arXiv subjects

Hans J. Herrmann

Publications and source records attributed to Hans J. Herrmann.

At least 19 recordsLinked to original sources

arXiv2026

Residual Saturation under Pressure-Controlled Drainage

Here, pressure-controlled drainage is formulated as bond percolation with trapping on the pore-network graph, establishing a direct connection between percolation theory and pressure--saturation relations. In two dimensions, the deviation of the residual saturation from its non-vanishing thermodynamic limit obeys a finite-size scaling law with exponent $\delta \approx 0.25$, independent of microscopic details of the lattice. In three dimensions, finite-size corrections decay more rapidly ($\delta \approx 0.75$), while the asymptotic residual saturation remains finite and depends on coordination number. This extends the standard invasion-percolation picture beyond the breakthrough state, where the invading cluster is fractal and the invaded-phase saturation vanishes in the infinite-size limit.

cond-mat.stat-mech↗

arXiv2026

Tricriticality and chaos in a generalized Allee-logistic map

We present a novel nonlinear dynamical model, the generalized Allee-logistic (GAL) map given by $x_{t+1} = r x_t (1 - x_t) G(x_t)$ where $G(x_t) = m (x_t - h) + 1 - m$ incorporates the Allee effect with magnitude $m$ and threshold $h$. The case $m = 0$ yields the logistic map with a continuous transition to extinction. Conversely, $m = 1$ recovers a previously studied model that undergoes only a discontinuous extinction-to-active transition. Between these extremes, the GAL map exhibits nontrivial phenomena, including tricriticality with a closed-form expression for the tricritical point and a universal crossover function. Under a small external input, we verify Widom-like relations. We also note that the Allee effect disfavors the onset of chaos. Our work establishes additional bridges between analytically tractable chaotic maps, nonequilibrium tricriticality, and Allee effects.

nlin.CD↗

arXiv2025

Allometric scaling of brain activity explained by avalanche criticality

Allometric scaling laws, such as Kleiber's law for metabolic rate, highlight how efficiency emerges with size across living systems. The brain, with its characteristic sublinear scaling of activity, has long posed a puzzle: why do larger brains operate with disproportionately lower firing rates? Here we show that this economy of scale is a universal outcome of avalanche dynamics. We derive analytical scaling laws directly from avalanche statistics, establishing that any system governed by critical avalanches must exhibit sublinear activity-size relations. This theoretical prediction is then verified in integrate-and-fire neuronal networks at criticality and in classical self-organized criticality models, demonstrating that the effect is not model-specific but generic. The predicted exponents align with experimental observations across mammal species, bridging dynamical criticality with the allometry of brain metabolism. Our results reveal avalanche criticality as a fundamental mechanism underlying Kleiber-like scaling in the brain.

q-bio.NC↗

arXiv2025

Loewner Evolution for Critical Invasion Percolation Tree

Extending the Schramm--Loewner Evolution (SLE) to model branching structures while preserving conformal invariance and other stochastic properties remains a formidable research challenge. Unlike simple paths, branching structures, or trees, must be associated with discontinuous driving functions. Moreover, the driving function of a particular tree is not unique and depends on the order in which the branches are explored during the SLE process. This study investigates trees formed by nontrapping invasion percolation (NTIP) within the SLE framework. Three strategies for exploring a tree are employed: the invasion percolation process itself, Depth--First Search (DFS), and Breadth--First Search (BFS). We analyze the distributions of displacements of the Loewner driving functions and compute their spectral densities. Additionally, we investigate the inverse problem of deriving new traces from the driving functions, achieving a reasonably accurate reconstruction of the tree-like structures using the BFS and NTIP methods. Our results suggest the lack of conformal invariance in the exploration paths of the trees, as evidenced by the non-Brownian nature of the driving functions for the BFS and NTIP methods, and the inconsistency of the diffusion constants for the DFS method.

