Complex molecular details of transcriptional regulation can be coarse-grained by assuming that reaction waiting times for promoter-state transitions, the mRNA synthesis, and the mRNA degradation follow general distributions. However, how such a generalized two-state model is analytically solved is a long-standing issue. Here we first present analytical formulas of burst-size distributions for this model. Then, we derive an iterative equation for the mRNA moment-generating function, by which mRNA raw and binomial moments of any order can be conveniently calculated. The analytical results obtained in the special cases of phase-type waiting-time distributions not only provide insights into the mechanisms of complex transcriptional regulations but also bring conveniences for experimental data-based statistical inferences.

Active scalar baths consisting of active Brownian particles are characterized by a non-Gaussian velocity distribution, a kinetic temperature, and a diffusion coefficient that scale with the square of the active velocity $v_0$. While these results hold in overdamped active systems, inertial effects lead to normal velocity distributions, with kinetic temperature and diffusion coefficient increasing as $\sim v_0^{\alpha }$ with $1<\alpha <2$. Remarkably, the late-time diffusivity and mobility decrease with mass. Moreover, we show that the equilibrium Einstein relation is asymptotically recovered with inertia. In summary, the inertial mass restores an equilibriumlike behavior.

The order parameter for a continuous transition shows diverging fluctuation near the critical point. Here we show, through numerical simulations and scaling arguments, that the inequality (or variability) between the values of an order parameter, measured near a critical point, is independent of the system size. Quantification of such variability through the Gini index ($g$) therefore leads to a scaling form $g=G\left[\right|F-F_c\left|N^{1/d\nu }\right]$, where $F$ denotes the driving parameter for the transition (e.g., temperature $T$ for ferromagnetic to paramagnetic transition, or lattice occupation probability $p$ in percolation), $N$ is the system size, $d$ is the spatial dimension and $\nu$ is the correlation length exponent. We demonstrate the scaling for the Ising model in two and three dimensions, site percolation on square lattice, and the fiber bundle model of fracture.

There are two main categories of networks studied in the complexity physics community: Monopartite and bipartite networks. In this paper, we present a general framework that provides insights into the connection between these two classes. When a random bipartite network is projected into a monopartite network, under quite general conditions, the result is a nonrandom monopartite network, the features of which can be studied analytically. Unlike previous studies in the physics literature on complex networks, which rely on sparse-network approximations, we provide a complete analysis, focusing on the degree distribution and the clustering coefficient. Our findings primarily offer a technical contribution, adding to the current body of literature by enhancing the understanding of bipartite networks within the community of physicists. In addition, our model emphasizes the substantial difference between the information that can be extracted from a network measuring its degree distribution, or using higher-order metrics such as the clustering coefficient. We believe that our results are general and have broad real-world implications.

Sessile species compete for space and accessible light, with directed interactions evident in one species overgrowing another and with multispecies systems characterized by nontransitive relationships. Such patterns are observed in coral reefs or lichens on rock surfaces. Open systems with episodic invasions of such species have been predicted to exhibit a stable high-diversity state when the interaction probability is below a certain critical threshold. Here, we explore this metastable high-diversity state and find that the diversity in the high-diversity state scales with the square root of the system area. When introducing two different environments, we predict a hugely increased diversity along mutual environment border. Further, the presence of spatially segregated environments is predicted to allow for increased robustness of the high-diversity state.

