Explore the vast range of titles available.

The Mpemba effect occurs when a hot system cools faster than an initially colder one, when both are refrigerated in the same thermal reservoir. Using the custom-built supercomputer Janus II, we study the Mpemba effect in spin glasses and show that it is a nonequilibrium process, governed by the coherence length ξ of the system. The effect occurs when the bath temperature lies in the glassy phase, but it is not necessary for the thermal protocol to cross the critical temperature. In fact, the Mpemba effect follows from a strong relationship between the internal energy and ξ that turns out to be a sure-tell sign of being in the glassy phase. Thus, the Mpemba effect presents itself as an intriguing avenue for the experimental study of the coherence length in supercooled liquids and other glass formers.

It is not fully understood why we cooperate with strangers on a daily basis. In an increasingly global world, where interaction networks and relationships between individuals are becoming more complex, different hypotheses have been put forward to explain the foundations of human cooperation on a large scale and to account for the true motivations that are behind this phenomenon. In this context, population structure has been suggested to foster cooperation in social dilemmas, but theoretical studies of this mechanism have yielded contradictory results so far; additionally, the issue lacks a proper experimental test in large systems. We have performed the largest experiments to date with humans playing a spatial Prisoner’s Dilemma on a lattice and a scale-free network (1,229 subjects). We observed that the level of cooperation reached in both networks is the same, comparable with the level of cooperation of smaller networks or unstructured populations. We have also found that subjects respond to the cooperation that they observe in a reciprocal manner, being more likely to cooperate if, in the previous round, many of their neighbors and themselves did so, which implies that humans do not consider neighbors’ payoffs when making their decisions in this dilemma but only their actions. Our results, which are in agreement with recent theoretical predictions based on this behavioral rule, suggest that population structure has little relevance as a cooperation promoter or inhibitor among humans.

The number of people using online social networks in their everyday life is continuously growing at a pace never saw before. This new kind of communication has an enormous impact on opinions, cultural trends, information spreading and even in the commercial success of new products. More importantly, social online networks have revealed as a fundamental organizing mechanism in recent country-wide social movements. In this paper, we provide a quantitative analysis of the structural and dynamical patterns emerging from the activity of an online social network around the ongoing May 15th (15M) movement in Spain. Our network is made up by users that exchanged tweets in a time period of one month, which includes the birth and stabilization of the 15M movement. We characterize in depth the growth of such dynamical network and find that it is scale-free with communities at the mesoscale. We also find that its dynamics exhibits typical features of critical systems such as robustness and power-law distributions for several quantities. Remarkably, we report that the patterns characterizing the spreading dynamics are asymmetric, giving rise to a clear distinction between information sources and sinks. Our study represents a first step towards the use of data from online social media to comprehend modern societal dynamics.

Network analysis allows us to introduce different metrics that complement the traditional indicators to measure academic performance, generally based on individual production. In this paper, we show how the use of these techniques provides a more global point of view, introducing indicators that, beyond individual merits, measure the capacity of researchers to generate more intangible assets. We focus on collaboration among groups that can enrich the potential of the research ecosystem as a whole. We present not only numerical indicators, but also several visualisation schemes to see how this approach can help in the academic evaluation and decision-making process of research managers. We have used, as a case study, the research ecosystem formed by more than five thousand economists from Spanish institutions.

The implementation of the United Nations (UN) Sustainable Development Goals (SDGs) presents a vast and intricate array of challenges, including the establishment of governance systems that engage all societal actors, particularly nongovernmental entities and youth, in proposing solutions and decision-making. This article investigates the potential of collective intelligence as a tool within citizen science to create solutions for SDG-related challenges and to establish or enhance necessary governance mechanisms. We detail a collective intelligence experiment conducted during the UN Climate Change Conference 2019 (COP25; Madrid, December 2-13), which aimed to generate a prioritised list of actions addressing SDG 6, Water and Sanitation and SDG 13, Climate Action. The experiment involved 1,253 students aged 15 to 17 who proposed, modified, and prioritised 14,517 ideas using an online platform created by Kampal, a spin-off of the University of Zaragoza. We discuss: a) participation protocols following citizen science methodologies; b) the platform description; c) results concerning the participation process, the tool's effectiveness in collectively extracting the best solutions, and the quality of the generated proposals; and d) enhancements and new research directions for using citizen science and collective intelligence to tackle SDG-related challenges in a collaborative and participatory way.

