Correlation Effects Research Articles

Selected Configuration Interaction for Resonances.

Electronic resonances are metastable states that can decay by electron loss. They are ubiquitous across various fields of science, such as chemistry, physics, and biology. However, current theoretical and computational models for resonances cannot yet rival the level of accuracy achieved by bound-state methodologies. Here, we generalize selected configuration interaction (SCI) to treat resonances by using the complex absorbing potential (CAP) technique. By modifying the selection procedure and the extrapolation protocol of standard SCI, the resulting CAP-SCI method yields resonance positions and widths of full configuration interaction quality. Initial results for the shape resonances of N2- and CO- reveal the important effect of high-order correlation, which shifts the values obtained with CAP-augmented equation-of-motion coupled-cluster with singles and doubles by more than 0.1 eV. The present CAP-SCI approach represents a cornerstone in the development of highly accurate methodologies for resonances.

Prediction and analysis of dominant factors influencing moisture content during vacuum screening based on machine learning

The study of the dominant factors influencing moisture content is essential for investigating vacuum filtration mechanisms. In view of the present situation where there is insufficient experimental data and the dominant factors influencing the moisture content of a filter cake have not been identified, in this study a vacuum filtration apparatus was designed and constructed. Quartz sand particles were used as the filtration material. 300 datasets of moisture contents of a filter cake were obtained under different experimental conditions. Multiple Linear Regression, artificial neural network, decision tree, random forest, and extreme gradient boosting were used to establish a prediction model for moisture content during vacuum screening. By comprehensively analyzing the feature importance rankings and the effects of positive and negative correlations, the dominant factors influencing the moisture content of the filter cake during vacuum screening were the particle ratio, screen mesh, and airflow rate. This finding not only provides a scientific basis for the optimization of vacuum screening technology but also points the way for improving screening efficiency in practical applications. It is of significant importance for deepening the understanding of the vacuum screening mechanism and promoting its extensive application.

Investigating Flow-Induced Vibration by Regarding the Alignment of Flow Modes and Structural Modes

In this work, a modal matching approach is developed to investigate the impact of the spatial correlation of wall pressure fluctuations on structural vibration and its role in suppressing flow-induced vibration in aircraft. The modal matching method defines the wavelength ratio between the convection wave and the flexural wave to capture the spatial characteristics of both the flow mode and the structural mode. In comparison to conventional methods such as the finite element method and analytical method, the proposed modal matching approach allows for obtaining the vibration response in the spatial–wavenumber domain. To validate the spatial correlation effect on structural vibrations obtained with the modal matching approach, a wind tunnel test was conducted to measure flow-induced vibrations. The calculated spatial–wavenumber data for flow-induced vibrations reveal that the crests and troughs of the vibration velocity alternate periodically as the wavelength of the wall pressure fluctuations changes. At the resonance frequency, a vibration velocity trough can be observed when the spatial correlation of wall pressure fluctuations aligns with the structural mode. Additionally, the concept of resonance independence of flow-induced vibrations is introduced to describe the phenomenon where the most severe structural vibration, determined by the matching value between the aerodynamic mode and the structural mode, does not always occur at the resonance frequency. The modal matching approach effectively suppresses structural vibration by utilizing the spatial correlation of wall pressure fluctuations, offering a new perspective on controlling flow-induced vibrations.

Kadanoff-Baym Equations for Interacting Systems with Dissipative Lindbladian Dynamics.

The extraordinary quantum properties of nonequilibrium systems governed by dissipative dynamics have become a focal point in contemporary scientific inquiry. The nonequilibrium Green's functions (NEGF) theory provides a versatile method for addressing driven nondissipative systems, utilizing the powerful diagrammatic technique to incorporate correlation effects. We here present a second-quantization approach to the dissipative NEGF theory, reformulating Keldysh ideas to accommodate Lindbladian dynamics and extending the Kadanoff-Baym equations accordingly. Generalizing diagrammatic perturbation theory for many-body Lindblad operators, the formalism enables correlated and dissipative real-time simulations for the exploration of transient and steady-state changes in the electronic, transport, and optical properties of materials.

