This paper demonstrates a pathway to topological superconductivity in monolayer triangular lattices through long-range pairing without requiring spin−orbit coupling and magnetic field, contrasting conventional frameworks reliant on superconductivity and spin−orbit coupling and time-reversal symmetry (TRS) breaking. Berry curvature analysis reveals spontaneous TRS-breaking-induced peaks or valleys under long-range pairing, signaling nontrivial topology superconducting states. Notably, the increase in the long-range pairing strength only changes the size of the energy band-gap, without triggering a topological phase transition. This characteristic is verified by calculating Berry curvature and topological edge states. In zigzag and armchair-edge ribbons of finite width, the topological edge states are influenced by the ribbon boundary symmetry and the interaction range of long-range pairing. Under nearest-neighbor pairing, the topological edge states maintain particle−hole symmetry and match the corresponding Chern number. However, next-nearest-neighbor and third-nearest-neighbor pairings break the particle-hole symmetry of the topological edge states in armchair-edge ribbon. This work proposes a mechanism to realize topological superconductivity without relying on spin−orbit coupling and magnetic field, thereby offering a theoretical foundation for simplifying the design of topological quantum devices.

Magnetization switching plays a pivotal role in many spintronic devices. Distinct from conventional field-driven approaches, we propose a self-induced magnetization reversal mechanism that exploits the intrinsic periodic energy focusing and dispersing behavior of magnetic breathers. In this paper, we explore magnetic breather excitations and potential applications of Kuznetsov−Ma (KM) breather in an anisotropic ferromagnet. Under the long-wavelength approximation, the magnetization dynamics of a ferromagnetic nanowire are governed by a generalized derivative nonlinear Schrödinger equation. By employing a two-fold Darboux transformation, we derive the general breather solution and classify it into five distinct types through modulation instability analysis. Numerical simulations reveal a reversible transition between magnetic solitons and KM breathers, achieved by tuning the amplitude of the background plane wave. The KM breather exhibits periodic magnetization oscillations capable of inducing time-dependent magnetoresistance. When coupled with an appropriately defined critical current, this feature facilitates the realization of autonomous timing switches. These results provide theoretical foundations for the advancement of breather-enabled spintronic technologies.

We investigate a two-dimensional non-Hermitian Fermi system with spin imbalance and dissipative interaction. We employ the mean-field approximation to derive and minimize the thermodynamic potential, and determine the zero-temperature phase diagram upon variation of imbalance and dissipation. Notably, we identify a Fulde−Ferrell−Larkin−Ovchinnikov (FFLO) state characterized by a pairing order parameter with finite center-of-mass momentum, along with the normal, Bardeen−Cooper−Schrieffer (BCS), and metastable BCS states. The FFLO state is favored with increasing spin imbalance but diminishes and eventually disappears with elevated dissipation. Additionally, we present the quasiparticle energy spectrum and momentum distribution, highlighting the spatial asymmetry features that can be used to deterministically identify the FFLO state.

Characterizing quantum critical states towards the thermodynamic limit is essential for understanding phases of matter. The power of quantum simulators for preparing the critical states relies crucially on the structure of quantum circuits and in return provides new insight into the critical states. Here, we explore the critical states of the quantum Rabi model (QRM) by preparing them variationally with Hamiltonian variational ansätze (HVA), in which the intricated interplay among different quantum fluctuations can be parameterized at different levels. We find that the required circuit depth scales linearly with the effective system size, suggesting that HVA can efficiently capture the behavior of critical states of QRM towards the thermodynamic limit. Moreover, we reveal that HVA gradually squeeze the initial state to the target critical state, with a number of blocks increasing only linearly with the effective system size. Our work suggests variational quantum algorithm as a new probe for the complicated critical states.

Subwavelength slit diffraction, as a fundamental diffraction phenomenon, is of great significance in various fields. However, governed by the symmetry of coupling modes and diverse diffraction orders, designing a device that can independently achieve excellent extraordinary transmission performance and a desirable collimation effect remains a challenging task. Here, we propose a new paradigm for manipulating acoustic slit diffraction by engineering a reversed phase gradient on one side of the structural surface. For instance, under forward incidence, the extraordinary transmission efficiency can be significantly enhanced, where the phase gradient plays a key role in exciting unidirectional evanescent waves along the surface; under backward incidence, the beam collimation effect can be well maintained, as the phase gradient functions to suppress unwanted diffraction orders. We further experimentally demonstrate this novel phenomenon. Our work enriches the methods for manipulating acoustic single-slit diffraction and shows potential applications in sensors and holography.