Intracellular ions, including sodium $\left({\mathrm{Na}}^{+}\right)$, calcium $\left({\mathrm{Ca}}^{2+}\right)$, and potassium $\left({\mathrm{K}}^{+}\right)$, etc., accumulate slowly after a change of the state of the heart, such as a change of the heart rate. The goal of this study is to understand the roles of slow ion accumulation in the genesis of cardiac memory and complex action-potential duration (APD) dynamics that can lead to lethal cardiac arrhythmias. We carry out numerical simulations of a detailed action potential model of ventricular myocytes under normal and diseased conditions, which exhibit memory effects and complex APD dynamics. We develop a low-dimensional iterated map (IM) model to describe the dynamics of ${\mathrm{Na}}^{+},$ ${\mathrm{Ca}}^{2+}$, and APD and use it to uncover the underlying dynamical mechanisms. The development of the IM model is informed by simulation results under the normal condition. We then use the IM model to perform linear stability analyses and computer simulations to investigate the bifurcations and complex APD dynamics, which depend on the feedback loops between APD and intracellular ${\mathrm{Ca}}^{2+}$ and ${\mathrm{Na}}^{+}$ concentrations and the steepness of the APD response to the ion concentrations. When the feedback between APD and ${\mathrm{Ca}}^{2+}$ concentration is positive, a Hopf bifurcation leading to periodic oscillatory behavior occurs as the steepness of the APD response to the ion concentrations increases. The negative feedback loop between APD and ${\mathrm{Na}}^{+}$ concentration is required for the Hopf bifurcation. When the feedback between APD and ${\mathrm{Ca}}^{2+}$ concentration is negative, period-doubling bifurcations leading to high periodicity and chaos occurs. In this case, ${\mathrm{Na}}^{+}$ accumulation plays little role in the dynamics. Finally, we carry out simulations of the detailed action potential model under two diseased conditions, which exhibit steep APD responses to ion concentrations. Under both conditions, Hopf bifurcations leading to slow oscillations or period-doubling bifurcations leading to high periodicity and chaotic APD dynamics occur, depending on the strength of the ion $\text{pump}\text{—}{\mathrm{Na}}^{+}\text{−}{\mathrm{Ca}}^{2+}$ exchanger. Using functions reconstructed from the simulation data, the IM model accurately captures the bifurcations and dynamics under the two diseased conditions. In conclusion, besides using computer simulations of a detailed high-dimensional action-potential model to investigate the effects of slow ion accumulation and short-term memory on bifurcations and genesis of complex APD dynamics in cardiac myocytes under diseased conditions, this study also provides a low-dimensional mathematical tool, i.e., the IM model, to allow stability analyses for uncovering the underlying mechanisms.

We use molecular dynamics (MD) simulation and nanofluidic experiments to probe the non-equilibrium transient physics of two nanochannel-confined polymers driven against a permeable barrier in a flow field. For chains with a persistence length $P$ smaller than the channel diameter $D$, both simulation and experiment with dsDNA reveal nonuniform mixing of the two chains, with one chain dominating locally in what we term “aggregates.” Aggregates undergo stochastic dynamics, persisting for a limited time, then disappearing and reforming. Whereas aggregate-prone mixing occurs immediately at sufficiently high flow speeds, chains stay segregated at intermediate flow for some time, often attempting to mix multiple times, before suddenly successfully mixing. Observation of successful mixing nucleation events in nanofluidic experiments reveal that they arise through a peculiar “back-propagation” mechanism whereby the upstream chain, closest to the barrier, penetrates and passes through the downstream chain (farthest from the barrier) moving against the flow direction. Simulations suggest that the observed back-propagation nucleation mechanism is favored at intermediate flow speeds and arises from a special configuration where the upstream chain exhibits one or more folds facing the downstream chain, while the downstream chain has an unfolded chain end facing upstream.

Collective actuation describes the spontaneous synchronized oscillations taking place in active solids when the elasto-active feedback, which generically couples the reorientation of the active forces and the elastic stress, is large enough. In the absence of noise, collective actuation takes the form of a strong condensation of the dynamics on a specific pair of modes and their generalized harmonics. Here we report experiments conducted with centimetric active elastic structures, where collective oscillation takes place along the single lowest energy mode of the system, gapped from the other modes because of the system's geometry. Combining the numerical and theoretical analysis of an agent-based model, we demonstrate that this form of collective actuation is noise-induced. The effect of the noise is first analyzed in a single-particle toy model that reveals the interplay between the noise and the specific structure of the phase space. We then show that in the continuous limit, any finite amount of noise turns this new form of transition to collective actuation into a bona fide supercritical Hopf bifurcation.

We investigate the influence of quenched disorder on the steady states of driven systems of the elastic interface with nonlocal hydrodynamic interactions. The generalized elastic model (GEM), which has been used to characterize numerous physical systems such as polymers, membranes, single-file systems, rough interfaces, and fluctuating surfaces, is a standard approach to studying the dynamics of elastic interfaces with nonlocal hydrodynamic interactions. The criticality and phase transition of the quenched generalized elastic model are investigated numerically and the results are presented in a phase diagram spanned by two tuning parameters. We demonstrate that in the one-dimensional disordered driven GEM, three qualitatively different behavior regimes are possible with a proper specification of the order parameter (mean velocity) for this system. In the vanishing order parameter regime, the steady-state order parameter approaches zero in the thermodynamic limit. A system with a nonzero mean velocity can be in either the continuous regime, which is characterized by a second-order phase transition, or the discontinuous regime, which is characterized by a first-order phase transition. The focus of this research is to investigate the critical scaling features near the pinning-depinning threshold. The behavior of the quenched generalized elastic model at the critical depinning force is explored. Near the depinning threshold, the critical exponent is obtained numerically.

