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Simone Pigolotti

Publications and source records attributed to Simone Pigolotti.

At least 19 recordsLinked to original sources
arXiv2026

Non-equilibrium symmetry of cyclic first-passage times

We study the sum of first passage times along an arbitrary cycle made up of N>2 states of a small physical system. We show that, if the system is at thermodynamic equilibrium, this sum follows the same probability distribution regardless of whether the cycle is explored clockwise or counterclockwise. Out of equilibrium, the distributions of clockwise and counterclockwise cyclic first passage times are related by a detailed fluctuation theorem. This result descends from a symmetry of clockwise and counterclockwise trajectories, which combines time reversal with swapping portions of the trajectories. We then relate the entropy produced along the cycle with the entropy production of the whole system using large deviation theory. Our results reveal a novel symmetry in stochastic systems, of potential broad applicability in non-equilibrium physics.

cond-mat.stat-mech↗
arXiv2025

Unifying Theories in High-Dimensional Biology: Approaches, Challenges and Opportunities

Across biological subdisciplines, the last decade has seen an explosion of high-dimensional datasets, including datasets for cells, species, immune systems, neurons and behaviour. At the ICTS workshop 'Unifying Theories in High-Dimensional Biophysics' we discussed whether this high dimensionality poses a challenge or opportunity for describing, understanding and predicting biological systems theoretically. We discussed methods, models and frameworks that can help with addressing empirical observations based on these high-dimensional datasets. We summarize the challenges and opportunities that emerged in discussions according to individual participants below.

physics.bio-ph↗
arXiv2024

Fast and exact simulations of stochastic epidemics on static and temporal networks

Epidemic models on complex networks have been widely used to study how the social structure of a population affect the spreading of epidemics. However, their numerical simulation can be computationally heavy, especially for large networks. In this paper, we introduce NEXT-Net: a flexible implementation of the next reaction method for epidemic spreading on both static and temporal networks. By systematic tests on artificial and real-world networks, we find that NEXT-Net is substantially faster than alternative algorithms, while being exact. It permits, in particular, to efficiently simulate epidemics on networks with million of nodes on a standard computer. It is also versatile enough to simulate a broad range of epidemic models of temporal networks, including cases in which the network structure changes in response to the epidemic. Our code is implemented in C++ and accessible from Python and R, thus combining speed with user friendliness. Because of these features, our algorithm constitutes an ideal tool for a broad range of applications.

physics.soc-ph↗
arXiv2024

Coarsening and universality on a growing surface

We introduce a model in which cells belonging to two species proliferate with volume exclusion on an expanding surface. If the surface expands uniformly, we show that the domains formed by the two species present a critical behavior. We compute the critical exponents characterizing the decay of interfaces and the size distribution of domains using a mean-field theory. These mean-field exponents agree very accurately with those fitted in numerical simulations, suggesting that the theory is exact.

cond-mat.stat-mech↗
arXiv2024

Hyperdisordered cell packing on a growing surface

While the physics of disordered packing in non-growing systems is well understood, unexplored phenomena can emerge when packing takes place in growing domains. We study the arrangements of pigment cells (chromatophores) on squid skin as a biological example of a packed system on an expanding surface. We find that relative density fluctuations in cell numbers grow with spatial scale. We term this behavior ``hyperdisordered'', in contrast with hyperuniform behavior in which relative fluctuations tend to zero at large scale. We find that hyperdisordered scaling, akin to that of a critical system, is quantitatively reproduced by a model in which hard disks are randomly inserted in a homogeneously growing surface. In addition, we find that chromatophores increase in size during animal development, but maintain a stationary size distribution. The physical mechanisms described in our work may apply to a broad class of growing dense systems.

cond-mat.soft↗
arXiv2024

Inspection paradox and jump detection in glassy systems

Dynamics in glassy systems near the phase transition is characterized by particle jumps. Approaches to describe these dynamics are based on models in which the time and length scales defining the jumps are parameters to be determined. We instead propose a model-independent method to detect these jumps. Our method uses the theory of the inspection paradox to analyze particle trajectories and reveals the time and length scales defining a jump without free parameters. Given its simplicity and generality, our method can be applied to resolve hopping motion in a broad class of systems, including experimental ones.

