Search Results (1,947)

We extend the Quantum Memory Matrix (QMM) framework, originally developed to reconcile quantum mechanics and general relativity by treating space–time as a dynamic information reservoir, to incorporate the full suite of Standard Model gauge interactions. In this discretized, Planck-scale formulation, each space–time cell possesses a finite-dimensional Hilbert space that acts as a local memory, or quantum imprint, for matter and gauge field configurations. We focus on embedding non-Abelian SU(3)c (quantum chromodynamics) and SU(2)L× U(1)Y (electroweak interactions) into QMM by constructing gauge-invariant imprint operators for quarks, gluons, electroweak bosons, and the Higgs mechanism. This unified approach naturally enforces unitarity by allowing black hole horizons, or any high-curvature region, to store and later retrieve quantum information about color and electroweak charges, thereby preserving subtle non-thermal correlations in evaporation processes. Moreover, the discretized nature of QMM imposes a Planck-scale cutoff, potentially taming UV divergences and modifying running couplings at trans-Planckian energies. We outline major challenges, such as the precise formulation of non-Abelian imprint operators and the integration of QMM with loop quantum gravity, as well as possible observational strategies—ranging from rare decay channels to primordial black hole evaporation spectra—that could provide indirect probes of this discrete, memory-based view of quantum gravity and the Standard Model. Full article

In this study, we present an exact solution to the Lindblad master equation describing the interaction of two quantized electromagnetic fields in a decaying cavity coupled to a thermal reservoir at a finite temperature. The solution is obtained using the superoperator technique, leveraging commutation relations to factorize the exponential of the Lindblad superoperators into a product of exponentials. To demonstrate the applicability of this approach, we analyze the dynamics of the system both analytically and numerically for two initial conditions: nonentangled and entangled coherent states, exploring their temporal evolution. Additionally, we employ entropy and quantum discord analysis to characterize quantum correlations and analyze the behavior of entanglement (or lack thereof) during the evolution. This comprehensive analysis provides valuable insights into the behavior of open quantum systems and their interaction with the environment. Full article

In recent years, optimization algorithms have developed rapidly, especially those which introduce quantum ideas, which perform excellently. Inspired by quantum thought, this paper proposes a quantum dynamics framework (QDF) which converts optimization problems into the problem of the constrained ground state of the quantum system and analyzes optimization algorithms by simulating the dynamic evolution process of physical optimization systems in the ground state. Potential energy equivalence and Taylor expansion are performed on the objective function to obtain the basic iterative operations of optimization algorithms. Furthermore, a quantum dynamics framework based on the quantum tunneling effect (QDF-TE) is proposed which adopts dynamic multiple group collaborative sampling to improve the quantum tunneling effect of the QDF, thereby increasing the population diversity and improving algorithm performance. The probability distribution of solutions can be visually observed through the evolution of the wave function, which also indicates that the QDF-TE can strengthen the tunneling effect. The QDF-TE was evaluated on the CEC 2017 test suite and shown to be competitive with other heuristic optimization algorithms. The experimental results reveal the effectiveness of introducing a quantum mechanism to analyze and improve optimization algorithms. Full article

We studied relaxation processes in heavily doped two-dimensional Dirac systems associated with electron scattering by acoustic and optical phonons and by static disorder. The frequency dependence of the real and imaginary parts of the relaxation function is calculated for different temperatures. The two-component low-frequency dynamical conductivity is found to be strongly dependent on temperature. At low temperatures, the imaginary part of the zero-frequency relaxation function and the DC resistivity are characterized by the scaling law aTx with the exponent x between 2.5 and 3. Full article

The Quantum Internet (QI) necessitates a complete revision of the classical protocol stack and the technologies used, whereas its operating principles depend on the physical laws governing quantum mechanics. Recent experiments demonstrate that Optical Fibers (OFs) allow connections only in urban areas. Therefore, a novel Quantum Satellite Backbone (QSB) composed of a considerable number of Quantum Satellite Repeaters (QSRs) deployed in Low Earth Orbit (LEO) would allow for the overcoming of typical OFs’ attenuation problems. Nevertheless, the dynamic nature of the scenario represents a challenge for novel satellite networks, making their design and management complicated. Therefore, we have designed an ad hoc QSB considering the interaction between Digital Twin (DT) and Software-Defined Networking (SDN). In addition to defining the system architecture, we present a DT monitoring protocol that allows efficient status recovery for the creation of multiple End-to-End (E2E) entanglement states. Moreover, we have evaluated the system performance by assessing the path monitoring and configuration time, the time required to establish the E2E entanglement, and the fidelity between a couple of Ground Stations (GSs) interconnected through the QSB, also conducting a deep analysis of the created temporal paths. Full article

