arXiv subjects

Frank Cichos

Publications and source records attributed to Frank Cichos.

At least 19 recordsLinked to original sources

arXiv2026

Feedback control and delayed interactions in active matter

Feedback control plays a central role in active matter, yet it is inevitably accompanied by noise and finite perception--action delays. This Perspective reviews recent advances on active systems with delayed interactions, showing how time delay can induce activity, chirality, transport, and collective pattern formation, and can act as an effective control parameter for switching between dynamical states. We discuss representative single-particle and many-body systems, highlight key experimental realizations, and argue that time delay constitutes an underexplored dimension of morphological intelligence--where intrinsic response dynamics, rather than explicit sensors or computation, enable functional behavior in active matter.

cond-mat.soft↗

arXiv2025

Programmable Hydrodynamics of Active Particles

Self-propelled microparticles create flow fields that determine how they interact with surfaces, external flows, and each other. These flow fields fall into distinct classes--pushers, pullers, and neutral swimmers--each exhibiting fundamentally different collective behaviors. In all existing synthetic systems, this hydrodynamic character is permanently set during fabrication, making it impossible to explore how adaptive switching between these classes might enable new functions or emergent phenomena. Here we demonstrate that the hydrodynamic character of a microswimmer can be programmed and switched on demand. Using patterned laser heating of surface-bound nanoparticles, we create tailored temperature gradients that drive controllable boundary flows at the particle surface. By changing the illumination pattern in real time, we dynamically transform the swimmers flow field continuously tuning from pusher to puller, while the particle continues to swim. Flow measurements confirm quantitative agreement with theory and allow us to simultaneously track how symmetry, power consumption, and efficiency change across modes. This control over hydrodynamic modes opens experimental access to questions that have remained largely theoretical: How do adaptive swimmers respond to crowding or confinement? Can mixtures with tunable pusher-puller ratios reveal new collective states? Our approach provides a platform to address these questions and explore the morphological developments of active matter systems under external physical constraints.

cond-mat.soft↗

arXiv2025

Physical Embodiment Enables Information Processing Beyond Explicit Sensing in Active Matter

Living microorganisms have evolved dedicated sensory machinery to detect environmental perturbations, processing these signals through biochemical networks to guide behavior. Replicating such capabilities in synthetic active matter remains a fundamental challenge. Here, we demonstrate that synthetic active particles can adapt to hidden hydrodynamic perturbations through physical embodiment alone, without explicit sensing mechanisms. Using reinforcement learning to control self-thermophoretic particles, we show that they learn navigation strategies to counteract unobserved flow fields by exploiting information encoded in their physical dynamics. Remarkably, particles successfully navigate perturbations that are not included in their state inputs, revealing that embodied dynamics can serve as an implicit sensing mechanism. This discovery establishes physical embodiment as a computational resource for information processing in active matter, with implications for autonomous microrobotic systems and bio-inspired computation.

cond-mat.soft↗

arXiv2025

Fourier Plane Tomographic Spectroscopy Reveals Orientation-Dependent Multipolar Plasmon Modes in Micrometer-Scale Janus Particles

Plasmonic Janus particles, comprising dielectric cores with thin metallic caps, exhibit complex optical properties due to their asymmetric structure. Despite applications in active matter research, their orientation-dependent scattering properties remain largely unexplored. We introduce Fourier plane tomographic spectroscopy for simultaneous four-dimensional characterization of scattering from individual micrometer-scale particles across wavelength, incident angle, scattering angle, and polarization. Combining measurements with finite-element simulations, we identify discrete spectral markers in visible and near-infrared regions that evolve predictably with cap orientation. Spherical-harmonics decomposition reveals these markers arise from three distinct multipolar modes up to fifth order: axial-propagating transverse-electric, transverse-propagating transverse-electric, and transverse-propagating axial-electric, with retardation-induced splitting. We observe progressive red-shifts and linewidth narrowing of higher-order resonances, demonstrating curvature's influence on mode dispersion. Orientation-specific scattering patterns exhibit polarization-dependent features enabling optical tracking of particle rotation. Our framework applies to diverse material combinations and geometries, offering a toolkit for designing orientation-responsive nanoantennas, reconfigurable metasurfaces, and active colloidal systems with tailored light-matter interactions.

