As Android has become the most widely used mobile operating system, it has also become a primary target for cyberattacks, leading to a continuous surge in malicious applications with increasingly complex behaviors. Traditional malware detection approaches struggle to maintain stability and robustness against such dynamic threats. To address these issues, an Android malicious application detection model ADMFW-MalDet based on adversarial distillation and multimodal feature weighting is proposed. Through the multimodal feature weighting and adversarial distillation framework optimized by quantum particle swarm optimization, the teacher-student adversarial distillation fanatic is adopted to enhance the robustness of the model. Experiments were conducted on the Drebin dataset and a high evaluation rate was achieved through five evaluations, and significantly enhancing robustness and adaptability. These results not only validate the effectiveness of the adversarial distillation and multimodal feature weighting strategies but also provide a new paradigm for constructing adaptive and resilient Android malware detection systems.

We discuss the problem of singularity crossing in isotropic and anisotropic universes. First, we consider the so called soft or sudden singularities and, in particular the Big Brake singularity. This singularity was discovered in a particular tachyon cosmological model and it was also shown that this kind of singularity arises in a very simple model, where matter is represented by the anti-Chaplygin gas. At the the encounter with the Big Brake singularity the universe has a finite scale factor, a vanishing expansion velocity and an infinite deceleration. The Christoffel symbols also vanish the geodesics are regular and the universe easily can cross such a singularity. Adding to the anti-Chaplygin gas or to the tachyon matter some amount of dust we see that the Big Brake singularity is substituted by a more general soft singularity, its crossing implies a certain transformation of the properties of matter. The crossing of the Big Bang – Big Crunch singularity is more counter-intuitive. However, we describe it for both Friedmann universe and Bianchi-I universe using the field reparametrization of the variables present in models (a scalar field and the metric). Then we consider the Wheeler-DeWitt equation and show that the probability for the universe to find itself at the soft singularity is different from zero, while the encounter with the Big Bang – Big Crunch singularity is suppressed. We analyze the possibility to construct Fock spaces of quantum particles at the vicinity of different cosmological singularities and see when it is possible and when it is not possible. Finally, we present some attempts to develop general approach to the connection between the field reparametrization and the elimination of singularities.

In this paper, the Economic and Environmental Dispatch (EED) problem in wind-powered power systems is solved using the Quantum Grey Wolf Optimizer (QGWO), Quantum Particle Swarm Optimizer (QPSO), and Quantum Flower Pollination Algorithm (QFPA) metaheuristics. The EED is a multi-objective problem that aims to minimize two conflicting objectives: generation costs and pollutant emissions. The cost of wind power was modeled through the composition of three components: overestimation, underestimation, and direct costs. The quantum metaheuristics were compared using statistical indices. The simulations were carried out in an electrical system composed of 6 generators. The QFPA algorithm performed better, providing better-quality solutions compared to those obtained by the other quantum metaheuristics.

Emergent viscous hydrodynamics from a single quantum particle

Self-Interacting Quantum Particles and the Dirac Delta Potential

Quantum groups have been widely explored as a tool to encode possible nontrivial generalisations of reference frame transformations, relevant in quantum gravity. In quantum information, it was found that the reference frames can be associated to quantum particles, leading to quantum reference frames transformations. The connection between these two frameworks is still unexplored, but if clarified it will lead to a more profound understanding of symmetries in quantum mechanics and quantum gravity. Here, we establish a correspondence between quantum reference frame transformations and transformations generated by a quantum deformation of the Galilei group with commutative time, taken at first order in the quantum deformation parameter. This is found once the quantum group noncommutative transformation parameters are represented on the phase space of a quantum particle, and upon setting the quantum deformation parameter to be proportional to the inverse of the mass of the particle serving as the quantum reference frame. These results allow us to show that quantum reference frame transformations are physically relevant when the state of the quantum reference frame is in a quantum superposition of semiclassical states. We conjecture that the all-order quantum Galilei group describes quantum reference frame transformations between more general quantum states of the quantum reference frame.

Flocks of animals represent a prominent archetype of collective behavior in the macroscopic classical world, where the constituents, such as birds, concertedly perform motions and actions as if being one single entity. Here, we address the so far open question of whether flocks can also form in the microscopic world at the quantum level. For that purpose, we introduce the concept of active quantum matter by formulating a class of models of active quantum particles on a one-dimensional lattice. We provide both analytical and large-scale numerical evidence that these systems can give rise to quantum flocks. A key finding is that these quantum flocks exhibit distinct quantum properties by developing strong quantum coherence over long distances. We propose that quantum flocks could be experimentally observed in Rydberg atom arrays.

