Conventions spreading in open-ended systems

We introduce a simple open-ended model that describes the emergence of a shared vocabulary. The ordering transition toward consensus is generated only by an agreement mechanism. This interaction defines a finite and small number of states, despite each individual having the ability to invent an unlimited number of new words. The existence of a phase transition is studied by analyzing the convergence times, the cognitive efforts of the agents and the scaling behavior in memory and timeComment: 11 pages, 5 figure

Group interactions modulate critical mass dynamics in social convention

How can minorities of individuals overturn social conventions? The theory of critical mass states that when a committed minority reaches a critical size, a cascade of behavioural changes can occur, overturning apparently stable social norms. Evidence comes from theoretical and empirical studies in which minorities of very different sizes, including extremely small ones, manage to bring a system to its tipping point. Here, we explore this diversity of scenarios by introducing group interactions as a crucial element of realism into a model for social convention. We find that the critical mass necessary to trigger behaviour change can be very small if individuals have a limited propensity to change their views. Moreover, the ability of the committed minority to overturn existing norms depends in a complex way on the group size. Our findings reconcile the different sizes of critical mass found in previous investigations and unveil the critical role of groups in such processes. This further highlights the importance of the emerging field of higher-order networks, beyond pairwise interactions

The Spitzer-IRAC/MIPS Extragalactic survey (SIMES) in the South Ecliptic Pole field

We present the Spitzer-IRAC/MIPS Extragalactic survey (SIMES) in the South Ecliptic Pole field. The large area covered (7.7 deg^2), together with one of the lowest Galactic cirrus emissions in the entire sky and a very extensive coverage by Spitzer, Herschel, Akari, and GALEX, make the SIMES field ideal for extragalactic studies. The elongated geometry of the SIMES area (≈4:1), allowing for significant cosmic variance reduction, further improves the quality of statistical studies in this field. Here we present the reduction and photometric measurements of the Spitzer/IRAC data. The survey reaches depths of 1.93 and 1.75 μJy (1σ) at 3.6 and 4.5 μm, respectively. We discuss the multiwavelength IRAC-based catalog, completed with optical, mid-, and far-IR observations. We detect 341,000 sources with F_(3.6µm) ⩾3σ. Of these, 10% have an associated 24 μm counterpart, while 2.7% have an associated SPIRE source. We release the catalog through the NASA/IPAC Infrared Science Archive. Two scientific applications of these IRAC data are presented in this paper. First, we compute integral number counts at 3.6 μm. Second, we use the [3.6]–[4.5] color index to identify galaxy clusters at z > 1.3. We select 27 clusters in the full area, a result consistent with previous studies at similar depth

Non Sequential Recursive Pair Substitution: Some Rigorous Results

We present rigorous results on some open questions on NSRPS, non sequential recursive pairs substitution method (see Grassberger in \cite{G}). In particular, starting from the action of NSRPS on finite strings we define a corresponding natural action on measures and we prove that the iterated measure becomes asymptotically Markov. This certify the effectiveness of NSRPS as a tool for data compression and entropy estimation.Comment: 20 page

A Multiwavelength Consensus on the Main Sequence of Star-Forming Galaxies at z~2

We compare various star formation rate (SFR) indicators for star-forming galaxies at $1.4<z<2.5$ in the COSMOS field. The main focus is on the SFRs from the far-IR (PACS-Herschel data) with those from the ultraviolet, for galaxies selected according to the BzK criterion. FIR-selected samples lead to a vastly different slope of the SFR-stellar mass ($M_*$) relation, compared to that of the dominant main sequence population as measured from the UV, since the FIR selection picks predominantly only a minority of outliers. However, there is overall agreement between the main sequences derived with the two SFR indicators, when stacking on the PACS maps the BzK-selected galaxies. The resulting logarithmic slope of the SFR-{$M_*$} relation is $\sim0.8-0.9$, in agreement with that derived from the dust-corrected UV-luminosity. Exploiting deeper 24$\mu$m-Spitzer data we have characterized a sub-sample of galaxies with reddening and SFRs poorly constrained, as they are very faint in the $B$ band. The combination of Herschel with Spitzer data have allowed us to largely break the age/reddening degeneracy for these intriguing sources, by distinguishing whether a galaxy is very red in B-z because of being heavily dust reddened, or whether because star formation has been (or is being) quenched. Finally, we have compared our SFR(UV) to the SFRs derived by stacking the radio data and to those derived from the H$\alpha$ luminosity of a sample of star-forming galaxies at $1.4<z<1.7$. The two sets of SFRs are broadly consistent as they are with the SFRs derived from the UV and by stacking the corresponding PACS data in various mass bins.Comment: Accepted for publication in MNRA