physics.optics↗

arXiv2025

Delayed Active Swimmer in a Velocity Landscape

Self-propelled active particles exhibit delayed responses to environmental changes, modulating their propulsion speed through intrinsic sensing and feedback mechanisms. This adaptive behavior fundamentally determines their dynamics and self-organization in active matter systems, with implications for biological microswimmers and engineered microrobots. Here, we investigate active Brownian particles whose propulsion speed is governed by spatially varying activity landscapes, incorporating a temporal delay between environmental sensing and speed adaptation. Through analytical solutions derived for both short-time and long-time delay regimes, we demonstrate that steady-state density and polarization profiles exhibit maxima at characteristic delays. Significantly, we observe that the polarization profile undergoes sign reversal when the swimming distance during the delay time exceeds the characteristic diffusion length, providing a novel mechanism for controlling particle transport without external fields. Our theoretical predictions, validated through experimental observations and numerical simulations, establish time delay as a crucial control parameter for particle transport and organization in active matter systems. These findings provide insights into how biological microorganisms might use response delays to gain navigation advantages and suggest design principles for synthetic microswimmers with programmable responses to heterogeneous environments.

cond-mat.soft↗

arXiv2024

Regulated polarization of active particles in local osmotic flow fields

Regulation to a well-defined target state is a fundamental requirement for achieving reliable functionality in living systems and maintaining specific non-equilibrium states. The control of certain properties and functionalities of systems on the microscale presents a particular challenge since thermal fluctuations and environmental perturbations dominate. While synthetic active matter has demonstrated remarkable self-organization capabilities, examples of autonomous regulation processes at the single-particle level remain scarce. Here, we show that the interplay of two non-equilibrium processes leads to a regulated polarization state of active particles in local osmotic flow fields. The balance between thermophoretic repulsion and attraction by thermo-osmotic boundary flows, both generated by a single heat source, yields a steady state at which active particles encircle the heat source at a distance that depends on the temperature of the heat source. The balance of both temperature-induced processes causes a polarization of the active particles that is independent of the heat source temperature. The individual control of heat source and active particles in the experiment allows a detailed investigation of the self-regulated polarization effect in which we find that hydrodynamic interactions dominate. As the effects rely on osmotic flows and phoretic interactions, we expect that the observed phenomena can be generalized to other active systems and flow fields.

cond-mat.soft↗

arXiv2024

Thermofluidic non-equilibrium assembly of reconfigurable functional structures

Non-equilibrium assembly, driven by fluxes controllable by continuous external energy inputs, enables dynamic and reconfigurable structures. Such controlled 3D assembly is desired for the design of adaptive materials that exploit structure-function relationships, but has remained challenging. We present a non-equilibrium assembly of colloidal particles mediated by laser-induced local heating and continuous heat dissipation. These 3D out-of-equilibrium structures, assembled in a matter of a few minutes, were highly ordered and exhibited tunable photonic stopbands. We quantify the particle fluxes from the underlying assembly processes and report the growth dynamics of the assembled structures. Furthermore, we demonstrate the modulation of the photonic stopband achieved by modulating the particle fluxes, highlighting the prospects of such thermofluidic assembly for creating reconfigurable functional structures.

cond-mat.soft↗

arXiv2024

The 2024 Motile Active Matter Roadmap

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired by biological active systems, various types of autonomous synthetic nano- and micromachines have been designed, which provide the basis for multifunctional, highly responsive, intelligent active materials. A major challenge for understanding and designing active matter is their inherent non-equilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Furthermore, interactions in ensembles of active agents are often non-additive and non-reciprocal. An important aspect of biological agents is their ability to sense the environment, process this information, and adjust their motion accordingly. It is an important goal for the engineering of micro-robotic systems to achieve similar functionality. With many fundamental properties of motile active matter now reasonably well understood and under control, the ground is prepared for the study of physical aspects and mechanisms of motion in complex environments, of the behavior of systems with new physical features like chirality, of the development of novel micromachines and microbots, of the emergent collective behavior and swarming of intelligent self-propelled particles, and of particular features of microbial systems. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter poses major challenges, which can only be addressed by a truly interdisciplinary effort involving scientists from biology, chemistry, ecology, engineering, mathematics, and physics.