Abstract Stimulated Raman scattering (SRS) is highly relevant to quantum memories
involving Raman system. Using quantum Langevin equations with complete noise
operators couples to the quantum field propagation equation we present a
general theory of SRS for moving quantum particles where quantum Stokes
pulse couples to both transitions (m1 and m3) while an arbitrary laser pulses
couple to only one (m1) transition. Our coupled equations contain dynamical
ac Stark shift due to laser pulses, complete quantum noise operators and atomic coherences corresponding to all possible three transitions (not only the ground state coherence), quantum mechanical microscopic expressions for linear and nonlinear
interactions with nonlocal (memory) or temporal dispersion effects. We
obtain analytical solution of the quantum Stokes field in laboratory
spacetime with generalized quantum noise operators that include all initial atomic coherences and arbitrary initial
and boundary quantum fields, valid for arbitrary laser pulses. The general
solution provides a complete physical picture, composed of basically two
parts: above and below the light line, t=z/c. This robust framework offers a
powerful tool for optimizing Raman-based quantum information processes,
particularly for modeling the spatial-temporal dynamics of quantum Stokes
pulses in storage and retrieval stages of quantum memory.

Interface layout design of agricultural harvester based on analytic network process and quantum particle swarm optimization

Real-time quality monitoring during oyster cold chain transportation is a critical component in ensuring food safety. Addressing the issues of high redundancy and insufficient environmental adaptability in existing electronic nose systems, this study proposes a multi-algorithm collaborative optimization strategy for sensor array optimization. The system integrates ten gas sensors (TGS series, MQ series), employing Random Forest (RFA), Simulated Annealing (SA), and Genetic Quantum Particle Swarm Optimization (GA-QPSO) for sensor selection. KNN combined with K-means analysis validates the optimization outcomes. Under cold chain environments at 4 °C, 12 °C, 20 °C, and 28 °C, a multidimensional dataset was constructed by extracting global variables using feature correlation functions. Experiments demonstrate that the optimized sensor count decreases from 10 to 5–6 units while maintaining recognition accuracy above 95%, with redundancy decreased by over 40%. This multi-algorithm collaborative optimization effectively balances sensor array recognition precision, resource efficiency, and environmental adaptability, providing an intelligent, high-precision technical solution for oyster cold chain monitoring.

Abstract In quantum mechanics, the time evolution of particles is given by the Schrödinger equation. It is valid in a nonrelativistic regime where the interactions with the particle can be modelled by a potential and quantised fields are not required. This has been verified in countless experiments when the interaction is of electromagnetic origin, but also corrections due to the quantised field are readily observed. When the interaction is due to gravity, then one cannot expect to see effects of the quantised field in current-technology Earth-bound experiments. However, this does not yet guarantee that in the accessible regime, the time evolution is accurately given by the Schrödinger equation. Here we propose to measure the effects of an asymmetric mass configuration on a quantum particle in an interferometer. For this setup we show that with parameters within experimental reach, one can be sensitive to possible deviations from the Schrödinger equation, beyond the already verified lowest-order regime. Performing this experiment will hence directly test the nonclassical behaviour of a quantum particle in the gravitational field.

Abstract Efficient scheduling of vehicles and drivers is crucial for airport bus services. Traditional methods face challenges such as separate services for commuter and shuttle trips and fixed vehicle‐driver pairings, leading to resource wastage and uneven driver workloads. This study addresses a multi‐objective optimization problem for scheduling airport buses and drivers, using time windows to reduce the chance of passengers missing the bus due to delays like baggage claim. It promotes cooperative scheduling across units and supports flexible vehicle‐driver pairings, aiming to improve utilization and balance workloads. We developed a mixed integer linear programming model and designed an improved hybrid quantum particle swarm optimization algorithm to achieve high‐quality solutions efficiently. The performance of this algorithm was benchmarked against the GAMS solver and other existing algorithms. Applied to a real‐world scenario at Xianyang Airport in China, our approach significantly reduced costs and balanced workloads among drivers, underscoring its benefits for airport bus operations.

