André Barato (University of Houston).

Second Law for Active Heat Engines

Abstract 

Macroscopic cyclic heat engines have been a major motivation for the emergence of thermodynamics. In the past decade, cyclic heat engines that have large fluctuations and operate at finite time were studied within the more modern framework of stochastic thermodynamics. The second law for such heat engines states that the efficiency cannot be larger than the Carnot efficiency. The concept of cyclic active heat engines for a system in the presence of hidden dissipative degrees of freedom, also known as a nonequilibrium or active reservoir, has also been studied in theory and experiment. Such active engines show rather interesting behavior such as an “efficiency” larger than the Carnot bound. They are also likely to play an important role in future developments, given the ubiquitous presence of active media. However, a general second law for cyclic active heat engines has been lacking so far. Here, by using a known inequality in stochastic thermodynamics for the excess entropy, we obtain a general second law for active heat engines, which does not involve the energy dissipation of the hidden degrees of freedom and is expressed in terms of quantities that can be measured directly from the observable degrees of freedom. Besides heat and work, our second law contains an information-theoretic term, which allows an active heat engine to extract work beyond the limits valid for a passive heat engine. To obtain a second law expressed in terms of observable variables in the presence of hidden degrees of freedom, we introduce a coarse-grained excess entropy and prove a fluctuation theorem for this quantity.

11/Jul/2025: Ricardo Martinez-Garcia (CASUS, Germany).

Ergodicity shapes inference in biological reactions driven by a latent trajectory

Many natural phenomena are quantified by counts of observable events, from the annihilation of quasiparticles in a lattice to predator-prey encounters on a landscape to spikes in a neural network. These events are triggered at random intervals when an underlying dynamical system occupies a set of reactive states in its phase space. We derive a general expression for the distribution of times between events in such counting processes assuming the underlying triggering dynamics is a stochastic process that converges to a stationary distribution. Our results contribute to resolving a long-standing dichotomy in the study of reaction-diffusion processes, showing the inter-reaction point process interpolates between a reaction- and a diffusion-limited regime. At low reaction rates, the inter-reaction process is Poisson with a rate depending on stationary properties of the event-triggering stochastic process. At high reaction rates, inter-reaction times are dominated by the hitting times to the reactive states. To further illustrate the power of this approach we apply our framework to obtain the counting statistics of two counting processes appearing in several biophysical scenarios. First, we study the common situation of estimating an animal's activity level by how often it crosses a detector, showing that the mean number of crossing events can decrease monotonically with the hitting rate, a seemingly 'paradoxical' result that could possibly lead to misinterpretation of experimental count data. Second, we derive the ensemble statistics for the detection of many particles, recovering and generalizing known results in the biophysics of chemosensation. Overall, we develop a unifying theoretical framework to quantify inter-event time distributions in reaction-diffusion systems that clarifies existing debates in the literature and provide examples of application to real-world scenarios.

27/Jun/2025: Silvina Ponce Dawson (UBA, CONICET & ICTP-SAIFR).

How do cells derive accurate concentration estimates from individual bindings/unbindings?

Information transmission in cells often depends on individual molecule binding/unbindings. In spite of the intrinsic stochasticity of these processes, in front of a given stimulus, cells and cell components generate reproducible responses within reasonable time frames. This reproducibility can be studied in terms of how fast mean ligand concentrations can be inferred from the number of bindings that occur over a finite time interval. This problem was addressed many years ago by Berg and Purcell within the context of bacteria chemoreception. They showed that the time it takes for a receptor (binding site) to estimate the bulk concentration of its ligand can be derived from the autocorrelation function (ACF) of the bound state of the receptor which, in turn, depends on the diffusion of the ligand and on the rates of binding/unbindings. Some years ago, the correct expression for the correlation time was a matter of debate (with one expression derived by Bialek and Setayeshgar using a system of reaction-diffusion equations and another derived by Kaizu et al building upon previous studies on diffusion- limited reactions). New microscopy experiments allow the direct visualization in vivo of single-molecule intracellular processes (e.g., RNA fluorescence labeling technologies have revealed directly the stochastic bursting that characterizes transcription in cell cultures and in animals and the way it is modulated by different regulators such as transcription factors, TFs). Thus, having correct expressions of the correlation times or of the dwell-time distributions between successive TF bindings or transcription events is key to quantitate biophysical parameters from these observations. Building on our work on the analysis of Fluorescence Correlation Spectroscopy (FCS) experiments, we derived analytic expressions for the ACF in the limits in which diffusion or binding/unbinding were the limiting rates of the process. These expressions allowed us to explain various experimental observations, but several questions remained unanswered. On one hand, we found that the expressions of Bialek and Setayeshgar and of Kaizu et al could be derived using the same machinery but starting from two linear versions of the underlying diffusion system. The meaning of one of those linearizations is not completely clear. Interestingly, different linearizations yield different “effective” diffusion coefficients (effective transport rates that embrace both pure “free” diffusion and binding/unbinding), something we had encountered in the past when comparing different methods to estimate diffusion coefficients from experiments. The other question that remained unanswered was what is the diffusion coefficient that rules the arrival of ligand molecules in the vicinity of a given binding site when thereare several others which compete for the same ligand. The two unanswered questions are intimately related among themselves and are at the basis of many of my research projects. On the other hand, recent observations on the modulation of transcription pose new questions such as the role of transcription factor clusters on the resulting In this seminar I will try to give you a flavor of this conundrum and of the way I tried to approach these problems with the aim of discussing (with you) possible future pathways.

