arXiv subjects

Gustavo A. L. Forão

Publications and source records attributed to Gustavo A. L. Forão.

11 recordsLinked to original sources

arXiv2026

Universal splitting of nonequilibrium phase transitions in driven Potts heat engines

We investigate nonequilibrium phase transitions and thermodynamic properties of driven Potts models coupled to two thermal reservoirs at different temperatures. The interplay with the multi-state structure of the Potts model leads to distinct phase-transition scenarios. The proposed driving scheme breaks the symmetry between the Potts states and gives rise to multiple transitions within the ordered phases, where the phases are characterized by different numbers of stable fixed points. This number can vary from $q$ fixed points to $1$ fixed point, corresponding to $q-1$ distinct transitions. The driving scheme strongly affects the thermodynamic operation regimes, allowing the system to operate as a heat engine. We demonstrate that these phenomena persist for both a mean-field (MF) model and a two-dimensional model, confirming the robustness of the results with respect to dimensionality. For the MF case, we also develop a phenomenological description in the strongly ordered regime that yields analytical expressions for the power, heat currents, and efficiency. Our results show how multi-state collective interactions, nonequilibrium driving, and thermal bias jointly generate a rich phase structure and the emergence of a collective heat engine.

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arXiv2026

Cyclic Heat Engine with the Ising model: role of interactions and criticality

Heat engines that convert thermal energy into work are a cornerstone of classical thermodynamics and remain an active area of contemporary research. Notable examples include microscopic heat engines, trade-off relations between power and efficiency, and the attainability of Carnot efficiency at finite power. We propose a cyclic heat engine based on the Ising model, in which the thermodynamic cycle involves variations of both temperature and magnetic field. We analyze the one-dimensional and mean-field Ising models, which allow for simple analytical results and provide new insight into the role of interactions in cyclic heat engines. In particular, we show that interactions can enhance both power and efficiency. Moreover, a system that does not operate as an engine in the absence of interactions can become an engine upon tuning the interaction strength. The mean-field model enables us to investigate the relevance of the phase transition for the performance of this Ising heat engine. Owing to the emergence of spontaneous magnetization, the mean-field model can still operate as an engine even when one of the magnetic fields is set to zero. Remarkably, when the work is maximized, we find that the optimal parameters are numerically consistent with this regime, in which one magnetic field vanishes and the cycle explores the phase transition. We also consider an alternative cycle for the mean-field model, obtained by varying the interaction strength while keeping both temperatures below the critical temperature and setting the magnetic field to zero throughout the cycle. The power and efficiency of this cycle are analyzed as well. Finally, while our analytical results are valid for the limit of large period we use numerical simulations for finite periods and show that the power decreases monotonically with the period.

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arXiv2026

Pareto-optimal control strategies in intrinsically nonequilibrium systems

Thermodynamic control is typically formulated as the optimisation of a single objective, yet competing costs rarely admit a common optimum, so single-objective control captures only one corner of the achievable performance space. We develop a general framework for multi-objective thermodynamic control of intrinsically nonequilibrium systems that maps out the full Pareto front of optimal control strategies. We show that Pareto-optimal protocols generically consist of smooth branches connected by boundary jumps, and that the relative weights of the objectives combine with the physical parameters into a single intrinsic scale that alone governs the trade-off. Remarkably, this scale plays a double role: it parametrizes a single functional form that generates the entire front, and it defines control equivalence classes, in which systems with different parameters but the same scale share identical optimal strategies. We illustrate the framework for two paradigmatic systems that are experimentally accessible: transport of an active particle in a harmonic trap, and a cyclic quantum-dot engine. For both, we obtain the Pareto front and optimal strategies in closed form.