cond-mat.soft↗

arXiv2024

Run-and-tumble motion of ellipsoidal microswimmers

A hallmark of bacteria is their so-called "run-and-tumble" motion, consisting of a sequence of linear directed "runs" and random rotations that constantly alternate due to biochemical feedback. It plays a crucial role in the ability of bacteria to move through chemical gradients and inspired a fundamental active particle model. Nevertheless, synthetic active particles generally do not exhibit run-and-tumble motion but rather active Brownian motion. We show in experiments that ellipsoidal thermophoretic Janus particles, propelling along their short axis, can yield run-and-tumble-like motion even without feedback. Their hydrodynamic wall interactions under strong confinement give rise to an effective double-well potential for the declination of the short axis. The geometry-induced timescale separation of the in-plane rotational dynamics and noise-induced transitions in the potential then yields run-and-tumble-like motion.

cond-mat.soft↗

arXiv2024

Unleashing Urease Protein Dynamics with Metamaterial Optical Tweezers

Investigating the dynamics of single biomolecules is essential for unlocking new frontiers in biophysics and medicine. Here, we present a transformative approach using metamaterial optical tweezers to trap and study individual urease molecules - an enzyme that catalyzes urea hydrolysis and serves as a key biomarker for pathogenic infections. By generating thermally induced drifts and rapid hydrodynamic flows with optically induced local temperature fields at the metamaterial/water interface, we achieve unprecedented guidance and control over single urease molecules at low trapping laser intensities of 0.13~mW/{\mu}m^2 facilitating their precise delivery to plasmonic hotspots. The interplay of thermophoresis, thermo-osmosis and depletion forces shapes the trapping potential, enabling real-time observation of ureases` conformational changes and interactions with the environment. This innovative approach not only enhances our understanding of enzyme dynamics but also paves the way for label-free characterization of biomolecules, ushering in a new era in life sciences and nanotechnology.

physics.optics↗

arXiv2023

Harnessing Synthetic Active Particles for Physical Reservoir Computing

The processing of information is an indispensable property of living systems realized by networks of active processes with enormous complexity. They have inspired many variants of modern machine learning one of them being reservoir computing, in which stimulating a network of nodes with fading memory enables computations and complex predictions. Reservoirs are implemented on computer hardware, but also on unconventional physical substrates such as mechanical oscillators, spins, or bacteria often summarized as physical reservoir computing. Here we demonstrate physical reservoir computing with a synthetic active microparticle system that self-organizes from an active and passive component into inherently noisy nonlinear dynamical units. The self-organization and dynamical response of the unit is the result of a delayed propulsion of the microswimmer to a passive target. A reservoir of such units with a self-coupling via the delayed response can perform predictive tasks despite the strong noise resulting from Brownian motion of the microswimmers. To achieve efficient noise suppression, we introduce a special architecture that uses historical reservoir states for output. Our results pave the way for the study of information processing in synthetic self-organized active particle systems.

cond-mat.soft↗

arXiv2023

Active particles with delayed attractions form quaking crystallites

Perception-reaction delays have experimentally been found to cause a spontaneous circling of microswimmers around a targeted center. Here we investigate the many-body version of this experiment with Brownian-dynamics simulations of active particles in a plane. For short delays, the soft spherical discs form a hexagonal colloidal crystallite around a fixed target particle. Upon increasing the delay time, we observe a bifurcation to a chiral dynamical state that we can map onto that found for a single active particle. The different angular velocities at different distances from the target induce shear stresses that grow with increasing delay. As a result, tangential and, later, also radial shear bands intermittently break the rotating crystallite. Eventually, for long delays, the discs detach from the target particle to circle around it near the preferred single-particle orbit, while spinning and trembling from tidal quakes