Some bibliography:

• Berg HC, Purcell EM. Physics of chemoreception. Biophysical Journal. 1977;20(2):193– 219.

• Bialek W, Setayeshgar S. Physical limits to biochemical signaling. Proc Natl Acad Sci (USA). 2005;102(29):10040–10045.

• Eck E, Moretti B, Schlomann BH, Bragantini J, Lange M, Zhao X, et al. Single-cell transcriptional dynamics in a living vertebrate. bioRxiv. 2025;doi:10.1101/2024.01.03.574108.

• Kaizu K, de Ronde W, Paijmans J, Takahashi K, Tostevin F, ten Wolde PR. The Berg-Purcell Limit Revisited. Biophysical Journal. 2014;106(4):976–985

• Meeussen JVW, Lenstra TL. Time will tell: comparing timescales to gain insight into transcriptional bursting. Trends in Genetics. 2024;40(2):160–174

• Pando B, Dawson SP, Mak DOD, Pearson JE. Messages diffuse faster than messengers. Proc Natl Acad Sci (USA). 2006;103(14):5338–5342.

• Pŕez Ipiña E, Ponce Dawson S. Fluctuations, Correlations and the Estimation of Concentrations inside Cells. PLOS ONE. 2016;11(3):1–20. doi:10.1371/journal.pone.0151132.

• ten Wolde PR, Becker NB, Ouldridge TE, Mugler A. Fundamental Limits to Cellular Sensing. Journal of Statistical Physics. 2016;162(5):1395–1424. doi:10.1007/s10955-015-1440-5.

06/Jun/2025: Gilles Koudafoke (IFT-UNESP & ICTP-SAIFR).

Modeling and generation of the electrodynamic mode of MEMS/NEMS with Josephson Junction

The first ideas of a miniaturization of an electrical and motor apparatus were issued by the famous physicist Richard Feyman in the 1950s. Launched as a challenge by Richard Feyman, William Mclellam was able to meet this challenge by building such a device size less than (1/64) inch by hand. The electrical and especially the physical properties of this type of apparatus interested other researchers and the industries of manufacture of electro-mechanical devices. In the following years and decades, everyone really sought to miniaturize their devices which often weighed too much and occupied enough space (camera and computers for example).  The goal is to create, alongside electronic functions, miniaturized mechanical functions to serve as sensors, actuators and signal processing systems.  M.L Roukes in his article entitled “Nanoelectromechanical systems facing the future” has demonstrated from time to time what is an electromechanical system, the contributions of nanomachines, the procedure of their manufacture, the challenge of NEMS and some interesting applications of these last. Two of the main challenges of NEMS are amplitude and frequency of vibration of the mechanical part.

This work  deals with a technique for possible modeling of the frequency, amplitudes and electro-dynamic modes of a NEMS (Nano Electro-Mechanical System) obtained by coupling resonators at  Josephson junction. After a mathematical modeling of the electromechanical system, we firstly illustrated the fixed points and their conditions of stability. A numerical study illustrates how one could simultaneously increase the frequency and amplitude of vibration of the nanobeam using different types of Josephson junctions.