The task of protecting quantum entanglement is crucial for quantum communication. Conventionally, correlated noise correction requires an electro-optic modulation process, which limits the application of such correction schemes in constructing broadband quantum communication. Here, we experimentally demonstrate a scheme of all-optical entanglement recovery in a correlated noisy channel without electro-optic modulation. In our scheme, the correlated noisy channel is enabled by an Einstein−Podolsky−Rosen entangled state, a low-noise parametric amplifier, and a beam splitter, thereby avoiding electro-optic conversion. Quantum entanglement is destroyed after one half of the quantum entangled state passes through the noisy channel. Such quantum entanglement can be recovered in the auxiliary noisy channel which shares correlated noise with the noisy channel. Our results pave the way for deterministically implementing all-optical quantum secure communication.

The output prediction of quantum circuits is a formidably challenging task imperative in developing quantum devices. Motivated by the natural graph representation of quantum circuits, this paper proposes a Graph Neural Networks (GNNs)-based framework to predict the output expectation values of quantum circuits under noisy and noiseless conditions and compare the performance of different parameterized quantum circuits (PQCs). We construct datasets under noisy and noiseless conditions using a non-parameterized quantum gate set to predict circuit expectation values. The node feature vectors for GNNs are specifically designed to include noise information. In our simulations, we compare the prediction performance of GNNs in both noisy and noiseless conditions against Convolutional Neural Networks (CNNs) on the same dataset and their qubit scalability. GNNs demonstrate superior prediction accuracy across diverse conditions. Subsequently, we utilize the parameterized quantum gate set to construct noisy PQCs and compute the ground state energy of hydrogen molecules using the Variational Quantum Eigensolver (VQE). We propose two schemes: the Indirect Comparison scheme, which involves directly predicting the ground state energy and subsequently comparing circuit performances, and the Direct Comparison scheme, which directly predicts the relative performance of the two circuits. Simulation results indicate that the Direct Comparison scheme significantly outperforms the Indirect Comparison scheme by an average of 36.2% on the same dataset, providing a new and effective perspective for using GNNs to predict the overall properties of PQCs, specifically by focusing on their performance differences.

The development of efficient catalysts for the electrocatalytic CO reduction reaction toward high-value C₂ products is critical for addressing pressing energy and environmental challenges. Dual-metal catalysts have emerged as promising candidates due to their potential to facilitate C−C coupling, a key step in C₂ product formation. However, their activity and selectivity are highly dependent on the charge states of the active sites. Modulating asymmetric charge distribution between metal centers offers a viable strategy to enhance C−C coupling efficiency and product selectivity. In this study, we employ density functional theory to investigate heteronuclear dual-atom catalysts (DACs) anchored on ferroelectric In₂Se₃ and impact of polarization on charge states of metal sites. We find that Pd−Nb and Rh−Nb DACs form spatially separated charge centers with opposite signs, which significantly reduce the energy barrier for C−C coupling compared to homonuclear Nb−Nb DACs, enabling thermodynamically favorable C−C bond formation. The Coulomb interaction between oppositely charged centers is identified as a key descriptor governing C−C coupling efficiency. Furthermore, ferroelectric polarization switching of In₂Se₃ offers dynamic modulation of reaction pathways and product selectivity. Pd−Nb@In₂Se₃ under downward polarization (P↓) favors ethane formation with a limiting potential of −1.06 eV, whereas upward polarization (P↑) shifts the reaction toward an alternative C−C coupling pathway with a higher overpotential (−1.47 eV). Similarly, Rh−Nb@In₂Se₃ selectively produces ethanol under P↓, but methane under P↑. Importantly, both Pd−Nb and Rh−Nb DACs exhibit stronger CO adsorption than H adsorption, favoring CORR over the competing hydrogen evolution reaction. These findings underscore the potential of ferroelectric DACs as tunable and selective catalysts for CORR, offering a compelling strategy for the rational design of next-generation electrocatalysts for decarbonization.