Low-dimensional Systems Research Articles

Dynamics of the Davydov’s soliton in external oscillating magnetic field

The influence of an external oscillating in time magnetic field on the dynamics of the Davydov’s soliton is studied. It is shown that soliton parameters depend on the amplitude and frequency of the magnetic field, as well as on the field orientation with respect to the molecular chain axis. Electron dynamics in the parallel magnetic field is a composition of the “free” soliton coherent propagation along the molecular chain and oscillatory movement in the transverse direction. The latter is described by the functions of the harmonic oscillator with the cyclotron frequency depending on the field frequency. In a perpendicular field the soliton dynamics is a superposition of (i) the free electron plane wave in the plane perpendicular to the molecular chain, and (ii) propagation along the chain which is described by the modified Nonlinear Schrödinger equation with an extra term depending on the field. This equation is solved using the nonlinear perturbation theory. It is shown that the soliton velocity and phase are given by expressions which include the terms oscillating in time with the frequency of the main harmonic, given by the external field frequency, and higher multiple harmonics. Such complex effects of external time-depending magnetic fields on the dynamics of solitons modify the charge transport in low-dimensional molecular systems, which in its turn, can affect the functioning of the devices based on such compounds. These results suggest also the physical mechanism of therapeutic effects of oscillating magnetic fields, based on the field influence on the dynamics of solitons which provide charge transport through biological macromolecules in the redox processes.

Continuous symmetry breaking of low-dimensional systems driven by inhomogeneous oscillatory driving forces.

The driving forces of chiral active particles and deformations of cells are often modeled by spatially inhomogeneous but temporally periodic driving forces. Such inhomogeneous oscillatory driving forces have only recently been proposed in the context of active matter, and their effects on the systems are not yet fully understood. In this work, we theoretically study the impact of spatially inhomogeneous oscillatory driving forces on continuous symmetry breaking. We first analyze the linear model for the soft modes in the ordered phase to derive the lower critical dimension of the model, and then analyze the spherical model to investigate more detailed phase behaviors. Interestingly, our analysis reveals that symmetry breaking occurs even in one and two dimensions, where the Hohenberg-Mermin-Wagner theorem prohibits continuous symmetry breaking in equilibrium. Furthermore, fluctuations of conserved quantities, such as density, are anomalously suppressed in the long-wavelength, i.e., show hyperuniformity.

Simulating thermodynamic properties of dinuclear metal complexes using Variational Quantum Algorithms

Abstract In this paper, we investigate the use of variational quantum algorithms for simulating the thermodynamic properties of dinuclear metal complexes. Our study highlights the potential of quantum computing to transform advanced simulations and provide insights into the physical behavior of quantum systems. The results demonstrate the effectiveness of variational quantum algorithms in simulating thermal states and exploring the thermodynamic properties of low-dimensional molecular magnetic systems. The findings from this research contribute to broadening our understanding of quantum systems and pave the way for future advancements in materials science through quantum computing.

Quantitative Disorder Effects in Low-Dimensional Spin Systems

The Imry–Ma phenomenon, predicted in 1975 by Imry and Ma and rigorously established in 1989 by Aizenman and Wehr, states that first-order phase transitions of low-dimensional spin systems are ‘rounded’ by the addition of a quenched random field coupled to the quantity undergoing the transition. The phenomenon applies to a wide class of spin systems in dimensions d≤2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$d\\le 2$$\\end{document} and to spin systems possessing a continuous symmetry in dimensions d≤4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$d\\le 4$$\\end{document}. This work provides quantitative estimates for the Imry–Ma phenomenon: in a cubic domain of side length L, we study the effect of the boundary conditions on the spatial and thermal average of the quantity coupled to the random field. We show that the boundary effect diminishes at least as fast as an inverse power of loglogL\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\log \\log L$$\\end{document} in general two-dimensional spin systems. For systems possessing a continuous symmetry, we show that the boundary effect diminishes at least as fast as an inverse power of L in two and three dimensions and at least as fast as an inverse power of loglogL\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\log \\log L$$\\end{document} in four dimensions. Finally, we establish a partial uniqueness results for translation-covariant Gibbs states, and prove that, for almost every realization of the random field, all such states must agree on the thermally-averaged value of the quantity coupled to the random field. Specific models of interest for the obtained results include the random-field q-state Potts model, the Edwards-Anderson spin glass model, and the random-field spin O(n) models.

Single droplet or bubble and its stability: Kinetic theory and dynamical system approaches.