References

[1] "Passive sensor with Josephson junction coupled to an electric resonator and a nanobeam" Sensors and Actuators A (2021) Physical 318(2021)112509  https://doi.org/10.1016/j.sna.2020.112509

G. N. Koudafokê, A. L. Hinvi, C. H, Miwadinou, A. V. Monwanou and J. B.  Chabi Orou. 

[2] "Modeling and study of dynamics of micro-beam coupled to two  Josephson junctions" 

 Physica Scripta 95 ( 2020 ) 045205 ( 29pp ) https://doi.org/10.1088/1402-4896/ab30e6 

G. N. Koudafokê, C. H Miwadinou, A. L. Hinvi, A. V. Monwanou and J. B. Chabi Orou. 

[3] "Modeling and generation of electrodynamic modes of a self-sustaining active sensor with Josephson junction"

 International Journal of Dynamics and Control (2020) 8  https://doi.org/10.1007/s40435-019-00595-w

N. G. Koudafokê, C. H. Miwadinou, A. V. Monwanou, L. A. Hinvi and J. B. Chabi Orou.

16/May/2025: Jaron Kent-Dobias (IFT-UNESP & ICTP-SAIFR).

From Bell inequalities to grasshoppers via ferrofluids: Symmetry breaking and dimensionality in a geometric problem

The study of non-classicality in certain quantum measurement protocols motivates the following geometric problem: what shape of fixed area maximizes the probability that, starting from a point inside the shape, a displacement of fixed distance but random direction will remain inside the shape? Despite being simply stated, numeric solutions to this problem produce a strange menagerie of shapes depending on the fixed distance chosen. I will discuss analytic approaches to the problem borrowed from work on pattern formation in ferrofluids. The results predict the form of symmetry breaking for small displacements, and clearly differentiate behavior in two and higher dimensions.

References: 

Olga Goulko and Adrian Kent "The grasshopper problem" Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (2017) 

David Llamas, Jaron Kent-Dobias, et al. "Origin of symmetry breaking in the grasshopper model" Physical Review Research (2024)

25/Apr/2025: Rafael Menezes (IFT-UNESP & ICTP-SAIFR)

Not so well-mixed: moving from individual behavior to population dynamics in theoretical ecology

Understanding how individual behavior scales up to shape macroscopic population dynamics remains a key challenge in ecological modeling. Traditional models often rely on simplistic law of mass-action assumptions, neglecting realistic movement patterns crucial for ecological processes. With the fast development of movement data acquisition and analysis in past years, the need for a broader framework incorporating realistic features of animal movement in population models has become increasingly evident. In this talk, I will present how agent-based models incorporating stochastic representations of movement allow us to bridge the gap between microscopic organism behavior and its macroscopic consequences at the population level. For instance, using the Ornstein-Uhlenbeck process to represent range-resident behavior, we developed the range-resident logistic model. This model generalizes earlier spatial logistic approaches and correctly recovers the well-known dynamics of traditional (well-mixed) and sessile spatial models as particular cases of the movement parameters. Using this framework, we introduce a 'crowding index', derived from the pair correlation function weighted by the competition kernel, which effectively encapsulates the relevant spatial correlations driving the population dynamics. This index serves as a quantitative bridge connecting micro-scale movement parameters to the macro-scale carrying capacity. Lastly, I will highlight promising interdisciplinary research avenues related to this topic where concepts and methods from the physics of complex systems could provide powerful new insights into spatial ecological dynamics.

04/Apr/2025: Guilherme S. Costa (IFT-UNESP & ICTP-SAIFR)

Contagion percolation between aggregates of active particles

Mobility and aggregation are two important ingredients that influence the outcomes of a contagion dynamics. Whether it is the spreading of a disease in a crowded environment or the chemical signaling of bacteria, the interplay between the movement of the agents and the transmission of internal states is important to fully understand these phenomena. In order to contribute to this discussion, we employed a model of self-propelled particles embedded in a square lattice.  This configuration induces the spontaneous creation of multiple clusters, by which contagion can occur following the rules of usual epidemic models, such as the Susceptible-Infected-Recovered (SIR). The persistent movement of the particles may lead to a contagion percolation for densities way below the site percolation threshold, by effectively bridging clusters together over time. In addition, the size of the contagion cluster depends non-monotonically on the  particle reorientation rate, due to the favoring of spreading within the aggregates or between them.

