arXiv subjects

Luca Cocconi

Publications and source records attributed to Luca Cocconi.

At least 19 recordsLinked to original sources

arXiv2026

Finite-Time Optimal Control by Noisy Traps

The optimal control of passive systems in equilibrium typically favours quasistatic (infinite-time) protocols. We show that a breakdown of quasistatic optimality occurs when the controller itself is dissipative. Concretely, we study a Brownian particle confined by a harmonic trap with stochastically fluctuating stiffness, driven by an external protocol. When these fluctuations violate detailed balance, the probe-controller coupling continuously exchanges work with the system, altering the optimisation landscape. In this regime, optimal protocols are characterised by a finite duration which vanishes above a critical fluctuation strength. This transition can be directly observed in a short-time expansion of the mean work functional. When imposing an endpoint constraint, the transition to zero duration disappears and finite duration protocols remain optimal for all values of the controller fluctuations. These results demonstrate that finite-time optimality can emerge in passive systems under nonequilibrium control.

cond-mat.stat-mech↗

arXiv2026

Effective attraction by repulsion

Repulsive self-propelled particles tend to cluster, leading to Motility-Induced Phase Separation (MIPS). By analogy with equilibrium phase separation, the onset of MIPS has been associated with a transition to effective attraction between particles. Using an exact microscopic theory, we quantify the emergence of effective attraction in a minimal model: two soft run-and-tumble particles in a periodic domain. We show that, as repulsion increases, the leading-order behaviour is that of effective repulsion, while effective attraction emerges as a higher-order contribution to the renormalisation of the pair potential.

cond-mat.stat-mech↗

arXiv2026

Microscopic theory of soft run-and-tumble particles

Soft, repulsive run-and-tumble particles display emergent effective interactions as they appear to stick to each other in spite of the absence of attractive forces. This effective attraction emerges at strong enough repulsion and large self-propulsion. Complementing a companion paper that characterises effective attraction between two soft run-and-tumble particles [Garcia-Millan et al., Effective attraction by repulsion (2026)], here we provide a thorough derivation of our microscopic theory, which is an exact representation of the particle dynamics. We report the systematic calculation of the effective interaction vertices iteratively, in a perturbation expansion about the interaction couplings, by adding, order by order, loop corrections. We use the effective interaction vertices to calculate the two-point correlation function, fully characterising the stationary state. Other observables, such as the structure factor, overlap probability and entropy production rate are calculated as well.

cond-mat.stat-mech↗

arXiv2026

Odd pathways speed up self-assembly

Active self-assembly can bypass equilibrium bottlenecks through external energy injection. However, generic driving typically distorts target structures and requires sustained energy input even after assembly is complete. Here, we investigate a class of non-reciprocal interactions that accelerates assembly while preserving the equilibrium Boltzmann distribution. The probability currents induced by these odd interactions reshape fundamental processes, including activated barrier crossing, soft-mode relaxation, and transitions between metastable states. In particular, these currents enhance Arrhenius rates by driving particles across otherwise inaccessible free-energy barriers. We show that this acceleration arises from an effective increase in the mobility of the reaction coordinate, mediated by non-reciprocal coupling between mechanical modes. In turn, we discover a trade-off between kinetic acceleration and power dissipation when active forces are engaged. Our results suggest a route to energy-efficient, high-fidelity self-assembly via active catalysts that transiently accelerate relaxation toward equilibrium targets and deactivate upon reaching the desired state.

cond-mat.soft↗

arXiv2026

Nonequilibrium energetics of sensing and actuation by a smart active particle

Smart active agents must allocate finite energetic resources across distinct functions, yet the underlying thermodynamic trade-offs remain poorly understood. Here, we introduce a minimal model of a self-steering particle with an internal polarity-cue sensor coupled to an external environmental field, decomposing its steady-state entropy production rate into locomotion, actuation, and sensing costs. This separation exposes an energetic bookkeeping structure underlying even the simplest form of embodied navigation. The emergence of Pareto fronts linking energetic expenditure to localisation precision and path-following performance shows that feedback-controlled active motion is constrained by quantitative thermodynamic bounds that persist across distinct task geometries.

