Physical review. E最新文献

Diffusion-dominated mix in inertial confinement fusion (ICF) is characterized where the majority of the mix occurs in the immediate fuel-shell interface while hydrodynamic-dominated mix pulls shell material from farther away into the central fuel. A thin (150 nm) separated reactants ICF mix platform is highly sensitive to the amount of mix from the first micron of shell-fuel interface. This fine-spatial resolution platform has revealed that material mix in moderate convergence (CR∼12) ICF implosions is dominated by a diffusion mechanism. This technique has now been expanded across a set of OMEGA ICF implosions, observing an increase in mix width and mix amount for cooler, slower, and more compressive implosions. Hydrodynamic simulations require a buoyancy-drag mix model to capture the increasing mix width, suggesting a transition between these two mix mechanisms.

Dynamics of non-Markovian systems is a classic problem yet it attracts everlasting activity in physics and beyond. A powerful tool for modeling such setups is the generalized Langevin equation, however, its analysis typically poses a major challenge even for numerical means. For this reason, various approximations have been proposed over the years that simplify the original model. In this paper, we compare two methods allowing us to tackle this great challenge: (i) the well-known and successful Markovian embedding technique and (ii) the recently developed effective mass approach. We discuss their scope of applicability, numerical accuracy, and computational efficiency. In doing so, we consider a paradigmatic model of a free Brownian particle subjected to power-law correlated thermal noise. We show that when the memory time is short, the effective mass approach offers satisfying precision and typically is much faster than the Markovian embedding. Moreover, the concept of effective mass can be used to find optimal parameters allowing us to reach supreme accuracy and minimal computational cost within the embedding. Our paper therefore provides a blueprint for investigating the dynamics of non-Markovian systems.

The mechanism underlying the spatiotemporal chromosome organization in Escherichia coli cells remains an open question, though experiments have been able to visually see the evolving chromosome organization in fast- and slow-growing cells. We had proposed [D. Mitra et al., Soft Matter 18, 5615 (2022)1744-683X10.1039/D2SM00734G] that the DNA ring polymer adopts a specific polymer topology as it goes through its cell cycle, which in turn self-organizes the chromosome by entropic forces during slow growth. The fast-growing E. coli cells have four (or more) copies of the replicating DNA, with overlapping rounds of replication going on simultaneously. This makes the spatial segregation and the subsequent organization of the multiple generations of DNA a complex task. Here, we establish that the same simple principles of entropic repulsion between polymer segments which provided an understanding of self-organization of DNA in slow-growth conditions also explains the organization of chromosomes in the much more complex scenario of fast-growth conditions. Repulsion between DNA-polymer segments through entropic mechanisms is harnessed by modifying polymer topology. The ring-polymer topology is modified by introducing crosslinks (emulating the effects of linker proteins) between specific segments. Our simulation reproduces the emergent evolution of the organization of chromosomes as seen in vivo in fluorescent in situ hybridization experiments. Furthermore, we reconcile the mechanism of longitudinal organization of the chromosomes arms in fast-growth conditions by a suitable adaptation of the model. Thus, polymer physics principles, previously used to understand chromosome organization in slow-growing E. coli cells also resolve DNA organization in more complex scenarios with multiple rounds of replication occurring in parallel.

The transmission of cytoskeletal forces to the extracellular matrix through focal adhesion complexes is essential for a multitude of biological processes, such as cell migration, cell differentiation, tissue development, and cancer progression, among others. During migration, focal adhesions arrest the actin retrograde flow towards the cell interior, allowing the cell front to move forward. Here, we address a puzzling observation of the existence of two distinct phenomena: a biphasic vs a monotonic relationship of the retrograde flow and cell traction force with substrate rigidity. In the former, maximum traction force and minimum retrograde flow velocity are observed at an intermediate optimal substrate stiffness; while in the latter, the actin retrograde flow decreases and traction force increases with increasing substrate stiffness. We propose a theoretical model for cell-matrix adhesions at the leading edge of a migrating cell, incorporating a novel approach in force loading rate sensitive binding and reinforcement of focal adhesions assembly and the subsequent force-induced slowing down of actin flow. Our model exhibits both biphasic and monotonic responses of the retrograde flow and cell traction force with increasing substrate rigidity, owing to the cell's ability to sense and adapt to the fast-growing forces. Furthermore, our analysis shows how competition between different timescales regulated by loading rate sensitivity influences the biphasic versus monotonic behavior and the emergence of optimal substrate rigidity in the biphasic scenario. We also elucidate how the viscoelastic properties of the substrate regulate these nonlinear responses and predict the loss of cell sensitivity to variation in substrate rigidity when adhesions are subjected to high forces.

