arXiv subjects

A. K. Hartmann

Publications and source records attributed to A. K. Hartmann.

At least 19 recordsLinked to original sources

arXiv2024

Work Distribution for Unzipping Processes

A simple zipper model is introduced, representing in a simplified way, e.g., the folded DNA double helix or hairpin structures in RNA. The double stranded hairpin is connected to a heat bath at temperature $T$ and subject to an external force $f$, which couples to the free length $L$ of the unzipped sequence. Increasing the force, leads to an zipping/unzipping first-order phase transition at a critical force $f_c(T)$ in the thermodynamic limit of a very large chain. We compute analytically, as a function of temperature $T$ and force $f$, the full distribution $P(L)$ of free lengths in the thermodynamic limit and show that it is qualitatively very different for $f f_c$. Next we consider quasistatic work processes where the force is incremented according to a linear protocol. Having obtained $P(L)$ already allows us to derive an analytical expression for the work distribution $P(W)$ in the zipped phase $f<f_c$ for a long chain. We compute the large-deviation tails of the work distribution explicitly. Our analytical result for the work distribution is compared over a large range of the support down to probabilities as small as $10^{-200}$ with numerical simulations, which were performed by applying sophisticated large-deviation algorithms.

cond-mat.stat-mech↗

arXiv2024

First-passage area distribution and optimal fluctuations of fractional Brownian motion

We study the probability distribution $P(A)$ of the area $A=\int_0^T x(t) dt$ swept under fractional Brownian motion (fB\ m) $x(t)$ until its first passage time $T$ to the origin. The process starts at $t=0$ from a specified point $x=L$. We show that $P(A)$ obeys exact scaling relation $$ P(A) = \frac{D^\frac{1}{2H}}{L^{1+\frac{1}{H}}}\,Φ_H\left(\frac{D^\frac{1}{2H} A}{L^{1+\frac{1}{H}}}\right)\,, $$ where $0<H<1$ is the Hurst exponent characterizing the fBm, $D$ is the coefficient of fractional diffusion, and $Φ_H(z)$ is a scaling function. The small-$A$ tail of $P(A)$ has been recently predicted by Meerson and Oshanin [Phys. Rev. E 105, 064137 (2022)], who showed that it has an essential singularity at $A=0$, the character of which depends on $H$. Here we determine the large-$A$ tail of $P(A)$. It is a fat tail, in particular such that the average value of the first-passage area $A$ diverges for all $H$. We also verify the predictions for both tails by performing simple-sampling as well as large-deviation Monte Carlo simulations. The verification includes measurements of $P(A)$ up to probability densities as small as $10^{-190}$. We also perform direct observations of paths conditioned to the area $A$. For the steep small-$A$ tail of $P(A)$ the "optimal paths", i.e. the most probable trajectories of the fBm, dominate the statistics. Finally, we discuss extensions of theory to a more general first-passage functional of the fBm.

cond-mat.stat-mech↗

arXiv2023

Time-dependent probability density function for partial resetting dynamics

Stochastic resetting is a rapidly developing topic in the field of stochastic processes and their applications. It denotes the occasional reset of a diffusing particle to its starting point and effects, inter alia, optimal first-passage times to a target. Recently the concept of partial resetting, in which the particle is reset to a given fraction of the current value of the process, has been established and the associated search behaviour analysed. Here we go one step further and we develop a general technique to determine the time-dependent probability density function (PDF) for Markov processes with partial resetting. We obtain an exact representation of the PDF in the case of general symmetric Lévy flights with stable index $0<α\le2$. For Cauchy and Brownian motions (i.e., $α=1,2$), this PDF can be expressed in terms of elementary functions in position space. We also determine the stationary PDF. Our numerical analysis of the PDF demonstrates intricate crossover behaviours as function of time.

cond-mat.stat-mech↗

arXiv2023

Metastate analysis of the ground states of two-dimensional Ising spin glasses

Using an efficient polynomial-time ground state algorithm we investigate the Ising spin glass state at zero temperature in two dimensions. For large sizes, we show that the spin state in a central region is independent of the interactions far away, indicating a ``single-state" picture, presumably the droplet model. Surprisingly, a single power law describes corrections to this result down to the smallest sizes studied.

