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In order to solve problem of spacetime singularity in theoretical physics, researchers proposed the regular black holes (BH). The generalized black-bounce (GBB) spacetime, as a unified treatment of distinct kinds of geometries in the framework of general relativity (e.g. regular BH and wormholes), has been extensively studied. Firstly, we derive to give the explicit forms of Lagrangian for a nonlinear electromagnetic field and potential for a non-canonical phantom field in the action of gravitational system corresponding to GBB solution. Secondly, this paper computes the radius of the innermost stable circular orbit (ISCO) and the stable circular orbit region for different types of celestial bodies in GBB spacetime. The research suggests that traversable wormholes may have two ISCOs or one ISCO depending on the throat's scale, whereas regular BH and extremal BH possess only one ISCO. Thirdly, quasi-periodic oscillations (QPOs) have been found to be a reliable tool for testing gravitational theories. Therefore, we compute the radial and azimuthal epicyclic angular frequencies of particles oscillating on stable circular orbits around various celestial bodies and compare them with the oscillation frequency properties of schwarzschild BH. Moreover, due to the limited amount of research on the high-frequency quasi-periodic oscillations (HFQPOs) phenomenon and its generation mechanisms around particles near wormholes using observational data, this paper aims to study theoretical models that can simultaneously describe both BH and wormholes by fitting observational data. Using resonance models and associated frequency ratios, we are able to locate the resonances of different celestial bodies within the GBB spacetime., Comment: 20 pages, 8 figures

We investigate dynamical effects of particles moving around rotating SV regular BH and traversable wormholes, and the deviation from Kerr BH. We found that the rotating SV traversable wormhole spacetime has a closer innermost stable circular orbit to the central object than Kerr and rotating regular BHs. Furthermore, the paper provides the general form of the epicycle frequency in this spacetime, presenting the radial profile of the angular frequency of particles undergoing oscillatory motion. Unlike the commonly used $\chi$-square analysis method, with considering a generalized data analysis approach in this paper we hypothesize that the observational data of three microguasars can be explained through an axisymmetric SV spacetime, fitting the data to find the range of spin values for three types of SV objects, and analyzing the possible mechanisms of HFQPOs (high-frequency quasi-periodic oscillations) generation for different types of axisymmetric SV objects. We found that for a Kerr BH with $l^*=0$, the observational data of three microquasars can be explained by the HFQPOs model used in this paper (excluding ER4 model); for a regular BH with $l^*=1$, the HFQPO phenomenon observed through the three microquasars can be explained by the ER0, ER1, ER2, ER3, RP0, RP1, RP2, TD and WD models. For a traversable wormhole with $l^*=3$, the mechanism of HFQPO can be interpreted by the ER1, ER3, RP0, RP1, RP2, TD and WD models. Moreover, we observed that for the same HFQPOs model, the limiting range of the spin parameter $\alpha^*$ increases with the increase of the parameter $l^*$., Comment: 18 pages, 6 figures

In the framework of the theory of general relativity, in order to obtain stable traversable wormholes, matter needs to violate the null energy condition. It is well known that the violation of the energy condition (EC) of matter leads to various physical problems. To address this issue, researchers have turned their attention to exploring modified theories of gravity, aiming to avoid the violation of ECs by introducing geometric terms. In this paper, within the framework of the $f(Q)$ modified gravitational theory, we investigate the effectiveness of ECs for matter in traversable wormholes. We examine the compliance of four types of energy conditions (weak energy condition, null energy condition, dominant energy condition, and strong energy condition) in the model by selecting a power-law model for $f(Q)$ and considering different shape functions $b(r)$. Our study reveals that for traversable wormholes realized through the $f(Q)$ modified gravity theory using the power-law model $f(Q)=a(-Q)^n$, all four types of ECs for matter can be satisfied. There is no need to introduce exotic matter (violating the null energy condition) or special matter (violating other energy conditions) artificially in the physics of wormholes., Comment: 18 pages, 5 figures

This paper reports on the development of a resource-efficient FPGA-based neural network regression model for potential applications in the future hardware muon trigger system of the ATLAS experiment at the Large Hadron Collider (LHC). Effective real-time selection of muon candidates is the cornerstone of the ATLAS physics programme. With the planned ATLAS upgrades for the High Luminosity LHC, an entirely new FPGA-based hardware muon trigger system will be installed that will process full muon detector data within a 10 ${\mu}s$ latency window. The large FPGA devices planned for this upgrade should have sufficient spare resources to allow deployment of machine learning methods for improving identification of muon candidates and searching for new exotic particles. Our neural network regression model promises to improve rejection of the dominant source of background trigger events in the central detector region, which are due to muon candidates with low transverse momenta. This model was implemented in FPGA using 157 digital signal processors and about 5,000 lookup tables. The simulated network latency and deadtime are 122 and 25 ns, respectively, when implemented in the FPGA device using a 320 MHz clock frequency. Two other FPGA implementations were also developed to study the impact of design choices on resource utilisation and latency. The performance parameters of our FPGA implementation are well within the requirements of the future muon trigger system, therefore opening a possibility for deploying machine learning methods for future data taking by the ATLAS experiment., Comment: 13 pages, 17 figures