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Spin effect on the low-temperature resistivity maximum in a strongly interacting 2D electron system
Get PDFThe increase in the resistivity with decreasing temperature followed by a drop by more than one order of magnitude is observed on the metallic side near the zero-magnetic-field metal-insulator transition in a strongly interacting two-dimensional electron system in ultra-clean SiGe/Si/SiGe quantum wells. We find that the temperature T-max, at which the resistivity exhibits a maximum, is close to the renormalized Fermi temperature. However, rather than increasing along with the Fermi temperature, the value T-max decreases appreciably for spinless electrons in spin-polarizing (parallel) magnetic fields. The observed behaviour of T-max cannot be described by existing theories. The results indicate the spin-related origin of the effect
Blunt-End Driven Re-entrant Ordering in Quasi Two-Dimensional Dispersions of Spherical DNA Brushes
Get PDFWe investigate the effects of crowding on the conformations and assembly of confined, highly charged, and thick polyelectrolyte brushes in the osmotic regime. Particle tracking experiments on increasingly dense suspensions of colloids coated with ultralong double-stranded DNA (dsDNA) fragments reveal nonmonotonic particle shrinking, aggregation, and re-entrant ordering. Theory and simulations show that aggregation and re-entrant ordering arise from the combined effect of shrinking, which is induced by the osmotic pressure exerted by the counterions absorbed in neighbor brushes and of a short-range attractive interaction competing with electrostatic repulsion. An unconventional mechanism gives origin to the short-range attraction: blunt-end interactions between stretched dsDNA fragments of neighboring brushes, which become sufficiently intense for dense and packed brushes. The attraction can be tuned by inducing free-end backfolding through the addition of monovalent salt. Our results show that base stacking is a mode parallel to hybridization to steer colloidal assembly in which attractions can be fine-tuned through salinity and, potentially, grafting density and temperature
Evolution of Cohesion between USA Financial Sector Companies before, during, and Post-Economic Crisis: Complex Networks Approach
Get PDFVarious mathematical frameworks play an essential role in understanding the economic systems and the emergence of crises in them. Understanding the relation between the structure of connections between the system’s constituents and the emergence of a crisis is of great importance. In this paper, we propose a novel method for the inference of economic systems’ structures based on complex networks theory utilizing the time series of prices. Our network is obtained from the correlation matrix between the time series of companies’ prices by imposing a threshold on the values of the correlation coefficients. The optimal value of the threshold is determined by comparing the spectral properties of the threshold network and the correlation matrix. We analyze the community structure of the obtained networks and the relation between communities’ inter and intra-connectivity as indicators of systemic risk. Our results show how an economic system’s behavior is related to its structure and how the crisis is reflected in changes in the structure. We show how regulation and deregulation affect the structure of the system. We demonstrate that our method can identify high systemic risks and measure the impact of the actions taken to increase the system’s stability
Rate chaos and memory lifetime in spiking neural networks
Get PDFRate chaos is a collective state of a neural network characterized by slow irregular fluctuations of firing rates of individual neurons. We study a sparsely connected network of spiking neurons which demonstrates three different scenarios for the emergence of rate chaos, based either on increasing the synaptic strength, increasing the synaptic integration time, or clustering of the excitatory synaptic connections. Although all the scenarios lead to collective dynamics with similar statistical features, it turns out that the implications for the computational capability of the network in performing a simple delay task are strongly dependent on the particular scenario. Namely, only the scenario involving slow dynamics of synapses results in an appreciable extension of the network's dynamic memory. In other cases, the dynamic memory remains short despite the emergence of long timescales in the neuronal spike trains. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/)
Tribological properties of vanadium oxides investigated with reactive molecular dynamics
Get PDFWe present a reactive molecular dynamics study on tribological properties of five vanadium oxides (V2O3, V3O5, V8O15, V9O17, VO2) under elevated temperatures and pressures. All considered stoichiometries provide lubrication with a comparatively low coefficient of friction (COF similar to 0.2 at 600 K, COF < 0.2 at 800 and 1000 K) which is a valuable information relevant for the design of coatings containing vanadium as a lubricious agent. An overall tendency of the decrease of friction coefficient with the increase of temperature represents a tribological effect useful for self-adjusting lubrication. We observed the increasing trend of adhesion-related offset of the friction force with the decrease of oxygen content in vanadium oxides
Electronic Properties of Silver–Bismuth Iodide Rudorffite Nanoplatelets
