Interplay between temperature and trap effects in one-dimensional lattice systems of bosonic particles

We investigate the interplay of temperature and trap effects in cold particle systems at their quantum critical regime, such as cold bosonic atoms in optical lattices at the transitions between Mott-insulator and superfluid phases. The theoretical framework is provided by the one-dimensional Bose-Hubbard model in the presence of an external trapping potential, and the trap-size scaling theory describing the large trap-size behavior at a quantum critical point. We present numerical results for the low-temperature behavior of the particle density and the density-density correlation function at the Mott transitions, and within the gapless superfluid phase.Comment: 9 page

Ferromagnetic-glassy transitions in three-dimensional Ising spin glasses

We investigate the ferromagnetic-glassy transitions which separate the low-temperature ferromagnetic and spin-glass phases in the temperature-disorder phase diagram of three-dimensional Ising spin-glass models. For this purpose, we consider the cubic-lattice +-J (Edwards-Anderson) Ising model with bond distribution $P(J) = p \delta(J - 1) + (1-p) \delta(J + 1)$, and present a numerical Monte Carlo study of the critical behavior along the line that marks the onset of ferromagnetism. The finite-size scaling analysis of the Monte Carlo data shows that the ferromagnetic-glassy transition line is slightly reentrant. As a consequence, for an interval of the disorder parameter p, around p=0.77, the system presents a low-temperature glassy phase, an intermediate ferromagnetic phase, and a high-temperature paramagnetic phase. Along the ferromagnetic-glassy transition line magnetic correlations show a universal critical behavior with critical exponents nu=0.96(2) and eta=-0.39(2). The hyperscaling relation beta/nu = (1 + eta)/2 is satisfied at the transitions, so that beta/nu = 0.305(10). This magnetic critical behavior represents a new universality class for ferromagnetic transitions in Ising-like disordered systems. Overlap correlations are apparently not critical and show a smooth behavior across the transition.Comment: 24 page

Systematic meta-analysis of research on AI tools to deal with misinformation on social media during natural and anthropogenic hazards and disasters

The spread of misinformation on social media has led to the development of artificial intelligence (AI) tools to deal with this phenomenon. These tools are particularly needed when misinformation relates to natural or anthropogenic disasters such as the COVID-19 pandemic. The major research question of our work was as follows: what kind of gatekeepers (i.e. news moderators) do we wish social media algorithms and users to be when misinformation on hazards and disasters is being dealt with? To address this question, we carried out a meta-analysis of studies published in Scopus and Web of Science. We extracted 668 papers that contained keyterms related to the topic of “AI tools to deal with misinformation on social media during hazards and disasters.” The methodology included several steps. First, we selected 13 review papers to identify relevant variables and refine the scope of our meta-analysis. Then we screened the rest of the papers and identified 266 publications as being significant for our research goals. For each eligible paper, we analyzed its objective, sponsor’s location, year of publication, research area, type of hazard, and related topics. As methods of analysis, we applied: descriptive statistics, network representation of keyword co-occurrences, and flow representation of research rationale. Our results show that few studies come from the social sciences (5.8%) and humanities (3.5%), and that most of those papers are dedicated to the COVID-19 risk (92%). Most of the studies deal with the question of detecting misinformation (68%). Few countries are major funders of the development of the topic. These results allow some inferences. Social sciences and humanities seem underrepresented for a topic that is strongly connected to human reasoning. A reflection on the optimum balance between algorithm recommendations and user choices seems to be missing. Research results on the pandemic could be exploited to enhance research advances on other risks

