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We study the zeros of the partition function in the complex temperature plane (Fisher zeros) and in the complex external field plane (Lee-Yang zeros) of a frustrated Ising model with competing nearest-neighbor ($J_1 > 0$) and next-nearest-neighbor ($J_2 < 0$) interactions on the honeycomb lattice. We consider the finite-size scaling (FSS) of the leading Fisher and Lee-Yang zeros as determined from a cumulant method and compare it to a traditional scaling analysis based on the logarithmic derivative of the magnetization $\partial \ln \langle |M| \rangle /\partial\beta$ and the magnetic susceptibility $\chi$. While for this model both FSS approaches are subject to strong corrections to scaling induced by the frustration, their behavior is rather different, in particular as the ratio $\mathcal{R} = J_2/J_1$ is varied. As a consequence, an analysis of the scaling of partition function zeros turns out to be a useful complement to a more traditional FSS analysis. For the cumulant method, we also study the convergence as a function of cumulant order, providing suggestions for practical implementations. The scaling of the zeros convincingly shows that the system remains in the Ising universality class for $\mathcal{R}$ as low as $-0.22$, where results from traditional FSS using the same simulation data are less conclusive. The approach hence provides a valuable additional tool for mapping out the phase diagram of models afflicted by strong corrections to scaling., Comment: 31 pages, 7 figures

We investigate the aging properties of phase-separation kinetics following quenches from $T=\infty$ to a finite temperature below $T_c$ of the paradigmatic two-dimensional conserved Ising model with power-law decaying long-range interactions $\sim r^{-(2 + \sigma)}$. Physical aging with a power-law decay of the two-time autocorrelation function $C(t,t_w)\sim \left(t/t_w\right)^{-\lambda/z}$ is observed, displaying a complex dependence of the autocorrelation exponent $\lambda$ on $\sigma$. A value of $\lambda=3.500(26)$ for the corresponding nearest-neighbor model (which is recovered as the $\sigma \rightarrow \infty$ limes) is determined. The values of $\lambda$ in the long-range regime ($\sigma < 1$) are all compatible with $\lambda \approx 4$. In between, a continuous crossover is visible for $1 \lesssim \sigma \lesssim 2$ with non-universal, $\sigma$-dependent values of $\lambda$. The performed Metropolis Monte Carlo simulations are primarily enabled by our novel algorithm for long-range interacting systems.

Modelling the inorganic exciton contribution to 2D hybrid organic-inorganic perovskites is essential to understand their properties and screen for new materials. Here, we combine hybrid density functional theory calculations including spin orbit coupling (SOC) with the experimental relationship between the inorganic band gap and exciton binding energy to predict the inorganic exciton energy. For this purpose, we determine a universal exchange parameter for the HSE06 hybrid functional with SOC for lead-based 2D hybrid organic-inorganic perovskites. We further identify a relationship that connects PBE calculations to experiment-quality optical gaps and allows us to generalize the exchange mixing parameter other SOC approximations. Our approach opens the path to screen for 2D hybrid organic-inorganic perovskites with optimized spectra, e.g., for new solar cell or light emitting materials.

Dynamics of a polymer chain in solution gets significantly affected by the temperature and the frictional forces arising due to solvent viscosity. Here, using an explicit solvent framework for polymer simulation with the liberty to tune the solvent viscosity, we study the nonequilibrium dynamics of a flexible homopolymer when it is suddenly quenched from an extended coil state in good solvent to poor solvent conditions. Results from our extensive simulations reveal that depending on the temperature $T$ and solvent viscosity, one encounters long-lived sausage-like intermediates following the usual pearl-necklace intermediates. Use of shape factors of polymers allows us to disentangle these two distinct stages of the overall collapse process, and the corresponding relaxation times. The relaxation time $\tau_s$ of the sausage stage, which is the rate-limiting stage of the overall collapse process, follows an anti-Arrhenius behavior in the high-$T$ limit, and the Arrhenius behavior in the low-$T$ limit. Furthermore, the variation of $\tau_s$ with the solvent viscosity provides evidence of internal friction of the polymer, that modulates the overall collapse significantly, analogous to what is observed for relaxation rates of proteins during their folding. This suggests that the origin of internal friction in proteins is plausibly intrinsic to its polymeric backbone rather than other specifications., Comment: 14 pages, 10 captioned figures