21/Mar/2025: Jorge Mario Escobar Agudelo (IFT-UNESP)

Generalized Effective Medium Theory for Elastic Systems with Correlated Disorder

How do spatial correlations influence rigidity transitions in disordered materials? Motivated by this question, we develop a generalized Coherent Potential Approximation (CPA) framework, extending traditional effective medium theories to incorporate correlated disorder. Our approach introduces a bond-removal protocol that enables the description of general probability distributions, accounting for spatial correlations and allowing the study of complex systems beyond traditional CPA. 

Applied to a colloidal gel-inspired model, the framework provides a description of how correlations influence rigidity transitions. The key contribution of this master’s thesis is a versatile theoretical tool that bridges classical EMT and real-world disordered materials, offering new insights into the role of correlations in rigidity transitions.

13/Dec/2024: Denise Cammarota (IFT-UNESP)

Inferring the role of susceptibility and climatic drivers of dengue epidemics

Dengue is a viral disease transmitted to humans through the bite of the Aedes Aegypti mosquito, causing significant burden on health worldwide, especially in tropical and subtropical countries, as it is estimated by the Word Health Organization that around half of the population worldwide is at risk for dengue. Nevertheless, understanding the mechanism behind dengue epidemics remains a difficult task, since their occurrence is associated with demographic, social and climatic factors. In this talk, I will show how age patterns of infection might give us hints about the susceptibility of different populations, by comparing real and model-generated age patterns. Furthermore, by introducing a susceptibility index and climatic data, I will show how the relative importance of these predictors can be understood by using a framework consisting of Empirical Dynamical Modeling (EDM) methods and Machine Learning (ML) algorithms for predicting epidemic weeks.

29/Nov/2024: Yhony Arce (IFT-UNESP)

Dynamic behavior of an active particle embedded in a smectic liquid crystal

Self-propelled (active) swimmers exhibit fascinating dynamic behavior with relevance to a wide range of disparate systems found in biology, chemistry, and physics [1]. When embedded in a smectic liquid crystal, swimmer trajectories are affected by layer fluctuations that ultimately lead to anomalous logarithmic tails for the transverse mean-square displacement at long times [2]. This anomalous behavior is different from what is observed for isotropic or nematic fluids, thus motivating us to extend the analysis of Ref. [2] to include the effects of complex smectic microstructures that are produced in diverse protocols. Here we discuss preliminary results, where we use numerical simulation data of Refs. [3,4] to investigate the anomalous dynamic behavior of an active particle embedded in a smectic liquid crystal, with focus on the interplay between activity, flow instabilities and focal conic domains. 

[1] C. Bechinger, R. Di Leonardo, H. Löwen, C. Reichhardt, G. Volpe and G. Volpe, Rev. of Mod. Phys. 88, 045006 (2016). 

[2] C. Ferreiro-Córdova, J. Toner, H. Löwen and H. H. Wensink, Phys. Rev. E 97, 062606 (2018) 

[3] D. B. Liarte, M. Bierbaum, M. Zhang, B. D. Leahy, I. Cohen and J. P. Sethna, Phys. Rev. E 92, 062511 (2015). 

[4] D. B. Liarte, M. Bierbaum, R. A. Mosna, R. D. Kamien and J. P. Sethna, Phys. Rev. Lett. 116, 147802 (2016).

01/Nov/2024: P. de Castro (ICTP-SAIFR), A. Timpanaro (UFABC) & Fernando Silva (USP).

Short Talks on Statistical Physics 

1. Epidemics in active matter. Pablo de Castro (IFT-UNESP & ICTP-SAIFR) 

2. Emergence of echo chambers in a noisy adaptive voter model. André Timpanaro (UFABC): 

3. Powerful ordered collective heat engines. Fernando Silva (IFUSP)

23/Aug/2024: Masayuki Oka Hase (USP).

The "first epidemiologic model" in scale-free networks

Traditional mean-field approaches to epidemiological models rely on the homogeneous mixing hypothesis, which assumes that all individuals have a similar number of connections. Introducing heterogeneities in the interconnections between individuals requires improved tools to better analyze such systems, and the degree-based mean-field (or heterogeneous mean-field) approach is a first step that allows for a more detailed consideration of the network structure of interacting vertices. This work investigates a Susceptible-Infected-Susceptible epidemic model where the infection process follows a threshold-based mechanism, first proposed by En'ko and often recognized as the "first epidemic model", although it remains surprisingly underexplored in the context of epidemiology on complex networks.