cond-mat.soft↗

arXiv2025

Conditional splitting probabilities for hidden-state inference in drift-diffusive processes

Splitting probabilities quantify the likelihood of particular outcomes out of a set of mutually-exclusive possibilities for stochastic processes and play a central role in first-passage problems. For two-dimensional Markov processes $\{X(t),Y(t)\}_{t\in T}$, a joint analogue of the splitting probabilities can be defined, which captures the likelihood that the variable $X(t)$, having been initialised at $x_0 \in \mathbb{L}$, exits $\mathbb{L}$ for the first time via either of the interval boundaries \emph{and} that the variable $Y(t)$, initialised at $y_0$, is given by $y_{\rm exit}$ at the time of exit. We compute such joint splitting probabilities for two classes of processes: processes where $X(t)$ is Brownian motion and $Y(t)$ is a decoupled internal state, and unidirectionally coupled processes where $X(t)$ is drift-diffusive and depends on $Y(t)$, while $Y(t)$ evolves independently. For the first class we obtain generic expressions in terms of the eigensystem of the Fokker-Planck operator for the $Y$ dynamics, while for the second we carry out explicit derivations for three paradigmatic cases (run-and-tumble motion, diffusion in an intermittent piecewise-linear potential and diffusion with stochastic resetting). Drawing on Bayes' theorem, we subsequently introduce the related notion of conditional splitting probabilities, defined as the posterior likelihoods of the internal state $Y$ \emph{given} that the observable degree of freedom $X$ has undergone a specific exit event. After computing these conditional splitting probabilities, we propose a simple scheme that leverages them to partially infer the assumedly hidden state $Y(t)$ from point-wise detection events.

math-ph↗

arXiv2025

Mechanical inhibition of dissipation in a thermodynamically consistent active solid

The study of active solids offers a window into the mechanics and thermodynamics of dense living matter. A key aspect of the non-equilibrium dynamics of such active systems is a mechanistic description of how the underlying mechano-chemical couplings arise, which cannot be resolved in models that are phenomenologically constructed. Here, we follow a bottom-up theoretical approach to develop a thermodynamically consistent active solid (TCAS) model, and uncover a non-trivial cross-talk that naturally ensues between mechanical response and dissipation. In particular, we show that dissipation reaches a maximum at finite stresses, while it is inhibited under large stresses, effectively reverting the system to a passive state. Our findings establish a generic mechanism plausibly responsible for the non-monotonic behaviour observed in recent experimental measurements of entropy production rate in an actomyosin material and enzymatic activity in crowded condensates.

cond-mat.soft↗

arXiv2025

Mechanical work extraction from an error-prone active dynamic Szilard engine

Isothermal information engines operate by extracting net work from a single heat bath through measurement and feedback control. In this work, we analyze a realistic active Szilard engine operating on a single active particle by means of steric interaction with an externally controlled mechanical element. In particular, we provide a comprehensive study of how finite measurement accuracy affects the engine's work and power output, as well as the cost of operation. Having established the existence of non-trivial optima for work and power output, we study the dependence of their loci on the measurement error parameters and identify conditions for their positivity under one-shot and cyclic engine operation. By computing a suitably defined information efficiency, we also demonstrate that this engine design allows for the violation of Landauer's bound on the efficiency of information-to-work conversion. Notably, the information efficiency for one-shot operation exhibits a discontinuous transition and a non-monotonic dependence on the measurement precision. Finally, we show that cyclic operation improves information efficiency by harvesting residual mutual information between successive measurements.

cond-mat.stat-mech↗

arXiv2025

Intelligent Soft Matter: Towards Embodied Intelligence

Intelligent soft matter stands at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field seeks to create materials that possess life-like capabilities, such as perception, learning, memory, and adaptive behavior. Unlike traditional materials, which typically perform static or predefined functions, intelligent soft matter dynamically interacts with its environment. It integrates multiple sensory inputs, retains experiences, and makes decisions to optimize its responses. Inspired by biological systems, these materials intend to leverage the inherent properties of soft matter: flexibility, self-evolving, and responsiveness to perform functions that mimic cognitive processes. By synthesizing current research trends and projecting their evolution, we present a forward-looking perspective on how intelligent soft matter could be constructed, with the aim of inspiring innovations in fields such as biomedical devices, adaptive robotics, and beyond. We highlight new pathways for integrating design of sensing, memory and action with internal low-power operations and discuss challenges for practical implementation of materials with "intelligent behavior". These approaches outline a path towards to more robust, versatile and scalable materials that can potentially act, compute, and "think" by their inherent intrinsic material behaviour beyond traditional smart technologies relying on external control.