Laplacian renormalization group: an introduction to heterogeneous coarse-graining

The renormalization group (RG) constitutes a fundamental framework in modern theoretical physics. It allows the study of many systems showing states with large-scale correlations and their classification into a relatively small set of universality classes. The RG is the most powerful tool for investigating organizational scales within dynamic systems. However, the application of RG techniques to complex networks has presented significant challenges, primarily due to the intricate interplay of correlations on multiple scales. Existing approaches have relied on hypotheses involving hidden geometries and based on embedding complex networks into hidden metric spaces. Here, we present a practical overview of the recently introduced Laplacian RG (LRG) for heterogeneous networks. First, we present a brief overview that justifies the use of the Laplacian as a natural extension of well-known field theories to analyze spatial disorder. We then draw an analogy to traditional real-space RG procedures, explaining how the LRG generalizes the concept of ‘Kadanoff supernodes’ as block nodes that span multiple scales. These supernodes help mitigate the effects of cross-scale correlations due to small-world properties. Additionally, we rigorously define the LRG procedure in momentum space in the spirit of the Wilson RG. Finally, we show different analyses for the evolution of network properties along the LRG flow following structural changes when the network is properly reduced.

Effects of Indirect Correlations between Interacting Particles on the Label, Mass, and Momentum Transfer Coefficients

Effects of Indirect Correlations between Interacting Particles on the Label, Mass, and Momentum Transfer Coefficients

Temporal scaling theory for bursty time series with clusters of arbitrarily many events.

Long-term temporal correlations in time series in a form of an event sequence have been characterized using an autocorrelation function that often shows a power-law decaying behavior. Such scaling behavior has been mainly accounted for by the heavy-tailed distribution of interevent times, i.e., the time interval between two consecutive events. Yet, little is known about how correlations between consecutive interevent times systematically affect the decaying behavior of the autocorrelation function. Empirical distributions of the burst size, which is the number of events in a cluster of events occurring in a short time window, often show heavy tails, implying that arbitrarily many consecutive interevent times may be correlated with each other. In the present study, we propose a model for generating a time series with arbitrary functional forms of interevent time and burst size distributions. Then, we analytically derive the autocorrelation function for the model time series. In particular, by assuming that the interevent time and burst size are power-law distributed, we derive scaling relations between power-law exponents of the autocorrelation function decay, interevent time distribution, and burst size distribution. These analytical results are confirmed by numerical simulations. Our approach helps to rigorously and analytically understand the effects of correlations between arbitrarily many consecutive interevent times on the decaying behavior of the autocorrelation function.

Pressure effect investigation of structural, electronic, elastic and magnetic properties of X2CrSb (X = Mn, Co and Cu) Heusler alloys

Using the plane-wave pseudo-potential approach and generalized-gradient approximation for the exchange–correlation effects in the framework of the density functional theory, the structural, electronic, elastic and magnetic properties of X2CrSb ( ▪ and Cu) Heusler alloys were investigated. For ▪ , a structural phase-transition from XA to L21-phase is expected at 8.933GPa. This compound exhibits half-metallic behavior before becoming a magnetic metal at 17.5GPa. The ▪ is a half-metal under expansion and nearly half-metal above 1GPa. The total magnetic moments for ▪ , ▪ and ▪ are respectively equal to 5.0μB, 1.0μB and 3.4μB, and are mainly localized on Cr except for ▪ in XA-phase where the magnetic moment is localized on Mn. The DOS analysis shows weak spin-polarizations for ▪ and a higher polarization under expansion for ▪ and ▪ . Under compression, the polarization is weakened in ▪ , it remains at a high level before it vanishes at 29.4μB in ▪ .