16/Aug/2024: Pedro Paraguassú (PUC-Rio).

Qual a chance? Explorando Probabilidades na Termodinâmica Estocástica

Em sistemas estocásticos, a dinâmica aleatória leva a trocas de energia igualmente imprevisíveis. Na termodinâmica estocástica, grandezas como trabalho, calor e entropia são tratadas como variáveis aleatórias, cada uma com sua própria distribuição de probabilidade. As leis termodinâmicas, que tradicionalmente se aplicam às médias dessas quantidades, permitem flutuações ao redor da média, algumas das quais podem desviar significativamente das previsões clássicas. Neste seminário, investigaremos as probabilidades dessas flutuações e a possível violação aparente da segunda lei da termodinâmica em diversos contextos, como a ocorrência de "free lunches", máquinas Brownianas e o uso de pinças ópticas.

09/Aug/2024: Pablo de Castro (IFT-UNESP & ICTP-SAIFR).

Active particles interacting via steric repulsion and quorum-sensing motility regulation

The persistent motion of active particles induces the formation of macroscopic clusters, a phenomenon known as motility-induced phase separation (MIPS). Although MIPS arises even for purely repulsive particle-particle interactions, biological active particles also interact via quorum-sensing motility regulation. In this scenario, biochemical communication allows for activity to depend on particle density. We will present preliminary results on the often-overlooked combination of quorum sensing and steric repulsion. In particular, we identify two reentrant MIPS transitions. Our results may help understand data for agglomerating social organisms in different contexts. 

This work is in collaboration with Lucas de Souza (UFRN & University of Göttingen), Peter Sollich (University of Göttingen & King's College London), Gandhimohan M. Viswanathan (UFRN), and Emanuel F. Teixeira (UFRGS).

28/Jun/2024: Jorge Mario Escobar Agudelo (IFT-UNESP).

Correlated disorder and viscoelasticity of soft colloidal gels

Within solid state physics it is known that periodic networks can be used to describe crystalline solids. However, in nature, there are disordered structures that lack this periodicity, known as amorphous solids [1-3]. Due to their diverse characteristics they have multiple applications [3]. Since these materials and the particularities in their structures are diverse, there is not yet a generalized theory that can describe them all, which represents an exciting challenge. 

In our case we will focus on colloidal gels, where colloidal particles in a solvent form a structure with both solid and liquid properties [3]. The property we are most interested in is their subisosticity, which means they exhibit a rigid structure even when their average coordination number is below its critical value [4]. In other words, they are rigid even when the number of links between colloids is insufficient to counteract the non-trivial degrees of freedom of the system [5]. This has been attributed to internal stresses in the system [3] as well as the existence of spatial correlations in the gels [5], where the presence of a bond between two colloids affects the probability of bonds in the surroundings. 

Our objective is to design a theoretical model to predict this subisostaticity and study other universal properties of our system. We propose to generalize a mean-field theory, such as the coherent potential approximation, by introducing an appropriate description of the correlations. 

References: 

[1] Del Gado, Emanuela. "Constructing a theory for amorphous solids." Physics 11:88 (2018). 

[2] Barrat, Jean-Louis, et al. "Soft matter roadmap." Journal of Physics: Materials 7(1):012501 (2023).

[3] Wyart, Matthieu. "On the rigidity of amorphous solids." Annales de Physique 30:1 (2005). 

[4] Binder, Kurt, and Walter Kob. Glassy materials and disordered solids: An introduction to their statistical mechanics. World scientific, 2011. [5] Zhang, Shang, et al. "Correlated rigidity percolation and colloidal gels." Physical review letters 123(5):058001 (2019).

21/Jun/2024: André de Pinho Vieira (IFUSP).

Physical modelling of pedestrian movement

The collective behavior of pedestrians shows various complex phenomena akin to those exhibited by usual many-body physical systems, especially granular matter, and has connections to active-matter systems, in which mechanical energy is continuously injected. We will offer a bird's eye view of studies on the physical modelling of pedestrians, emphasizing Helbing's "social-force" model and its extensions. In the end, we will discuss applications to the optimal separation of pedestrian counterflow along a corridor.

14/Jun/2024: Alberto Petri (Università La Sapienza).

