arXiv subjects

G. R. Jafari

Publications and source records attributed to G. R. Jafari.

At least 19 recordsLinked to original sources

arXiv2025

Fractional Schwarzschild-Tangherlini black hole with a fractal event horizon

We demonstrate that the implementation of the fractional and non-local Wheeler--DeWitt (WDW) equation within the context of Schwarzschild geometry leads to the emergence of a Schwarzschild--Tangherlini black hole (BH), which is uniquely characterized by an event horizon that exhibits fractal properties and is defined by a non-integer dimension that lies in the continuum between the values of 1 and 2. Our calculations further reveal that this intriguing fractional BH may potentially possess a temperature that is substantially lower than that of a conventional BH, thereby suggesting a significant deviation from the expected thermodynamic properties of standard BHs. These remarkable characteristics, which are intrinsically linked to the non-integer dimensionality of the event horizon, likely arise from applying the Riesz fractional derivative as a sophisticated non-local operator, thus introducing fascinating dynamics into the theoretical framework of BH physics.

gr-qc↗

arXiv2023

Frustration of triplet interaction in spin-glass background

Parisi demonstrated in 1979 that pairwise interactions exhibit a glass spin phase when there is disorder. While he discovered an equilibrium solution of the Sherrington-Kirkpatrick (SK) spin-glass model and we know it as a continuous phase transition, the model dedicated to pairwise interactions and higher-order interactions has not been addressed. This research intends to determine whether this phase exists in triplet interactions. Due to the intractable nature of the three interacting spins alone, we employed a perturbation approach to provide an analytical solution for the triplet interactions in the background of the SK spin-glass model. Our results show the existence of this phase in the third-order interaction and a sudden transition that indicates a change in the nature of a glassy spin system transitioning from the continuous order to the first order. It causes a forward shift in the critical temperature by identifying the frustration of triplet interactions.

cond-mat.dis-nn↗

arXiv2022

Second to first order phase transition; coevolutionary versus structural balance

In social networks, the balance theory has been studied by considering either the triple interactions between the links (structural balance) or the triple interaction of nodes and links (coevolutionary balance). In the structural balance theory, the links are not independent from each other, implying a global effect of this term and it leads to a discontinuous phase transition in the system's balanced states as a function of temperature. However, in the coevolutionary balance the links only connect two local nodes and a continuous phase transition emerges. In this paper, we consider a combination of both in order to understand which of these types of interactions will identify the stability of the network. We are interested to see how adjusting the robustness of each term versus the other might affect the system to reach a balanced state. We use statistical mechanics methods and the mean field theory and also the Monte-Carlo numerical simulations to investigate the behaviour of the order parameters and the total energy of the system. We find the phase diagram of the system which demonstrates the competition of these two terms at different ratios against each other and different temperatures. The system shows a tricritical point above which the phase transition switches from continuous to discrete. Also the superiority of the local perspective is observed at low temperatures and the global view will be the dominant term in determining the stability of the system at higher temperatures.

cond-mat.stat-mech↗

arXiv2022

Modified Heider Balance on Sparse Random Networks

The lack of signed random networks in standard balance studies has prompted us to extend the Hamiltonian of the standard balance model. Random networks with tunable parameters are suitable for better understanding the behavior of standard balance as an underlying dynamics. Moreover, the standard balance model in its original form does not allow preserving tensed triads in the network. Therefore, the thermal behavior of the balance model has been investigated on a fully connected signed network recently. It has been shown that the model undergoes an abrupt phase transition with temperature. Considering these two issues together, we examine the thermal behavior of the structural balance model defined on Erdős-Rényi random networks. We provide a Mean-Field solution for the model. We observe a first-order phase transition with temperature, for both the sparse and densely connected networks. We detect two transition temperatures, $T_{cold}$ and $T_{hot}$, characterizing a hysteresis loop. We find that with increasing the network sparsity, both $T_{cold}$ and $T_{hot}$ decrease. But the slope of decreasing $T_{hot}$ with sparsity is larger than the slope of decreasing $T_{cold}$. Hence, the hysteresis region gets narrower, until, in a certain sparsity, it disappears. We provide a phase diagram in the temperature-tie density plane to observe the meta-stable/coexistence region behavior more accurately. Then we justify our Mean-Field results with a series of Monte-Carlo simulations.

physics.soc-ph↗

arXiv2021

Mean-Field Solution for Critical Behavior of Signed Networks in Competitive Balance Theory

