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DOE OSTI2025

Azimuthal correlation anisotropies in p + p collisions simulated using Pythia

Stimulated by a keen interest in possible collective behavior in high-energy proton-proton and proton-nucleus collisions, we study two-particle angular correlations in pseudorapidity and azimuthal differences in simulated p + p interactions using the Pythia 8 event generator. Multi-parton interactions and color connection are included in these simulations, which have been perceived to produce collectivity in final-state particles. Meanwhile, contributions from genuine few-body nonflow correlations, not of collective flow behavior, are known to be severe in these small-system collisions. We present our Pythia correlation studies pedagogically and report azimuthal harmonic anisotropies analyzed using several methods. We observe anisotropies in these Pythia simulated events qualitatively and semi-quantitatively, similar to experimental data. Furthermore, our findings highlight the delicate nature of azimuthal anisotropies in small-system collisions and provide a benchmark that can aid in improving data analysis and interpreting experimental measurements in small-system collisions.

Pythia↗

DOE OSTI2022

Spontaneous self-propulsion and nonequilibrium shape fluctuations of a droplet enclosing active particles

Active particles, such as swimming bacteria or self-propelled colloids, spontaneously assemble into large-scale dynamic structures. Geometric boundaries often enforce different spatio-temporal patterns compared to unconfined environment and thus provide a platform to control the behavior of active matter. Here, we report collective dynamics of active particles enclosed by soft, deformable boundary, that is responsive to the particles’ activity. We reveal that a quasi two-dimensional fluid droplet enclosing motile colloids powered by the Quincke effect (Quincke rollers) exhibits strong shape fluctuations with a power spectrum consistent with active fluctuations driven by particle-interface collisions. A broken detailed balance confirms the nonequilibrium nature of the shape dynamics. We further find that rollers self-organize into a single drop-spanning vortex, which can undergo a spontaneous symmetry breaking and vortex splitting. The droplet acquires motility while the vortex doublet exists. Our findings provide insights into the complex collective behavior of active colloidal suspensions in soft confinement.

42 ENGINEERING↗

DOE OSTI2022

Confinement and Collective Escape of Active Particles

Active matter broadly covers the dynamics of self-propelled particles. While the onset of collective behavior in homogenous active systems is relatively well understood, the effect of inhomogeneities such as obstacles and traps lacks overall clarity. Here, we study how interacting, self-propelled particles become trapped and released from a trap. We have found that captured particles aggregate into an orbiting condensate with a crystalline structure. As more particles are added, the trapped condensates escape as a whole. Our results shed light on the effects of confinement and quenched disorder in active matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Emergence of self-organized multivortex states in flocks of active rollers

Active matter, both synthetic and biological, demonstrates complex spatiotemporal self-organization and the emergence of collective behavior. A coherent rotational motion, the vortex phase, is of great interest because of its ability to orchestrate well-organized motion of self-propelled particles over large distances. However, its generation without geometrical confinement has been a challenge. Here, we show by experiments and computational modeling that concentrated magnetic rollers self-organize into multivortex states in an unconfined environment. We find that the neighboring vortices more likely occur with the opposite sense of rotation. Our studies provide insights into the mechanism for the emergence of coherent collective motion on the macroscale from the coupling between microscale rotation and translation of individual active elements. These results may stimulate design strategies for self-assembled dynamic materials and microrobotics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Programmable chiral states in flocks of active magnetic rollers

Inspired by nature, active matter exemplified by self-organization of motile units into macroscopic structures holds great promise for advanced tunable materials capable of flocking, shape-shifting, and self-healing. Active particles driven by external fields have repeatedly demonstrated potential for complex self-organization and collective behavior, yet how to guide the direction of their collective motion largely remains unexplored. Here, we report a system of microscopic ferromagnetic rollers driven by an alternating magnetic field that demonstrates programmable control of the direction of a self-organized coherent vortical motion (i.e., chirality). Facilitated by a droplet confinement, the rollers get synchronized and display either right- or left-handed spontaneous vortical motion, such that their moving direction determines the vortex chirality. Here, we reveal that one can remotely command a flock of magnetic rollers to switch or maintain its chiral state by modulating a phase shift of the sinusoidal magnetic field powering the active rollers. Building on our findings, we realize a self-assembled remotely controlled micro-pump architecture capable of switching the fluid transport direction on demand. Our studies may stimulate new design strategies for directed transport and flocking robotics at the microscale based on active colloids.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

Electrochemical and spectroelectrochemical characterization of bacteria and bacterial systems