Algo catastrófico está a punto de suceder; la Tierra se está convirtiendo en la nueva religión a la que los políticos deben rendir culto en las cumbres del clima y en sus discursos diarios. Si en la Edad Media se visitaban líderes religiosos, ahora se visitan plantas de reciclaje y de energías renovables. En lugar de advertir que el fin del mundo llegará tras desatar la cólera de Dios, se pregona el fin del planeta por la insensatez del ser humano. De unos años a esta parte, el cambio climático se ha convertido en un argumento polémico de constante aparición en medios, al que se le tiende a achacar el origen de la práctica totalidad de nuestros problemas actuales. Pero ¿está justificada tan abrumadora presencia? Y lo que es más importante, ¿cuánto de premonición y cuánto de rigor científico hay en este fenómeno? En Premoniciones, los científicos Alfonso Tarancón y Javier del Valle arrojan una buena dosis de cordura sobre un tema que, a pesar del empeño por parte de ciertos sectores en afirmar lo contrario, no está ni mucho menos claro. En sus páginas, examinan las variaciones del clima a lo largo de los siglos, y dilucidan la a menudo inexistente relación entre multitud de problemas medioambientales, sociales o económicos. Una fresca y necesaria mirada a un fenómeno que la ciencia no respalda con la rotundidad que muchos dan por sentada.

Experiments featuring non-equilibrium glassy dynamics under temperature changes still await interpretation. There is a widespread feeling that temperature chaos (an extreme sensitivity of the glass to temperature changes) should play a major role but, up to now, this phenomenon has been investigated solely under equilibrium conditions. In fact, the very existence of a chaotic effect in the non-equilibrium dynamics is yet to be established. In this article, we tackle this problem through a large simulation of the 3D Edwards-Anderson model, carried out on the Janus II supercomputer. We find a dynamic effect that closely parallels equilibrium temperature chaos. This dynamic temperature-chaos effect is spatially heterogeneous to a large degree and turns out to be controlled by the spin-glass coherence length ξ . Indeed, an emerging length-scale ξ * rules the crossover from weak (at ξ  ≪  ξ * ) to strong chaos ( ξ  ≫  ξ * ). Extrapolations of ξ * to relevant experimental conditions are provided. While temperature chaos is an equilibrium notion that denotes the extreme fragility of the glassy phase with respect to temperature changes, it remains unclear whether it is present in non-equilibrium dynamics. Here the authors use the Janus II supercomputer to prove the existence of dynamic temperature chaos, a nonequilibrium phenomenon that closely mimics equilibrium temperature chaos.

SignificanceThe unifying feature of glass formers (such as polymers, supercooled liquids, colloids, granulars, spin glasses, superconductors, etc.) is a sluggish dynamics at low temperatures. Indeed, their dynamics are so slow that thermal equilibrium is never reached in macroscopic samples: in analogy with living beings, glasses are said to age. Here, we show how to relate experimentally relevant quantities with the experimentally unreachable low-temperature equilibrium phase. This relation is made quantitative via a statics-dynamics dictionary, established for spin glasses. In our dictionary, the aging response to a magnetic field is related to the spin-glass order parameter as obtained on samples small enough to equilibrate. We remark that all of the observables we consider can be measured with current experimental methods. We have performed a very accurate computation of the nonequilibrium fluctuation–dissipation ratio for the 3D Edwards–Anderson Ising spin glass, by means of large-scale simulations on the special-purpose computers Janus and Janus II. This ratio (computed for finite times on very large, effectively infinite, systems) is compared with the equilibrium probability distribution of the spin overlap for finite sizes. Our main result is a quantitative statics-dynamics dictionary, which could allow the experimental exploration of important features of the spin-glass phase without requiring uncontrollable extrapolations to infinite times or system sizes.

Spin glasses are a longstanding model for the sluggish dynamics that appear at the glass transition. However, spin glasses differ from structural glasses in a crucial feature: they enjoy a time reversal symmetry. This symmetry can be broken by applying an external magnetic field, but embarrassingly little is known about the critical behavior of a spin glass in a field. In this context, the space dimension is crucial. Simulations are easier to interpret in a large number of dimensions, but one must work below the upper critical dimension (i.e., in d < 6) in order for results to have relevance for experiments. Here we show conclusive evidence for the presence of a phase transition in a four-dimensional spin glass in a field. Two ingredients were crucial for this achievement: massive numerical simulations were carried out on the Janus special-purpose computer, and a new and powerful finite-size scaling method.

We have performed a very accurate computation of the nonequilibrium fluctuation–dissipation ratio for the 3D Edwards–Anderson Ising spin glass, by means of large-scale simulations on the specialpurpose computers Janus and Janus II. This ratio (computed for finite times on very large, effectively infinite, systems) is compared with the equilibrium probability distribution of the spin overlap for finite sizes. Our main result is a quantitative statics-dynamics dictionary, which could allow the experimental exploration of important features of the spin-glass phase without requiring uncontrollable extrapolations to infinite times or system sizes.