Steady solutions of a single droplet or bubble in the van der Waals fluid are investigated on the basis of the kinetic model equationthat has been recently proposed by Miyauchi etal. [Gas Dynamics with Applications in Industry and Life Sciences (Springer, Cham, 2023), pp. 19-39]. Under the thermal equilibrium condition and isotropic assumption with respect to the origin of the coordinates, the kinetic equationis reduced to an ordinary differential equationfor the density, which can be regarded as a low-dimensional dynamical system. The possible density distribution is studied as a flow in the low-dimensional phase space. It is clarified that a single droplet or bubble can be understood as a flow that goes into a fixed point and that the flow is qualitatively different in the unstable and metastable parameter regions. The features of the obtained density distributions in individual regions are also clarified. Finally, the stability of those solutions is studied by direct numerical experiments of the kinetic equation.

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys.

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Study of Electronic and Optical Properties of Low-Dimensional Nanosystems by First Principles Calculations

The development of new techniques for material manipulation at the nanoscale, as well as advanced numerical tools for material design, has opened up new prospects in the engineering of novel low-dimensional systems with properties specifically designed for applications in different fields, from photonics to energy conversion. Zero-, one-, and two-dimensional nanosystems show unique electronic, optical, and transport properties that can be tuned, for instance, by size reduction, passivation, and doping. In this talk, we discuss ab-initio results obtained in the study of structural, electronic, and optical properties of low-dimensional systems, in particular focusing on silicon, germanium, and silicon/germanium nanostructures. The analysis of mechanisms that can be exploited to tune Auger recombination and carrier multiplication processes, as well as of those that affect the formation of the band offset (Type I and Type II) at the nanoscale, will be discussed. At the end, effects induced by anion ordering on electronic and optical properties of metal oxynitrides will be analyzed.

(Invited) Optical Excitations and Growth in Layered Organic Metal Halide Semiconductors

Hybrid organic metal halides, such as CH3NH3PbI3, have garnered attention because they are earth-abundant, solution-processable materials that can be used to form solar cells with high power conversion efficiency (>20%). There are significant questions about the unusual electronic properties of this class of materials because of the coupling between excitations and the lattice. We will present our work investigating the optoelectronic properties of layered organic metal halide systems and the relationship to structure and growth conditions. We will discuss the nature of optical excitations in layered compounds of the class R2PbX4 where R is an organic cation and X is a halide. These systems show signatures of unusually strong optical frequency magnetic dipole transitions that can be understood through self-trapped exciton formation. We will then discuss how mechanical strain during growth influences broad photoluminescence in a model layered system based on the large cation ethylammonium (EA) with the structure (EA)2(EA)n-1PbnBr3n+1. In this system the emission is strongly impacted by growth-induced strain in thin films quantified using X-ray scattering. Our results suggest that broad emission, relevant for LEDs, can be tuned in thin films. Recent work on how growth impacts the behavior of low dimensional system will also be presented.

Parsimonious streamflow forecasting system based on a dynamical systems approach

Operational hydrologic forecasting often relies on the use of physically-based computer models at the catchment scale. However, our understanding of streamflow generation is still evolving and incomplete, and oftentimes linearization assumptions must be made to make physically-based hydrologic and hydraulic models tractable. In addition to uncertainty in the physical runoff-generation mechanisms, many physically-based approaches do not formally assimilate observed streamflow data. Streamflow is their output, deterministically simulated from observed inputs (such as precipitation, temperature, etc.). Divergences between observed and simulated streamflow may be due to input uncertainty, calibration issues, or problems with the inherent physical process representation. Thus, data-driven approaches that are responsive to observed streamflow by including assimilation as an essential feature are promising in operational hydrology. In this study, we use a novel forcings-weighted k-Nearest Neighbor (kNN) nonlinear timeseries forecasting method developed in the context of the modeling of nonlinear dynamical systems. The rainfall-runoff transform is assumed to be a low-dimensional system of (unknown) nonlinear differential equations; the deterministic state space is reconstructed based on the streamflow timeseries; and a forecast is generated based on how “similar” the current hydrograph is to historical events encoded within the reconstructed state space, weighted by the similarity of forcings. We tested the model in a long-term test period with no real data assimilation, and in forecast mode with daily data assimilation. When used for forecasting, we also illustrate two different uncertainty quantification approaches: forecast postprocessing and internal-to-the-model ensemble generation. The method is conceptually and computationally simple, but offers promising results. We tested the model in three different scenarios. First, investigating a long-term test period with no real data assimilation in a rainfall-dominated research catchment at the Coweeta Hydrologic Lab in North Carolina, USA. The simulation exhibited an NSE of 0.73. Next, we included a conceptual snowmelt model to drive the long term simulation and studied boreal-temperate transition zone catchments in northern Minnesota, USA. The study area included a small (<0.1 mi2) reference research catchment at the Marcell Experimental Forest, and a large river basin (>19 k mi2) with incomplete forcings information. The kNN method yielded NSEs from 0.28 to 0.50. And finally, we conducted a pseudo-operational forecasting test for a large river basin in northern Minnesota, USA with a focus on performance forecasting a flood-of-record on the Rainy River. The test involved reforecasting, data assimilation, and implementation of ensemble and postprocessing bias correction uncertainty-quantification schemes. The technique demonstrated good performance capturing a flood-of-record on a large catchment (−5.7 to −3.3 % crest error with 1-day of lead time). For the entire test period in forecast mode, the 1-day lead time NSE was 0.99, going down to 0.79 for the 7-day lead time, showing its general utility as an operational forecasting tool.