cond-mat.soft↗

arXiv2023

Roadmap on Deep Learning for Microscopy

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

physics.optics↗

arXiv2022

Spontaneous vortex formation by microswimmers with retarded attractions

Collective states of inanimate particles self-assemble through physical interactions and thermal motion. Despite some phenomenological resemblance, including signatures of criticality, the autonomous dynamics that binds motile agents into flocks, herds, or swarms allows for much richer behavior. Low-dimensional models have hinted at the crucial role played in this respect by perceived information, decision-making, and feedback implying that the corresponding interactions are inevitably retarded. Here we present experiments on spherical Brownian microswimmers with delayed self-propulsion toward a spatially fixed target. We observe a spontaneous symmetry breaking to a transiently chiral dynamical state and concomitant critical behavior that does not rely on many-particle cooperativity. By comparison with the stochastic delay differential equation of motion of a single swimmer, we pinpoint the delay-induced effective synchronization of the swimmers with their own past as its key mechanism. Increasing numbers of swimmers self-organize into layers with pro- and retrograde orbital motion, synchronized and stabilized by steric and hydrodynamic interactions. Our results demonstrate how even most simple retarded non-reciprocal interactions can foster emergent complex adaptive behavior in relatively small ensembles.

cond-mat.soft↗

arXiv2021

Hydrodynamic Manipulation of Nano-Objects by Thermo-Osmotic Flows

The manipulation of micro- and nano-objects is of great technological significance to construct new materials, manipulate tiny amounts of liquids in fluidic systems, or detect minute concentrations of analytes. It is commonly approached by the generation of potential energy landscapes, for example, with optical fields. Here we show that strong hydrodynamic boundary flows enable the trapping and manipulation of nano-objects near surfaces. These thermo-osmotic flows are induced by modulating the van der Waals interaction at a solid-liquid interface with optically induced temperature fields. We use a thin gold film on a glass substrate to provide localized but reconfigurable point-like optical heating. Convergent boundary flows with velocities of tens of micrometres per second are observed and substantiated by a quantitative physical model. The hydrodynamic forces acting on suspended nanoparticles and attractive van der Waals or depletion induced forces to enable precise positioning and guiding of the nanoparticles. Fast multiplexing of flow fields further provides the means for parallel manipulation of many nano-objects. Our findings have direct consequences for the field of plasmonic nano-tweezers and other thermo-plasmonic trapping schemes and pave the way for a general scheme of nanoscopic manipulation with boundary flows.

cond-mat.soft↗

arXiv2021

Finite-size scaling at the edge of disorder in a time-delay Vicsek model

Living many-body systems often exhibit scale-free collective behavior reminiscent of thermal critical phenomena. But their mutual interactions are inevitably retarded due to information processing and delayed actuation. We numerically investigate the consequences for the finite-size scaling in the Vicsek model of motile active matter. A growing delay time initially facilitates but ultimately impedes collective ordering and turns the dynamical scaling from diffusive to ballistic. It provides an alternative explanation of swarm traits previously attributed to inertia.

cond-mat.soft↗

arXiv2021

Thermotaxis of Janus Particles

The interactions of autonomous microswimmers play an important role for the formation of collective states of motile active matter. We study them in detail for the common microswimmer-design of two-faced Janus spheres with hemispheres made from different materials. Their chemical and physical surface properties may be tailored to fine-tune their mutual attractive, repulsive or aligning behavior. To investigate these effects systematically, we monitor the dynamics of a single gold-capped Janus particle in the external temperature field created by an optically heated metal nanoparticle. We quantify the orientation-dependent repulsion and alignment of the Janus particle and explain it in terms of a simple theoretical model for the induced thermoosmotic surface fluxes. The model reveals that the particle's angular velocity is solely determined by the temperature profile on the equator between the Janus particle's hemispehres and their phoretic mobility contrast. The distortion of the external temperature field by their heterogeneous heat conductivity is moreover shown to break the apparent symmetry of the problem.

cond-mat.soft↗

arXiv2021

Polarization-Density Patterns of Active Particles in Motility Gradients

The co-localization of density modulations and particle polarization is a characteristic emergent feature of motile active matter in activity gradients. It can therefore play the role of a smoking gun for the mesoscale detection of intrinsic microscopic activity. We employ the active-Brownian-particle (ABP) model to derive precise analytical expressions for the density and polarization profiles of a single Janus-type swimmer in the vicinity of an abrupt activity step, including situations with an orientation-dependent propulsion speed. Our results agree well with measurement data for a hot microswimmer presented in the companion paper [1] and can serve as a template for more complex applications, e.g., to motility-induced phase separation or studies of physical boundaries. The essential physics behind our formal results is robustly captured and elucidated by a schematic two-species ``run-and-tumble'' model.

cond-mat.soft↗