arXiv subjects

Nikta Fakhri

Publications and source records attributed to Nikta Fakhri.

12 recordsLinked to original sources

arXiv2025

Curved Odd Elasticity

Living materials such as membranes, cytoskeletal assemblies, cell collectives and tissues can often be described as active solids---materials that are energized from within, with elastic response about a well defined reference configuration. These materials often live in complex and curved manifolds, yet most descriptions of active solids are flat. Here, we explore the interplay between curvature and non-reciprocal elasticity via a covariant effective theory on curved manifolds in combination with numerical simulations. We find that curvature spatially patterns activity, gaps the spectrum, modifies exceptional points and introduces non-Hermitian defect modes. Together these results establish a foundation for hydrodynamic and rheological models on curved manifolds, with direct implications for living matter and active metamaterials.

cond-mat.soft↗

arXiv2025

Topological flowscape reveals state transitions in nonreciprocal living matter

Nonreciprocal interactions -- where forces between entities are asymmetric -- govern a wide range of nonequilibrium phenomena, yet their role in structural transitions in living and active systems remains elusive. Here, we demonstrate a transition between nonreciprocal states using starfish embryos at different stages of development, where interactions are inherently asymmetric and tunable. Experiments, interaction inference, and topological analysis yield a nonreciprocal state diagram spanning crystalline, flocking, and fragmented states, revealing that weak nonreciprocity promotes structural order while stronger asymmetry disrupts it. To capture these transitions, we introduce topological landscapes, mapping the distribution of structural motifs across state space. We further develop topological flowscapes, a dynamic framework that quantifies transitions between collective states and detects an informational rate shift from the experimental state transition. Together, these results establish a general approach for decoding nonequilibrium transitions and uncover how asymmetric interactions sculpt the dynamical and structural architecture of active and living matter.

cond-mat.soft↗

arXiv2024

Selective excitation of work-generating cycles in nonreciprocal living solids

Emergent nonreciprocity in active matter drives the formation of self-organized states that transcend the behaviors of equilibrium systems. Integrating experiments, theory and simulations, we demonstrate that active solids composed of living starfish embryos spontaneously transition between stable fluctuating and oscillatory steady states. The nonequilibrium steady states arise from two distinct chiral symmetry breaking mechanisms at the microscopic scale: the spinning of individual embryos resulting in a macroscopic odd elastic response, and the precession of their rotation axis, leading to active gyroelasticity. In the oscillatory state, we observe long-wavelength optical vibrational modes that can be excited through mechanical perturbations. Strikingly, these excitable nonreciprocal solids exhibit nonequilibrium work generation without cycling protocols, due to coupled vibrational modes. Our work introduces a novel class of tunable nonequilibrium processes, offering a framework for designing and controlling soft robotic swarms and adaptive active materials, while opening new possibilities for harnessing nonreciprocal interactions in engineered systems.

cond-mat.soft↗

arXiv2024

Light-induced cortical excitability reveals programmable shape dynamics in starfish oocytes

Chemo-mechanical waves on active deformable surfaces are a key component for many vital cellular functions. In particular, these waves play a major role in force generation and long-range signal transmission in cells that dynamically change shape, as encountered during cell division or morphogenesis. Reconstituting and controlling such chemically controlled cell deformations is a crucial but unsolved challenge for the development of synthetic cells. Here, we develop an optogenetic method to elucidate the mechanism responsible for coordinating surface contraction waves that occur in oocytes of the starfish Patiria miniata during meiotic cell division. Using spatiotemporally-patterned light stimuli as a control input, we create chemo-mechanical cortical excitations that are decoupled from meiotic cues and drive diverse shape deformations ranging from local pinching to surface contraction waves and cell lysis. We develop a quantitative model that entails the hierarchy of chemical and mechanical dynamics, which allows to relate the variety of mechanical responses to optogenetic stimuli. Our framework systematically predicts and explains transitions of programmed shape dynamics. Finally, we qualitatively map the observed shape dynamics to elucidate how the versatility of intracellular protein dynamics can give rise to a broad range of mechanical phenomenologies. More broadly, our results pave the way toward real-time control over dynamical deformations in living organisms and can advance the design of synthetic cells and life-like cellular functions.