cond-mat.stat-mech↗

arXiv2024

Coastlines violate the Schramm-Loewner Evolution

Mandelbrot's empirical observation that the coast of Britain is fractal has been confirmed by many authors, but it can be described by the Schramm--Loewner Evolution? Since the self-affine surface of our planet has a positive Hurst exponent, one would not expect a priori any critical behavior. Here, we investigate numerically the roughness and fractal dimension of the isoheight lines of real and artificial landscapes. Using a novel algorithm to take into account overhangs, we find that the roughness exponent of isoheight lines is consistent with unity regardless of the Hurst exponent of the rough surface. Moreover, the effective fractal dimension of the iso-height lines decays linearly with the Hurst exponent of the surface. We perform several tests to verify if the complete and accessible perimeters would follow the Schramm--Loewner Evolution and find that the left passage probability test is clearly violated, implying that coastlines violate SLE.

cond-mat.stat-mech↗

arXiv2024

Modeling public opinion control by a charismatic leader

We study the average long-time behavior of the binary opinions of a social group with peer-to-peer interactions under the influence of an external bias and a persuadable leader, a strongly-biased agent with a dynamic opinion with the intention of spreading it across the system. We use a generalized, fully-connected Ising model, with each spin representing the binary opinion of an agent at a given time and a single, super spin representing the opinion of the leader. External fields and interaction constants model the opinion bias and peer-to-peer interactions, respectively, while the temperature $T$ models an idealized social climate, representing an authoritarian regime if $T$ is low or a liberal one if $T$ is high. We derive a mean-field solution for the average magnetization $m$, the "social mood", and investigate how $m$ and the super spin magnetization vary as a function of $T$. We find that, depending on the initial conditions, due to the presence of metastable states, the sign of the average magnetization depends on the temperature. Finally, we verify that this effect is also present even if we consider only nearest-neighbor interactions within the social group.

cond-mat.stat-mech↗

arXiv2023

Tricritical behavior in epidemic dynamics with vaccination

We scrutinize the phenomenology arising from a minimal vaccination-epidemic (MVE) dynamics using three methods: mean-field approach, Monte Carlo simulations, and finite-size scaling analysis. The mean-field formulation reveals that the MVE model exhibits either a continuous or a discontinuous active-to-absorbing phase transition, accompanied by bistability and a tricritical point. However, on square lattices, we detect no signs of bistability, and we disclose that the active-to-absorbing state transition has a scaling invariance and critical exponents compatible with the continuous transition of the directed percolation universality class. Additionally, our findings indicate that the tricritical and crossover behaviors of the MVE dynamics belong to the universality class of mean-field tricritical directed percolation.

physics.soc-ph↗

arXiv2022

Random networks with q-exponential degree distribution

We use the configuration model to generate networks having a degree distribution that follows a $q$-exponential, $P_q(k)=(2-q)λ[1-(1-q)λk]^{1/(q-1)}$, for arbitrary values of the parameters $q$ and $λ$. We study the assortativity and the shortest path of these networks finding that the more the distribution resembles a pure power law, the less well connected are the corresponding nodes. In fact, the average degree of a nearest neighbor grows monotonically with $λ^{-1}$. Moreover, our results show that $q$-exponential networks are more robust against random failures and against malicious attacks than standard scale-free networks. Indeed, the critical fraction of removed nodes grows logarithmically with $λ^{-1}$ for malicious attacks. An analysis of the $k_s$-core decomposition shows that $q$-exponential networks have a highest $k_s$-core, that is bigger and has a larger $k_s$ than pure scale-free networks. Being at the same time well connected and robust, networks with $q$-exponential degree distribution exhibit scale-free and small-world properties, making them a particularly suitable model for application in several systems.

cond-mat.stat-mech↗

arXiv2022

On the scaling of avalanche shape and activity power spectrum in neuronal networks