Statistics and modeling of intermittent flow in sheared granular beds

Although many natural elements and human products look and behave like grains (rocks, debris, soils, food, pharmaceuticals, industrial materials, etc.), the physics of granular systems is still poorly understood.  In fact, these systems are an example of dissipative, nonlinear, out-of-equilibrium systems. One consequence is that they often respond to small perturbations in a highly fluctuating and irregular manner (avalanches), with poor reproducibility (as everyone knows from trying to slowly pour sugar or coffee powder), and their dynamics can only be characterized statistically and described stochastically. This seminar reviews some experimental results on grain beds subjected to low rate shear stress and discusses some models for their description.

07/Jun/2024: André M. Timpanaro (UFABC).

The search for a quantum thermodynamic uncertainty relation

The thermodynamic uncertainty relation (TUR) is a fairly recent development in stochastic thermodynamics that connects the fluctuations of currents with their averages and their associated entropy productions. It has found applications in the description of molecular motors and anomalous diffusion, among others and even though its exact physical origin is still up for debate, it has been rigorously proven for classical Markovian systems.  As such, the community set out to try to find a derivation valid for quantum systems, but quickly quantum systems that violate the traditional TUR were found in the context of coherent transport using thermoelectric devices. At the same time some results for systems with low gradients point that there might exist a modification of the TUR valid for quantum systems. In this talk I will show some of my contributions to this debate and why they point to the question being much more complicated when we allow the possibility of high gradients.

03/May/2024: Rui Aquino (IFT-UNESP & ICTP-SAIFR).

Effects of the kinetic energy in heat for overdamped systems

The field of stochastic thermodynamics aims to describe exchange of energy in the mesoscale. In this regime, heat is a random variable with a probability distribution associated. Although intuition may lead us to consider that the dynamics and the energetics of Brownian systems are not completely attached, in this talk I will argue that to properly define the heat distribution in different dynamical regimes, one always needs to consider the effect of kinetic energy. This allows us to correctly compute a correspondence between the underdamped and overdamped cases, meaning that the velocity can not be fully ignored in the thermodynamics of these systems. This correction allows more fluctuations in generic Brownian systems and could be employed in the development of more efficient thermal machines.

19/Apr/2024: Guilherme S. Costa (IFT-UNESP & ICTP-SAIFR).

Extensions of the Kuramoto model for coupled oscillators

 Synchronization and its general features are of particular interest to scientists working on several areas, such as physics, engineering, social sciences and biology. From neurons to population dynamics and fireflies, nature showcases several examples of synchronized and collective behavior. The paradigmatic model to investigate synchronization  was proposed by Y. Kuramoto in 1975, with several extensions and generalizations being studied in the years that followed. This presentation aims at overviewing some interesting modifications of this model, in addition to discussing some fundamental aspects of synchronization phenomena. Finally, I will comment on some contributions from our research group and some prospects on this subject.

12/Apr/2024: Pablo de Castro (IFT-UNESP & ICTP-SAIFR).

Epidemic-like dynamics between agglomerates of active particles

Motile organisms can form stable agglomerates such as cities or colonies. In the outbreak of a highly contagious disease, the control of large-scale epidemic spread depends on factors like the number and size of agglomerates, travel rate between them, as well as disease infection and recovery rates. While the emergence of agglomerates permits early interventions, it also explains longer real epidemics. We will discuss the spread of epidemics (or any sort of information exchange by contact) in spatially-structured systems. For that, we will employ a model of self-propelled particles which spontaneously form multiple clusters. In particular, we will examine the time evolution averaged over many epidemics and how it is affected by the existence of clusters [1]. Furthermore, we will discuss the scenario of phage therapy, i.e., when viruses are deliberately used to infect and kill colonies of bacteria.

 [1] P. de Castro, F. Urbina, A. Norambuena, and F. Guzmán-Lastra, Physical Review E 108, 044104 (2023).

05/Apr/2024: Danilo B. Liarte (IFT-UNESP & ICTP-SAIFR).

Effective-medium theories for disordered elastic systems

Effective-medium theory has become one of the most powerful theoretical tools to describe the universal critical behavior of disordered elastic systems near the onset of a rigidity transition. I will discuss the approximations involved in this formalism and apply it to suitably crafted network models that exhibit transitions to a disordered rigid phase. I will then extract well-tested critical exponents as well as explicit formulas for the universal scaling functions governing the behavior of a large class of disordered viscoelastic materials near the onset of rigidity.

22/Mar/2024: Ahmed El Hady (Max Planck Institute of Animal Behavior).  

