important paradigms in modern cosmology. In its simplest form, inflation is driven by a single inflaton field. However, multi-field inflation has become increasingly attractive because it can solve many theoretical and observational challenges. In this paper, we propose a particular model involving two axion-like fields with simply monodromy-dominated potentials. We demonstrate that this model is consistent with current cosmological observations.
In this work we study gravitational lensing of the wormhole in the Eddington-inspired Born–Infeld (EiBI) spacetime that incorporates with a cosmic string. It is found that the presence of a cosmic string can enhance the light deflection in the strong-field limit, compared to the Ellis–Bronnikov wormhole. The magnification effects of this composite structure could cause some substantial impacts on the angle separation between the first and the rest of the images, and their relative brightness. Furthermore, based on these observables, we model some observable aspects in the strong- and the weak-field limits. The presence of a cosmic string can affect some distinguishable observables compared to the wormhole without cosmic string. This work could deepen our understanding of the spacetime structure of the wormhole in EiBI spacetime with one-dimensional topological defects.
Verlinde's emergent gravity (VEG) posits that gravity arises as an emergent phenomenon rooted in the entropic properties of spacetime, challenging the traditional view of gravity as a fundamental force. Building on this paradigm, recent developments have introduced a novel class of black holes within the VEG framework, revealing intriguing connections between apparent dark matter effects and the distribution of baryonic matter. In this study, we delve into the observational signatures of a Simpson–Visser (SV) Minkowski core regular black hole in VEG, focusing on its shadow images and intensity profiles. Our analysis highlights the profound influence of model parameters, including A (governing baryonic matter distribution), B (strength of interaction between apparent dark matter and baryonic matter), and n (characterizing diverse spacetime geometries), on the effective potential and observable properties. Notably, we find that the modifications introduced by these parameters lead to distinct changes in the black hole's shadow size and intensity distribution. Comparing our results to the Reissner–Nordström (RN) black hole, we uncover a striking reduction in the apparent shadow size and an enhancement in intensity for the SV solution in VEG.
We investigate the dynamic behavior of vector soliton train propagating in optical media, modeled by the coherently coupled nonlinear Schrodinger (NLS) equation. It is shown that an increase in phase parameters, induces an increase in intensity of the periodic soliton train, as well as the number of pulses for each transverse electric (TE) and transverse magnetic (TM) mode. From the perturbation approach, when examining the propagation states for the transverse electric and magnetic (TEM) mode, we found a family of three bound-vector soliton states with a different propagation parameter at the first order, representing the three possible distinct vector optical fields reconfiguration of the initial profiles one of which is the ‘replication'. At the second order, we obtain an eigenvalue problem with an optical external field, giving rise to five high intensity periodic vector soliton structures described by elliptic functions. Such vector soliton trains are intended to complement single-pulse solitons for multi-channel communication applications.
In this paper, we investigate the distinctions between dynamical quantum chaotic systems and random models from the perspective of observable properties, particularly focusing on the eigenstate thermalization hypothesis (ETH). Through numerical simulations, we find that for dynamical systems, the envelope function of off-diagonal elements of observables exhibits an exponential decay at large ΔE, while for randomized models, it tends to be flat. We demonstrate that the correlations of chaotic eigenstates, originating from the delicate structures of Hamiltonians, play a crucial role in the non-trivial structure of the envelope function. Furthermore, we analyze the numerical results from the perspective of the dynamical group elements in Hamiltonians. Our findings highlight the importance of correlations in physical chaotic systems and provide insights into the deviations from random matrix theory (RMT) predictions. These understandings offer valuable directions for future research.
