arXiv subjects

Farhad Shahbazi

Publications and source records attributed to Farhad Shahbazi.

At least 19 recordsLinked to original sources

arXiv2026

Supernova Neutrinos and the Origin of Biomolecular Homochirality

We investigate the role of parity-violating interactions between supernova neutrinos and chiral molecules in nearby interstellar molecular clouds as a potential source of biomolecular homochirality. We introduce neutrino interactions into the autocatalytic chemical reactions in a far-from-equilibrium noise-induced system. These interactions create a directional bias between L and D enantiomers in the racemization reactions, which is amplified by autocatalysis and stochastic fluctuations. We solve the stochastic equations within the Ito sense to obtain the dynamics of the probability distribution of the enantiomeric excesses, offering an astrophysical scenario for the delivery of homochirality seeds to Earth by meteorites. In spite of the weak interactions of supernova neutrinos, our framework introduces an amplification mechanism to yield a considerable enantiomeric excess of more than $10\%$, in agreement with the latest chemical analysis of the meteorites. Moreover, we scan over the parameter space of the model, inferring from the observational values in order to explore the window of opportunity to generate the initial seeds of homochiral states in interstellar molecular clouds.

astro-ph.HE↗

arXiv2026

Nonlinear effects in a strongly coupled Nanoelectromechanical System

Controlling nonlinear effects in micro- and nano-electro-mechanical systems is essential for unlocking their full potential in sensing, signal processing, and frequency control. In this study, we develop a voltage-dependent Hamiltonian framework for a nanoelectromechanical resonator with two strongly coupled vibrational modes, representative of a nanostring platform. The mode frequencies and couplings of the system are tuned electrostatically using a DC voltage, which also controls the strength of the interactions. Our theoretical model reproduces the experimentally observed avoided crossing in the absence of an AC drive and generates tunable frequency-comb spectra when a parametric drive is applied. By scanning the DC voltage, we generate a phase diagram that links comb formation and sharp regime boundaries to underlying bifurcations, multi-stability, and attractor switching. Phase-resolved diagnostics based on a Kuramoto order parameter, together with autocorrelation and Poincaré analyses, quantify coherence and critical slowing down near these transitions. We further explore the relationship between nonlinear coupling, parametric excitation, and stability transitions within a single device of experimental relevance and establish a dynamical framework for engineering nanoelectromechanical resonators that offer enhanced tunability, functionality, and a predictive link to experimental outcomes.

cond-mat.mes-hall↗

arXiv2025

Time-Delayed Dynamics in Regular Kuramoto Networks with Inertia: Multistability, Traveling Waves, Chimera States, and Transitions to Seizure-Like Activity

This study examines the complex interplay between inertia and time delay in regular rotor networks within the framework of the second-order Kuramoto model. By combining analytical and numerical methods, we demonstrate that intrinsic time delays -- arising from finite information transmission speeds - induce multistability among fully synchronized phase-locked states. Unlike systems without inertia, the presence of inertia destabilizes these phase-locked states, reduces their basin of attraction, and gives rise to nonlinear phase-locked dynamics over specific inertia ranges. In addition, we show that time delays promote the emergence of turbulent chimera states, while inertia enhances their spatial extent. Notably, the combined influence of inertia and time delay produces dynamic patterns reminiscent of partial epileptic seizures. These findings provide new insights into synchronization phenomena by revealing how inertia and time delay fundamentally reshape the stability and dynamics of regular rotor networks, with broader implications for neuronal modeling and other complex systems.

nlin.AO↗

arXiv2025

Complexity of Financial Time Series: Multifractal and Multiscale Entropy Analyses

We employed Multifractal Detrended Fluctuation Analysis (MF-DFA) and Refined Composite Multiscale Sample Entropy (RCMSE) to investigate the complexity of Bitcoin, GBP/USD, gold, and natural gas price log-return time series. This study provides a comparative analysis of these markets and offers insights into their predictability and associated risks. Each tool presents a unique method to quantify time series complexity. The RCMSE and MF-DFA methods demonstrate a higher complexity for the Bitcoin time series than others. It is discussed that the increased complexity of Bitcoin may be attributable to the presence of higher nonlinear correlations within its log-return time series.