Mechanistic theory of (social) foraging

Foraging is a ubiquitous behavior performed by all animals and human beings as they search for food needed to survive. Foraging theory has been key to understand a variety of model systems but it still lacks mechanistic insights that relate it to neurobiological and other physiological mechanisms. In this talk, I will present work that aims to develop a quantitative mechanistic framework of foraging with a specific focus on patch foraging either of an individual agent or in a social context. I will also present a learning model that accounts for how agents learn the structure of the environment.

13/Dez/2023: Fernando A. Oliveira (UnB).

Dynamics, fractal geometry and the exponents of the Kardar- Parisi-Zhang equation

The KPZ equation [1] is connected to a large number of processes, such as atomic deposition, evolution of bacterial colonies, the direct polymer model, the weakly asymmetric simple exclusion process, the totally asymmetric ex- clusion process, direct d-mer diffusion, fire propagation, turbulent liquid- crystal, spin dynamics, polymer deposition in semiconductors, and etching  [2]. We present a short review of the field, some modern problems and perspectives. We discuss as well how a new interpretation of the fluctuation-dissipation theorem [3] allows us to give a solution for the KPZ exponents [4], and fractal dimension [5].

 [1] M. Kardar, G. Parisi, and Y. C. Zhang, Phys. Rev. Lett. 56, 9, 889 (1986).

[2] B. A. Mello, A. S. Chaves, and F. A. Oliveira, Phys. Rev. E 63, 041113 (2001). — E. A. Rodrigues, B. A. Mello, and F. A. Oliveira, J. Phys. A 48, 035001 (2015). — W. S. Alves, E. A. Rodrigues, H. A. Fernandes, B. A. Mello, F. A. Oliveira and I. V. L. Costa 1, Phys. Rev. E 94, 042119 (2016). — W. R. Gomes, A. L. A. Penna and F. A. Oliveira, Phys. Rev. E 100 02101 (2019).

[3] M. S. Gomes-Filho, and F. A. Oliveira, EPL 133 10001 (2021) — P. R. H. dos Anjos, W. S. Alves, M. S. Gomes-Filho, D. L. Azevedo and F. A. Oliveira, Frontiers in Physics 9 , 741590 (2021) https://doi.org/10.3389/fphy.2021.741590.

[4] M. S. Gomes-Filho, A. L. A. Penna and F. A. Oliveira, Results in Physics 26, 104435 (2021).

[5] E. E. M. Luis, T. A. de Assis, F. A. Oliveira, Journal of Statistical Mechanics: Theory and Experiment 8, 083202 (2022).

29/Nov/2023: Carolina P. Vignoto (IFGW-UNICAMP).  

Transições de fase em monocamadas de Langmuir lipídicas: modelo teórico.

Moléculas anfifílicas, em particular, fosfolipídios, são constituintes essenciais das membranas celulares de todos seres vivos. Estas são formadas pela autoagregação de lipídios sob a forma de uma bicamada lipídica, na qual outras macromoléculas biológicas são agregadas a fim de manter sua função biológica. Embora soluções aquosas contendo bicamadas possam ser investigadas diretamente, as chamadas monocamadas de Langmuir representam um sistema modelo experimental de certa forma mais acessível e controlável, que se formam quando uma camada única de moléculas anfifílicas reside na interface ar-água. Do ponto de vista teórico, há várias propostas para a modelagem de transições de fase em fosfolipídios zwitteriônicos, quando a cabeça polar das moléculas não apresenta carga elétrica líquida. Dentre estas propostas, há o gás de rede de Doniach, que consiste num modelo de três estados [lipídio de caudas desordenadas, lipídio de caudas ordenadas e estado vacante (molécula de água)], que pode ser mapeado num modelo de spin-1. Tal modelo representa uma extensão do modelo Blume-Emery-Griffiths (BEG) proposto no contexto de misturas ternárias. Neste seminário apresentaremos uma sinopse dos resultados para o modelo de gás de rede de Doniach obtidos em duas aproximações: campo médio em redes bipartidas e de pares em redes tripartidas (cacto de Husimi). Em particular, através da comparação das duas abordagens, serão discutidas a profusão e diversidade dos diagramas de fases típicos encontrados em cada método. Além disso, será apresentada uma comparação entre os resultados do modelo teórico obtidos nos dois tratamentos com dados experimentais de isotermas de pressão lateral x área por molécula para o fosfolipídio DMPC (dimiristoilfosfatidilcolina).