Competitive balance model has been proposed as an extension to the balance model to address the conflict of interests in signed networks arXiv:2001.04664 . In this model two different paradigms compete with each other due to the competitive interests to dominate the system and impose their own values. Using mean-field solution method in this paper, we examine the thermal behavior of the competitive balance model. Our results show that under a certain temperature, the symmetry between two competitive interests will spontaneously break which leads to a discrete phase transition. So, starting with a heterogeneous signed network, if agents aim to ultimately decrease tension stemming from balance theory, evolution ultimately chooses only one of the existing interests and stability arises where one paradigm dominates the network. The critical temperature depends linearly on the number of nodes, which was a linear dependence in the thermal balance theory as well. Finally the results obtained through the mean-field theory are verified by a series of simulations.

physics.soc-ph↗

arXiv2021

Altered structural balance of resting-state networks in autism

What makes a network complex, in addition to its size, is the interconnected interactions between elements, disruption of which inevitably results in dysfunction. Likewise, the brain networks' complexity arises from interactions beyond pair connections, as it is simplistic to assume that in complex networks state of a link is independently determined only according to its two constituting nodes. This is particularly of note in genetically complex brain impairments, such as the autism spectrum disorder (ASD), which has a surprising heterogeneity in manifestations with no clear-cut neuropathology. Accordingly, structural balance theory (SBT) affirms that in real-world signed networks, a link is remarkably influenced by each of its two nodes' interactions with the third node within a triadic interrelationship. Thus, it is plausible to ask whether ASD is associated with altered structural balance resulting from atypical triadic interactions. In other words, it is the abnormal interplay of positive and negative interactions that matters in ASD, besides and beyond hypo (hyper) pair connectivity. To address this question, we explore triadic interactions based on SBT in the weighted signed resting-state functional magnetic resonance imaging networks of participants with ASD relative to healthy controls (CON). We demonstrate that balanced triads are overrepresented in the ASD and CON networks while unbalanced triads are underrepresented, providing first-time empirical evidence for the strong notion of structural balance on the brain networks. We further analyze the frequency and energy distributions of different triads and suggest an alternative description for the reduced functional integration and segregation in the ASD brain networks. Moreover, results reveal that the scale of change in the whole-brain networks' energy is more narrow in the ASD networks during development.

q-bio.NC↗

arXiv2021

The structure of gene-gene networks beyond pairwise interactions

Despite its high and direct impact on nearly all biological processes, the underlying structure of gene-gene interaction networks is investigated so far according to pair connections. To address this, we explore the gene interaction networks of the yeast Saccharomyces cerevisiae beyond pairwise interaction using the structural balance theory (SBT). Specifically, we ask whether essential and nonessential gene interaction networks are structurally balanced. We study triadic interactions in the weighted signed undirected gene networks and observe that balanced and unbalanced triads are over and underrepresented in both networks, thus beautifully in line with the strong notion of balance. Moreover, we note that the energy distribution of triads is significantly different in both essential and nonessential networks compared with the shuffled networks. Yet, this difference is greater in the essential network regarding the frequency as well as the energy of triads. Additionally, results demonstrate that triads in the essential gene network are more interconnected through sharing common links, while in the nonessential network they tend to be isolated. Last but not least, we investigate the contribution of all-length signed walks and its impact on the degree of balance. Our findings reveal that interestingly when considering longer cycles the nonessential gene network is more balanced compared to the essential network.

q-bio.MN↗

arXiv2021

Hybrid balance theory: Heider balance under higher order interactions

Heider's Balance Theory in signed networks, which consists of friendship or enmity relationships, is a model that relates the type of relationship between two people to the third person. In this model, there is an assumption of the independence of triadic relations, which means that the balance or imbalance of one triangle does not affect another and the energy only depends on the number of each type of triangle. There is evidence that in real network data, in addition to third-order interactions (Heider Balance), higher-order interactions also play a role. One step beyond the Heider Balance, the effect of Quartic Balance has been studied by removing the assumption of triangular independence. Application of quartic balance results in the influence of the balanced or imbalanced state of neighboring triangles on each specific one. Here, a question arises that how the Heider Balance is affected by the existence of Quartic Balance (fourth-order). The phase diagram obtained from the mean-field method shows there is a threshold for higher-order interaction strength, below which a third-order interaction dominates and there are no imbalance triangles in the network, and above this threshold, squares effectively determine the balance state in which the imbalance triangles can survive. The solution of the mean-field indicates that we have a first-order phase transition in terms of random behavior of agents (temperature) which is in accordance with the Monte Carlo simulation results.