cond-mat.soft↗

arXiv2025

Information-optimal mixing at low Reynolds number

Mutual information between particle positions before and after mixing provides a universal assumption-free measure of mixing efficiency at low Reynolds number which accounts for the kinematic reversibility of the Stokes equation. For a generic planar shear flow with time-dependent shear rate, we derive a compact expression for the mutual information as a nonlinear functional of the shearing protocol and solve the associated extremisation problem exactly to determine the optimal control under both linear and non-linear constraints, specifically total shear and total dissipation per unit volume. Remarkably, optimal protocols turn out to be universal and time-reversal symmetric in both cases. Our results establish a minimum energetic cost of erasing information in a broad class of non-equilibrium drift-diffusive systems.

cond-mat.stat-mech↗

arXiv2024

Dissipation-accuracy tradeoffs in autonomous control of smart active matter

The study of motility control by smart agents offers a promising platform for systematically exploring the fundamental physical constraints underlying the functioning of bio-inspired micro-machines operating far from equilibrium. Here, we address the question of the energy cost required for a self-steering active agent to localise itself within a specific region of space or follow a pre-defined trajectory under the influence of fluctuations and external flows. Building on a stochastic thermodynamic formulation of the problem, we derive a generic relationship between dissipation and localisation accuracy, which reveals a fundamental dissipation-accuracy tradeoff constraining the agent's performance. In addition, we illustrate how our framework enables the derivation of optimal steering policies that achieve localisation at minimum energy expenditure.

cond-mat.stat-mech↗

arXiv2024

The OU$^2$ process: Characterising dissipative confinement in noisy traps

The Ornstein-Uhlenbeck (OU) process describes the dynamics of Brownian particles in a confining harmonic potential, thereby constituting the paradigmatic model of overdamped, mean-reverting Langevin dynamics. Despite its widespread applicability, this model falls short when describing physical systems where the confining potential is itself subjected to stochastic fluctuations. However, such stochastic fluctuations generically emerge in numerous situations, including in the context of colloidal manipulation by optical tweezers, leading to inherently out-of-equilibrium trapped dynamics. To explore the consequences of stochasticity at this level, we introduce a natural extension of the OU process, in which the stiffness of the harmonic potential is itself subjected to OU-like fluctuations. We call this model the OU$^2$ process. We examine its statistical, dynamic, and thermodynamic properties through a combination of analytical and numerical methods. Importantly, we show that the probability density for the particle position presents power-law tails, in contrast to the Gaussian decay of the standard OU process. In turn, this causes the trapping behavior, extreme value statistics, first passage statistics, and entropy production of the OU$^2$ process to differ qualitatively from their standard OU counterpart. Due to the wide applicability of the standard OU process and of the proposed OU$^2$ generalisation, our study sheds light on the peculiar properties of stochastic dynamics in random potentials and lays the foundation for the refined analysis of the dynamics and thermodynamics of numerous experimental systems.

cond-mat.stat-mech↗

arXiv2024

On the efficiency of an autonomous dynamic Szilard engine operating on a single active particle

The Szilard engine stands as a compelling illustration of the intricate interplay between information and thermodynamics. While at thermodynamic equilibrium, the apparent breach of the second law of thermodynamics was reconciled by Landauer and Bennett's insights into memory writing and erasure, recent extensions of these concepts into regimes featuring active fluctuations have unveiled the prospect of exceeding Landauer's bound, capitalizing on information to divert free energy from dissipation towards useful work. To explore this question further, we investigate an autonomous dynamic Szilard engine, addressing the thermodynamic consistency of work extraction and measurement costs by extending the phase space to incorporate an auxiliary system, which plays the role of an explicit measurement device. The nonreciprocal coupling between active particle and measurement device introduces a feedback control loop, and the cost of measurement is quantified through excess entropy production. The study considers different measurement scenarios, highlighting the role of measurement precision in determining engine efficiency.

