Directional clogging and phase separation for disk flow through periodic and diluted obstacle arrays.

We model collective disk flow though a square array of obstacles as the flow direction is changed relative to the symmetry directions of the array. At lower disk densities there is no clogging for any driving direction, but as the disk density increases, the average disk velocity decreases and develops a drive angle dependence. For certain driving angles, the flow is reduced or drops to zero when the system forms a heterogeneous clogged state consisting of high density clogged regions coexisting with empty regions.

Directional locking effects for active matter particles coupled to a periodic substrate.

Directional locking occurs when a particle moving over a periodic substrate becomes constrained to travel along certain substrate symmetry directions. Such locking effects arise for colloids and superconducting vortices moving over ordered substrates when the direction of the external drive is varied. Here we study the directional locking of run-and-tumble active matter particles interacting with a periodic array of obstacles.

Collective effects and pattern formation for directional locking of disks moving through obstacle arrays.

We examine directional locking effects in an assembly of disks driven through a square array of obstacles as the angle of drive rotates from 0^{∘} to 90^{∘}. For increasing disk densities, the system exhibits a series of different dynamic patterns along certain locking directions, including one-dimensional or multiple-row chain phases and density-modulated phases. For nonlocking driving directions, the disks form disordered patterns or clusters.

Machine learning approaches for structural and thermodynamic properties of a Lennard-Jones fluid.

Predicting the functional properties of many molecular systems relies on understanding how atomistic interactions give rise to macroscale observables. However, current attempts to develop predictive models for the structural and thermodynamic properties of condensed-phase systems often rely on extensive parameter fitting to empirically selected functional forms whose effectiveness is limited to a narrow range of physical conditions. In this article, we illustrate how these traditional fitting paradigms can be superseded using machine learning.

Dynamics of Magnus-dominated particle clusters, collisions, pinning, and ratchets.

Motivated by the recent work in skyrmions and active chiral matter systems, we examine pairs and small clusters of repulsively interacting point particles in the limit where the dynamics is dominated by the Magnus force. We find that particles with the same Magnus force can form stable pairs, triples, and higher ordered clusters or exhibit chaotic motion. For mixtures of particles with opposite Magnus force, particle pairs can combine to form translating dipoles.

Jamming, fragility and pinning phenomena in superconducting vortex systems.

We examine driven superconducting vortices interacting with quenched disorder under a sequence of perpendicular drive pulses. As a function of disorder strength, we find four types of behavior distinguished by the presence or absence of memory effects. The fragile and jammed states exhibit memory, while the elastic and pinning dominated regimes do not.

Colloidal Dynamics on a Choreographic Time Crystal.

A choreographic time crystal is a dynamic lattice structure in which the points comprising the lattice move in a coordinated fashion. These structures were initially proposed for understanding the motion of synchronized satellite swarms. Using simulations, we examine colloids interacting with a choreographic crystal consisting of traps that could be created optically.

Determination of Structural Correlation Functions.

Determining the structural properties of condensed-phase systems is a fundamental problem in theoretical statistical mechanics. Here we present a machine learning method that is able to predict structural correlation functions with significantly improved accuracy in comparison with traditional approaches. The usefulness of this (from the machine) approach is illustrated by predicting the radial distribution functions of two paradigmatic condensed-phase systems, a Lennard-Jones fluid and a hard-sphere fluid, and then comparing those results to the results obtained using both integral equation methods and empirically motivated analytical functions.

Commensurate states and pattern switching via liquid crystal skyrmions trapped in a square lattice.

Using continuum based simulations we show that a rich variety of skyrmion liquid crystal states can be realized in the presence of a periodic obstacle array. As a function of the number of skyrmions per obstacle we find hexagonal, square, dimer, trimer and quadrimer ordering, where the n-mer structures are a realization of a molecular crystal state of skyrmions. As a function of external field and obstacle radius we show that there are transitions between the different crystalline states as well as mixed and disordered structures.

Plastic flow and the skyrmion Hall effect.

Skyrmions in chiral magnets are a particle-like texture that has been attracting growing interest due to their novel dynamics and possible applications. Here, we discuss the role of disorder and skyrmion-skyrmion interaction in governing their motion under an external drive.

Jamming and tiling in fragmentation of rectangles.

We investigate a stochastic process where a rectangle breaks into smaller rectangles through a series of horizontal and vertical fragmentation events. We focus on the case where both the vertical size and the horizontal size of a rectangle are discrete variables. Because of this constraint, the system reaches a jammed state where all rectangles are sticks, that is, rectangles with minimal width.

Active microrheology, Hall effect, and jamming in chiral fluids.

We examine the motion of a probe particle driven through a chiral fluid composed of circularly swimming disks. We find that the probe particle travels in both the longitudinal direction, parallel to the driving force, and in the transverse direction, perpendicular to the driving force, giving rise to a Hall angle. Under constant driving force, we show that the probe particle velocity in both the longitudinal and transverse directions exhibits nonmonotonic behavior as a function of the activity of the circle swimmers.

Asymptotic Behavior of Memristive Circuits.