physics.soc-ph↗

arXiv2021

Heider and coevolutionary balance: From discrete to continuous phase transition

Structural balance in social complex networks has been modeled with two types of triplet interactions. First, the interaction that only considers dynamic role for links or relationships (Heider balance), and second, the interaction that considers both individual opinions (nodes) and relationships in network dynamics (coevolutionary balance). The question is, as the temperature varies, which is a measure of social disorder, how structural balance can be created or destroyed by each of these triplet interactions? We use statistical mechanics methods and observe through analytical calculation and numerical simulation that unlike the Heider balance triplet interaction which has a discrete phase transition, the coevolutionary balance has a continuous phase transition. The critical temperature of the presented model change with the root square of network size which is a linear dependence in thermal Heider balance.

physics.soc-ph↗

arXiv2021

Heider Balance under Disordered Triadic Interactions

The Heider balance addresses three-body interactions with the assumption that triads are equally important in the dynamics of the network. In many networks, the relations do not have the same strength so, triads are differently weighted. Now, the question is how social networks evolve to reduce the number of unbalanced triangles when they are weighted? Are the results foreseeable based on what we have already learned from the unweighted balance? To find the solution, we consider a fully connected network in which triads are assigned with different random weights. Weights are coming from Gaussian probability distribution with mean $μ$ and variance $σ$. We study this system in two regimes : (\RN{1}) the ratio of $\fracμσ \ge 1 $ corresponds to weak disorder (small variance) that triads' weight are approximately the same, (\RN{2}) $\fracμσ < 1 $ counts for strong disorder (big variance) and weights are remarkably diverse. Investigating the structural evolution of such a network is our intention. We see disorder plays a key role in determining the critical temperature of the system. Using the mean-field method to present an analytic solution for the system represents that the system undergoes a first-order phase transition. For weak disorder, our simulation results display the system reaches the global minimum as temperature decreases whereas for high disorder we manage to see a seudo-Kondo effect in triadic interactions. The Kondo effect explains the anomalous increase in electrical resistivity of metals due to magnetic impurities at low temperatures. Similar behavior is seen in the energy versus temperature in our work for the second regime and the system does not reach a global minimum.

physics.soc-ph↗

arXiv2020

Quartic Balance Theory: Global Minimum With Imbalanced Triangles

Balance theory proposed by Heider for the first time modeled triplet interaction in a signed network, stating that relationships between two people, friendship or enmity, is dependent on a third person. The Hamiltonian of this model has an implicit assumption that all triads are independent, meaning that state of each triad, being balanced or imbalanced, is ineffective to others. This independence forces the network to have completely balanced final states. However, there exists evidence indicating that real networks are partially balanced raising the question of what is the mechanism preventing the system to be perfectly balanced. Our suggestion is to consider a quartic interaction which dissolves the triad's independence. We use mean field method to study thermal behavior of such systems where the temperature is a parameter that allows the stochastic behavior of agents. We show that under a certain temperature, the symmetry between balanced and imbalanced triads will spontaneously break and we have a discrete phase transition. As consequence stability arises where either similar balanced or imbalanced triads dominate, hence the system obtains two new imbalanced stable states. In this model, the critical temperature depends on the second power of the number of nodes, which was a linear dependence in thermal balance theory. Our simulations are in good agreement with the results obtained by the mean field method.

physics.soc-ph↗

arXiv2020

Coexistence of exchange bias training effect and spin-orbit torque in IrMn-layer/ferromagnetic-ribbon heterostructures via magnetoimpedance effect

We investigate a possible correlation between spin orbit torque (SOT) and exchange-bias (EB) in IrMn-layer/ferromagnetic-ribbon heterostructure by performing magnetoimpedance (MI) measurements. To uncover this correlation, we benefit from EB training effect probed by MI effect at room temperature. A damping-like SOT driven by ac current through the antiferromagnetic IrMn applies to the ferromagnetic ribbon layer, determined by MI magnetic field and frequency sweeps. Importantly, magnitude of the SOT is observed to remain intact against EB training and decrease of EB through alternative magnetic field sweep cycles. Our results pave the way to better elucidate the EB effect, EB training and the SOT, useful for future spintronic elements.

cond-mat.mes-hall↗

arXiv2020

Coupled criticality analysis of inflation and unemployment

In this paper, we are interested to focus on the critical periods in the economy which are characterized by large fluctuations in macroeconomic indicators. To capture unusual and large fluctuations of inflation and unemployment, we concentrate on the non-Gaussianity of their distributions. To this aim, by using the coupled multifractal approach, we analyze US data for a period of 70 years from 1948 until 2018 and measure the non-Gausianity of the distributions. Then, we investigate how the non-Gaussianity of the variables affects the coupling structure of them. By applying the multifractal method, one can see that the non-Gaussianity depends on the scales. While the non-Gaussianity of unemployment is noticeable only for periods smaller than 1 year and for longer periods tends to Gaussian behavior, the non-Gaussianities of inflation persist for all time scales. Also, it is observed that the coupling structure of these variables tends to a Gaussian behavior after $2$ years.