Nonequilibrium (NEQ) phonon fluctuation in a nanosystem has been studied through the statistical assessment of the entropy-production and -consumption events in ultrasmall tin dioxide $\left(\mathrm{Sn}{\mathrm{O}}_2\right)$ nanorods. Size- and shape-dependent alteration in free energy leading to modulation of the probability distribution function of the phonon dynamics has been observed from the x-ray diffraction and Raman scattering characterizations. The Gallavotti-Cohen nonequilibrium fluctuation theorem has been utilized to qualitatively describe the aforementioned behaviors under the influence of a global flux. The observation of entropy consumption and thermodynamically favorable entropy-production events indicates the presence of NEQ fluctuations in the phonon modes. The effective energy scale of fluctuation in driven phonon modes, dissipating energy faster than relaxation time, is quantified on the order of nanojoules. From optical absorption and photoluminescence studies, the observation of the electron-phonon coupled state confirms the interaction of the NEQ phonons with electrons. The strength of the coupling has been estimated from the temperature-independent Barry center shift and found to be enhanced to 5.35. Valence band x-ray photoelectron spectroscopy and Fourier transformed infrared spectroscopy analyses reconcile NEQ phonon mediated alteration of the valence band density of states, activation of silent phonon modes, and superior excitonic transitions, suitable for the new generation of ultrafast quantum device applications.

Recent advances in experimental fluorescence microscopy allow high accuracy determination (resolution of 50 nm) of the three-dimensional physical location of multiple (up to $\sim {10}^2$) tagged regions of the chromosome. We investigate publicly available microscopy data for two loci of the human Chr21 obtained from multiplexed fluorescence in situ hybridization (FISH) methods for different cell lines and treatments. Inspired by polymer physics models, our analysis centers around distance distributions between different tags with the aim being to unravel the chromatin conformational arrangements. We show that for any specific genomic site, there are (at least) two different conformational arrangements of chromatin, implying coexisting distinct topologies which we refer to as phase $\alpha$ and phase $\beta$. These two phases show different scaling behaviors: the former is consistent with a crumpled globule, while the latter indicates a confined, but more extended conformation, such as a looped domain. The identification of these distinct phases sheds light on the coexistence of multiple chromatin topologies and provides insights into the effects of cellular context and/or treatments on chromatin structure.

We determine the phase diagram of DNA with inter- and intrastrand native-pair interactions that mimic the compaction of DNA. We show that DNA takes an overall sheetlike structure in the region where an incipient transition to a compact phase would have occurred. The stability of this phase is due to the extra entropy from the folding of the sheet, which is absent in the remaining polymerlike states of the phase diagram.

We investigate the elastic energy stored in a filament pair as a function of applied twist by measuring torque under prescribed end-to-end separation conditions. We show that the torque increases rapidly to a peak with applied twist when the filaments are initially separate, then decreases to a minimum as the filaments cross and come into contact. The torque then increases again while the filaments form a double helix with increasing twist. A nonlinear elasto-geometric model that combines the effect of geometrical nonlinearities with large stretching and self-twist is shown to capture the evolution of the helical geometry, torque profile, and stored energy with twist. We find that a large fraction of the total energy is stored in stretching the filaments, which increases with separation distance and applied tension. We find that only a small fraction of energy is stored in the form of bending energy, and that the contribution due to contact energy is negligible. Further, we provide analytical formulas for the torque observed as a function of the applied twist and the inverse relation of the observed angle for a given applied torque in the Hookean limit. Our study highlights the consequences of stretchablility on filament twisting, which is a fundamental topological transformation relevant to making ropes, tying shoelaces, actuating robots, and the physical properties of entangled polymers.

Sandberg and Thomas [Phys. Rev. Lett. 130, 085001 (2023)] proposed a scheme to generate ultrashort, high-energy pulses of XUV photons though dephasingless photon acceleration in a beam-driven plasma wakefield. An ultrashort laser pulse is placed in the plasma wake behind a relativistic electron bunch such that it experiences a comoving negative density gradient and therefore shifts up in frequency. Using a tapered density profile provides phase-matching between driver and witness pulses. In this paper, we give the details of the wakefield solutions and phase-matching conditions used to generate the phase-matching density profile. The short, high-density, and weak driver limits are considered. We show, explicitly, the numerical algorithm used to calculate the density profiles.