cond-mat.soft↗
arXiv2024

Exponential rate of epidemic spreading on complex networks

The initial phase of an epidemic is often characterized by an exponential increase in the number of infected individuals. In this paper, we predict the exponential spreading rate of an epidemic on a complex network. We first find an expression of the reproduction number for a network, based on the degree distribution, the network assortativity, and the level of clustering. We then connect this reproduction number and the disease infectiousness to the spreading rate. Our result holds for a broad range of networks, apart from networks with very broad degree distribution, where no clear exponential regime is present. Our theory bridges the gap between classic epidemiology and the theory of complex networks, with broad implications for model inference and policy making.

physics.soc-ph↗
arXiv2024

Target search in the CRISPR/Cas9 system: Facilitated diffusion with target cues

We study how Cas9, a central component of the CRISPR/Cas9 system, searches for a target sequence on the DNA. We propose a model that includes as key ingredients 3D diffusion, 1D sliding along the DNA, and the effect of short binding sequences preceding the target (protospacer adjacent sequences -- PAMs). This latter aspect constitutes the main difference with traditional facilitated diffusion of transcription factors. We solve our model, obtaining an expression for the average search time of Cas9 for its target. We find that experimentally measured kinetic parameters are close to the values yielding an optimal search time. Our results rationalize the role of PAMs in guiding the search process, and show that Cas9 searches for its targets in a nearly optimal way.

q-bio.SC↗
arXiv2023

Thermodynamic bounds on time-reversal asymmetry

Quantifying irreversibility of a system using finite information constitutes a major challenge in stochastic thermodynamics. We introduce an observable that measures the time-reversal asymmetry between two states after a given time lag. Our central result is a bound on the time-reversal asymmetry in terms of the total cycle affinity driving the system out of equilibrium. This result leads to further thermodynamic bounds on the asymmetry of directed fluxes; on the asymmetry of finite-time cross-correlations; and on the cycle affinity of coarse-grained dynamics.

cond-mat.stat-mech↗
arXiv2023

Genome replication in asynchronously growing microbial populations

Biological cells replicate their genomes in a well-planned manner. The DNA replication program of an organism determines the timing at which different genomic regions are replicated, with fundamental consequences for cell homeostasis and genome stability. Qualitatively, in a growing cell culture, one expects that genomic regions that are replicated early should be more abundant than regions that are replicated late. This abundance pattern can be experimentally measured using deep sequencing. However, a general quantitative theory to explain these data is still lacking. In this paper, we predict the abundance of DNA fragments in asynchronously growing cultures from any given stochastic model of the DNA replication program. As key examples, we present stochastic models of the DNA replication programs in Escherichia coli and in budding yeast. In both cases, our approach leads to analytical predictions that are in excellent agreement with experimental data and permit to infer key information about the replication program. In particular, our method is able to infer the locations of known replication origins in budding yeast with high accuracy. These examples demonstrate that our method can provide insight into a broad range of organisms, from bacteria to eukaryotes.

q-bio.SC↗
arXiv2022

Pareto optimal fronts of kinetic proofreading

Biological processes such as DNA replication, RNA transcription, and protein translation show remarkable speed and accuracy in selecting the right substrate from pools of chemically identical molecules. This result is obtained by nonequilibrium reactions that dissipate chemical energy. It is widely recognized that there must be a trade-off between speed, error, and dissipation characterizing these systems. In this paper, we quantify the trade-off between speed, error, and dissipation using tools from mathematical optimization theory. We characterize the Pareto optimal front for two paradigmatic models of biological error correction: Hopfield's kinetic proofreading model and a ribosome model. We find that error correction processes with more proofreading steps are characterized by better trade-offs. Furthermore, we identify scaling relations between speed, accuracy, and dissipation on the Pareto front.

cond-mat.stat-mech↗
arXiv2022

Coalescent dynamics of planktonic communities

Planktonic communities are extremely diverse and include a vast number of rare species. The dynamics of these rare species is best described by individual-based models. However, individual-based approaches to planktonic diversity face substantial difficulties, due to the large number of individuals required to make realistic predictions. In this paper, we study diversity of planktonic communities by means of a spatial coalescence model, that incorporates transport by oceanic currents. As a main advantage, our approach requires simulating a number of individuals equal to the size of the sample one is interested in, rather than the size of the entire community. By theoretical analysis and simulations, we explore the conditions upon which our coalescence model is equivalent to individual-based dynamics. As an application, we use our model to predict the impact of chaotic advection by oceanic currents on biodiversity. We conclude that the coalescent approach permits to simulate marine microbial communities much more efficiently than with individual-based models.