Ribonucleic Acid (RNA) contact prediction holds great significance for modeling RNA 3D structures and further understanding RNA biological functions. The rapid growth of RNA sequencing data has driven the development of diverse computational methods for RNA contact prediction, and a benchmark evaluation of these methods remains essential. In this work, we first classified RNA contact prediction methods into statistical inference-based and neural network-based ones. We then evaluated eight state-of-the-art methods on three test sets: a sequence-diverse set, a structurally non-redundant set and a CASP RNA targets set. Our evaluation shows that for identifying non-local and long-range contacts, neural network-based methods outperform statistical inference-based ones, with SPOT-RNA-2D achieving the best performance, followed by CoCoNet and RNAcontact. However, for identifying the long-range tertiary contacts, which are vital for stabilizing RNA tertiary structure, statistical inference-based methods exhibit superior performance with GREMLIN emerging as the top performer. This work provides a comprehensive benchmarking of RNA contact prediction methods, highlighting their strengths and limitations to guide further methodological improvements and applications in RNA structure modeling.
Systems with quenched disorder possess complex energy landscapes that are challenging to explore under conventional Monte Carlo methods. In this work, we implement an efficient entropy sampling scheme for accurate computation of the entropy function in low-energy regions. The method is applied to the two-dimensional ±J random-bond Ising model, where frustration is controlled by the fraction p of ferromagnetic bonds. We investigate the low-temperature paramagnetic–ferromagnetic phase boundary below the multicritical point at TN = 0.9530(4), PN = 0.89078(8), as well as the zero-temperature ferromagnetic–spin-glass transition. Finite-size scaling analysis reveals that the phase boundary for T < TN exhibits reentrant behavior. By analyzing the evolution of the magnetization-resolved density of states g(E, M) and ground-state spin configurations against increasing frustration, we provide strong evidence that the zero-temperature transition is a mixed-order. Finite-size scaling conducted on the spin-glass side supports the validity of β = 0, where β is the magnetization exponent, with a correlation length exponent ν = 1.50(8). Our results provide new insights into the nature of the ferromagnetic-to-spin-glass phase transition in an extensively degenerate ground state.
Combinatorial optimization problems and ground state problems of spin glasses are crucial in various fields of science and technology. However, they often belong to the computational class of NP-hard, presenting significant computational challenges. Traditional algorithms inspired by statistical physics like simulated annealing have been widely adopted. Recently, advancements in Ising machines, such as quantum annealers and coherent Ising machines, offer new paradigms for solving these problems efficiently by embedding them into the analog evolution of nonlinear dynamical systems. However, existing dynamics-based algorithms often suffer from low convergence rates and local minima traps. In this work, we introduce the dual mean-field dynamics into Ising machines. The approach integrates the gradient force and the transverse force into the dynamics of Ising machines in solving combinatorial optimization problems, making it easier for the system to jump out of the local minimums and allowing the dynamics to explore wider in configuration space. We conduct extensive numerical experiments using the Sherrington–Kirkpatrick spin glass up to 10 000 spins and the maximum cut problems with the standard G-set benchmarks. The numerical results demonstrate that our dual mean-field dynamics approach enhances the performance of base Ising machines, providing a more effective solution for large-scale combinatorial optimization problems.
The topological phases and edge states of a topological Euler insulator on a triangular lattice is studied. Differently from two-band Chern insulators, a topological Euler insulator is a kind of three-band model, described by the Euler number not the Chern number. The spin textures of a topological Euler insulator in the momentum space is like a Néel-type skyrmion. It is found that the topological edge states exist in the band gap of the topological Euler insulator, and the topological Euler insulator can be transformed into a topological metal without the topological phase transition.
We investigate the quantum phase transitions (QPTs) of the two-qubit quantum Rabi model with staggered qubit biases. In the limit of an infinite qubit-to-cavity frequency ratio, we analytically derive the mean-field Hamiltonian and the order-parameter-dependent energy density functional, which yields the ground-state energy and order parameter. The rich superradiant phase transitions (SRPTs), including both second- and first-order QPTs and a tricritical point (TCP), are analytically derived. Specifically, we derive the analytical expressions for all phase transition points, including the nonperturbative point of the first-order SRPT. The analytical findings are further corroborated by numerical finite-size scaling analysis. It is found that both the critical correlation-length and order-parameter exponents at the TCP differ from those of the original second-order SRPTs, implying that the TCP belongs to a new universality class. This work provides a reliable theoretical framework for designing new, simple experimental platforms to explore the rich QPTs.