Tuning nonequilibrium colloidal structure in external fields by density-dependent state switching.

Biological cells have the ability to switch internal states depending on the density of other cells in their local environment, referred to as "quorum sensing." The latter can be utilized to control collective structuring, such as in biofilm formation. In this work, we study a simple quorum sensing model of ideal (noninteracting) colloids with a switchable internal degree of freedom in the presence of external potentials. The colloids have two possible discrete states, in which they are affected differently by the external field, and switch with rates dependent on the local density in their environment. We study this model with reactive Brownian dynamics simulations, as well as with an appropriate reaction-diffusion theory. We find remarkable structuring in the system controlled by the density-mediated interactions between the ideal colloids. We report results of different functional forms for the rate dependence and quantify the influence of their parameters, in particular, discuss the role of the spatiotemporal sensing range, i.e., how the resulting structures depend on how the environmental information is "measured" by the colloids. Especially in the case of a rate function with sigmoidal dependence on local density, i.e., requiring a threshold density for switching, we observe significant correlation effects in the density profiles which are tuneable by the sensing ranges but also sensitive to noise and fluctuations. Hence, our model gives some basic insights into the nonequilibrium structuring mediated by simple quorum sensing protocols.

The singlet S-wave resonances of He atom in dense quantum plasmas

The singlet S-wave resonances of the He atom embedded in dense quantum plasmas are investigated by applying the complex-coordinate rotation method. The modified Debye–Hückel potential is used to model the effective interactions of the test atom in a dense quantum plasma environment. The explicitly correlated Hylleraas configuration-interaction basis function is employed to take into account the electron correlation effect. The first ten S-wave resonance states of the He atom below the N = 2 thresholds of the He+ ion are calculated, and the resonance energies and widths at a variety of screening parameters are obtained with high accuracy. The plasma screening effect on the expectation values of the radial and angular physical quantities are analyzed for the first time.

The combined effects of quantum and strong coupling on the nonlinear collective excitation in quantum dusty plasmas

The quantum hydrodynamic model for electrons and ions and the generalized hydrodynamic model for the strongly coupled dust particles are proposed in the strongly coupled quantum dusty plasma, where the combined quantum effects of quantum diffraction, quantum statistic pressure, as well as electron exchange and correlation effects are all considered in the quantum hydrodynamic model. The shear and bulk viscosity effects are included in the viscoelastic relaxation, which leads to the decay of the dust-ion-acoustic waves. The approximate time-dependent solitary solution is obtained by the momentum conservation law in the presence of viscosity.

Doping strategies for β-Ga2O3 based on high-throughput first-principles calculations

β-Ga2O3 is a promising material for advanced optoelectronic semiconductors due to its wide bandgap and high breakdown voltage. However, achieving efficient p-type doping remains a challenge. This investigation employs high-throughput (HT) first-principles calculations to explore doping effects in β-Ga2O3 systematically. The results of HT first-principles calculations indicate that changes in the Fermi levels (EF) can reflect the type of dopant elements. We systematically evaluated nine candidate dopants using GGA+U calculations. Through analysis of the (0/−1) transition levels, the ability to form shallow acceptors gradually decreases in the order of Zn, Mg, Cu, Hg, and Ag. Interestingly, due to the GGA+U optimization process considering electron correlation and localization effects, Mg-doped β-Ga2O3 exhibits an impurity level near the conduction band minimum (CBM), contributed by Mg2p and O2p orbitals. Mulliken population analysis reveals that Cu exhibits the highest charge density after doping compared to Hg, Zn, and Mg. Additionally, Ag-doped β-Ga2O3 shows potential for UV device applications within the 200 nm to 280 nm spectrum. The insights from this study delineate effective p-type doping strategies for β-Ga2O3, contributing to the advancement of optoelectronic device development involving semiconductors.

Correlative Effects on Nanoplastic Aggregation in Model Extracellular Biofilm Substances Investigated with Fluorescence Correlation Spectroscopy.

