arXiv subjects

Daniel S. Seara

Publications and source records attributed to Daniel S. Seara.

7 recordsLinked to original sources

arXiv2026

When is nonreciprocity relevant?

Nonreciprocal interactions are widely observed in nonequilibrium systems, from biological or sociological dynamics to open quantum systems. Despite the ubiquity of nonreciprocity, its impact on phase transitions is not fully understood. In this work, we derive criteria to perturbatively assess whether nonreciprocity changes the universality class of two-species systems undergoing a phase transition. These criteria, stated in terms of the unperturbed critical exponents in the spirit of the Harris criterion for disordered systems, assess whether static critical exponents change at first order under a given perturbation. For example, in the case of a nonreciprocal version of model A with two species, a homogeneous nonreciprocal perturbation is relevant whenever the two parts are initially identical and uncoupled, and irrelevant otherwise. Our results agree with existing renormalization group calculations and with numerical simulations.

cond-mat.stat-mech↗

arXiv2026

Information theory for dimensionality reduction in dynamical systems

The dynamics of many-body systems can often be captured in terms of only a few relevant variables. Mathematical and numerical approaches exist to identify these variables by exploiting a separation of time scales between slow relevant and fast irrelevant variables, but such a separation of scales is not always obvious or even available. In this work, we introduce an information-theoretic framework for dimensionality reduction in dynamical systems that bypasses this limitation by instead identifying relevant variables based on how predictive they are of the system's future. To do so, we mathematically formalize the intuition that model reduction is about keeping "relevant" information while throwing away "irrelevant" information. We characterize the solution of the resulting optimization problem and prove that it reduces to standard approaches when a separation of time scales is indeed present in the dynamics. Importantly, we find that within this framework, the problems of identifying relevant variables and identifying their effective dynamics decouple and may be solved separately. This makes the method tractable in practice and enables us to derive dimensionally-reduced variables from data with neural networks. Combined with existing equation learning methods, the procedure introduced in this work reveals the dynamical rules governing the system's evolution in a data-driven manner. We illustrate these tools in diverse settings including simulated chaotic systems, uncurated satellite recordings of atmospheric fluid flows, and experimental videos of cyanobacteria colonies in which we discover an emergent synchronization order parameter.

cond-mat.stat-mech↗

arXiv2025

Sociohydrodynamics: data-driven modelling of social behavior

Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially-generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data is available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard hydrodynamic assumptions to construct a sociohydrodynamic model. Solving our simple hydrodynamic model, calibrated using statistical inference, qualitatively captures key features of residential dynamics at the level of individual US counties. We highlight that a social memory, akin to hysteresis in magnets, emerges in the segregation-integration transition even with memory-less agents. This suggests an explanation for the phenomenon of neighborhood tipping, whereby a small change in a neighborhood's population leads to a rapid demographic shift. Beyond residential segregation, our work paves the way for systematic investigations of decision-guided motility in real space, from micro-organisms to humans, as well as fitness-mediated motion in more abstract genomic spaces.

cond-mat.soft↗

arXiv2023

Non-reciprocal interactions spatially propagate fluctuations in a 2D Ising model

Motivated by the anisotropic interactions between fish, we implement spatially anisotropic and therefore non-reciprocal interactions in the 2D Ising model. First, we show that the model with non-reciprocal interactions alters the system critical temperature away from that of the traditional 2D Ising model. Further, local perturbations to the magnetization in this out-of-equilibrium system manifest themselves as traveling waves of spin states along the lattice, also seen in a mean-field model of our system. The speed and directionality of these traveling waves are controllable by the orientation and magnitude of the non-reciprocal interaction kernel as well as the proximity of the system to the critical temperature.

cond-mat.soft↗

arXiv2020

Irreversibility in dynamical phases and transitions

Living and non-living active matter consumes energy at the microscopic scale to drive emergent, macroscopic behavior including traveling waves and coherent oscillations. Recent work has characterized non-equilibrium systems by their total energy dissipation, but little has been said about how dissipation manifests in distinct spatiotemporal patterns. We introduce a novel measure of irreversibility we term the entropy production factor (EPF) to quantify how time reversal symmetry is broken in field theories across scales. We use the EPF to characterize a dynamical phase transition in simulations of the Brusselator, a prototypical biochemically motivated non-linear oscillator. The EPF quantifies the distribution of irreversibility across spatiotemporal frequencies as the Brusselator transitions from local to global coherent oscillations, bounding the energetic cost to establish spatially synchronized biochemical oscillations.

cond-mat.stat-mech↗

arXiv2018

Entropy Production Rate is Maximized in Non-Contractile Actomyosin

The actin cytoskeleton is an active semi-flexible polymer network whose non-equilibrium properties coordinate both stable and contractile behaviors to maintain or change cell shape. While myosin motors drive the actin cytoskeleton out-of-equilibrium, the role of myosin-driven active stresses in the accumulation and dissipation of mechanical energy is unclear. To investigate this, we synthesize an actomyosin material in vitro whose active stress content can tune the network from stable to contractile. Each increment in activity determines a characteristic spectrum of actin filament fluctuations which is used to calculate the total mechanical work and the production of entropy in the material. We find that the balance of work and entropy does not increase monotonically and, surprisingly, the entropy production rate is maximized in the non-contractile, stable state. Our study provides evidence that the origins of system entropy production and activity-dependent dissipation arise from disorder in the molecular interactions between actin and myosin

cond-mat.soft↗

arXiv2018

Epithelial Wound Healing Coordinates Distinct Actin Network Architectures to Conserve Mechanical Work and Balance Power

How cells with diverse morphologies and cytoskeletal architectures modulate their mechanical behaviors to drive robust collective motion within tissues is poorly understood. During wound repair within epithelial monolayers in vitro, cells coordinate the assembly of branched and bundled actin networks to regulate the total mechanical work produced by collective cell motion. Using traction force microscopy, we show that the balance of actin network architectures optimizes the wound closure rate and the magnitude of the mechanical work. These values are constrained by the effective power exerted by the monolayer, which is conserved and independent of actin architectures. Using a cell-based physical model, we show that the rate at which mechanical work is done by the monolayer is limited by the transformation between actin network architectures and differential regulation of cell-substrate friction. These results and our proposed molecular mechanisms provide a robust quantitative model for how cells collectively coordinate their non-equilibrium behaviors to dynamically regulate tissue-scale mechanical output.

physics.bio-ph↗