cond-mat.dis-nn↗

arXiv2022

Replica symmetry breaking for Ulam's problem

We study increasing subsequences (IS) for an ensemble of sequences given by permutation of numbers {1,2,...,n}. We consider a Boltzmann ensemble at temperature T. Thus each IS appears with the corresponding Boltzmann probability where the energy is the negative length -l of the IS. For T -> 0, only ground states, i.e. longest IS (LIS) contribute, also called Ulam's problem. We introduce an algorithm which allows us to directly sample IS in perfect equilibrium in polynomial time, for any given sequence and any temperature. Thus, we can study very large sizes. We obtain averages for the first and second moments of number of IS as function of $n$ and confirm analytical predictions. Furthermore, we analyze for low temperature $T$ the sampled ISs by computing the distribution of overlaps and performing hierarchical cluster analyses. In the thermodynamic limit the distribution of overlaps stays broad and the configuration landscape remains complex. Thus, Ulam's problem exhibits replica symmetry breaking. This means it constitutes a model with complex behavior which can be studied numerically exactly in a highly efficient way, in contrast to other RSB-showing models, like spin glasses or NP-hard optimization problems, where no fast exact algorithms are known.

cond-mat.dis-nn↗

arXiv2022

Cutting-Plane Algorithms and Solution Whitening for the Vertex-Cover Problem

The phase-transition behavior of the NP-hard vertex-cover (VC) combinatorial optimization problem is studied numerically by linear programming (LP) on ensembles of random graphs. As the basic Simplex (SX) algorithm suitable for such LPs may produce incomplete solutions for sufficiently complex graphs, the application of cutting-plane (CP) methods is sought. We consider Gomory and {0,1/2} cuts. We measure the probability of obtaining complete solutions with these approaches as a function of the average node degree c and observe transition between typically complete and incomplete phase regions. While not generally complete solutions are obtained for graphs of arbitrarily high complexity, the CP approaches still advance the boundary in comparison to the pure SX algorithm, beyond the known replica-symmetry breaking (RSB) transition at c=e=2.718... . In fact, our results provide evidence for another algorithmic transition at c=2.90(2). Besides this, we quantify the transition between easy and hard solvability of the VC problem also in terms of numerical effort. Further we study the so-called whitening of the solution, which is a measure for the degree of freedom that single vertices experience with respect to degenerate solutions. Inspection of the quantities related to clusters of white vertices reveals that whitening is affected, only slightly but measurably, by the RSB transition.

cond-mat.stat-mech↗

arXiv2021

Ordering Behavior of the Two-Dimensional Ising Spin Glass with Long-Range Correlated Disorder

The standard two-dimensional Ising spin glass does not exhibit an ordered phase at finite temperature. Here, we investigate whether long-range correlated bonds change this behavior. The bonds are drawn from a Gaussian distribution with a two-point correlation for bonds at distance r that decays as $(1+r^2)^{-a/2}$, $a>0$. We study numerically with exact algorithms the ground state and domain wall excitations. Our results indicate that the inclusion of bond correlations does not lead to a spin-glass order at any finite temperature. A further analysis reveals that bond correlations have a strong effect at local length scales, inducing ferro/antiferromagnetic domains into the system. The length scale of ferro/antiferromagnetic order diverges exponentially as the correlation exponent approaches a critical value, $a \to a_c = 0$. Thus, our results suggest that the system becomes a ferro/antiferromagnet only in the limit $a \to 0$.

cond-mat.dis-nn↗

arXiv2018

Vertebrate pollinators: phase transition in a time-dependent generalized traveling-salesperson problem