08/Nov/2023: Carlos E. Fiore (USP).

Eficientes máquinas térmicas coletivas fora do equilíbrio.

Introduzimos uma classe de máquinas térmicas operando fora do equilíbrio, cuja operação coletiva melhora seu desempenho.  Para tal, propusemos um modelo  mínimo composto por unidades interagentes N colocadas em contato com dois reservatórios térmicos e sujeitas a uma fonte de trabalho constante. A interação entre unidades operando cooperativamente leva a um aumento da eficiência e potência bem como diferentes regimes de operação (máquina, refrigerador e outros). Resultados mostram que  interações do tipo Ising em um regime ordenado coletivo é crucial para operar como uma máquina térmica.  As principais características do sistema são investigadas por meio de uma análise linear próxima do equilíbrio e  desenvolvendo um modelo de estado discreto eficaz que captura os efeitos da fase síncrona.  A robustez de nossas descobertas vai além das interações de todos para todos e abre caminho para a construção de máquinas térmicas de não-equilíbrio promissoras baseadas em estruturas ordenadas.

01/Nov/2023: Guilherme S. Costa (IFT-UNESP & ICTP-SAIFR) 

Spreading dynamics in active matter models.

Spreading processes are a class of dynamical processes that mainly include the propagation of diseases, rumors and information on top of a given population of agents. For a long time, the study of these processes was mostly limited to static substrates or those lacking spatial structure. The popularization of research into active matter, that studies the dynamics of self-propelled agents, has opened up countless possibilities to investigate the behavior of some processes on top of them, as they simultaneously present the dynamics and spatial structure missing in usual substrates. In this presentation, I will review some important concepts and models on spreading dynamics followed by some findings and papers on epidemic spreading in self-propelled entities, ending with some research ideas in collaboration with Dr. Pablo de Castro.

27/Sep/2023: Pablo de Castro (IFT-UNESP & ICTP-SAIFR). 

Simple Models in Active Matter.

Active Matter is a fascinating field in Nonequilibrium Statistical Physics that investigates the dynamics of self-propelled entities such as fish, cells, and artificial particles. After a brief overview of the basic phenomenological features of active matter systems, I will review some simple theoretical approaches that are relevant to the field and which can be used as a starting point towards more complicated systems. In particular, I aim to discuss models for motility-induced phase separation, aligning self-propelled rods and cell tissues.

14/Aug/2023: Felipe Hawthorne (IFUSP). 

The role of translational noise in Motility Induced Phase Separation.

Active matter systems are composed of many self-propelled units, with examples ranging from birds and fish to bacteria, tissue cells and artificial colloids. Typically, the self-propulsion direction of each of these particles fluctuates stochastically and slowly in time. Thus, active particles are said to undergo persistent Brownian motion. For dense systems with low rotational noise (i.e., persistence), volume exclusion coupled with persistent motion generates the formation of clusters, a process called motility-induced phase separation (MIPS). Besides rotational noise dictating the evolution of the self-propulsion angular degree of freedom, translational noise can also exist, e.g., due to thermal noise from the surrounding fluid, acting on the self-propulsion velocity. We investigate the role of translational noise in MIPS and show how, by increasing the translational diffusivity, the system can first enter and then leave the coexistence region of parameters where MIPS occurs. Apart from our results in Active Matter, my research spans other areas within the field of non-equilibrium dynamics and stochastic thermodynamics. I hope to briefly discuss our investigations into the Majority Voter Model and a three-state quantum dot collisional model as a representation of heat engines.

24/Jul/2023: Hilda Cerdeira (IFT-UNESP & ICTP-SAIFR). 

Phase transitions in a system of swarmalators: the XY Model and other things.

Systems of oscillators called Swarmalators, whose phase and spatial dynamics are coupled, have been used to describe the dynamics of some living systems. Their collective behavior presents simultaneous aggregation in space and synchronization in phase which in turn leads in some cases to explosive synchronization in a finite population as a function of the coupling parameter between the phases of the internal dynamics. This phenomenon is described using the order parameter and the Hamiltonian formalism. Near the synchronization transition the internal phases of the particles are represented by the XY model, and their transition to synchronization, which will be discussed, can be of the first or second order. We shall also discuss a multilayer system of swarmalators, which presents some interesting phases on their way to synchronization.