Sharp transition towards shared vocabularies in multi-agent systems

What processes can explain how very large populations are able to converge on the use of a particular word or grammatical construction without global coordination? Answering this question helps to understand why new language constructs usually propagate along an S-shaped curve with a rather sudden transition towards global agreement. It also helps to analyze and design new technologies that support or orchestrate self-organizing communication systems, such as recent social tagging systems for the web. The article introduces and studies a microscopic model of communicating autonomous agents performing language games without any central control. We show that the system undergoes a disorder/order transition, going trough a sharp symmetry breaking process to reach a shared set of conventions. Before the transition, the system builds up non-trivial scale-invariant correlations, for instance in the distribution of competing synonyms, which display a Zipf-like law. These correlations make the system ready for the transition towards shared conventions, which, observed on the time-scale of collective behaviors, becomes sharper and sharper with system size. This surprising result not only explains why human language can scale up to very large populations but also suggests ways to optimize artificial semiotic dynamics.Comment: 12 pages, 4 figure

Identifying key players in dark web marketplaces through Bitcoin transaction networks

Dark web marketplaces have been a significant outlet for illicit trade, serving millions of users worldwide for over a decade. However, not all users are the same. This paper aims to identify the key players in Bitcoin transaction networks linked to dark markets and assess their role by analysing a dataset of 40 million Bitcoin transactions involving the 31 major markets in the period 2011–2021. First, we propose an algorithm that categorizes users either as buyers or sellers, and show that a large fraction of the trading volume is concentrated in a small group of elite market participants. We find that the dominance of markets is reflected in trading properties of buyers and sellers. Then, we investigate both market star-graphs and user-to-user networks, and highlight the importance of a new class of users, namely ‘multihomers’, who operate on multiple marketplaces concurrently. Specifically, we show how the networks of multihomers and seller-to-seller interactions can shed light on the resilience of the dark market ecosystem against external shocks. Our findings suggest that understanding the behavior of key players in dark web marketplaces is critical to effectively disrupting illegal activities

Contagion dynamics in time-varying metapopulation networks

The metapopulation framework is adopted in a wide array of disciplines to describe systems of well separated yet connected subpopulations. The subgroups or patches are often represented as nodes in a network whose links represent the migration routes among them. The connections have been so far mostly considered as static, but in general evolve in time. Here we address this case by investigating simple contagion processes on time-varying metapopulation networks. We focus on the SIR process and determine analytically the mobility threshold for the onset of an epidemic spreading in the framework of activity-driven network models. We find profound differences from the case of static networks. The threshold is entirely described by the dynamical parameters defining the average number of instantaneously migrating individuals and does not depend on the properties of the static network representation. Remarkably, the diffusion and contagion processes are slower in time-varying graphs than in their aggregated static counterparts, the mobility threshold being even two orders of magnitude larger in the first case. The presented results confirm the importance of considering the time-varying nature of complex networks

Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death

We analyze the dynamic properties of 10^7 words recorded in English, Spanish and Hebrew over the period 1800--2008 in order to gain insight into the coevolution of language and culture. We report language independent patterns useful as benchmarks for theoretical models of language evolution. A significantly decreasing (increasing) trend in the birth (death) rate of words indicates a recent shift in the selection laws governing word use. For new words, we observe a peak in the growth-rate fluctuations around 40 years after introduction, consistent with the typical entry time into standard dictionaries and the human generational timescale. Pronounced changes in the dynamics of language during periods of war shows that word correlations, occurring across time and between words, are largely influenced by coevolutionary social, technological, and political factors. We quantify cultural memory by analyzing the long-term correlations in the use of individual words using detrended fluctuation analysis.Comment: Version 1: 31 pages, 17 figures, 3 tables. Version 2 is streamlined, eliminates substantial material and incorporates referee comments: 19 pages, 14 figures, 3 table