Probing the top quark flavor-changing couplings at CEPC

We propose to study the flavor properties of the top quark at the future Circular Electron Positron Collider (CEPC) in China. We systematically consider the full set of 56 real parameters that characterize the flavor-changing neutral interactions of the top quark, which can be tested at CEPC in the single top production channel. Compared with the current bounds from the LEP2 data and the projected limits at the high-luminosity LHC, we find that CEPC could improve the limits of the four-fermion flavor-changing coefficients by one to two orders of magnitude, and would also provide similar sensitivity for the two-fermion flavor-changing coefficients. Overall, CEPC could explore a large fraction of currently allowed parameter space that will not be covered by the LHC upgrade. We show that the $c$-jet tagging capacity at CEPC could further improve its sensitivity to top-charm flavor-changing couplings. If a signal is observed, the kinematic distribution as well as the $c$-jet tagging could be exploited to pinpoint the various flavor-changing couplings, providing valuable information about the flavor properties of the top quark.Comment: 13 pages, 15 figure

Amplification of Isocurvature Perturbations induced by Active-Sterile Neutrino Oscillations

We show how the generation of a lepton number in the Early Universe induced by active-sterile neutrino oscillations, in presence of small baryon number inhomogeneities, gives rise to the formation of lepton domains, regions with different values of active neutrino chemical potential. The structure of these domains reflects the spectral features of the baryon number inhomogeneities that generated it. An interesting aspect of the mechanism is that the size of lepton domains can be super-horizon.Comment: 20 pages + 3 included ps figure

EsaNet: Environment Semantics Enabled Physical Layer Authentication

Wireless networks are vulnerable to physical layer spoofing attacks due to the wireless broadcast nature, thus, integrating communications and security (ICAS) is urgently needed for 6G endogenous security. In this letter, we propose an environment semantics enabled physical layer authentication network based on deep learning, namely EsaNet, to authenticate the spoofing from the underlying wireless protocol. Specifically, the frequency independent wireless channel fingerprint (FiFP) is extracted from the channel state information (CSI) of a massive multi-input multi-output (MIMO) system based on environment semantics knowledge. Then, we transform the received signal into a two-dimensional red green blue (RGB) image and apply the you only look once (YOLO), a single-stage object detection network, to quickly capture the FiFP. Next, a lightweight classification network is designed to distinguish the legitimate from the illegitimate users. Finally, the experimental results show that the proposed EsaNet can effectively detect physical layer spoofing attacks and is robust in time-varying wireless environments

DCPoint: global-local dual contrast for self-supervised representation learning of 3D point clouds

In recent years, 3D vision has gained increasing prominence in practical applications such as autonomous driving and robotics. However, the scarcity of large labeled point cloud datasets continues to be a bottleneck for deep networks. Self-supervised representation learning (SRL) has emerged as an effective approach to alleviate this issue by pre-training general feature encoders without requiring human annotations. Existing contrastive SRL methods for 3D point clouds have predominantly concentrated on object representations from a global or point perspective. They overlook essential local geometry information, thereby constraining the generalizability of pre-trained models. To address these challenges, we propose a local contrast module as an intermediate level between the scene and point levels. It is then integrated with a global contrast module to form a dual contrast method known as DCPoint. The local contrast module operates on point-wise representations of objects and designs contrastive pairs based on the spatial information of point clouds. It effectively addresses the challenges posed by the sparsity and irregularity of point clouds and imperfect partition issues. The point-wise local contrast module aims to enhance the internal connections between the components within the point cloud, while the global contrast module introduces semantic information about individual instances. Experimental results demonstrate the effectiveness of DCPoint across various downstream tasks on synthetic and real-world datasets. It consistently outperforms previously reported SRL methods and the randomly initialized counterparts. Additionally, the proposed local contrast module can enhance the performances of other SRL methods