No full textSilver-bismuth iodide (Ag-Bi-I) rudorffites are chemically stable and non-toxic materials that can act as a possible lead-free replacement for methylammonium lead halides in optoelectronic applications. We report on a simple route for fabricating Ag-Bi-I colloidal nanoplatelets approximately 160 nm in lateral dimensions and 1-8 nm in thickness via exfoliation of Ag-Bi-I rudorffite powders in acetonitrile. The valence band electronic structure of isolated Ag-Bi-I nanoplatelets was investigated using synchrotron radiation to perform X-ray aerosol photoelectron spectroscopy (XAPS). The ionization energy of the material was found to be 6.1 +/- 0.2 eV with respect to the vacuum level. UV-vis absorption and photoluminescence spectroscopies of the Ag-Bi-I colloids showed that the optical properties of the nanoplatelets originate from I 5p to Bi 6p and I 5p to I 5p transitions, which is further confirmed by density functional theory (DFT) calculations. Finally, calculations based on the DFT and k . p theoretical methods showed that the quantum confinement effect is very weak in the system studied
Shell-shaped Bose-Einstein condensates based on dual-species mixtures
No full textUltracold quantum gases confined in three-dimensional bubble traps are promising tools for exploring many -body effects on curved manifolds. As an alternative to the conventional technique of radio-frequency dressing, we propose to create such shell-shaped Bose-Einstein condensates in microgravity based on dual-species atomic mixtures, and we analyze their properties as well as the feasibility of realizing symmetrically filled shells. Beyond similarities with the radio-frequency dressing method, as in the collective excitation spectrum, our approach has several natural advantages like the robustness of the created quantum bubbles and the possibility of magnifying shell effects through an interaction-driven expansion
DFT+SIGMA2 method for electron correlation effects at transition metal surfaces
No full textWe present a computational approach for electronically correlated metallic surfaces and interfaces, which combines density functional and dynamical mean-field theory using a multiorbital perturbative solver for the many-body problem. Our implementation is designed to describe ferromagnetic metallic thin films on a substrate. The performances are assessed in detail for a Fe monolayer on a W(110) substrate, a prototypical nanoscale magnetic system. Comparing our results to photoemission data, we find qualitative and quantitative improvements in the calculated spectral function with respect to the results of density functional theory within the local spin density approximation. In particular, the spin splitting of the d states is drastically reduced and, at the same time, their spectral width becomes narrower. The method is, therefore, able to account for the main correlation effects in the system
Detecting few-body quantum chaos: out-of-time ordered correlators at saturation
Get PDFWe study numerically and analytically the time dependence and saturation of out-of-time ordered correlators (OTOC) in chaotic few-body quantum-mechanical systems: quantum Henon-Heiles system (weakly chaotic), BMN matrix quantum mechanics (strongly chaotic) and Gaussian random matrix ensembles. The growth pattern of quantum-mechanical OTOC is complex and nonuniversal, with no clear exponential regime at relevant timescales in any of the examples studied (which is not in contradiction to the exponential growth found in the literature for many-body systems, i.e. fields). On the other hand, the plateau (saturated) value of OTOC reached at long times decreases with temperature in a simple and universal way: exp(const./T-2) for strong chaos (including random matrices) and exp(const./T) for weak chaos. For small matrices and sufficiently complex operators, there is also another, high-temperature regime where the saturated OTOC grows with temperature. Therefore, the plateau OTOC value is a meaningful indicator of few-body quantum chaos. We also discuss some general consequences of our findings for the AdS/CFT duality
Universal growth of social groups: empirical analysis and modeling
No full textSocial groups are fundamental elements of any social system. Their emergence and evolution are closely related to the structure and dynamics of a social system. Research on social groups was primarily focused on the growth and the structure of the interaction networks of social system members and how members’ group affiliation influences the evolution of these networks. The distribution of groups’ size and how members join groups has not been investigated in detail. Here we combine statistical physics and complex network theory tools to analyze the distribution of group sizes in three data sets, Meetup groups based in London and New York and Reddit. We show that all three distributions exhibit log-normal behavior that indicates universal growth patterns in these systems. We propose a theoretical model that combines social and random diffusion of members between groups to simulate the roles of social interactions and members’ interest in the growth of social groups. The simulation results show that our model reproduces growth patterns observed in empirical data. Moreover, our analysis shows that social interactions are more critical for the diffusion of members in online groups, such as Reddit, than in offline groups, such as Meetup. This work shows that social groups follow universal growth mechanisms that need to be considered in modeling the evolution of social systems