physics.bio-ph↗

arXiv2023

Measuring irreversibility from learned representations of biological patterns

Thermodynamic irreversibility is a crucial property of living matter. Irreversible processes maintain spatiotemporally complex structures and functions characteristic of living systems. In high-dimensional biological dynamics, robust and general quantification of irreversibility remains a challenging task due to experimental noise and nonlinear interactions coupling many degrees of freedom. Here we use deep learning to identify tractable, low-dimensional representations of phase-field patterns in a canonical protein signaling process -- the Rho-GTPase system -- as well as complex Ginzburg-Landau dynamics. We show that factorizing variational autoencoder neural networks learn informative pattern features robustly to noise. Resulting neural-network representations reveal signatures of mesoscopic broken detailed balance and time-reversal asymmetry in Rho-GTPase and complex Ginzburg-Landau wave dynamics. Applying the compression-based Ziv-Merhav estimator of irreversibility to representations, we recover irreversibility trends across complex Ginzburg-Landau patterns varying widely in spatiotemporal frequency and noise level. Irreversibility estimates from representations similarly recapitulate cell-activity trends in a Rho-GTPase patterning system undergoing metabolic inhibition. Additionally, we find that our irreversibility estimates serve as a dynamical order parameter, distinguishing stable and chaotic dynamics in these nonlinear systems. Our framework leverages advances in deep learning to offer robust, model-free measurements of nonequilibrium and nonlinear behavior in complex living processes.

cond-mat.stat-mech↗

arXiv2023

Dissipative timescales from coarse-graining irreversibility

We propose and investigate a method for identifying timescales of dissipation in nonequilibrium steady states modeled as discrete-state Markov jump processes. The method is based on how the irreversibility-measured by the statistical breaking of time-reversal symmetry-varies under temporal coarse-graining. We observe a sigmoidal-like shape of the irreversibility as a function of the coarse-graining time whose functional form we derive for systems with a fast driven transition. This theoretical prediction allows us to develop a method for estimating the dissipative time scale from time-series data by fitting estimates of the irreversibility to our predicted functional form. We further analyze the accuracy and statistical fluctuations of this estimate.

cond-mat.stat-mech↗

arXiv2022

Odd dynamics of living chiral crystals

Active crystals are highly ordered structures that emerge from the self-organization of motile objects, and have been widely studied in synthetic and bacterial active matter. Whether collective crystallization phenomena can occur in groups of autonomously developing multicellular organisms is currently unknown. Here, we show that swimming starfish embryos spontaneously assemble into chiral crystals that span thousands of spinning organisms and persist for tens of hours. Combining experiments, theory, and simulations, we demonstrate that the formation, dynamics, and dissolution of these living crystals are controlled by the hydrodynamic properties and natural development of embryos. Remarkably, living chiral crystals exhibit self-sustained chiral oscillations as well as various unconventional deformation response behaviors recently predicted for odd elastic materials. Our results provide direct experimental evidence for how nonreciprocal interactions between autonomous multicellular components may facilitate novel nonequilibrium phases of chiral active matter.

cond-mat.soft↗

arXiv2021

Dynamic clustering of passive colloids in dense suspensions of motile bacteria

Mixtures of active and passive particles are predicted to exhibit a variety of nonequilibrium phases. Here we report a dynamic clustering phase in mixtures of colloids and motile bacteria. We show that colloidal clustering results from a balance between bond breaking due to persistent active motion and bond stabilization due to torques that align active particle velocity tangentially to the passive particle surface. Furthermore, dynamic clustering spans a broad regime between diffusivity-based and motility-induced phase separation that subsumes typical bacterial motility parameters.