We introduce a model for the global optimization problem of nectar harvesting by flower visitors, e.g., nectar-feeding bats, as a generalization of the (multiple) traveling-salesperson problem (TSP). The model includes multiple independent animals and many flowers with time-dependent content. This provides an ensemble of realistic combinatorial optimization problems, in contrast to previously studied models like random Satisfiability or standard TSP. We numerically studied the optimum harvesting of these foragers, with parameters obtained from experiments, by using genetic algorithms. For the distribution of travel distances, we find a power-law (or Lévy) distribution, as often found for natural foragers. Note, in contrast to many models, we make no assumption about the nature of the flight-distance distribution, the power law just emerges. This is in contrast to the TSP, where we find in the present study an exponential tail. Furthermore, the optimization problem exhibits a {phase transition}, similar to the TSP, at a critical value for the amount of nectar which can be harvested. This phase transition coincides with a dramatic increase in the typical running time of the optimization algorithm. For the value of the critical exponent nu, describing the divergence of the correlation length, we find nu=1.7(4), which is on the other hand compatible with the value found for the TSP. Finally, we also present data from field experiments in Costa Rica for the resource use for freely visiting flower bats. We found that the temporal patterns in experiments and model agree remarkably, confirming our model. Also the data show that the bats are able to memorize the positions of food sources and optimize, at least partially, their routes.

physics.bio-ph↗

arXiv2014

Analysis of the phase transition in the $2D$ Ising ferromagnet using a Lempel-Ziv string parsing scheme and black-box data-compression utilities

In this work we consider information-theoretical observables to analyze short symbolic sequences, comprising time-series that represent the orientation of a single spin in a $2D$ Ising ferromagnet on a square lattice of size $L^2=128^2$, for different system temperatures $T$. The latter were chosen from an interval enclosing the critical point $T_{\rm c}$ of the model. At small temperatures the sequences are thus very regular, at high temperatures they are maximally random. In the vicinity of the critical point, nontrivial, long-range correlations appear. Here, we implement estimators for the entropy rate, excess entropy (i.e. "complexity") and multi-information. First, we implement a Lempel-Ziv string parsing scheme, providing seemingly elaborate entropy rate and multi-information estimates and an approximate estimator for the excess entropy. Furthermore, we apply easy-to-use black-box data compression utilities, providing approximate estimators only. For comparison and to yield results for benchmarking purposes we implement the information-theoretic observables also based on the well-established M-block Shannon entropy, which is more tedious to apply compared to the the first two "algorithmic" entropy estimation procedures. To test how well one can exploit the potential of such data compression techniques, we aim at detecting the critical point of the $2D$ Ising ferromagnet. Among the above observables, the multi-information, which is known to exhibit an isolated peak at the critical point, is very easy to replicate by means of both efficient algorithmic entropy estimation procedures. Finally, we assess how good the various algorithmic entropy estimates compare to the more conventional block entropy estimates and illustrate a simple modification that yields enhanced results.

cond-mat.stat-mech↗

arXiv2013

Biased and greedy random walks on two-dimensional lattices with quenched randomness: the "greedy" ant within a disordered environment

The principle characteristics of biased greedy random walks (BGRWs) on two-dimensional lattices with real-valued quenched disorder on the lattice edges are studied. Here, the disorder allows for negative edge-weights. In previous studies, considering the negative-weight percolation (NWP) problem, this was shown to change the universality class of the existing, static percolation transition. In the presented study, four different types of BGRWs and an algorithm based on the ant colony optimization (ACO) heuristic were considered. Regarding the BGRWs, the precise configurations of the lattice walks constructed during the numerical simulations were influenced by two parameters: a disorder parameter rho that controls the amount of negative edge weights on the lattice and a bias strength B that governs the drift of the walkers along a certain lattice direction. Here, the pivotal observable is the probability that, after termination, a lattice walk exhibits a total negative weight, which is here considered as percolating. The behavior of this observable as function of rho for different bias strengths B is put under scrutiny. Upon tuning rho, the probability to find such a feasible lattice walk increases from zero to one. This is the key feature of the percolation transition in the NWP model. Here, we address the question how well the transition point rho_c, resulting from numerically exact and "static" simulations in terms of the NWP model can be resolved using simple dynamic algorithms that have only local information available, one of the basic questions in the physics of glassy systems.