Stability of lower dimensional counter-rotating thin-shell wormholes with scalar hair

The motivation for constructing a thin-shell wormhole from a (2+1)-dimensional rotating black hole arises from the desire to study the effects of a nonminimally coupled scalar field in this particular spacetime. By investigating the behavior of such a field in the presence of rotation, we can gain insights into the interplay between gravity and scalar fields in lower-dimensional systems. Additionally, this construction allows us to explore potential connections between black hole physics and exotic phenomena like traversable wormholes. The radial perturbation around the equilibrium throat radius is considered to explore the stable configuration for specific values of physical parameters. Then, the equations of state, specifically the phantom-like and generalized Chaplygin gas model for exotic matter is used to conduct an extensive investigation into the stability of the counter-rotating thin-shell wormholes. Our results show that the presence of a scalar field enhances the stability of the counter-rotating thin-shell wormholes.

Spatial analysis of multi-frequency SAW beams excited by slanted IDTs on ZnO-SiC heterostructures

Slanted (or fan-shaped) interdigital transducers (IDTs) with broadband response allow the selective excitation of surface acoustic waves (SAWs) with narrow beam widths and pathways controlled by the excitation frequency. Such SAW-based spatial and frequency control is important for applications in microfluidics, as well as in emerging applications in semiconductor nanostructures. In this contribution, we generate both Rayleigh and Sezawa modes with slanted IDTs on a 4H-SiC substrate coated with a piezoelectric ZnO film. We directly measure the phase wavefronts of narrow SAW beams in the 1200–1260 MHz frequency bandwidth using high-resolution ( <1μm ) optical interferometry, and discuss the mechanisms that directly affect the propagation direction and phase profiles of the SAW beams. The combination of multimodal and multi-frequency SAW delay lines provides rich opportunities for SAW-based control of low-dimensional systems, such as electrons in epitaxial graphene or spin centers near the surface of the SiC substrates.

Study of Size Effect on Ni60Nb40 Amorphous Particles and Thin Films by Molecular Dynamic Simulations

Ni60Nb40 amorphous particles (APs) and amorphous thin films (ATFs) with various sizes were investigated by molecular dynamic simulations. It is revealed that sample size has effects on both Ni60Nb40 APs and ATFs composed of shell or surface and core components. Ni60Nb40 APs have an average bond length of 2.57 Å with major fivefold-symmetry atomic packing and low bond-orientation orders of Q6 and Q4 in both core and shell components. Ni atoms in Ni60Nb40 APs and ATFs prefer to segregate to the shell and surface regions, respectively. Atomic packing structure differences between various-sized Ni60Nb40 APs and ATFs affect their glass transition temperatures Tg, i.e., Tg decreases as the particle size or the film thickness decreases in Ni60Nb40 APs and ATFs, respectively. Our obtained results for Ni60Nb40 APs and ATFs clearly reveal a size effect on atomic packing and glass transition temperature in low-dimensional metallic glass systems.