gRPC is at the heart of modern distributed system architectures. Based on HTTP/2 and Protocol Buffers, it provides highly performant, standardized, and polyglot communication across loosely coupled microservices and is increasingly preferred over REST- or GraphQL-based service APIs in practice. Despite its widespread adoption, gRPC lacks any advanced privacy techniques beyond transport encryption and basic token-based authentication. Such advanced techniques are, however, increasingly important for fulfilling regulatory requirements. For instance, anonymizing or otherwise minimizing (personal) data before responding to requests, or pre-processing data based on the purpose of the access may be crucial in certain usecases. In this paper, we therefore propose a novel approach for integrating such advanced privacy techniques into the gRPC framework in a practically viable way. Specifically, we present a general approach along with a working prototype that implements privacy techniques, such as data minimization and purpose limitation, in a configurable, extensible, and gRPC-native way utilizing a gRPC interceptor. We also showcase how to integrate this contribution into a realistic example of a food delivery use case. Alongside these implementations, a preliminary performance evaluation shows practical applicability with reasonable overheads. Altogether, we present a viable solution for integrating advanced privacy techniques into real-world gRPC-based microservice architectures, thereby facilitating regulatory compliance ``by design''., Comment: 15 pages, accepted for the ICWE, International Conference on Web Engineering, 2024, research paper

Aging in phase-ordering kinetics of the $d=3$ Ising model following a quench from infinite to zero temperature is studied by means of Monte Carlo simulations. In this model the two-time spin-spin autocorrelator $C_\text{ag}$ is expected to obey dynamical scaling and to follow asymptotically a power-law decay with the autocorrelation exponent $\lambda$. Previous work indicated that the lower Fisher-Huse bound of $\lambda\geq d/2 = 1.5$ is violated in this model. Using much larger systems than previously studied, the instantaneous exponent for $\lambda$ we obtain at late times does \emph{not} disagree with this bound. By conducting systematic fits to the data of $C_\text{ag}$ using different ansaetze for the leading correction term, we find $\lambda = 1.58(14)$ with most of error attributed to the systematic uncertainty regarding the ansaetze. This result is in contrast to the recent report that below the roughening transition universality might be violated., Comment: 9 pages, 7 figures

Semiflexible polymers are widely used as a paradigm for understanding structural phases in biomolecules including folding of proteins. Here, we compare bead-spring and bead-stick variants of coarse-grained semiflexible polymer models that cover the whole range from flexible to stiff by conducting extensive replica-exchange Monte Carlo computer simulations. In the data analysis we focus on knotted conformations whose stability is shown to depend on the ratio $r_b/r_{\rm min}$ with $r_b$ denoting the equilibrium bond length and $r_{\rm min}$ the distance of the strongest nonbonded interactions. For both models, our results provide evidence that at low temperatures for $r_b/r_{\rm min}$ outside a small range around unity one always encounters knots as generic stable phases along with the usual frozen and bent-like structures. By varying the bending stiffness, we observe rather strong first-order-like structural transitions between the coexisting phases characterized by these geometrically different motifs. Through analyses of the energy distributions close to the transition point, we present exploratory estimates of the free-energy barriers between the coexisting phases.

Observing spontaneous velocity ordering or flocking during motility induced phase separation (MIPS) in a system of spherical active Brownian particles without alignment interaction is challenging. We take up this problem by performing simulations of spherical active inertial particles with purely repulsive potential in presence of thermal noise and absence of any explicit alignment interaction. Our results not only show the presence of MIPS, but also reveal a micro-flocking transition. We characterize this transition in terms of a velocity order parameter as well as a characteristic length scale derived from the spatial correlation of the velocities.

By means of Brownian dynamics simulations we study the steady-state dynamic properties of a flexible active polymer in a poor solvent condition. Our results show that the effective diffusion constant of the polymer $D_{\rm eff}$ gets significantly enhanced as activity increases, much like in active particles. The simulation data are in agreement with a theoretically constructed Rouse model of active polymer, demonstrating that irrespective of the strength of activity, the long-time dynamics of the polymer chain is characterized by a universal Rouse-like scaling $D_{\rm eff} \sim N^{-1}$, where $N$ is the chain length., Comment: 6 pages, 4 figures

Using the recently introduced parsimonious Metropolis algorithm bead-stick polymers both with infinite-range Lennard-Jones interaction and with truncation are simulated. The focus lays on determining the Boyle temperature for long chains with thousands of repeat units and on testing for theoretically predicted logarithmic corrections. Subsequently the behavior at the infinite-chain transition temperature, i.e., the $\Theta$-temperature is studied for chains with up to $N = 32768$ repeat units by investigation of the scaling of the end-to-end distance, the radius of gyration, the specific heat, and their derivatives with $N$., Comment: 12 pages, 16 figures