Recent studies show that biofilm substances in contact with nanoplastics play an important role in the aggregation and sedimentation of nanoplastics. Consequences of these processes are changes in biofilm formation and stability and changes in the transport and fate of pollutants in the environment. Having a deeper understanding of the nanoplastics-biofilm interaction would help to evaluate the risks posed by uncontrolled nanoplastic pollution. These interactions are impacted by environmental changes due to climate change, such as, e.g., the acidification of surface waters. We apply fluorescence correlation spectroscopy (FCS) to investigate the pH-dependent aggregation tendency of non-functionalized polystyrene (PS) nanoparticles (NPs) due to intermolecular forces with model extracellular biofilm substances. Our biofilm model consists of bovine serum albumin (BSA), which serves as a representative for globular proteins, and the polysaccharide alginate, which is a main component in many biofilms, in solutions containing Na+ with an ionic strength being realistic for fresh-water conditions. Biomolecule concentrations ranging from 0.5 g/L up to at maximum 21 g/L are considered. We use non-functionalized PS NPs as representative for mostly negatively charged nanoplastics. BSA promotes NP aggregation through adsorption onto the NPs and BSA-mediated bridging. In BSA-alginate mixtures, the alginate hampers this interaction, most likely due to alginate-BSA complex formation. In most BSA-alginate mixtures as in alginate alone, NP aggregation is predominantly driven by weaker, pH-independent depletion forces. The stabilizing effect of alginate is only weakened at high BSA contents, when the electrostatic BSA-BSA attraction is not sufficiently screened by the alginate. This study clearly shows that it is crucial to consider correlative effects between multiple biofilm components to better understand the NP aggregation in the presence of complex biofilm substances. Single-component biofilm model systems based on comparing the total organic carbon (TOC) content of the extracellular biofilm substances, as usually considered, would have led to a misjudgment of the stability towards aggregation.

Correlation effect and sodium diffusion in silicate glass: molecular dynamics simulation

We conducted a molecular dynamics simulation to investigate the diffusion in sodium silicate glass. The result shows that the sodium diffusion is accompanied with the correlation effect that Na atoms often leave and then return to the starting polyhedron. We establish the expression for diffusion constant D via hopping rate γ, correlation factor F and average square distance per visiting polyhedron d2. The results show that unlike diffusion in crystal, F decreases with decreasing temperature. Moreover, F is dependent with SiO2 content of glass, and D exhibits a linear dependence on the product Fγ.

Analysis of financial markets by coupled criticality approach

Analysis of the criticality in finance and economics is an important topic for scholars. The crises are conditions in which unpredictable behavior have been emerged. On the other hand, the contagion from one market to another one due to the complex nature of them is a crucial concept. Therefore, we should consider economies and financial markets as entangled systems that interact with each other, and studying one’s behavior without considering its interacting structures will not provide us with adequate information. In this paper, we have considered the critical states of some emerging and mature markets’ indices. S&P500 and Nikkei 225 as representatives of mature markets, and SSE Composite and TEDPIX as representatives of emerging markets have been analyzed. Coupled criticality emerges when two interacting systems reach their critical state due to their interactions. One of the efficient methods to study the coupled criticality is the bi-variate multifractal random walk model. This method is useful to assess the correlation of rare events and coupled criticality in entangled systems such as financial markets. The observations in this paper show that TEDPIX and S&P500 have higher critical states among others in most time lags by assessing criticality parameter explained in the model, and in longer time lags criticality parameter decreases in all indices. Coupled criticality parameter explained in the model is assessed between each index mentioned and TEDPIX. Results show that TEDPIX and S&P500 have the highest level of coupled criticality. To figure out how long-range time correlation between rare events in each index affect its critical behavior, the data of each index are shuffled, and the criticality parameter is calculated for the shuffled data. From the observations, it can be concluded that this matter has more substantial effect on mature markets. As it is known, shuffling removes the effect of the long-range time correlations. Therefore, the coupled criticality parameter is calculated for the shuffled S&P500 data and TEDPIX. Results show that the long-range correlation of S&P500 data has a significant effect on the coupled criticality behavior of S&P500 and TEDPIX.