Many systems in Nature exhibit avalanche dynamics with scale-free features. A general scaling theory has been proposed for critical avalanche profiles in crackling noise, predicting the collapse onto a universal avalanche shape, as well as the scaling behaviour of the activity power spectrum as Brown noise. Recently, much attention has been given to the profile of neuronal avalanches, measured in neuronal systems in vitro and in vivo. Although a universal profile was evidenced, confirming the validity of the general scaling theory, the parallel study of the power spectrum scaling under the same conditions was not performed. The puzzling observation is that in the majority of healthy neuronal systems the power spectrum exhibits a behaviour close to $1/f$, rather than Brown, noise. Here we perform a numerical study of the scaling behaviour of avalanche shape and power spectrum for a model of integrate and fire neurons with a short-term plasticity parameter able to tune the system to criticality. We confirm that, at criticality, the average avalanche size and the avalanche profile fulfill the general avalanche scaling theory. However, the power spectrum consistently exhibits Brown noise behaviour, for both fully excitatory networks and systems with 30\% inhibitory networks. Conversely, a behaviour closer to $1/f$ noise is observed in systems slightly off-criticality. Results suggest that the power spectrum is a good indicator to determine how close neuronal activity is to criticality.

q-bio.NC↗

arXiv2022

Curvature-induced quantum spin-Hall effect on a Möbius strip

The quantum Hall effect has been predicted and discovered in various condensed-matter systems. A promising quantum material for such topological effects is graphene. We report the numerical observation of a curvature-induced spin-Hall effect in a monolayer graphene Möbius strip. The solution of the Dirac equation on the nontrivial and non-Euclidean manifold reveals that despite the absence of a Hall current, a spin-Hall current is a natural consequence for such a topology, as predicted from symmetry arguments.

cond-mat.mes-hall↗

arXiv2021

Self-similar but not conformally invariant traces obtained by modified Loewner forces

The two-dimensional Loewner exploration process is generalized to the case where the random force is self-similar with positively correlated increments. We model this random force by a fractional Brownian motion with Hurst exponent $H\geq \frac{1}{2}\equiv H_{\text{BM}}$, where $H_{\text{BM}}$ stands for the one-dimensional Brownian motion. By manipulating the deterministic force, we design a scale-invariant equation describing self-similar traces which lack conformal invariance. The model is investigated in terms of the "input diffusivity parameter" $κ$, which coincides with the one of the ordinary Schramm-Loewner evolution (SLE) at $H=H_{\text{BM}}$. In our numerical investigation, we focus on the scaling properties of the traces generated for $κ=2,3$, $κ=4$ and $κ=6,8$ as the representatives, respectively, of the dilute phase, the transition point and the dense phase of the ordinary SLE. The resulting traces are shown to be scale-invariant. Using two equivalent schemes, we extract the fractal dimension, $D_f(H)$, of the traces which decrease monotonically with increasing $H$, reaching $D_f=1$ at $H=1$ for all $κ$ values. The left passage probability (LPP) test demonstrates that, for $H$ values not far from the uncorrelated case (small $ε_H\equiv \frac{H-H_{\text{BM}}}{H_{\text{BM}}}$) the prediction of the ordinary SLE is applicable with an effective diffusivity parameter $κ_{\text{eff}}$. Not surprisingly, the $κ_{\text{eff}}$'s do not fulfill the prediction of SLE for the relation between $D_f(H)$ and the diffusivity parameter.

cond-mat.stat-mech↗

arXiv2021

Morphological transition between patterns formed by threads of magnetic beads

Magnetic beads attract each other forming chains. We pushed such chains into an inclined Hele-Shaw cell and discovered that they spontaneously form self-similar patterns. Depending on the angle of inclination of the cell, two completely different situations emerge, namely, above the static friction angle the patterns resemble the stacking of a rope and below they look similar to a fortress from above. Moreover, locally the first pattern forms a square lattice, while the second pattern exhibits triangular symmetry. For both patterns, the size distributions of enclosed areas follow power laws. We characterize the morphological transition between the two patterns experimentally and numerically and explain the change in polarization as a competition between friction-induced buckling and gravity.

cond-mat.stat-mech↗

arXiv2021

Phase transitions in a conservative Game of Life

We investigate the dynamics of a conservative version of Conway's Game of Life, in which a pair consisting of a dead and a living cell can switch their states following Conway's rules but only by swapping their positions, irrespective of their mutual distance. Our study is based on square-lattice simulations as well as a mean-field calculation. As the density of dead cells is increased, we identify a discontinuous phase transition between an inactive phase, in which the dynamics freezes after a finite time, and an active phase, in which the dynamics persists indefinitely in the thermodynamic limit. Further increasing the density of dead cells leads the system back to an inactive phase via a second transition, which is continuous on the square lattice but discontinuous in the mean-field limit.