cond-mat.dis-nn↗

arXiv2013

Typical and large-deviation properties of minimum-energy paths on disordered hierarchical lattices

We perform numerical simulations to study the optimal path problem on disordered hierarchical graphs with effective dimension d=2.32. Therein, edge energies are drawn from a disorder distribution that allows for positive and negative energies. This induces a behavior which is fundamentally different from the case where all energies are positive, only. Upon changing the subtleties of the distribution, the scaling of the minimum energy path length exhibits a transition from self-affine to self-similar. We analyze the precise scaling of the path length and the associated ground-state energy fluctuations in the vincinity of the disorder critical point, using a decimation procedure for huge graphs. Further, using an importance sampling procedure in the disorder we compute the negative-energy tails of the ground-state energy distribution up to 12 standard deviations away from its mean. We find that the asymptotic behavior of the negative-energy tail is in agreement with a Tracy-Widom distribution. Further, the characteristic scaling of the tail can be related to the ground-state energy flucutations, similar as for the directed polymer in a random medium.

cond-mat.dis-nn↗

arXiv2012

Information theoretic approach to ground-state phase transitions for two and three-dimensional frustrated spin systems

The information theoretic observables entropy (a measure of disorder), excess entropy (a measure of complexity) and multi information are used to analyze ground-state spin configurations for disordered and frustrated model systems in 2D and 3D. For both model systems, ground-state spin configurations can be obtained in polynomial time via exact combinatorial optimization algorithms, which allowed us to study large systems with high numerical accuracy. Both model systems exhibit a continuous transition from an ordered to a disordered ground state as a model parameter is varied. By using the above information theoretic observables it is possible to detect changes in the spatial structure of the ground states as the critical point is approached. It is further possible to quantify the scaling behavior of the information theoretic observables in the vicinity of the critical point. For both model systems considered, the estimates of critical properties for the ground-state phase transitions are in good agreement with existing results reported in the literature.

cond-mat.dis-nn↗

arXiv2012

Analysis of the loop length distribution for the negative weight percolation problem in dimensions d=2 through 6

We consider the negative weight percolation (NWP) problem on hypercubic lattice graphs with fully periodic boundary conditions in all relevant dimensions from d=2 to the upper critical dimension d=6. The problem exhibits edge weights drawn from disorder distributions that allow for weights of either sign. We are interested in in the full ensemble of loops with negative weight, i.e. non-trivial (system spanning) loops as well as topologically trivial ("small") loops. The NWP phenomenon refers to the disorder driven proliferation of system spanning loops of total negative weight. While previous studies where focused on the latter loops, we here put under scrutiny the ensemble of small loops. Our aim is to characterize -using this extensive and exhaustive numerical study- the loop length distribution of the small loops right at and below the critical point of the hypercubic setups by means of two independent critical exponents. These can further be related to the results of previous finite-size scaling analyses carried out for the system spanning loops. For the numerical simulations we employed a mapping of the NWP model to a combinatorial optimization problem that can be solved exactly by using sophisticated matching algorithms. This allowed us to study here numerically exact very large systems with high statistics.

cond-mat.dis-nn↗

arXiv2012

A computational mechanics approach to estimate entropy and (approximate) complexity for the dynamics of the 2D Ising Ferromagnet

We present a numerical analysis of the entropy rate and statistical complexity related to the spin flip dynamics of the 2D Ising Ferromagnet at different temperatures T. We follow an information theoretic approach and test three different entropy estimation algorithms to asses entropy rate and statistical complexity of binary sequences. The latter are obtained by monitoring the orientation of a single spin on a square lattice of side-length L=256 at a given temperature parameter over time. The different entropy estimation procedures are based on the M-block Shannon entropy (a well established method that yields results for benchmarking purposes), non-sequential recursive pair substitution (providing an elaborate and an approximate estimator) and a convenient data compression algorithm contained in the zlib-library (providing an approximate estimator only). We propose an approximate measure of statistical complexity that emphasizes on correlations within the sequence and which is easy to implement, even by means of black-box data compression algorithms. Regarding the 2D Ising Ferromagnet simulated using Metropolis dynamics and for binary sequences of finite length, the proposed approximate complexity measure is peaked close to the critical temperature. For the approximate estimators, a finite-size scaling analysis reveals that the peak approaches the critical temperature as the sequence length increases. Results obtained using different spin-flip dynamics are briefly discussed. The suggested complexity measure can be extended to non-binary sequences in a straightforward manner.

cond-mat.stat-mech↗

arXiv2012

Is negative-weight percolation compatible with SLE?