The Dependency of Friction on Temperature and Sliding Velocity in Low Dimensional Systems with Different Atom Electronegativity

The Dependency of Friction on Temperature and Sliding Velocity in Low Dimensional Systems with Different Atom Electronegativity

Robust topological bound states in the continuum in a quantum Hall bar with an anti-dot

Bound states in the continuum (BICs) are quantum states with normalizable wave functions and energies that lie within the continuous spectrum for which extended or dispersive states are also available. These special states, which have shown great applicability in photonic systems for devices such as lasers and sensors, are also predicted to exist in electronic low-dimensional solid-state systems. The non-trivial topology of materials is within the known mechanisms that prevent the bound states to couple with the extended states. In this work we search for topologically protected BICs in a quantum Hall bar with an anti-dot formed by a pore far from the borders of the bar. The bound state energies and wavefunctions are calculated by means of the Recursive S-Matrix method. The resulting bound state energies coexist with extended states and exhibit a pattern complimentary to the Hofstadter butterfly. A symmetry-breaking diagonal disorder was introduced, showing that the BICs with energies far from the Landau levels remain robust. Moreover, the energy difference between consecutive BICs multiplied by the anti-dot perimeter follows the same curve despite disorder. Finally, a BIC-mediated current switching effect was found in a multi-terminal setup for zero and finite temperature, which might permit their experimental detection.

Microscopic state equation for oscillator chains

Systems allowing anomalous transport of mass, momentum energy, etc., such as low-dimensional particles systems or highly confining media, are hard to characterize thermodynamically. Indeed, local thermodynamic equilibrium may not be established and their behaviour often strongly depends on many microscopic parameters, including the symmetry of the interaction potentials. Thermodynamic state equations, on the other hand, involve a small set of observables, which are obtained averaging in time and over the large number of particles that populate mesoscopic cells in which local equilibrium can be realized. In this work we show that a linear relation discovered earlier, that connects the average distance between pairs of consecutive particles with their kinetic energy, applies to quite a large set of 1-dimensional particle systems known to produce anomalous transport. This relation is microscopic in nature, since the quantities involved are neither averaged over many particles, neither over very large times. Nevertheless, its robustness is under variations of the external parameters, and the limited set of quantities it involves qualify it as a state equation, analogously to thermodynamic relations. We provide conditions for which the relation can be violated within a limited range of parameters values, and we find that it can be extended to two-dimensional networks of coupled oscillators. The validity of this relation further shows that the states of aggregation of matter in low-dimensional systems are often different from standard macroscopic ones.

Early Predictor for the Onset of Critical Transitions in Networked Dynamical Systems

Numerous natural and human-made systems exhibit critical transitions whereby slow changes in environmental conditions spark abrupt shifts to a qualitatively distinct state. These shifts very often entail severe consequences; therefore, it is imperative to devise robust and informative approaches for anticipating the onset of critical transitions. Real-world complex systems can comprise hundreds or thousands of interacting entities, and implementing prevention or management strategies for critical transitions requires knowledge of the exact condition in which they will manifest. However, most research so far has focused on low-dimensional systems and small networks containing fewer than ten nodes or has not provided an estimate of the location where the transition will occur. We address these weaknesses by developing a deep-learning framework which can predict the specific location where critical transitions happen in networked systems with size up to hundreds of nodes. These predictions do not rely on the network topology, the edge weights, or the knowledge of system dynamics. We validate the effectiveness of our machine-learning-based framework by considering a diverse selection of systems representing both smooth (second-order) and explosive (first-order) transitions: the synchronization transition in coupled Kuramoto oscillators; the sharp decline in the resource biomass present in an ecosystem; and the abrupt collapse of a Wilson-Cowan neuronal system. We show that our method provides accurate predictions for the onset of critical transitions well in advance of their occurrences, is robust to noise and transient data, and relies only on observations of a small fraction of nodes. Finally, we demonstrate the applicability of our approach to real-world systems by considering empirical vegetated ecosystems in Africa. Published by the American Physical Society 2024

Large magnetocaloric refrigeration performance near room temperature in monolayer transition metal dihalides

Magnetocaloric effect (MCE) exhibits highly efficient and ecological cooling abilities for solid-state refrigeration in contrast to traditional vapor-compression refrigeration. Successive emerging two-dimensional (2D) magnetic materials provide a fertile platform for exploring low-dimensional MCE systems. Here, we focus on a series of 2D transition metal dihalides MX2 (M = Fe, Ru, Os; X = Cl, Br) to explore the maximum isothermal magnetic entropy change (−ΔSmagmax) and adiabatic temperature change (ΔTadmax) under external magnetic field. It is found that FeCl2, FeBr2, and RuCl2 have intrinsically sizable −ΔSmagmax, ΔTadmax, and high thermal conductivity near room temperature, demonstrating superior comprehensive refrigeration performance in comparison with other 2D magnets. It is revealed that strong nearest-neighbor ferromagnetic exchange interaction plays a decisive role in −ΔSmagmax, and the high lattice thermal conductivities of FeCl2 and RuCl2 are attributed to the longer phonon lifetime and larger group velocity of low-frequency acoustic branch. Moreover, moderate strain and carriers doping are able to effectively regulate Curie temperature and magnetocrystalline anisotropy energy and correspondingly enhance −ΔSmagmax. The present work provides important insights for the exploration of 2D magnets for magnetocaloric refrigeration near room temperature.