The effective lifetime of ultra-cold atoms in specific quantum states plays a crucial role in studying interaction parameters within quantum systems. Measuring the effective lifetime of various quantum states within ultra-cold atoms is a fundamental task in quantum operations. In this paper, the effective lifetimes of the excited electronic states F=2,mF=−2, F=2,mF=−1, and F=2,mF=0 for a sodium atomic Bose–Einstein condensate (BEC) are investigated in both the optical dipole trap (ODT) and one-dimensional optical lattice. Through the analysis of experimental data, we demonstrate the significant advantage of lattice loading over the optical dipole trap in terms of atomic lifetimes. The results provide crucial insights into the temporal scales relevant for investigating the evolution of boson gases in optical lattices, facilitating the realization of quantum simulations pertaining to unique quantum phases, and providing an important experimental basis for the research of non-equilibrium dynamics between different spin states. Full article

Maintaining precise and robust control in robotic systems, particularly those with nonlinear dynamics and external disturbances, is a significant challenge in robotics. Sliding-mode control (SMC) is a widely used technique to tackle these issues; however, it is plagued by chattering and computational complexity, which limit its effectiveness in high-precision environments. This study aims to develop and assess a quantum-inspired sliding-mode control (QSMC) strategy to enhance the SMC’s robustness, precision, and computational efficiency, specifically in controlling a six-jointed articulated robotic arm. The methodology involves creating a comprehensive kinematic and dynamic model of the robot, followed by implementing both classic SMC and the proposed Q-SMC in a comparative way. The simulation results confirm that the Q-SMC method outperforms the classic SMC, particularly in reducing chattering, improving tracking accuracy, and decreasing energy consumption by approximately 3.79%. These findings suggest that the Q-SMC technique provides a promising alternative to classical control methods, with potential applications in tasks requiring high precision and efficient robotic manipulations. Full article

While billiard systems of various shapes have been used as paradigmatic model systems in the fields of nonlinear dynamics and quantum chaos, few studies have investigated anisotropic billiards. Motivated by the tremendous advances in using and controlling electronic and optical mesoscopic systems with bilayer graphene (BLG), representing an easily accessible anisotropic material for electrons when trigonal warping is present, we investigate billiards of various anisotropies and geometries using a trajectory-tracing approach founded on the concept of ray–wave correspondence. We find that the presence of anisotropy can change the billiards’ dynamics dramatically from its isotropic counterpart. It may induce chaotic and mixed dynamics in otherwise integrable systems and may stabilize originally unstable trajectories. We characterize the dynamics of anisotropic billiards in real and phase space using Lyapunov exponents and the Poincaré surface of section as phase space representation. Full article

We conducted a comprehensive study of the non-equilibrium dynamics of Cooper pair breaking, quasiparticle (QP) generation, and relaxation in niobium (Nb) cut from superconducting radio-frequency (SRF) cavities, as well as various Nb resonator films from transmon qubits. Using ultrafast pump–probe spectroscopy, we were able to isolate the superconducting coherence and pair-breaking responses. Our results reveal both similarities and notable differences in the temperature- and magnetic-field-dependent dynamics of the SRF cavity and thin-film resonator samples. Moreover, femtosecond-resolved QP generation and relaxation under an applied magnetic field reveals a clear correlation between non-equilibrium QPs and the quality factor of resonators fabricated by using different deposition methods, such as DC sputtering and high-power impulse magnetron sputtering. These findings highlight the pivotal influence of fabrication techniques on the coherence and performance of Nb-based quantum devices, which are vital for applications in superconducting qubits and high-energy superconducting radio-frequency applications. Full article

Mesoscopic billiard systems for electrons and light, realized as quantum dots or optical microcavities, have enriched the fields of quantum chaos and nonlinear dynamics not only by enlarging the class of model systems, but also by providing access to their experimental realization. Here, we add yet another system class, two-dimensional billiards with anisotropies. One example is the anisotropic dispersion relation relevant in bilayer graphene known as trigonal warping, and another is the birefringent closed optical disk cavity. We demonstrate that the established concept of ray–wave correspondence also provides useful insight for anisotropic billiard systems. First, we approach the dynamics of the anisotropic disk from the ray-tracing side that takes the anisotropy in momentum space into account, based on the non-spherical index ellipsoid. Second, we use transformation optics to solve the wave problem and find the resonances to be those of the isotropic elliptical cavity. We illustrate ray–wave correspondence and mark differences in the description of optical and electronic anisotropic systems. Full article

The accuracy of a space manipulator’s end trajectory and stability is significantly affected by joint clearance. Aiming to improve the prediction accuracy of vibration caused by clearance, a dynamic clearance modeling method is developed based on parameter identification in this study. First, a dynamic model framework for manipulator arms is established based on the Hamilton principle and hypothetical mode method with time-variation damping. Then, a multi-resolution identification is performed for identifying the instantaneous frequency and damping ratio to estimate stiffness and damping by the sensors. The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. Finally, a case study is conducted to verify the presented model. In comparison with the initial dynamic model based on constant damping, the modal assurance criterion (MAC) of the proposed improved model based on time-variation damping is improved by 43.97%, the mean relative error (MRE) of the frequency response function (FRF) is reduced by 32.6%, and the root mean square error (RMSE) is reduced by 18.19%. The comparison results indicate the advantages of the proposed model. This modeling method could be used for vibration prediction in control systems for space manipulators to improve control accuracy. Full article