We study numerically the geometrical properties of minimally weighted paths that appear in the negative-weight percolation (NWP) model on two-dimensional lattices assuming a combination of periodic and free boundary conditions (BCs). Each realization of the disorder consists of a random fraction 1-rho of bonds with unit strength and a fraction rho of bond strengths drawn from a Gaussian distribution with zero mean and unit width. For each such sample, the path is forced to span the lattice along the direction with the free BCs. The path and a set of negatively weighted loops form a ground state (GS). A ground state on such a lattice can be determined performing a non-trivial transformation of the original graph and applying sophisticated matching algorithms. Here we examine whether the geometrical properties of the paths are in accordance with predictions of Schramm-Loewner evolution (SLE). Measuring the fractal dimension and reviewing Schramm's left passage formula indicates that the paths cannot be described in terms of SLE.

cond-mat.dis-nn↗

arXiv2011

Optimal Vertex Cover for the Small-World Hanoi Networks

The vertex-cover problem on the Hanoi networks HN3 and HN5 is analyzed with an exact renormalization group and parallel-tempering Monte Carlo simulations. The grand canonical partition function of the equivalent hard-core repulsive lattice-gas problem is recast first as an Ising-like canonical partition function, which allows for a closed set of renormalization group equations. The flow of these equations is analyzed for the limit of infinite chemical potential, at which the vertex-cover problem is attained. The relevant fixed point and its neighborhood are analyzed, and non-trivial results are obtained both, for the coverage as well as for the ground state entropy density, which indicates the complex structure of the solution space. Using special hierarchy-dependent operators in the renormalization group and Monte-Carlo simulations, structural details of optimal configurations are revealed. These studies indicate that the optimal coverages (or packings) are not related by a simple symmetry. Using a clustering analysis of the solutions obtained in the Monte Carlo simulations, a complex solution space structure is revealed for each system size. Nevertheless, in the thermodynamic limit, the solution landscape is dominated by one huge set of very similar solutions.

cond-mat.dis-nn↗

arXiv2011

Mean-field behavior of the negative-weight percolation model on random regular graphs

We investigate both analytically and numerically the ensemble of minimum-weight loops and paths in the negative-weight percolation model on random graphs with fixed connectivity and bimodal weight distribution. This allows us to study the mean-field behavior of this model. The analytical study is based on a conjectured equivalence with the problem of self-avoiding walks in a random medium. The numerical study is based on a mapping to a standard minimum-weight matching problem for which fast algorithms exist. Both approaches yield results which are in agreement, on the location of the phase transition, on the value of critical exponents, and on the absence of any sizeable indications of a glass phase. By these results, the previously conjectured upper critical dimension of d_u=6 is confirmed.

cond-mat.dis-nn↗

arXiv2010

Large-deviation properties of largest component for random graphs

Distributions of the size of the largest component, in particular the large-deviation tail, are studied numerically for two graph ensembles, for Erdoes-Renyi random graphs with finite connectivity and for two-dimensional bond percolation. Probabilities as small as 10^-180 are accessed using an artificial finite-temperature (Boltzmann) ensemble. The distributions for the Erdoes-Renyi ensemble agree well with previously obtained analytical results. The results for the percolation problem, where no analytical results are available, are qualitatively similar, but the shapes of the distributions are somehow different and the finite-size corrections are sometimes much larger. Furthermore, for both problems, a first-order phase transition at low temperatures T within the artificial ensemble is found in the percolating regime, respectively.

cond-mat.dis-nn↗