Trade-off between bagging and boosting for quantum separability-entanglement classification

Certifying whether an arbitrary quantum system is entangled or not, is, in general, an NP-hard problem. Though various necessary and sufficient conditions have already been explored in this regard for lower-dimensional systems, it is hard to extend them to higher dimensions. Recently, an ensemble bagging and convex hull approximation (CHA) approach (together, BCHA) was proposed and it strongly suggests employing a machine learning technique for the separability-entanglement classification problem. However, BCHA does only incorporate the balanced dataset for classification tasks which results in lower average accuracy. In order to solve the data imbalance problem in the present literature, an exploration of the boosting technique has been carried out, and a trade-off between the boosting and bagging-based ensemble classifier is explored for quantum separability problems. For the two-qubit and two-qutrit quantum systems, the pros and cons of the proposed random under-sampling boost CHA (RUSBCHA) for the quantum separability problem are compared with the state-of-the-art CHA and BCHA approaches. As the data are highly unbalanced, performance measures such as overall accuracy, average accuracy, F-measure, and G-mean are evaluated for a fair comparison. The outcomes suggest that RUSBCHA is an alternative to the BCHA approach. Also, for several cases, performance improvements are observed for RUSBCHA since the data are imbalanced.

Floquet engineering of electronic states and optical absorption in laterally-coupled quantum rings under a magnetic field.

Tuning electronic and optical properties of low-dimensional quantum systems in a flexible way is of particular importance in designing semiconductor-based devices. Semiconductor quantum rings (QRs) are nanoscopic structures that have become promising systems for physical and technological applications due to their unique electronic and optical properties. Here, we explore the fundamental electronic and optical properties of laterally-coupled QRs by taking into account the combined effects of applied magnetic and non-resonant terahertz intense laser fields. The laser-dressed electronic states are solved using the Floquet theory of periodically driven quantum systems in high-frequency limits within the framework of effective mass approximation. We demonstrate that increasing the laser field parameter leads to reduced tunnel splitting in the energy spectrum and more pronounced Aharonov-Bohm oscillations for the ground state energy, due to the attenuation of the tunnel coupling. Furthermore, depending on the position of the avoided crossings in Aharonov-Bohm oscillations of laterally-coupled quantum rings, the evolution of the avoided crossings with increasing the laser field parameter can be elucidated as the attenuated tunnel coupling or the competition between the attenuated tunnel coupling and the strengthening anisotropy of the laser-dressed QR potential well. The intensity of the intraband optical transition of laterally-coupled QRs can be effectively tuned and reaches a larger value by manipulating the laser parameter and magnetic field. Optical Aharonov-Bohm oscillations in laterally-coupled QRs are still exhibited by changing laser field parameters. Our findings offer a novel approach to manipulate the electronic and optical performances as well as the Aharonov-Bohm oscillations based on the laterally-coupled QRs by using an intense terahertz laser field.

Existence and stability of a quasi-periodic two-dimensional motion of a self-propelled particle

The mechanism of self-propelled particle motion has attracted much interest in mathematical and physical understanding of the locomotion of living organisms. In a top-down approach, simple time-evolution equations are suitable for qualitatively analyzing the transition between the different types of solutions and the influence of the intrinsic symmetry of systems despite failing to quantitatively reproduce the phenomena. We aim to rigorously show the existence of the rotational, oscillatory, and quasi-periodic solutions and determine their stabilities regarding a canonical equation proposed by Koyano et al. (J Chem Phys 143(1):014117, 2015) for a self-propelled particle confined by a parabolic potential. In the proof, the original equation is reduced to a lower dimensional dynamical system by applying Fenichel’s theorem on the persistence of normally hyperbolic invariant manifolds and the averaging method. Furthermore, the averaged system is identified with essentially a one-dimensional equation because the original equation is O(2)-symmetric.