A well-defined higher recursive approximation of the pyrochlore lattice is introduced and its relevance and effectiveness for the systematic investigation of magnetic systems with the pyrochlore structure is studied within the classical antiferromagnetic as well as ferromagnetic spin-$1/2$ Ising model in the presence of the external magnetic field. The exact solution of the model is found with the explicit analytic expression for the free energy per site of the lattice. The magnetization and entropy properties of all ground states of the antiferromagnetic model are determined and compared to those obtained within the lower recursive approximation of the model on the recursive tetrahedral lattice. The exact analysis of the residual entropies of the model on the introduced recursive lattice explicitly shows that the well-known Pauling entropy of the water ice cannot represent the true residual entropy of the antiferromagnetic model on the regular pyrochlore lattice in the zero external magnetic field. The improvement of the value of the critical temperature of the ferromagnetic model obtained within the introduced higher recursive approximation is also discussed. The analysis performed demonstrates the great efficiency of recursive approximations in the investigation of various magnetic systems with the pyrochlore structure, especially for frustrated antiferromagnetic systems.

The synchronization modes of a nonlinear oscillator system consisting of three identical flickering buoyant diffusion flames in isosceles triangles were studied experimentally and theoretically. Five synchronization modes, such as the in-phase, flickering death, partially flickering death, partially in-phase, and rotation modes, were experimentally observed and identified by systematically adjusting the flame distance and fuel flow rates. Two toy models were adopted to interpret the experimentally identified dynamical modes: one is the classical Kuramoto model, and the other is a complexified Stuart-Landau model, which was proposed through the introduction of the complex coupling term. The theoretical results show that the Kuramoto model successfully interpreted the dynamical modes except for those associated with amplitude death, and the complexified Stuart-Landau model well interpreted all the dynamical modes identified in our experiment. Remarkably, the proposed complexified Stuart-Landau model breaks a new path in the investigation of globally coupled nonlinear dynamical systems with identical oscillators, especially for the study of amplitude death mode.

The inclusion of inertia in the Kuramoto model has long been reported to change the nature of a phase transition, providing a fertile ground to model the dynamical behaviors of interacting units. More recently, higher-order interactions have been realized as essential for the functioning of real-world complex systems ranging from the brain to disease spreading. Yet analytical insights to decipher the role of inertia with higher-order interactions remain challenging. Here, we study the Kuramoto model with inertia on simplicial complexes, merging two research domains. We develop an analytical framework in a mean-field setting using self-consistent equations to describe the steady-state behavior, which reveals a prolonged hysteresis in the synchronization profile. Inertia and triadic interaction strength exhibit isolated influence on system dynamics by predominantly governing, respectively, the forward and backward transition points. This paper sets a paradigm to deepen our understanding of real-world complex systems such as power grids modeled as the Kuramoto model with inertia.

Understanding how cooperation can evolve in populations despite its cost to individual cooperators is an important challenge. Models of spatially structured populations with one individual per node of a graph have shown that cooperation, modeled via the prisoner's dilemma, can be favored by natural selection. These results depend on microscopic update rules, which determine how birth, death, and migration on the graph are coupled. Recently, we developed coarse-grained models of spatially structured populations on graphs, where each node comprises a well-mixed deme, and where migration is independent from division and death, thus bypassing the need for update rules. Here, we study the evolution of cooperation in these models in the rare-migration regime, within the prisoner's dilemma. We find that cooperation is not favored by natural selection in these coarse-grained models on graphs where overall deme fitness does not directly impact migration from a deme. This is due to a separation of scales, whereby cooperation occurs at a local level within demes, while spatial structure matters between demes.

The steady-state firing rate and firing-rate response of the leaky and exponential integrate-and-fire models receiving synaptic shot noise with excitatory and inhibitory reversal potentials is examined. For the particular case where the underlying synaptic conductances are exponentially distributed, it is shown that the master equation for a population of such model neurons can be reduced from an integrodifferential form to a more tractable set of three differential equations. The system is nevertheless more challenging analytically than for current-based synapses: where possible, analytical results are provided with an efficient numerical scheme and code provided for other quantities. The increased tractability of the framework developed supports an ongoing critical comparison between models in which synapses are treated with and without reversal potentials, such as recently in the context of networks with balanced excitatory and inhibitory conductances.