cond-mat.soft↗

arXiv2021

Symmetry, Thermodynamics and Topology in Active Matter

This article summarizes some of the open questions in the field of active matter that have emerged during Active20, a nine-week program held at the Kavli Institute for Theoretical Physics (KITP) in Spring 2020. The article does not provide a review of the field, but rather a personal view of the authors, informed by contributions of all participants, on new directions in active matter research. The topics highlighted include: the ubiquitous occurrence of spontaneous flows and active turbulence and the theoretical and experimental challenges associated with controlling and harnessing such flows; the role of motile topological defects in ordered states of active matter and their possible biological relevance; the emergence of non-reciprocal effective interactions and the role of chirality in active systems and their intriguing connections to non-Hermitian quantum mechanics; the progress towards a formulation of the thermodynamics of active systems thanks to the feedback between theory and experiments; the impact of the active matter framework on our understanding of the emergent mechanics of biological tissue. These seemingly diverse phenomena all stem from the defining property of active matter - assemblies of self-driven entities that individually break time-reversal symmetry and collectively organize in a rich variety of nonequilibrium states.

cond-mat.soft↗

arXiv2021

Scale-dependent irreversibility in living matter

A defining feature of living matter is the ability to harness energy to self-organize multiscale structures whose functions are facilitated by irreversible nonequilibrium dynamics. While progress has been made in elucidating the underlying principles, what remains unclear is the role that thermodynamics plays in shaping these structures and their ensuing functions. Here, we unravel how a fundamental thermodynamic connection between the physical energy dissipation sustaining a nonequilibrium system and a measure of statistical irreversibility (arrow of time), can provide quantitative insight into the mechanisms of nonequilibrium activity across scales. Specifically, we introduce a multiscale irreversibility metric and demonstrate how it can be used to extract model-independent estimates of dissipative timescales. Using this metric, we measure the dissipation timescale of a multiscale cellular structure - the actomyosin cortex - and further observe that the irreversibility metric maintains a monotonic relationship with the underlying biological nonequilibrium activity. Additionally, the irreversibility metric can detect shifts in the dissipative timescales when we induce spatiotemporal patterns of biochemical signaling proteins upstream of actomyosin activation. Our experimental measurements are complemented by a theoretical analysis of a generic class of nonequilibrium dynamics, elucidating how dissipative timescales manifest in multiscale irreversibility.

physics.bio-ph↗

arXiv2019

Quantifying dissipation using fluctuating currents

Systems coupled to multiple thermodynamic reservoirs can exhibit nonequilibrium dynamics, breaking detailed balance to generate currents. To power these currents, the entropy of the reservoirs increases. The rate of entropy production, or dissipation, is a measure of the statistical irreversibility of the nonequilibrium process. By measuring this irreversibility in several biological systems, recent experiments have detected that particular systems are not in equilibrium. Here we discuss three strategies to replace binary classification (equilibrium versus nonequilibrium) with a quantification of the entropy production rate. To illustrate, we generate time-series data for the evolution of an analytically tractable bead-spring model. Probability currents can be inferred and utilized to indirectly quantify the entropy production rate, but this approach requires prohibitive amounts of data in high-dimensional systems. This curse of dimensionality can be partially mitigated by using the thermodynamic uncertainty relation to bound the entropy production rate using statistical fluctuations in the probability currents.

cond-mat.stat-mech↗

arXiv2016

Self-organization of stress patterns drives state transitions in actin cortices

Biological functions rely on ordered structures and intricately controlled collective dynamics. In contrast to systems in thermodynamic equilibrium, order is typically established and sustained in stationary states by continuous dissipation of energy. Non-equilibrium dynamics is a necessary condition to make the systems highly susceptible to signals that cause transitions between different states. How cellular processes self-organize under this general principle is not fully understood. Here, we find that model actomyosin cortices, in the presence of rapid turnover, display distinct steady states, each distinguished by characteristic order and dynamics as a function of network connectivity. The different states arise from a subtle interaction between mechanical percolation of the actin network and myosin-generated stresses. Remarkably, myosin motors generate actin architectures, which in turn, force the emergence of ordered stress patterns. Reminiscent of second order phase transitions, the emergence of order is accompanied by a critical regime characterized by strongly enhanced strain fluctuations. The striking dynamics in the critical regime were revealed using fluorescent single-walled carbon nanotubes as novel probes of cortical dynamics.

physics.bio-ph↗