q-fin.ST↗

arXiv2020

Memory effects on link formation in temporal networks: A fractional calculus approach

Memory plays a vital role in the temporal evolution of interactions of complex systems. To address the impact of memory on the temporal pattern of networks, we propose a simple preferential connection model, in which nodes have a preferential tendency to establish links with most active nodes. Node activity is measured by the number of links a node observes in a given time interval. Memory is investigated using a time-fractional order derivative equation, which has proven to be a powerful method to understand phenomena with long-term memory. The memoryless case reveals a characteristic time where node activity behaves differently below and above it. We also observe that dense temporal networks (high number of events) show a clearer characteristic time than sparse ones. Interestingly, we also find that memory leads to decay of the node activity; thus, the chances of a node to receive new connections reduce with the node's age. Finally, we discuss the statistical properties of the networks for various memory-length.

physics.soc-ph↗

arXiv2019

Controlling Magnetization of Gr/Ni Composite for Application in High Performance Magnetic Sensors

Graphene (Gr), a well-known 2D material, has been under intensive investigation in the last decade due to its high potential applications in industry and advanced technological elements. The Gr, while composed with magnetic materials, has opened new opportunities for further developments of magnetic based devices. Here, we report a mass production of Gr/Ni composite powders using electrochemical exfoliation/deposition method with different magnetic strengths of the final composite material. We applied the magnetic composite materials in a magnetoimpedance (MI) based sensor and observed significant enhancement in the MI effect and its field sensitivity. Such magnetic composites with controlled magnetization strengths are coated on the MI-ribbon sensor surface and different MI responses are observed. The MI response of a ribbon coated with a Gr/Ni layer is theoretically determined based on an electrodynamic model with a qualitative consistency between the experimental results and the theoretical model. Our comprehensive study can be applied in high performance functionalized MI based magnetic sensors and devices.

physics.app-ph↗

arXiv2019

Mean-field solution of structural balance dynamics in nonzero temperature

In signed networks with simultaneous friendly and hostile interactions, there is a general tendency to a global structural balance, based on the dynamical model of links status. Although the structural balance represents a state of the network with a lack of contentious situations, there are always tensions in real networks. To study such networks, we generalize the balance dynamics in nonzero temperatures. The presented model uses elements from Boltzmann-Gibbs statistical physics to assign an energy to each type of triad, and it introduces the temperature as a measure of tension tolerance of the network. Based on the mean-field solution of the model, we find out that the model undergoes a first-order phase transition from an imbalanced random state to structural balance with a critical temperature $T_{c}$, where in the case of $T > T_{c}$ there is no chance to reach the balanced state. A main feature of the first-order phase transition is the occurrence of a hysteresis loop crossing the balanced and imbalanced regimes.

physics.soc-ph↗

arXiv2018

Dynamical phase diagrams of a love capacity constrained prey-predator model

One interesting question in love relationships is: finally, what and when is the end of this love relationship? Using a prey-predator Verhulst-Lotka-Volterra (VLV) model we imply cooperation and competition tendency between people in order to describe a "love dilemma game". We select the most simple but immediately most complex case for studying the set of nonlinear differential equations, i.e. that implying three persons, being at the same time prey and predator. We describe four different scenarios in such a love game containing either a one-way love or a love triangle. Our results show that it is hard to love more than one person simultaneously. Moreover, to love several people simultaneously is an unstable state. We find some condition in which persons tend to have a friendly relationship and love someone in spite of their antagonistic interaction. We demonstrate the dynamics by displaying flow diagrams.

physics.soc-ph↗

arXiv2017

Glassy states of aging social networks

Individuals often develop reluctance to change their social relations, called "secondary homebody", even though their interactions with their environment evolve with time. Some memory effect is loosely present deforcing changes. In other words, in presence of memory, relations do not change easily. In order to investigate some history or memory effect on social networks, we introduce a temporal kernel function into the Heider conventional balance theory, allowing for the "quality" of past relations to contribute to the evolution of the system. This memory effect is shown to lead to the emergence of aged networks, thereby perfectly describing and the more so measuring the aging process of links ("social relations"). It is shown that such a memory does not change the dynamical attractors of the system, but does prolong the time necessary to reach the "balanced states". The general trend goes toward obtaining either global ("paradise" or "bipolar") or local ("jammed") balanced states, but is profoundly affected by aged relations. The resistance of elder links against changes decelerates the evolution of the system and traps it into so named glassy states. In contrast to balance

physics.soc-ph↗