This study presents a method for the active control of a follow-up lower extremity exoskeleton rehabilitation robot (LEERR) based on human motion intention recognition. Initially, to effectively support body weight and compensate for the vertical movement of the human center of mass, a vision-driven follow-and-track control strategy is proposed. Subsequently, an algorithm for recognizing human motion intentions based on machine learning is proposed for human-robot collaboration tasks. A muscle–machine interface is constructed using a bi-directional long short-term memory (BiLSTM) network, which decodes multichannel surface electromyography (sEMG) signals into flexion and extension angles of the hip and knee joints in the sagittal plane. The hyperparameters of the BiLSTM network are optimized using the quantum-behaved particle swarm optimization (QPSO) algorithm, resulting in a QPSO-BiLSTM hybrid model that enables continuous real-time estimation of human motion intentions. Further, to address the uncertain nonlinear dynamics of the wearer-exoskeleton robot system, a dual radial basis function neural network adaptive sliding mode Controller (DRBFNNASMC) is designed to generate control torques, thereby enabling the precise tracking of motion trajectories generated by the muscle–machine interface. Experimental results indicate that the follow-up-assisted frame can accurately track human motion trajectories. The QPSO-BiLSTM network outperforms traditional BiLSTM and PSO-BiLSTM networks in predicting continuous lower limb motion, while the DRBFNNASMC controller demonstrates superior gait tracking performance compared to the fuzzy compensated adaptive sliding mode control (FCASMC) algorithm and the traditional proportional–integral–derivative (PID) control algorithm. Full article

(1) Background: One of the greatest challenges students face when studying quantum mechanics is the lack of daily experience and intuition about its concepts. This article introduces a holistic activity designed to present some foundational ideas of quantum mechanics in a new pedagogical approach to enhance students’ motivation. Using real open data from CERN, the activity connects classical concepts of dynamics and electromagnetism to their quantum counterparts, emphasizing both their similarities and differences. Teaching physics must consider the way the brain learns. That is why the activity is based on observed neuroscientific principles of physics learning. The approach maintains the rigor and precision required for these abstract concepts. (2) Methods: To evaluate the activity’s impact by gender, intrinsic motivation was assessed using a Likert-type scale with 81 undergraduate students from fields including artificial intelligence systems engineering, computer engineering, mathematical engineering, and architecture. (3) Results: a Mann–Whitney U test analysis indicates the activity significantly enhances students’ intrinsic motivation to study quantum mechanics, with improvements observed in both male and female students. (4) Conclusions: This result highlights the potential of the activity to promote greater interest in physics, both in men and women, since no significant differences have been observed between both samples. Full article

The fifth generation (5G) of wireless communication is in its finalization stage and has received favorable reception in many nations. However, research is now geared towards the anticipated sixth-generation (6G) wireless network. The new 6G promises even more severe performance criteria than the current 5G generation. New sophisticated technologies and paradigms are expected to be incorporated into the 6G network designs and procedures to meet the ever-dynamic user needs and standards. These 6G-enabling technologies include digital twin (DT), intelligent reflecting surface (IRS), visible light communication (VLC), quantum computing (QC), blockchain, unmanned aerial vehicles (UAVs), and non-orthogonal multiple access (NOMA), among others. Optimal network performance requires that machine learning (ML) techniques be integrated over the 6G wireless network to provide solutions to highly complex networking problems, massive users, high overhead, and computational complexity. Consequently, we have provided a state-of-the-art overview of wireless network generations leading to the future 6G, and huge emphases have been laid on ML’s role in optimization applications for different enabling 6G technologies. Several key performance indicators for the different application scenarios have been highlighted. ML has proved to significantly improve the performance of the existing 6G-enabling technologies, and choosing the appropriate approach can ultimately yield optimal results. Full article

Nuclear quantum effects play a significant role in the dissociation dynamics of HCl ions during collisions with the (H₂O)₄₉ ice cluster. These effects become particularly important when analyzing proton transfer, tunneling, and zero-point energy contributions during the dissociation process. In this study, we investigate the dissociation behavior of HCl when colliding with the (H₂O)₄₉ ice cluster, focusing on the influence of the nuclear quantum effects on the proton transfer mechanism, ionic dissociation rates, and subsequent solvation dynamics. Through a combination of classical molecular dynamics (MD) and ring-polymer molecular dynamics (RPMD) simulations, we explore how quantum fluctuations in the proton’s position alter the dissociation pathway of HCl. The inclusion of nuclear quantum effects reveals enhanced proton mobility, leading to differences in dissociation behavior compared to classical simulations. Our findings indicate that nuclear quantum effects significantly affect the dissociation dynamics, with the proton more readily transferring to the hydrogen-bond network in the (H₂O)₄₉ ice cluster. This study provides insights into the quantum mechanical nature of ionic dissociation in hydrogen-bonded systems and highlights the importance of incorporating nuclear quantum effects for accurate modeling of proton transfer processes in complex environments. Full article