Microbes, such as bacteria, can be described, at one level, as small, self-sustaining chemical factories. Based on the species, strain, and even the environment, bacteria can be useful, neutral or pathogenic to human life, so it is increasingly important that we be able to characterize them at the molecular level with chemical specificity and spatial and temporal resolution in order to understand their behavior. Bacterial metabolism involves a large number of internal and external electron transfer processes, so it is logical that electrochemical techniques have been employed to investigate these bacterial metabolites. In this mini-review, we focus on electrochemical and spectroelectrochemical methods that have been developed and used specifically to chemically characterize bacteria and their behavior. First, we discuss the latest mechanistic insights and current understanding of microbial electron transfer, including both direct and mediated electron transfer. Second, we summarize progress on approaches to spatiotemporal characterization of secreted factors, including both metabolites and signaling molecules, which can be used to discern how natural or external factors can alter metabolic states of bacterial cells and change either their individual or collective behavior. Finally, we address in situ methods of single-cell characterization, which can uncover how heterogeneity in cell behavior is reflected in the behavior and properties of collections of bacteria, e.g. bacterial communities. Recent advances in (spectro)electrochemical characterization of bacteria have yielded important new insights both at the ensemble and the single-entity levels, which are furthering our understanding of bacterial behavior. Furthermore, these insights, in turn, promise to benefit applications ranging from biosensors to the use of bacteria in bacteria-based bioenergy generation and storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Evidence of a distinct collective mode in Kagome superconductors

The collective modes of the superconducting order parameter fluctuation can provide key insights into the nature of the superconductor. Recently, a family of superconductors has emerged in non-magnetic kagome materials AV 3 Sb 5 (A = K, Rb, Cs), exhibiting fertile emergent phenomenology. However, the collective behaviors of Cooper pairs have not been studied. Here, we report a distinct collective mode in CsV 3-x Ta x Sb 5 using scanning tunneling microscope/spectroscopy. The spectral line-shape is well-described by one isotropic and one anisotropic superconducting gap, and a bosonic mode due to electron-mode coupling. With increasing x, the two gaps move closer in energy, merge into two isotropic gaps of equal amplitude, and then increase synchronously. The mode energy decreases monotonically to well below 2Δ and survives even after the charge density wave order is suppressed. We propose the interpretation of this collective mode as Leggett mode between different superconducting components or the Bardasis-Schrieffer mode due to a subleading superconducting component.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Shape-anisotropy inverses the behavior of emergent vortices in active chiral fluids

Active colloidal fluids exhibit spontaneous emergence of correlated states, characterized by complex collective dynamics and self-organization. In geometrically confined systems, activity modulations trigger robust polar state reversals of a macroscopic vortex formed by colloidal rollers. Here, we reveal that the shape anisotropy of dielectric rollers transforms the system into a chiral active fluid comprised of rollers of arbitrary handedness. The chiral rollers self-assemble into multiple freestanding vortices with a spontaneously selected sense of rotation. We demonstrate that upon reactivation of the system after a complete cessation of activity beyond all relevant timescales, the vortices simultaneously restore their previous chiral states in striking contrast to the chiral state reversals demonstrated by spherical rollers. The analysis reveals that shape-anisotropy modifies the collective state memory of the ensemble. The findings provide insights into the emergence of complex collective behavior in chiral colloidal fluids governed by an interplay between shape anisotropy, chiral motion, and activity modulations.

Colloids↗

DOE OSTI2022

Threat emulation framework

A method for emulating threats in virtual network computing environment is provided. The method comprises creating a number of virtual machines in the virtual network computing environment. A number of threat actors are emulated, wherein each threat actor comprises a number of threat artifacts that form a sequence of attack steps against the virtual network computing environment. The threat actors are then deployed against the virtual network computing environment. Behavioral data about actions of the threat actors in the virtual network computing environment is collected, as is performance data about the virtual network computing environment in response to the threat actors. The collected behavioral and performance data is then presented to a user via an interface.

Urias, Vincent↗

DOE OSTI2025

Electronic superradiance mediated by nuclear dynamics

Superradiance, in which the collective behavior of emitters can generate enhanced radiative decay, was first predicted by a model, now known as the Dicke model, that contains a collection of two-level systems (the emitters) all interacting with the same photonic mode. In this article, we extend the original Dicke model to elucidate the influence of nuclear motion on superradiant emission. Our dynamical simulations of the combined electronic, nuclear, and photonic system reveal a new time scale attributed to the population leakage of the dark, subradiant states. Furthermore, this dark-state emission pathway can be controlled by tuning the nuclear potential energy landscape. These findings impact how superradiant states and molecular degrees of freedom can be leveraged and utilized in quantum optical systems. Published by the American Physical Society 2025

Tao, Xuecheng (ORCID:0000000329073839)↗

DOE OSTI2022

Shape-driven, emergent behavior in active particle mixtures

Abstract Active particle systems can vary greatly from one-component systems of spheres to mixtures of particle shapes at different composition ratios. We investigate computationally the combined effect of anisotropy and stoichiometry on the collective behavior of two-dimensional active colloidal mixtures of polygons. We uncover three emergent phenomena not yet reported in active Brownian particle systems. First, we find that mixtures containing hexagons exhibit micro-phase separation with large grains of hexagonal symmetry. We quantify a measurable, implicit ‘steric attraction’ between the active particles as a result of shape anisotropy and activity. This calculation provides further evidence that implicit interactions in active systems, even without explicit attraction, can lead to an effective preferential attraction between particles. Next, we report stable fluid clusters in mixtures containing one triangle or square component. We attribute the fluidization of the dense cluster to the interplay of cluster destabilizing particles, which introduce grain boundaries and slip planes into the system, causing solid-like clusters to break up into fluid clusters. Third, we show that fluid clusters can coexist with solid clusters within a sparse gas of particles in a steady state of three coexisting phases. Our results highlight the potential for a wide variety of behavior to be accessible to active matter systems and establish a route to control active colloidal systems through simple parameter designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Exploring the influence of bulk viscosity of QCD on dilepton tomography