q-fin.ST↗

arXiv2025

Synchronization of the time-delayed Kuramoto model in a regular network

This study investigates the impact of delayed coupling on the global and local synchronization of identical coupled oscillators residing in a ring. Utilizing the Kuramoto model, we examine the effects of delayed coupling on collective dynamics. Our analytical and numerical results reveal distinct synchronization behaviors across various time delay regimes, including fully synchronized states, helical patterns, dynamically incoherent states, and random phase-locked states. We identify the regime in which time delay inhibits synchrony, which aligns with theoretical predictions derived from stability analysis. In the region between the synchrony-possible and synchrony-forbidden zones, a coexistence of synchronized and unsynchronized dynamics is observed, referred to as Chimera states. We ascertain that the type of Chimera states present is moving-turbulent.

nlin.AO↗

arXiv2024

Synchronization of two coupled massive oscillators in the time-delayed Kuramoto model

We examine the impact of time delay on two coupled massive oscillators within the second-order Kuramoto model, which is relevant to the operations of real-world networks that rely on signal transmission speed constraints. Our analytical and numerical exploration shows that time delay can cause multi-stability within phase-locked solutions, and the stability of these solutions decreases as inertia increases. In addition to phase-locked solutions, we discovered non-phase-locked solutions that exhibit periodic and chaotic behaviors, depending on the amount of inertia and time delay.

nlin.CD↗

arXiv2022

Do Cellular Automaton Avalanche Models Simulate the Quasi-Periodic Pulsations of Solar Flares?

Quasi-periodic pulsations (QPPs) with various periods that originate in the underlying magnetohydrodynamic processes of the flaring structures are detected repeatedly in the solar flare emissions. We apply a 2D cellular automaton (CA) avalanche model to simulate QPPs as a result of a repetitive load/unload mechanism. We show that the frequent occurrence of magnetic reconnections in a flaring loop could induce quasi-periodic patterns in the detected emissions. We obtain that among 21070 simulated flares, 813 events endure over 50 seconds, scaled with the temporal resolution of the Yohkoh Hard X-ray Telescope, and about 70 percent of these rather long-lasting events exhibit QPPs. We also illustrate that the applied CA model provides a wide range of periodicities for QPPs. Furthermore, we observe the presence of multiple periods in nearly 50 percent of the cases applying the Lomb-Scargle periodogram. A lognormal distribution is fitted to the unimodal distribution of the periods as a manifestation of an underlying multiplicative mechanism that typifies the effect of the system's independent varying parameters. The global maximum of the periods' lognormal distribution is located at 29.29 seconds. We compare statistics of the simulated QPPs with parameters of the host flares and discuss the impacts of flare properties on QPPs' periods. Considering the intrinsic characteristic of CA models, namely the repetitive load/unload mechanism, and the obtained pieces of evidence, we suggest that CA models may generate QPPs. We also examine the applicability of the autoregressive integrated moving average models to describe the simulated and observational QPPs.

astro-ph.SR↗

arXiv2022

Synchronization of frustrated phase oscillators in the small-world networks

We numerically study the synchronization of an identical population of Kuramoto-Sakaguchi phase oscillators in Watts-Strogatz networks. We find that, unlike random networks, phase-shift could enhance the synchronization in small-world networks. We also observe abrupt phase transition with hysteresis at some values of phase shifts in small-world networks, signs of an explosive phase transition. Moreover, we report the emergence of Chimera states at some values of phase-shift close to the transition points, which consist of spatially coexisting synchronized and desynchronized domains.

nlin.AO↗

arXiv2020

Contrariety and Inhibition enhance synchronization in a small-world network of phase oscillators

We numerically study the Kuramoto model's synchronization consisting of the two groups of conformist-contrarian and excitatory-inhibitory phase oscillators with equal intrinsic frequency. We consider random and small-world (SW) topologies for the connectivity network of the oscillators. In random networks, regardless of the contrarian to conformist connection strength ratio, we found a crossover from the $π$-state to the blurred $π$-state and then a continuous transition to the incoherent state by increasing the fraction of contrarians. However, for the excitatory-inhibitory model in a random network, we found that for all the values of the fraction of inhibitors, the two groups remain in-phase, and the transition point of fully synchronized to incoherent state reduced by strengthening the ratio of inhibitory to excitatory links. In the SW networks, we found that the order parameters for both models have not monotonic behavior in terms of the fraction of contrarians and inhibitors. Up to the optimal fraction of contrarians inhibitors, the synchronization rises by introducing the contrarians and inhibitors and then falls. We discuss that this non-monotonic behavior in synchronization is due to the weakening of the defects formed already in conformists and excitatory agents in SW networks.

