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Francisco J. Pérez-Reche

Publications and source records attributed to Francisco J. Pérez-Reche.

6 recordsLinked to original sources

Higher-Order Interactions in Complex Systems: Mechanisms, Behaviour, Representation and Reducibility

Higher-order interactions couple three or more elements in ways that cannot be decomposed into pairwise contributions. In diverse complex systems they produce striking collective behaviours such as explosive synchronization, discontinuous transitions and altered stability. Neither such behaviour nor a description written in many-body terms establishes a many-body mechanism, since both depend on how the system is represented. This review distinguishes three questions: what mechanism governs the system, what behaviour does it produce, and how is either represented? Representation covers both which variables are included and how relations among them are encoded. We examine direct many-body mechanisms, nonlinear but pairwise mechanisms that mimic them, and indirect routes through shared environments or eliminated variables, together with temporal aggregation, an artefact of observation rather than a mechanism. The same behaviour can arise from different mechanisms, and a given higher-order mechanism has no universal behavioural consequence. We then formulate reducibility, the question of whether a higher-order model can be replaced by a lower-order one, as a comparison between a source model and an admissible class of lower-order models, relative to a target and a tolerance. The target may be a microscopic rule, an observable or a qualitative feature. Information-theoretic and inferential methods are reviewed as complementary tools for detecting higher-order dependence, testing lower-order alternatives and reconstructing interaction structure. However, observational data alone generally cannot establish the mechanism. We close by identifying open problems in linking mechanisms to measurable signatures, coarse-graining, identifiability and causality, and in extending reductions beyond mean field. (Abridged)

cond-mat.stat-mech↗

Environment-Driven Emergence of Higher-Order Collective Behavior

Collective behavior is commonly attributed to direct interactions among system components. Using a minimal stochastic model, we show that higher-order collective structure can instead emerge from shared stochastic environments, even in the absence of interactions. Quantified via the O-information, environmental fluctuations induce both redundant and synergistic dependencies, with the latter occupying larger regions of the correlation space. We establish a no-go theorem showing that time-independent coupling between the system variables and a shared stochastic environment rules out synergistic higher-order behavior. Crucially, this constraint can be overcome dynamically: transitions between redundancy and synergy arise from time-dependent environmental coupling or from the nontrivial interplay between shared environments and direct interactions. Together, these results identify environmental mediation as a distinct mechanism of higher-order collective organization beyond the conventional interaction-centric paradigm.

physics.soc-ph↗

Bifurcations in synergistic epidemics on random regular graphs

The role of cooperative effects (i.e. synergy) in transmission of infection is investigated analytically and numerically for epidemics following the rules of Susceptible-Infected-Susceptible (SIS) model defined on random regular graphs. Non-linear dynamics are shown to lead to bifurcation diagrams for such spreading phenomena exhibiting three distinct regimes: non-active, active and bi-stable. The dependence of bifurcation loci on node degree is studied and interesting effects are found that contrast with the behaviour expected for non-synergistic epidemics.

physics.soc-ph↗

Effects of local and global network connectivity on synergistic epidemics

The effects of local and global connectivity on the spread of synergistic susceptible-infected-removed epidemics were studied in lattice models with infinite- and finite-range rewiring (small-world and small-world-like models). Several effects were found numerically and supported analytically within a simple model: (i) rewiring enhanced resilience to epidemics with strong constructive synergy on networks with high local connectivity; (ii) rewiring enhanced spread of epidemics with destructive or weak constructive synergy on networks with arbitrary local connectivity; (iii) rewiring enhanced spread of epidemics, independent of synergy, in networks with low local connectivity.

physics.soc-ph↗

Effect of disorder on condensation in the lattice gas model on a random graph

The lattice gas model of condensation in a heterogeneous pore system, represented by a random graph of cells, is studied using an exact analytical solution. A binary mixture of pore cells with different coordination numbers is shown to exhibit two phase transitions as a function of chemical potential in a certain temperature range. Heterogeneity in interaction strengths is demonstrated to reduce the critical temperature and, for large enough degree of disorder, divides the cells into ones which are either on average occupied or unoccupied. Despite treating the pore space loops in a simplified manner, the random-graph model provides a good description of condensation in porous structures containing loops. This is illustrated by considering capillary condensation in a structural model of mesoporous silica SBA-15.

cond-mat.stat-mech↗

Effects of variable neighbourhood on spreading processes

A theoretical framework for the description of Susceptible-Infected-Removed (SIR) spreading processes with synergistic transmission of infection on a lattice is developed. The model incorporates explicitly the effects of a time-dependent environment on the transmission of infection between hosts. Exact solution of the model shows that time-dependence of the neighbourhood of recipient hosts is a key factor for synergistic spreading processes. It is demonstrated that the higher the connectivity of a lattice, the more prominent is the effect of synergy on spread.

q-bio.PE↗