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arXiv2025

Universal splitting of phase transitions and performance optimization in driven collective systems

Spontaneous symmetry breaking is a hallmark of equilibrium systems, typically characterized by a single critical point separating ordered and disordered phases. Recently, a novel class of non-equilibrium phase transitions was uncovered [Phys. Rev. Res. {\bf 7}, L032049 (2025)], showing that the combined effects of simultaneous contact with thermal baths at different temperatures and external driving forces can split the conventional order-disorder transition into two distinct critical points, determined by which ordered state initially dominates. We show the robustness of this phenomenon by extending a minimal interacting-spin model from the idealized case of simultaneous bath coupling to a finite-time coupling protocol. In particular, we introduce two protocols in which the system interacts with a single bath at a time: a stochastic protocol, where the system randomly switches between the baths at different temperatures, and a deterministic protocol where the coupling alternates periodically. Our analysis reveals two key results: (i) the splitting of phase transitions persists across all coupling schemes -- simultaneous, stochastic, and deterministic -- and (ii) different optimizations of power and efficiency in a collectively operating heat engine reveal that both the stochastic and deterministic protocols exhibit superior global performance at intermediate switching rates and periods when compared to simultaneous coupling. The global trade-off between power and efficiency is described by an expression solely depending on the temperatures of thermal reservoirs as the efficiency approaches to the ideal limit.

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arXiv2025

Statistics of power and efficiency for collisional Brownian engines

Collisional Brownian engines have attracted significant attention due to their simplicity, experimental accessibility, and amenability to exact analytical solutions. While previous research has predominantly focused on optimizing mean values of power and efficiency, the joint statistical properties of these performance metrics remain largely unexplored. Using stochastic thermodynamics, we investigate the joint probability distributions of power and efficiency for collisional Brownian engines, revealing how thermodynamic fluctuations influence the probability of observing values exceeding their respective mean maxima. Our conditional probability analysis demonstrates that when power fluctuates above its maximum mean value, the probability of achieving high efficiency increases substantially, suggesting fluctuation regimes where the classical power-efficiency trade-off can be probabilistically overcome. Notably, our framework extends to a broader class of engines, as the essential features of the statistics of the system are fully determined by the Onsager coefficients. Our results contribute to a deeper understanding of the role of fluctuations in Brownian engines, highlighting how stochastic behavior can enable performance beyond traditional thermodynamic bounds.

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arXiv2025

Characterization and optimization of heat engines: Pareto-optimal fronts and universal features

Characterizing and optimizing nanoscopic heat engines require an appropriate understanding of the interplay between power, efficiency, entropy production and fluctuations. Despite significant recent advancements, including linear stochastic thermodynamics and thermodynamic uncertainty relations (TURs), a complete scenario remains elusive. In this work, we give a further step by showing that, under certain common and general conditions, the heat engine regime can be characterized by the minima of power fluctuations and entropy production, which together delimit its optimal performance, achieved when these conditions are fully satisfied. Conversely, when these conditions are not strictly met, the occurrence of the minimum still approximately describes the system, suggesting a broader range of applicability. Contrasting with most of studies in which the system optimization is carried out solely taking into account the power and efficiency, we introduce a multi-objective optimization framework based on Pareto fronts, also considering the role of fluctuation and dissipation. Our results reveal a general trend: while simultaneous optimization over a few parameters typically yields convex Pareto fronts, these fronts become concave as more parameters are varied freely and non-conservative driving becomes significant. Illustrating our findings, we consider simple two and three state systems as well as richer collective systems, exhibiting novel aspects of optimizations and protocol phase transitions.

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arXiv2025

Optimal control strategy for collisional Brownian engines

Collisional Brownian engines have recently gained attention as alternatives to conventional nanoscale engines. However, a comprehensive optimization of their performance, which could serve as a benchmark for future engine designs, is still lacking. In this work, we address this gap by deriving and analyzing the optimal driving protocol for a collisional Brownian engine. By maximizing the average output work, we show that the optimal protocol consists of linear force segments separated by impulsive delta-like kicks that instantaneously reverse the particle's velocity. This structure enforces constant velocity within each stroke, enabling fully analytical expressions for optimal output power, efficiency, and entropy production. We demonstrate that the optimal protocol significantly outperforms standard strategies (such as constant, linear, or periodic drivings) achieving higher performance while keeping entropy production under control. Remarkably, when evaluated using realistic experimental parameters, the efficiency approaches near-unity at the power optimum, with entropy production remaining well controlled, a striking feature of the optimal protocol. To analyze a more realistic scenario, we examine the impact of smoothing the delta-like forces by introducing a finite duration and find that, although this reduces efficiency and increases entropy production, the optimal protocol still delivers high power output in a robust manner. Altogether, our results provide a theoretical benchmark for finite-time thermodynamic optimization of Brownian engines under time-periodic drivings.