Structure changes or transitions are common in growing networks (complex networks, graphs, etc.) and must be precisely determined. The introduced quantitative measure of the structural complexity of the network based on a procedure similar to the renormalization process allows one to reveal such changes. The proposed concept of the network structural complexity accounts for the difference between the actual and averaged network structures on different scales and corresponds to the qualitative comprehension of complexity. The structural complexity can be found for the weighted networks also. The structural complexities for various types of growing networks exhibiting transitions similar to phase transitions were found-the deterministic infinite and finite size artificial networks of different natures including percolation structures, and the time series of various types of cardiac rhythms mapped to complex networks using the parametric visibility graph algorithm. In all the cases the structural complexity of the growing network reaches a maximum near the transition point: the formation of a giant component in the graph or at the percolation threshold for two-dimensional and three-dimensional square lattices when a giant cluster having a fractal structure has emerged. Therefore, the structural complexity of the network allows us to detect and study processes similar to a second-order phase transition in complex networks. The structural complexity of a network node can serve as a kind of centrality index, auxiliary, or generalization to the local clustering coefficient. Such an index provides another new ranking manner for the network nodes. Being an easily computable measure, the network structural complexity might help to reveal different features of complex systems and processes of the real world.

We investigate the effects of quenched elastic disorder on the nature of the crumpling-to-flat transition of D-dimensional polymerized membranes using a two-loop computation near the upper critical dimension D_{c}=4. While the pure system undergoes fluctuation-induced first-order transitions below D_{c} and for an embedding dimension d

In this work, we shall study the role of threefold and fivefold coordination defects in the structure and dynamics of the hydrogen bond network of liquid water, with special emphasis on the glassy regime. A significant defect clusterization propensity will be made evident, with a prevalence of mixed pairs, that is, threefold- and fivefold-coordinated defects being first neighbors of each other. This structural analysis will enable us to determine the existence of defective and nondefective regions compatible with the high local density and low local density molecular states of liquid water, respectively. Hydrogen bond coordination defects will also be shown to promote water's structural relaxation, with the undercoordinated ones playing a main role in driving glassy relaxation dynamics. Moreover, we shall show that the three-foldcoordinated molecules together with their first neighbors present at the initial configuration act as markers of the dynamical heterogeneities that would emerge at later times commensurate with the structural relaxation of the supercooled system.

We study dynamical localization in an ultracold atom confined in an optical lattice that is simultaneously shaken by two competing pulsatile modulations with different amplitudes, periods, and waveforms. The effects of finite-width time pulses, modulation waveforms, and commensurable and incommensurable driving periods are investigated. We describe a particularly complex scenario and conclude that dynamical localization can survive, or even increase, when a periodic modulation is replaced by a quasiperiodic one of equal amplitude. Our analytical and numerical results indicate that there exists a strong correlation between the strengths of chaos (stochastic layer width) and dynamical localization (difference between the classical and quantum momentum dispersions) over the entire parameter space, which is maintained regardless of the periodic or quasiperiodic nature of the modulation. This persistent correlation provides a useful guide to optimally control the strength of dynamical localization by tuning the modulation parameters in real-world systems subjected to pulses of finite width.

Space-fractional diffusion equations find widespread application in nature. They govern the anomalous dynamics of many stochastic processes, generalizing the standard diffusion equation to superdiffusive behavior. Strikingly, the solution of space-fractional diffusion equations on bounded domains is still an open problem. This is in part due to the difficulty of handling nonlocal boundary conditions ascribed to the space-fractional derivative, leading to the failure of standard methods. Here we revisit the space-fractional diffusion equation in one spatial dimension with bounded domains and present a solution in terms of weighted Jacobi polynomials. Calculated eigenvalues and eigenfunctions in the superdiffusive regime show remarkable agreement with results from numerical discretization of the space-fractional derivative operator and Monte Carlo simulations. To exemplify, we apply the proposed solution to obtain the exact mean residence time or mean first-passage time, first-passage-time distribution, and survival probability, in agreement with known results for the superdiffusive regime. The system of equations converges rather fast for the first eigensolutions, as is desirable for practical application purposes in superdiffusive phenomena.

A common intuition in thermodynamics is that bubbles can spontaneously grow in unstable liquids, which will be detrimental to a variety of physical and chemical processes, such as evaporation-induced self-assembly and electrocatalysis. Here, we show that this common intuition can be significantly reversed by demonstrating a suppression of bubbles in unstable active liquids induced by fast evaporation, which is in contrast to the bubble growth in passive liquids. Such anomalous bubble suppression can be attributed to an activity-induced inversion of pressure difference between bubbles and their surrounding liquid. Moreover, this pressure flip depends on the activity as well as the thermodynamics of passive liquids, and it can generate different kinetic pathways that allow controlling the bubble dynamics in unstable liquids. Our results establish a foundation for promoting applications of unstable active liquids in various physical and chemical processes.