nlin.CD↗

arXiv2019

Spike-Phase Coupling As an Order Parameter in a Leaky Integrate-and-Fire Model

While criticality is widely observed in neural networks, its underlying neural mechanism is not known well. We consider a network of $N$ excitatory leaky integrated and fire (LIF) neurons that reside on a regular lattice with periodic boundary conditions. The cooperation between neurons, $K$, plays the role of the control parameter that is expected to generate criticality when the critical cooperation strength, $K_c$, is adopted. We show that the coupling between spike timing and the phase of temporal fluctuations of a cooperative activity of the network, i.e. population-averaged voltage (PAV), resorts to identifying an order parameter. By increasing $K$, we find a continuous transition from irregular spiking to a phase-locked state at the critical point, $K_c$. Moreover, we deploy the finite-size scaling analysis to obtain the critical exponents of this transition. We also show that the neuronal avalanches created at this critical point, display a remarkable scaling behavior with the exponents in a fair agreement with the experimental values.

nlin.AO↗

arXiv2019

Ab initio investigation of magnetic ordering in the double perovskite Sr$_{2}$NiWO$_{6}$

{\it Ab initio} calculations, GGA/GGA+$U$, are used to propose a spin Hamiltonian for the B-site ordered double perovskite, Sr$_{2}$NiWO$_{6}$. Our results show that the exchange interaction constants between the next nearest neighbors in both intra- and inter- $ab$ plane ($J_2$ and $J_{2c}$) are an order of magnitude larger than the ones between the nearest neighbors ($J_1$ and $J_{1c}$). Employing the Monte Carlo simulation, we show that the obtained Hamiltonian properly describes the finite temperature properties of Sr$_{2}$NiWO$_{6}$. Our {\it ab initio} calculations also reveal a small magnetic anisotropy and non-trivial bi-quadratic interaction between the nearest inter-$ab$ plane neighbors, which play essential roles in stabilizing the type-II anti-ferromagnetic ground state of Sr$_{2}$NiWO$_{6}$.

cond-mat.str-el↗

arXiv2018

Crossover between tricritical and Lifshitz points in pyrochlore FeF$_{3}$

Pyrochlore FeF$_{3}$ (pyr-FeF$_{3}$) is a Heisenberg anti-ferromagnetic (AF) with a magnetic susceptibility deviating from the Curie-Weiss law, even at the room temperature. This compound shows a transition to a long-range ordered state with all-in all-out (AIAO) spin configuration. The critical properties of this transition have remained a matter of dispute. In this work, to gain more insight into the critical properties of pyr-FeF$_{3}$, using ab initio density functional theory (DFT), we obtain spin Hamiltonian of this material under the relative volume change with respect to the experimental volume ($\frac{ΔV}{V_0}$) from $-0.2$ to $0.2$. We show that the relevant terms in the spin Hamiltonians are the AF exchange up to third neighbors, the nearest neighbor bi-quadratic and the direct Dyzaloshinski-Moriya (DM) interactions and find how these coupling constants vary under the volume change. Then we study the effect of volume change on the finite temperature critical behavior, using classical Monte Carlo (MC) simulation. We show that the spin system undergoes a weakly first order transition to AIAO at small volumes which turns to a second order transition close to the experimental structure. However, increasing $\frac{ΔV}{V_0}$ to $\sim0.2$, systems shows a transition to a modular spin structure. This finding suggests the existence of a Lifshitz point in pyr-FeF$_{3}$ and may explain the unusual critical exponents observed for this compound.

physics.comp-ph↗

arXiv2017

Origin of magnetic frustration in Bi$_3$Mn$_4$O$_{12}$(NO$_3$)

Bi$_3$Mn$_4$O$_{12}$(NO$_3$) (BMNO) is a honeycomb bilayers anti-ferromagnet, not showing any ordering down to very low temperatures despite having a relatively large Curie-Weiss temperature. Using ab initio density functional theory, we extract an effective spin Hamiltonian for this compound. The proposed spin Hamiltonian consists of anti-ferrimagnetic Heisenberg terms with coupling constants ranging up to third intra-layer and fourth inter-layer neighbors. Performing Monte Carlo simulation, we obtain the temperature dependence of magnetic susceptibility and so the Curie-Weiss temperature and find the coupling constants which best matches with the experimental value. We discover that depending on the strength of the interlayer exchange couplings, two collinear spin configurations compete with each other in this system. Both states have in plane N{é}el character, however, at small interlayer coupling spin directions in the two layers are antiparallel (N$_1$ state) and discontinuously transform to parallel (N$_2$ state) by enlarging the interlayer couplings at a first order transition point. Classical Monte Carlo simulation and density matrix renormalization group calculations confirm that exchange couplings obtained for BMNO are in such a way that put this material {at the phase boundary of a first order phase transition}, where the trading between these two collinear spin states prevents it from setting in a magnetically ordered state.