The interest in memristors has risen due to their possible application both as memory units and as computational devices in combination with CMOS. This is in part due to their nonlinear dynamics, and a strong dependence on the circuit topology. We provide evidence that also purely memristive circuits can be employed for computational purposes.

Kink-Kink and Kink-Antikink Interactions with Long-Range Tails.

In this Letter, we address the long-range interaction between kinks and antikinks, as well as kinks and kinks, in φ^{2n+4} field theories for n>1. The kink-antikink interaction is generically attractive, while the kink-kink interaction is generically repulsive. We find that the force of interaction decays with the 2n/(n-1)th power of their separation, and we identify the general prefactor for arbitrary n.

In Silico Evolution of Signaling Networks Using Rule-Based Models: Bistable Response Dynamics.

One of the ultimate goals in biology is to understand the design principles of biological systems. Such principles, if they exist, can help us better understand complex, natural biological systems and guide the engineering of de novo ones. Toward deciphering design principles, in silico evolution of biological systems with proper abstraction is a promising approach.

Using RuleBuilder to Graphically Define and Visualize BioNetGen-Language Patterns and Reaction Rules.

RuleBuilder is a tool for drawing graphs that can be represented by the BioNetGen language (BNGL), which is used to formulate mathematical, rule-based models of biochemical systems. BNGL provides an intuitive plain text, or string, representation of such systems, which is based on a graphical formalism. Reactions are defined in terms of graph-rewriting rules that specify the necessary intrinsic properties of the reactants, a transformation, and a rate law.

Disordering, clustering, and laning transitions in particle systems with dispersion in the Magnus term.

We numerically examine a two-dimensional system of repulsively interacting particles with dynamics that are governed by both a damping term and a Magnus term. The magnitude of the Magnus term has one value for half of the particles and a different value for the other half of the particles. In the absence of a driving force, the particles form a triangular lattice, while when a driving force is applied, we find that there is a critical drive above which a Magnus-induced disordering transition can occur even if the difference in the Magnus term between the two particle species is as small as one percent.

Reversibility, pattern formation, and edge transport in active chiral and passive disk mixtures.

We numerically examine mixtures of circularly moving and passive disks as a function of density and active orbit radius. For low or intermediate densities and/or small orbit radii, the system can organize into a reversible partially phase separated labyrinth state in which there are no collisions between disks, with the degree of phase separation increasing as the orbit radius increases. As a function of orbit radius, we find a divergence in the number of cycles required to reach a collision-free steady state at a critical radius, while above this radius, the system remains in a fluctuating liquid state.

Prediction of Optimal Drug Schedules for Controlling Autophagy.

The effects of molecularly targeted drug perturbations on cellular activities and fates are difficult to predict using intuition alone because of the complex behaviors of cellular regulatory networks. An approach to overcoming this problem is to develop mathematical models for predicting drug effects. Such an approach beckons for co-development of computational methods for extracting insights useful for guiding therapy selection and optimizing drug scheduling.

Thermal creep and the skyrmion Hall angle in driven skyrmion crystals.

We numerically examine thermal effects on the skyrmion Hall angle for driven skyrmions interacting with quenched disorder. We identify a creep regime in which motion occurs via intermittent jumps between pinned and flowing states. Here the skyrmion Hall angle is zero since the skyrmions have time to relax into equilibrium positions in the pinning sites, eliminating the side-jump motion induced by the Magnus force.

NEXMD Modeling of Photoisomerization Dynamics of 4-Styrylquinoline.

Isomerization of molecular systems is ubiquitous in chemistry and biology, and is also important for many applications. Atomistic simulations can help determine the tunable parameters influencing this process. In this paper, we use the Nonadiabatic EXcited state Molecular Dynamics (NEXMD) software to study the photoisomerization of a representative molecule, 4-styrylquinoline (SQ).

Preassembled GPCR signaling complexes mediate distinct cellular responses to ultralow ligand concentrations.

G protein-coupled receptors (GPCRs) are the largest class of cell surface signaling proteins, participate in nearly all physiological processes, and are the targets of 30% of marketed drugs. Typically, nanomolar to micromolar concentrations of ligand are used to activate GPCRs in experimental systems. We detected GPCR responses to a wide range of ligand concentrations, from attomolar to millimolar, by measuring GPCR-stimulated production of cyclic adenosine monophosphate (cAMP) with high spatial and temporal resolution.

Laning and clustering transitions in driven binary active matter systems.

It is well known that a binary system of nonactive disks that experience driving in opposite directions exhibits jammed, phase separated, disordered, and laning states. In active matter systems, such as a crowd of pedestrians, driving in opposite directions is common and relevant, especially in conditions which are characterized by high pedestrian density and emergency. In such cases, the transition from laning to disordered states may be associated with the onset of a panic state.

Controlled Fluidization, Mobility, and Clogging in Obstacle Arrays Using Periodic Perturbations.

We show that the clogging susceptibility and flow of particles moving through a random obstacle array can be controlled with a transverse or longitudinal ac drive. The flow rate can vary over several orders of magnitude, and we find both an optimal frequency and an optimal amplitude of driving that maximizes the flow. For dense arrays, at low ac frequencies, a heterogeneous creeping clogged phase appears in which rearrangements between different clogged configurations occur.