cond-mat.stat-mech↗

arXiv2023

Optimal power extraction from active particles with hidden states

We identify generic protocols achieving optimal power extraction from a single active particle subject to continuous feedback control under the assumption that its spatial trajectory, but not its instantaneous self-propulsion force, is accessible to direct observation. Our Bayesian approach draws on the Onsager-Machlup path integral formalism and is exemplified in the cases of free run-and-tumble and active Ornstein-Uhlenbeck dynamics in one dimension. Such optimal protocols extract positive work even in models characterised by time-symmetric positional trajectories and thus vanishing informational entropy production rates. We argue that the theoretical bounds derived in this work are those against which the performance of realistic active matter engines should be compared.

cond-mat.stat-mech↗

arXiv2023

Irreversibility across a nonreciprocal ${\cal PT}$-symmetry-breaking phase transition

Nonreciprocal interactions are commonplace in continuum-level descriptions of both biological and synthetic active matter, yet studies addressing their implications for time-reversibility have so far been limited to microscopic models. Here, we derive a general expression for the average rate of informational entropy production in the most generic mixture of conserved phase fields with nonreciprocal couplings and additive conservative noise. For the particular case of a binary system with Cahn-Hilliard dynamics augmented by nonreciprocal cross-diffusion terms, we observe a non-trivial scaling of the entropy production rate across a parity-time symmetry breaking phase transition. We derive a closed-form analytic expression in the weak-noise regime for the entropy production rate due to the emergence of a macroscopic dynamic phase, showing it can be written in terms of the global polar order parameter, a measure of parity-time symmetry breaking.

cond-mat.stat-mech↗

arXiv2023

Active Bound States Arise From Transiently Nonreciprocal Pair Interactions

Static nonreciprocal forces between particles generically drive persistent motion reminiscent of self-propulsion. Here, we demonstrate that reciprocity-breaking fluctuations about a reciprocal mean coupling strength are sufficient to generate this behavior in a minimal two-particle model, with the velocity of the ensuing \textit{active} bound state being modulated in time according to the nature of these fluctuations. To characterize the ensuing nonequilibrium dynamics, we derive exact results for the time-dependent center of mass mean-squared displacement and average rate of entropy production for two simple examples of discrete- and continuous-state fluctuations. We find that the resulting dimer can exhibit unbiased persistent motion akin to that of an active particle, leading to a significantly enhanced effective diffusivity.

cond-mat.soft↗

arXiv2022

Particle Entity in the Doi-Peliti and Response Field Formalisms

We introduce a procedure to test a theory for point particle entity, that is, whether said theory takes into account the discrete nature of the constituents of the system. We then identify the mechanism whereby particle entity is enforced in the context of two field-theoretic frameworks designed to incorporate the particle nature of the degrees of freedom, namely the Doi-Peliti field theory and the response field theory that derives from Dean's equation. While the Doi-Peliti field theory encodes the particle nature at a very fundamental level that is easily revealed, demonstrating the same for Dean's equation is more involved and results in a number of surprising diagrammatic identities. We derive those and discuss their implications. These results are particularly pertinent in the context of active matter, whose surprising and often counterintuitive phenomenology rests wholly on the particle nature of the agents and their degrees of freedom as particles.

cond-mat.stat-mech↗

arXiv2022

Scaling of Entropy Production under Coarse Graining in Active Disordered Media

Entropy production plays a fundamental role in the study of non-equilibrium systems by offering a quantitative handle on the degree of time-reversal symmetry breaking. It depends crucially on the degree of freedom considered as well as on the scale of description. It was hitherto unknown how the entropy production at one resolution of the degrees of freedom is related to the entropy production at another resolution. This relationship is of particular relevance to coarse grained and continuum descriptions of a given phenomenon. In this work, we derive the scaling of the entropy production under iterative coarse graining on the basis of the correlations of the underlying microscopic transition rates. Our approach unveils a natural criterion to distinguish equilibrium-like and genuinely non-equilibrium macroscopic phenomena based on the sign of the scaling exponent of the entropy production per mesostate.

cond-mat.stat-mech↗