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arXiv2025

Exact Mapping of Nonequilibrium to Equilibrium Phase Transitions for Systems in Contact with Two Thermal Baths

We show that a large class of nonequilibrium many-body systems in contact with two thermal baths admit an exact mapping onto equivalent equilibrium systems. This mapping provides direct access to nonequilibrium phase transition points from known equilibrium results, irrespective of the model, interaction topology, or distance from equilibrium. We verify the universality of this correspondence using paradigmatic models (Ising, Potts, and Blume-Capel), and highlight distinctive features in entropy production close to critical and tricritical points. Our findings connect equilibrium and nonequilibrium statistical mechanics, with implications for microscopic thermal machines and stochastic thermodynamics.

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arXiv2024

Splitting of nonequilibrium phase transitions in driven Ising models

Spontaneous symmetry breaking occurs in various equilibrium and nonequilibrium systems, where phase transitions are typically marked by a single critical point that separates ordered and disordered regimes. We reveal a novel phenomenon in which the interplay between different temperatures and driving forces splits the order-disorder transition into two distinct transition points depending on which ordered state initially dominates. Crucially, these two emerging phases have distinct scaling behaviors and thermodynamic properties. To study this, we propose a minimal variant of the Ising model where spins are coupled to two thermal baths and subjected to two opposite driving forces associated to them. Our findings, robust both for all-to-all interactions (where exact solutions are possible) and nearest-neighbor couplings on a square lattice, uncover unique nonequilibrium behaviors and scaling laws for crucial thermodynamic quantities, such as efficiency, dissipation, power and its fluctuations, that are different between the two ordered phases. We also highlight that one of these emerging phases enables heat-engine operations that are less dissipative and show reduced fluctuations. In this setup, the system can also operate near maximum power and efficiency over a wide parameter range. Our results offer new insights into the relevance of phase transitions under nonequilibrium conditions.

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arXiv2024

Thermodynamics of underdamped Brownian collisional engines: New insights and resonant phenomena

Collisional Brownian engines have been proposed as alternatives for nonequilibrium nanoscale engines. However, most studies have focused on the simpler overdamped case, leaving the role of inertia much less explored. In this work, we introduce the idea of collisional engines to underdamped Brownian particles, where each stage is sequentially subjected to a distinct driving force. A careful comparison between the performance of underdamped and overdamped Brownian work-to-work engines has been undertaken. The results show that underdamped Brownian engines generally outperform their overdamped counterparts. A key difference is the presence of a resonant regime in underdamped engines, in which both efficiency and power output are enhanced across a broad set of parameters. Our study highlights the importance of carefully selecting dynamics and driving protocols to achieve optimal engine performance.

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arXiv2023

Powerful ordered collective heat engines

We introduce a class of stochastic engines in which the regime of units operating synchronously can boost the performance. Our approach encompasses a minimal setup composed of $N$ interacting units placed in contact with two thermal baths and subjected to a constant driving worksource. The interplay between unit synchronization and interaction leads to an efficiency at maximum power between the Carnot, $η_{c}$, and the Curzon-Ahlborn bound, $η_{CA}$. Moreover, these limits can be respectively saturated maximizing the efficiency, and by simultaneous optimization of power and efficiency. We show that the interplay between Ising-like interactions and a collective ordered regime is crucial to operate as a heat engine. The main system features are investigated by means of a linear analysis near equilibrium, and developing an effective discrete-state model that captures the effects of the synchronous phase. The present framework paves the way for the building of promising nonequilibrium thermal machines based on ordered structures.

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