With the increasing sophistication of electromagnetic environments in modern combat platforms, joint sensing and communication (JSAC) technology has emerged as a critical research frontier. Among these, JSAC waveform design plays a crucial role, as it enables the simultaneous achievement of both sensing and communication functions using the same transmit waveform. This paper presents a novel waveform design for a multi-input multi-output (MIMO) JSAC system. The proposed design leverages orthogonal frequency division multiplexing (OFDM) to reduce signal interference through low cross-correlation characteristics. Linear frequency modulation (LFM) is used as the carrier waveform, effectively narrowing the main lobe width of the autocorrelation function. We introduce phase perturbation into binary phase shift keying (BPSK) signals to enhance waveform performance, formulating the resulting problem as a high-dimensional, non-convex optimization challenge. To address this, we propose a hybrid optimization algorithm QGPV combining a quantum genetic algorithm (QGA), quantum particle swarm optimization (QPSO), and variable neighborhood search (VNS). The simulation results demonstrate that the proposed algorithm achieves superior performance compared with several typical methods. Notably, the peak sidelobe level (PSL) can be suppressed to around −21 dB with five iterations, highlighting the efficiency of the optimization process. These results validate the effectiveness of the proposed approach, showing improved waveform characteristics with an acceptable trade-off in communication performance.

Walkers are oil drops surfing on a vibrated oil surface and driven by their self-generated capillary waves. Since some of the first measurements on walkers seemingly showed quantum-like behavior, walkers have been considered a model system for a hydrodynamic pilot-wave system. An early experiment showed that the passage of the walker over a submerged barrier resulted in what was coined "unpredictable walker tunneling" in analogy with quantum tunneling. Together with the double slit experiment, tunneling is one of the fundamental phenomena that show the probabilistic nature of quantum mechanics. A later experiment that refined the measurement of position and timing of the walker narrowed the region where transmission changed from 0 to 1 by a factor 10 but still found "unpredictable tunneling." However, at a certain small distance close to the rim of the barrier, predictability sets in, and separation between reflected and transmitted trajectories is observed. After careful analysis of identified noise sources, the authors find that neither noise nor insufficient knowledge of initial conditions alone could explain the unpredictability. They therefore conclude that it is more likely due to changes in the drop's vertical dynamics arising when it interacts with the barrier. They also analyzed a quantum particle impinging on a barrier by step-wise collapsing the wave function and showed a similar behavior for this. Here we revisit the "tunneling" of walkers. Enforcing a stringent control of temperature in all aspects of the experiment results in the observation of a much sharper transition, much like that of a classical system, reducing the unpredictability by another factor of 10. Apart from varying the velocity of the walker by changing the drop size, we varied it by changing the amplitude of the drive. We furthermore found that a micron-size change in fluid height changes transmission from 0 to 1. The observed sharpness of the transition suggests that in a noise-free environment the transition would be truly abrupt, at least in the regions of phase-space for the drop that have been investigated so far.

The classification of the unitary irreducible representations of symmetry groups is a cornerstone of modern quantum physics, as it provides the fundamental building blocks for constructing the Hilbert spaces of theories admitting these symmetries. In the context of gravitational theories, several arguments point toward the existence of a universal symmetry group associated with corners, whose structure is the same for every diffeomorphism-invariant theory in any dimension. Recently, the representations of the maximal central extension of this group in the two-dimensional case have been classified using purely algebraic techniques. In this work, we present a complementary and independent derivation based on Kirillov’s orbit method. We study the coadjoint orbits of the group SL ( 2 , R ) ˜ ⋉ H 3 , where H 3 is the Heisenberg group of a quantum particle in one dimension. Our main result is that, despite the non-Abelian nature of the normal subgroup in the semidirect product, these orbits admit a simple description. In a coordinate system associated with modified Lie algebra generators, the orbits factorize into a product of coadjoint orbits of SL ( 2 , R ) and H 3 . The subsequent geometric quantization of these factorized orbits successfully reproduces the known representations.

Abstract Polyfluorenes and their derivatives containing tetraphenylethenes and nitro‐substituted tetraphenylethenes have been successfully synthesized by the Suzuki–Miyaura cross‐coupling reaction. The presence of nitrated side chains plays an important role in controlling photophysical and electrochemical properties. In addition, the introduction of benzothiadiazole units into the polymer backbone not only lowers bandgap energy but also reduces LUMO energy relative to vacuum. The impacts of solvation on quantum yields and particle sizes were explored by adjusting water fractions. Polyfluorenes with nitro‐substituted tetraphenylethenes show aggregation‐induced emission characteristics. Despite a low quantum yield of the polymers with nitro‐substituted tetraphenylethenes, a deeper LUMO level observed in these polymers is useful for the detection of picric acid. The polymers with tetraphenylethene substituents are more sensitive for the detection of aniline due to an appropriate HOMO level. © 2025 Society of Chemical Industry.