The collective behavior of hadrons and of electromagnetic radiation in heavy-ion collisions has been widely used to study the properties of the quark-gluon plasma (QGP). Indeed this collectivity, as measured by anisotropic flow coefficients, can be used to constrain the transport properties of QGP. The goal of this contribution is to investigate the influence of the specific bulk viscosity (ζ/s) on dilepton production, both at Relativistic Heavy-Ion Collider and Large Hadron Collider energies. We explore the sensitivity of dileptons to dynamical features that bulk viscosity induces on the evolution of a strongly interacting medium, and highlight what makes them a valuable probe in the pursuit to also constrain ζ/s.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Bulk Photovoltaic Effect Driven by Collective Excitations in a Correlated Insulator

We investigate the bulk photovoltaic effect, which rectifies light into electric current, in a collective quantum state with correlation driven electronic ferroelectricity. We show via explicit real-time dynamical calculations that the effect of the applied electric field on the electronic order parameter leads to a strong enhancement of the bulk photovoltaic effect relative to the values obtained in a conventional insulator. The enhancements include both resonant enhancements at sub-band-gap frequencies, arising from excitation of optically active collective modes, and broadband enhancements arising from nonresonant deformations of the electronic order. The deformable electronic order parameter produces an injection current contribution to the bulk photovoltaic effect that is entirely absent in a rigid-band approximation to a time-reversal symmetric material. Furthermore, our findings establish that correlation effects can lead to the bulk photovoltaic effect and demonstrate that the collective behavior of ordered states can yield large nonlinear optical responses.

14 SOLAR ENERGY↗

DOE OSTI2025

Terahertz-field activation of polar skyrons

Unraveling collective modes arising from coupled degrees of freedom is crucial for understanding complex interactions in solids and developing new functionalities. Unique collective behaviors emerge when two degrees of freedom, ordered on distinct length scales, interact. Polar skyrmions, three-dimensional electric polarization textures in ferroelectric superlattices, disrupt the lattice continuity at the nanometer scale with nontrivial topology, leading to previously unexplored collective modes. Here, using terahertz-field excitation and femtosecond x-ray diffraction, we discover subterahertz collective modes, dubbed “skyrons”, which appear as swirling patterns of atomic displacements functioning as atomic-scale gearsets. The key to activating skyrons is the use of the THz field that couples primarily to skyrmion domain walls. Momentum-resolved time-domain measurements of diffuse scattering reveal an avoided crossing in the dispersion relation of skyrons. Atomistic simulations and dynamical phase-field modeling provide microscopic insights into the three-dimensional crystallographic and polarization dynamics. The amplitude and dispersion of skyrons are demonstrated to be controlled by sample temperature and electric-field bias. The discovery of skyrons and their coupling with terahertz fields opens avenues for ultrafast control of topological polar structures.

ferroelectrics↗

DOE OSTI2021

Temperature-dependent collective magnetization reversal in a network of ferromagnetic nanowires

The collective behavior of geometrically frustrated magnetization in connected networks of ferromagnetic nanowires, known as artificial spin ice, leads to complex magnetotransport behavior in those structures. Here, we present temperature- and current-dependent magnetotransport studies on a connected square artificial spin-ice system and correlate our observations to micromagnetic simulations. We find that the field at which the lattice magnetization collectively switches increases as the temperature is lowered. Our experimental findings highlight the importance of the global and local temperatures for the onset of a collective magnetization reversal in the connected system. These studies may also provide useful insights into novel storage concepts and applications in neuromorphic computing.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Bridging nuclear physics across energy scales: from neutrinoless double-beta decay to high-energy heavy-ion collisions

This paper exemplifies how connecting methods at disparate energy scales can illuminate fundamental questions. By demonstrating that nuclear wave function properties governing rare decay processes also influence collective behavior at extreme temperatures and densities, the authors have opened a new pathway for constraining physics beyond the Standard Model. With multiple ton-scale 0νββ experiments under construction, any method reducing NME uncertainties will directly impact our ability to interpret discoveries or constrain neutrino properties. The general principle—that collective phenomena in high-energy collisions can illuminate subtle features of many-body correlations in the colliding nuclei—may find applications across nuclear and particle physics. Furthermore, this intersection of nuclear structure theory, heavy-ion physics, and fundamental symmetry tests represents fertile ground for future discoveries in modern physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Structured ground states of randomly interacting bosons

Bosonic degrees of freedom and their emergence as part of complex quantum many-body dynamics, symmetries, collective behavior, clustering, and phase transitions play an important role in modern studies of quantum systems. In this paper, we present a systematic study of many-boson systems governed by random interactions. Our findings show that ground states of randomly interacting bosons are not random, being dominated by a few collective configurations containing condensates of clusters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