cond-mat.stat-mech↗

arXiv2020

Thermostat for a relativistic gas

Molecular dynamics simulations of a three dimensional relativistic gas with a soft potential are conducted with different interactions and particle masses. For all cases the velocity distribution agrees numerically with the Jüttner distribution. We show how the relativistic gas can be coupled to a thermostat to simulate the canonical ensemble at a given temperature T. The behaviour of the thermostat is investigated as a function of the thermal inertia and its appropriate range is determined by evaluating the kinetic energy fluctuations.

cond-mat.stat-mech↗

arXiv2020

Simulating isothermal aging of snow

A Monte Carlo algorithm to simulate the isothermal recrystallization process of snow is presented. The snow metamorphism is approximated by two mass redistribution processes, surface diffusion and sublimation-deposition. The algorithm is justified and its parametrization is determined. The simulation results are compared to experimental data, in particular, the temporal evolution of the specific surface area and the ice thickness. We find that the two effects of surface diffusion and sublimation-deposition can accurately model many aspects of the isothermal metamorphism of snow. Furthermore, it is shown that sublimation-deposition is the dominant contribution for temperatures close to the melting point, whereas surface diffusion dominates at temperatures far below the melting point. A simple approximation of gravitational compaction is implemented to simulate density change.

cond-mat.soft↗

arXiv2020

Spatio-temporal characteristics of dengue outbreaks

After their re-emergence in the last decades, dengue fever and other vector-borne diseases are a potential threat to the lives of millions of people. Based on a data set of dengue cases in the Brazilian city of Fortaleza, collected from 2011 to 2016, we study the spatio-temporal characteristics of dengue outbreaks to characterize epidemic and non-epidemic years. First, we identify regions that show a high prevalence of dengue cases and mosquito larvae in different years and also analyze their corresponding correlations. Our results show that the characteristic correlation length of the epidemic is of the order of the system size, suggesting that factors such as citizen mobility may play a major role as a drive for spatial spreading of vector-borne diseases. Inspired by this observation, we perform a mean-field estimation of the basic reproduction number and find that our estimated values agree well with the values reported for other regions, pointing towards similar underlying spreading mechanisms. These findings provide insights into the spreading characteristics of dengue in densely populated areas and should be of relevance for the design of improved disease containment strategies.

physics.soc-ph↗

arXiv2019

Three cooperative mechanisms required for recovery after brain damage

Stroke is one of the main causes of human disabilities. Experimental observations indicate that several mechanisms are activated during the recovery of functional activity after a stroke. Here we unveil how the brain recovers by explaining the role played by three mechanisms: Plastic adaptation, hyperexcitability and synaptogenesis. We consider two different damages in a neural network: A diffuse damage that simply causes the reduction of the effective system size and a localized damage, a stroke, that strongly alters the spontaneous activity of the system. Recovery mechanisms observed experimentally are implemented both separately and in a combined way. Interestingly, each mechanism contributes to the recovery to a limited extent. Only the combined application of all three together is able to recover the spontaneous activity of the undamaged system. This explains why the brain triggers independent mechanisms, whose cooperation is the fundamental ingredient for the system recovery.

q-bio.NC↗

arXiv2019

The Impact of Technologies in Political Campaigns

Recent political campaigns have demonstrated how technologies are used to boost election outcomes by microtargeting voters. We propose and analyze a framework which analyzes how political activists use technologies to target voters. Voters are represented as nodes of a network. Political activists reach out locally to voters and try to convince them. Depending on their technological advantage and budget, political activists target certain regions in the network where their activities are able to generate the largest vote-share gains. Analytically and numerically, we quantify vote-share gains and savings in terms of budget and number of activists from employing superior targeting technologies compared to traditional campaigns. Moreover, we demonstrate that the technological precision must surpass a certain threshold in order to lead to a vote-share gain or budget advantage. Finally, by calibrating the technology parameters to the recent U.S. presidential election, we show that a pure targeting technology advantage is consistent with Trump winning against Clinton.

physics.soc-ph↗