Enhancing sideband cooling by initial photon-phonon correlation

We propose an optimized sideband cooling protocol for an optomechanical system coupled to a mechanical non-Markovian reservoir, considering the presence of initial system correlations. By incorporating the effect of initial correlations in the Heisenberg equations, we derive a more stringent dependence on the initial conditions and time-dependent evolution of the phonon numbers. Our findings demonstrate that considering the initial correlations can significantly reduce the number of phonons during the cooling process. Moreover, by adjusting the strength and phase of the initial correlation, the ground-state cooling process can be accelerated. We observe a characterization of this cooling optimization process that resembles the phenomenon of entanglement death and revival. This work provides a promising platform for effectively manipulating phonons and facilitating quantum information processing in optomechanical systems.

Spatial differentiation and driving factors of scientific and technological innovation efficiency under the background of the digital economy

Scientific and technological innovation (STI) activities are facilitated under the influence of the digital economy and depend on digital elements to support innovation activities. This study measures digital element inputs and outputs using data related to the digital economy and estimates STI efficiency in 29 provincial regions in mainland China from 2010 to 2021 employing the global super-efficiency slacks-based measure (SBM) model. Then, spatial characteristics and driving forces of STI efficiency are quantified using spatial autocorrelation and geographic detectors. The results reveal that STI efficiency exhibits a fluctuating, W-shaped pattern, and the spatial correlation effect shows a gradually declining trend from 2010 to 2021. The findings reveal that the core drivers of STI efficiency are digital financial development, e-commerce development, digital access level, and related factors. Therefore, strengthening inter-regional innovation links, promoting the construction of 5 G mobile internet and accelerating the integration of digital industries into traditional industries are recommended.

Ab initio density response and local field factor of warm dense hydrogen

We present quasi-exact ab initio path integral Monte Carlo (PIMC) results for the partial static density responses and local field factors of hydrogen in the warm dense matter regime, from solid density conditions to the strongly compressed case. The full dynamic treatment of electrons and protons on the same footing allows us to rigorously quantify both electronic and ionic exchange–correlation effects in the system, and to compare the results with those of earlier incomplete models such as the archetypal uniform electron gas or electrons in a fixed ion snapshot potential that do not take into account the interplay between the two constituents. The full electronic density response is highly sensitive to electronic localization around the ions, and our results constitute unambiguous predictions for upcoming X-ray Thomson scattering experiments with hydrogen jets and fusion plasmas. All PIMC results are made freely available and can be used directly for a gamut of applications, including inertial confinement fusion calculations and the modeling of dense astrophysical objects. Moreover, they constitute invaluable benchmark data for approximate but computationally less demanding approaches such as density functional theory or PIMC within the fixed-node approximation.

Correlation and price spillover effects among green assets

Correlation and price spillover effects among green assets

Nonadiabatic Molecular Dynamics with Fermionic Subspace-Expansion Algorithms on Quantum Computers.

We introduce a novel computational framework for excited-state molecular quantum dynamics simulations driven by quantum-computing-based electronic-structure calculations. This framework leverages the fewest-switches surface-hopping method for simulating the nuclear dynamics and calculates the required excited-state transition properties with different flavors of the quantum subspace expansion and quantum equation-of-motion algorithms. We apply our method to simulate the collision reaction between a hydrogen atom and a hydrogen molecule. For this system, we critically compare the accuracy and efficiency of different quantum subspace expansion and equation-of-motion algorithms and show that only methods that can capture both weak and strong electron correlation effects can properly describe the nonadiabatic effects that tune the reactive event.