The particle surface of spinning test particles

In this work, inspired by the definition of the photon surface given by Claudel, Virbhadra, and Ellis, we give an alternative quasi-local definition to study the circular orbits of single-pole particles. This definition does not only apply to photons but also to massive point particles. For the case of photons in spherically symmetric spacetime, it will give a photon surface equivalent to the result of Claudel, Virbhadra, and Ellis. Meanwhile, in general static and stationary spacetime, this definition can be regarded as a quasi-local form of the effective potential method. However, unlike the effective potential method which can not define the effective potential in dynamical spacetime, this definition can be applied to dynamical spacetime. Further, we generalize this definition directly to the case of pole-dipole particles. In static spherical symmetry spacetime, we verify the correctness of this generalization by comparing the results obtained by the effective potential method.Comment: 12pages, no figures; accepted by The European Physical Journal C; the title has been revies

Extensive Thiol Profiling for Assessment of Intracellular Redox Status in Cultured Cells by HPLC-MS/MS

Oxidative stress may contribute to the pathology of many diseases, and endogenous thiols, especially glutathione (GSH) and its metabolites, play essential roles in the maintenance of normal redox status. Understanding how these metabolites change in response to oxidative insult can provide key insights into potential methods of prevention and treatment. Most existing methodologies focus only on the GSH/GSH disulfide (GSSG) redox couple, but GSH regulation is highly complex and depends on several pathways with multiple redox-active sulfur-containing species. In order to more fully characterize thiol redox status in response to oxidative insult, a high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS) method was developed to simultaneously determine seven sulfur-containing metabolites, generating a panel that systematically examines several pathways involved in thiol metabolism and oxidative stress responses. The sensitivity (LOQ as low as 0.01 ng/mL), accuracy (88-126% spike recovery), and precision (≤ 12% RSD) were comparable or superior to those of existing methods. Additionally, the method was used to compare the baseline thiol profiles and oxidative stress responses of cell lines derived from different tissues. The results revealed a previously unreported response to oxidative stress in lens epithelial (B3) cells, which may be exploited as a new therapeutic target for oxidative-stress-related ocular diseases. Further application of this method may uncover new pathways involved in oxidative-stress-related diseases and endogenous defense mechanisms

RIS-Assisted Physical Layer Authentication for 6G Endogenous Security

The physical layer authentication (PLA) is a promising technology which can enhance the access security of a massive number of devices in the near future. In this paper, we propose a reconfigurable intelligent surface (RIS)-assisted PLA system, in which the legitimate transmitter can customize the channel fingerprints during PLA by controlling the ON-OFF state of the RIS. Without loss of generality, we use the received signal strength (RSS) based spoofing detection approach to analyze the feasibility of the proposed architecture. Specifically, based on the RSS, we derive the statistical properties of PLA and give some interesting insights, which showcase that the RIS-assisted PLA is theoretically feasible. Then, we derive the optimal detection threshold to maximize the performance in the context of the presented performance metrics. Next, the actual feasibility of the proposed system is verified via proof-of-concept experiments on a RIS-assisted PLA prototype platform. The experiment results show that there are 3.5% and 76% performance improvements when the transmission sources are at different locations and at the same location, respectively

Perturbative Formulation and Non-adiabatic Corrections in Adiabatic Quantum Computing Schemes

Adiabatic limit is the presumption of the adiabatic geometric quantum computation and of the adiabatic quantum algorithm. But in reality, the variation speed of the Hamiltonian is finite. Here we develop a general formulation of adiabatic quantum computing, which accurately describes the evolution of the quantum state in a perturbative way, in which the adiabatic limit is the zeroth-order approximation. As an application of this formulation, non-adiabatic correction or error is estimated for several physical implementations of the adiabatic geometric gates. A quantum computing process consisting of many adiabatic gate operations is considered, for which the total non-adiabatic error is found to be about the sum of those of all the gates. This is a useful constraint on the computational power. The formalism is also briefly applied to the adiabatic quantum algorithm.Comment: 5 pages, revtex. some references adde