Abstract This paper introduces a rotational quantum particle swarm optimizer (RQPSO) that updates particles via quantum rotation–gate dynamics on a compact phase representation. Real-valued amplitudes decoded from phases are mapped feasibly by construction into the decision space, removing the need for bound repair. Lightweight π-flip perturbations and brief stagnation-triggered reseeding sustain diversity, and a short local polish consolidates the incumbent near termination. RQPSO is benchmarked against PSO, QPSO, GWO, MA, jDE, and CMA-ES under a common protocol of 3000 function evaluations with 30 independent runs per problem. Reporting uses median [IQR] as the primary statistic with Friedman/Nemenyi global tests and Holm-corrected Wilcoxon pairwise tests; effect sizes are summarized by Cliff’s δ. Experiments cover 23 classical functions and 10 CEC-2019 functions. On the classical suite, RQPSO attains the best or tied-best median on a majority of functions and achieves a leading global rank under the fixed budget. On CEC-2019, it records three best medians (including one tie) and a top mean rank; post-hoc tests show significant gains over MA and jDE and broadly comparable performance to PSO, QPSO, GWO, and CMA-ES. A combined economic–emission dispatch (CEED) study on a six-unit system with cubic cost and emission models further demonstrates budget-efficient performance. The rotational-gate RQPSO attains the lowest mean operating cost and the smallest dispersion at all loads versus PSO and QPSO. A percentage-recovery repair enforces generator limits and power balance without penalty functions by proportionally rescaling outputs. Together, the rotation-gate updates, feasibility-preserving decoding, and proportional repair provide a robust alternative to classical swarms for both benchmark and power-system optimization under tight evaluation budgets.

ABSTRACT The presence of sulfonamide antibiotic residues, such as sulfadiazine (SDZ), in aquatic ecosystems presents significant ecological risks, including the emergence of antibiotic resistance. Therefore, the development of precise and sensitive detection methods is of paramount importance. This study focuses on the design of a highly sensitive sensor for detecting SDZ by exploring the effects of quantum dot (QD) emission wavelength, particle size, and surface characteristics on sensor performance. Green, yellow, and red‐emitting cadmium telluride (CdTe) QDs were synthesized through systematic adjustments in the molar ratio of Cd 2+ to Te, reflux time, and solution pH. These QDs were subsequently incorporated into silica nanoparticles (NH 2 ‐SiO 2 ) via molecular imprinting technology to fabricate a multicolor fluorescent imprinted sensor. The results indicated that the sensor incorporating green‐emitting QDs (MIPs@g‐QDs@SiO 2 ) exhibited the best performance, with a detection limit of 10.53 nM, a fluorescence quenching constant of , and a linear detection range of 10–60 μmol·L −1 . In comparison, the yellow and red‐emitting QD sensors displayed higher detection limits of 30.58 and 68.52 nM, with quenching constants of and , respectively. The sensitivity of the green‐emitting QD sensor is attributed to its smaller particle size, which results in a larger specific surface area and enhanced surface effects, thereby increasing the fluorescence intensity range. Moreover, fluorescence quenching and selective adsorption experiments demonstrated that MIPs@g‐QDs@SiO 2 exhibited excellent selective adsorption properties for SDZ, contributing to its enhanced fluorescent response.

An adaptive strategy quantum particle swarm optimization method based on intuitionistic fuzzy entropy and evolutionary game theory

The multipolar spherical vortices of any degree ℓ, which are exact solutions to the classical nonlinear equation of motion for a perfect fluid, exhibit two possible polarizations determined by the sign of the radial wavenumber k. We propose that the spin-up and spin-down states of spin-1/2 quantum particles correspond to these two classical polarization states of ℓ=1 vortices. In the presence of a homogeneous background vorticity field 2ν, these vortices precess around the axis defined by ν and propagate with a drift velocity equal to 2ν/k. This drift enables the experimental separation of vortices with opposite polarizations. It is shown that the correlation between measurements of the drift velocity 2ν/k for pairs of vortices, as observed by two independent observers, can lead to violations of the Clauser–Horne-Shimony–Holt inequality—suggesting a classical physics explanation of quantum entanglement.