The population annealing algorithm is a population-based equilibrium version of simulated annealing. It can sample thermodynamic systems with rough free-energy landscapes more efficiently than standard Markov chain Monte Carlo alone. A number of parameters can be fine-tuned to improve the performance of the population annealing algorithm. While there is some numerical and theoretical work on most of these parameters, there appears to be a gap in the literature concerning the role of resampling in population annealing which this work attempts to close. The two-dimensional Ising model is used as a benchmarking system for this study. At first various resampling methods are implemented and numerically compared. In a second part the exact solution of the Ising model is utilized to create an artificial population annealing setting with effectively infinite Monte Carlo updates at each temperature. This limit is first performed on finite population sizes and subsequently extended to infinite populations. This allows us to look at resampling isolated from other parameters. Many results are expected to generalize to other systems., Comment: 24 pages, 19 figures, version as published

Flexible district heating grids form an important part of future, low-carbon energy systems. We examine probabilistic state estimation in such grids, i.e., we aim to estimate the posterior probability distribution over all grid state variables such as pressures, temperatures, and mass flows conditional on measurements of a subset of these states. Since the posterior state distribution does not belong to a standard class of probability distributions, we use Markov Chain Monte Carlo (MCMC) sampling in the space of network heat exchanges and evaluate the samples in the grid state space to estimate the posterior. Converting the heat exchange samples into grid states by solving the non-linear grid equations makes this approach computationally burdensome. However, we propose to speed it up by employing a deep neural network that is trained to approximate the solution of the exact but slow non-linear solver. This novel approach is shown to deliver highly accurate posterior distributions both for classic tree-shaped as well as meshed heating grids, at significantly reduced computational costs that are acceptable for online control. Our state estimation approach thus enables tightening the safety margins for temperature and pressure control and thereby a more efficient grid operation., Comment: The code for this paper is available under https://github.com/EINS-TUDa/DNN_MCMC4DH

We derive a formula that expresses the density of states of a system with continuous degrees of freedom as a function of microcanonical averages of squared gradient and Laplacian of the Hamiltonian. This result is then used to propose a novel flat-histogram Monte Carlo algorithm, which is tested on a three-dimensional system of interacting Lennard-Jones particles, the O(n) vector spin model on hypercubic lattices in D = 1 to 5 dimensions, and the O(3) Heisenberg model on a triangular lattice featuring frustration effects., Comment: 10 pages, 8 figures

One key aspect of coarsening following a quench below the critical temperature is domain growth. For the non-conserved Ising model a power-law growth of domains of like spins with exponent $\alpha = 1/2$ is predicted. Including recent work, it was not possible to clearly observe this growth law in the special case of a zero-temperature quench in the three-dimensional model. Instead a slower growth with $\alpha<1/2$ was reported. We attempt to clarify this discrepancy by running large-scale Monte Carlo simulations of lattice sizes up to $L=2048$ employing an efficient GPU implementation. Indeed, at late times we measure domain sizes compatible with the expected growth law -- but surprisingly, at still later times domains even grow superdiffusively, i.e., with $\alpha > 1/2$. We argue that this new problem is possibly caused by sponge-like structures emerging at early times., Comment: 13 pages, 10 figures

On 26 September 2022 the Double Asteroid Redirection Test (DART) spacecraft impacted Dimorphos, a satellite of the asteroid 65803 Didymos. Because it is a binary system, it is possible to determine how much the orbit of the satellite changed, as part of a test of what is necessary to deflect an asteroid that might threaten Earth with an impact. In nominal cases, pre-impact predictions of the orbital period reduction ranged from ~8.8 - 17.2 minutes. Here we report optical observations of Dimorphos before, during and after the impact, from a network of citizen science telescopes across the world. We find a maximum brightening of 2.29 $\pm$ 0.14 mag upon impact. Didymos fades back to its pre-impact brightness over the course of 23.7 $\pm$ 0.7 days. We estimate lower limits on the mass contained in the ejecta, which was 0.3 - 0.5% Dimorphos' mass depending on the dust size. We also observe a reddening of the ejecta upon impact., Comment: Accepted by Nature

We consider the three-dimensional site-diluted Ising model with power-law correlated defects and study the critical behavior of the second-moment correlation length and the magnetic susceptibility in the high-temperature phase. By comparing, for various defect correlation strengths, the extracted critical exponents $\nu$ and $\gamma$ with the results of our previous finite-size scaling study, we consolidate the exponent estimates., Comment: 12 pages, 6 figures, 1 table