cond-mat.str-el↗

arXiv2017

Complexity of eye fixation duration time series in reading of Persian texts: A multifractal detrended fluctuation analysis

There is growing evidence that cognitive processes may have fractal structures as a signature of complexity. It is an an ongoing topic of research to study the class of complexity and how it may differ as a function of cognitive variables. Here, we explore the eye movement trajectories generated during reading different Persian texts. Features of eye movement trajectories were recorded during reading Persian texts using an eye tracker. We show that fixation durations, as the main components of eye movements reflecting cognitive processing, exhibits multifractal behavior. This indicates that multiple exponents are needed to capture the neural and cognitive processes involved in decoding symbols to derive meaning. We test whether multifractal behavior varies as a function of two different fonts, familiarity of the text for readers, and reading silently or aloud, and goal-oriented versus non-goal-oriented reading. We find that, while mean fixation duration is affected by some of these factors, the multifractal pattern in time series of eye fixation durations did not change significantly. Our results suggest that multifractal dynamics may be intrinsic to the reading process.

physics.data-an↗

arXiv2017

The effects of noise and time delay on the synchronization of the Kuramoto model in small-world networks

We study the synchronization of a small-world network of identical coupled phase oscillators with Kuramoto interaction. First, we consider the model with instantaneous mutual interaction and the normalized coupling constant to the degree of each node. For this model, similar to the constant coupling studied before, we find the existence of various attractors corresponding to the different defect patterns and also the noise enhanced synchronization when driven by an external uncorrelated white noise. We also investigate the synchronization of the model with homogenous time-delay in the phase couplings. For a given intrinsic frequency and coupling constant, upon varying the time delay we observe the existence a partially synchronized state with defect patterns which transforms to an incoherent phase characterized by randomly phase locked states. By further increasing of the time delay, this phase again undergoes a transition to another patterned partially synchronized state. We show that the transition between theses phases are discontinuous and moreover in each phase the average frequency of the oscillators decreases by increasing the time delay and shows an upward jump at the transition points.

cond-mat.dis-nn↗

arXiv2016

Neuronal Avalanches: Where Temporal Complexity and Criticality Meet

The model of the current paper is an extension of a previous publication, wherein we used the leaky integrate-and-fire model on a regular lattice with periodic boundary conditions, and introduced the temporal complexity as a genuine signature of criticality. In that work, the power-law distribution of neural avalanches was manifestation of supercriticality rather than criticality. Here, however, we show that continuous solution of the model and replacing the stochastic noise with a Gaussian zero-mean noise leads to the coincidence of power-law display of temporal complexity and spatiotemporal patterns of neural avalanches at the critical point. We conclude that the source of inconsistency may in fact be a numerical artifact originated by the discrete description of the model, which may imply slow numerical convergence of avalanche distribution compared to temporal complexity.

cond-mat.dis-nn↗

arXiv2016

Three phase classification of an uninterrupted traffic flow: a $k$-means clustering study

We investigate the speed time series of the vehicles recorded by a camera at a section of a highway in the city of Isfahan, Iran. Using $k$-means clustering algorithm, we find that the natural number of clustering for this set of data is $3$. This is in agreement with the three-phase theory of uninterrupted traffic flows. According to this theory, the three traffic phases are categorized as {\em free flow} (F), {\em synchronized} (S) and {\em wide moving jam} (J). We obtain the transition speeds and densities at F-S and also S-J transitions. We also apply the Shannon entropy analysis on the speed time series over finite windows, which equips us to monitor in areal time the instant state of a traffic flow.

physics.soc-ph↗

arXiv2016

Exactly solvable spin chain models corresponding to BDI class of topological superconductors

We present an exactly solvable extension of the quantum XY chain with longer range multi-spin interactions. Topological phase transitions of the model are classified in terms of the number of Majorana zero modes which are in turn related to an integer winding number. We further find a general relation between the winding number and the number of Majorana fermions at the ends of an open chain. The present class of exactly solvable models belong to the BDI class in the Altland-Zirnbauer classification (A. Altland, M. R. Zirnbauer, Phys. Rev. B (1997) 55 1142) of topological superconductors. We show that time reversal (TR) symmetry of the spin variables translates into a peculiar particle-hole transformation in the language of Jordan-Wigner (JW) fermions that is accompanied by a π shift in the wave vector ($π$PH). Presence of $π$PH symmetry restricts the winding number of TR symmetric extensions of XY to odd integers. The πPH operator may serve in further detailed classification of topological superconductors.

cond-mat.str-el↗