q-bio.PE↗
arXiv2021

Population genetics in microchannels

Spatial constraints such as rigid barriers affect the dynamics of cell populations, potentially altering the course of natural evolution. In this paper, we investigate the population genetics of Escherichia coli proliferating in microchannels with open ends. Our analysis is based on a population model in which reproducing cells shift entire lanes of cells towards the open ends of the channel. The model predicts that diversity is lost very rapidly within lanes, but at a much slower pace among lanes. As a consequence, two mixed, neutral E. coli strains competing in a microchannel must organize into an ordered regular stripe pattern in the course of a few generations. These predictions are in quantitative agreement with our experiments. We also demonstrate that random mutations appearing in the middle of the channel are much more likely to reach fixation than those occurring elsewhere. Our results illustrate fundamental mechanisms of microbial evolution in spatially confined space.

q-bio.PE↗
arXiv2021

Search and localization dynamics of the CRISPR/Cas9 system

The CRISPR/Cas9 system acts as the prokaryotic immune system and has important applications in gene editing. The protein Cas9 is one of its crucial components. The role of Cas9 is to search for specific target sequences on the DNA and cleave them. In this Letter, we introduce a model of facilitated diffusion for Cas9 and fit its parameters to single-molecule experiments. Our model confirms that Cas9 search for targets by sliding, but shows that its sliding length is rather short. We then investigate how Cas9 explores a long stretch of DNA containing randomly placed targets. We solve this problem by mapping it into the theory of Anderson localization in condensed matter physics. Our theoretical approach rationalizes experimental evidences on the distribution of Cas9 molecules along the DNA.

q-bio.SC↗
arXiv2021

Generalized Euler-Lotka equation for correlated cell divisions

Cell division times in microbial populations display significant fluctuations, that impact the population growth rate in a non-trivial way. If fluctuations are uncorrelated among different cells, the population growth rate is predicted by the Euler-Lotka equation, which is a classic result in mathematical biology. However, cell division times can be significantly correlated, due to physical properties of cells that are passed through generations. In this paper, we derive an equation remarkably similar to the Euler-Lotka equation which is valid in the presence of correlations. Our exact result is based on large deviation theory and does not require particularly strong assumptions on the underlying dynamics. We apply our theory to a phenomenological model of bacterial cell division in E.coli and to experimental data. We find that the discrepancy between the growth rate predicted by the Euler-Lotka equation and our generalized version is relatively small, but large enough to be measurable by our approach.

q-bio.PE↗
arXiv2019

Hyperaccurate currents in stochastic thermodynamics

Thermodynamic observables of mesoscopic systems can be expressed as integrated empirical currents. Their fluctuations are bound by thermodynamic uncertainty relations. We introduce the hyperaccurate current as the integrated empirical current with the least fluctuations in a given non-equilibrium system. For steady-state systems described by overdamped Langevin equations, we derive an equation for the hyperaccurate current by means of a variational principle. We show that the hyperaccurate current coincides with the entropy production if and only if the latter saturates the thermodynamic uncertainty relation, and it can be substantially more precise otherwise. The hyperaccurate current can be used to improve estimates of entropy production from experimental data.

cond-mat.stat-mech↗
arXiv2019

Bifractal nature of chromosome contact maps

Modern biological techniques such as Hi-C permit to measure probabilities that different chromosomal regions are close in space. These probabilities can be visualised as matrices called contact maps. In this paper, we introduce a multifractal analysis of chromosomal contact maps. Our analysis reveals that Hi-C maps are bifractal, i.e. complex geometrical objects characterized by two distinct fractal dimensions. To rationalize this observation, we introduce a model that describes chromosomes as a hierarchical set of nested domains and we solve it exactly. The predicted multifractal spectrum is in excellent quantitative agreement with experimental data. Moreover, we show that our theory yields to a more robust estimation of the scaling exponent of the contact probability than existing methods. By applying this method to experimental data, we detect subtle conformational changes among chromosomes during differentiation of human stem cells.

q-bio.BM↗