Magnetic-glassy multicritical behavior of the three-dimensional +- J Ising model

We consider the three-dimensional $\pm J$ model defined on a simple cubic lattice and study its behavior close to the multicritical Nishimori point where the paramagnetic-ferromagnetic, the paramagnetic-glassy, and the ferromagnetic-glassy transition lines meet in the T-p phase diagram (p characterizes the disorder distribution and gives the fraction of ferromagnetic bonds). For this purpose we perform Monte Carlo simulations on cubic lattices of size $L\le 32$ and a finite-size scaling analysis of the numerical results. The magnetic-glassy multicritical point is found at $p^*=0.76820(4)$, along the Nishimori line given by $2p-1={\rm Tanh}(J/T)$. We determine the renormalization-group dimensions of the operators that control the renormalization-group flow close to the multicritical point, $y_1 = 1.02(5)$, $y_2 = 0.61(2)$, and the susceptibility exponent $\eta = -0.114(3)$. The temperature and crossover exponents are $\nu=1/y_2=1.64(5)$ and $\phi=y_1/y_2 = 1.67(10)$, respectively. We also investigate the model-A dynamics, obtaining the dynamic critical exponent $z = 5.0(5)$.Comment: 17 page

Multicritical Nishimori point in the phase diagram of the +- J Ising model on a square lattice

We investigate the critical behavior of the random-bond +- J Ising model on a square lattice at the multicritical Nishimori point in the T-p phase diagram, where T is the temperature and p is the disorder parameter (p=1 corresponds to the pure Ising model). We perform a finite-size scaling analysis of high-statistics Monte Carlo simulations along the Nishimori line defined by $2p-1={\rm Tanh}(1/T)$, along which the multicritical point lies. The multicritical Nishimori point is located at p^*=0.89081(7), T^*=0.9528(4), and the renormalization-group dimensions of the operators that control the multicritical behavior are y_1=0.655(15) and y_2 = 0.250(2); they correspond to the thermal exponent \nu= 1/y_2=4.00(3) and to the crossover exponent \phi= y_1/y_2=2.62(6).Comment: 23 page

Critical behavior and scaling in trapped systems

We study the scaling properties of critical particle systems confined by a potential. Using renormalization-group arguments, we show that their critical behavior can be cast in the form of a trap-size scaling, resembling finite-size scaling theory, with a nontrivial trap critical exponent theta, which describes how the correlation length scales with the trap size l, i.e., $\xi\sim l^\theta$ at the critical point. theta depends on the universality class of the transition, the power law of the confining potential, and on the way it is coupled to the critical modes. We present numerical results for two-dimensional lattice gas (Ising) models with various types of harmonic traps, which support the trap-size scaling scenario.Comment: 4 pages, 6 figs, minor correction

The three-dimensional gauge-glass model

We investigate the temperature-disorder (T-S) phase diagram of a three-dimensional gauge glass model, which is a cubic-lattice nearest-neighbor XY model with quenched random phase shifts A_xy at the bonds, by numerical Monte Carlo simulations. We consider the uncorrelated phase-shift distribution P(A_xy)\sim \exp[(cos A_xy)/S], which has the pure XY model and the uniform distribution of random shifts as extreme cases at S=0 and S->infty respectively, and which gives rise to equal magnetic and overlap correlation functions when T=S. While the high-temperature phase is always paramagnetic, at low temperatures there is a ferromagnetic phase for weak disorder (small S) and a glassy phase at large disorder (large S). These three phases are separated by transition lines with different magnetic and glassy critical behaviors. The disorder induced by the random shifts turns out to be irrelevant at the paramagnetic-ferromagnetic transition line, where the critical behavior belongs to the 3D XY universality class of pure systems; disorder gives only rise to very slowly decaying scaling corrections. The glassy critical behavior along the finite-temperature paramagnetic-glassy transition line belongs to the gauge-glass universality class, with a quite large critical exponent nu=3.2(4). These transition lines meet at a multicritical point M, located at T=S=0.7840(2). The low-temperature ferromagnetic and glassy phases are separated by a third transition line, from M down to the T=0 axis, which is slightly reentrant.Comment: 12 page

Zero-temperature behavior of the random-anisotropy model in the strong-anisotropy limit

We consider the random-anisotropy model on the square and on the cubic lattice in the strong-anisotropy limit. We compute exact ground-state configurations, and we use them to determine the stiffness exponent at zero temperature; we find $\theta = -0.275(5)$ and $\theta \approx 0.2$ respectively in two and three dimensions. These results show that the low-temperature phase of the model is the same as that of the usual Ising spin-glass model. We also show that no magnetic order occurs in two dimensions, since the expectation value of the magnetization is zero and spatial correlation functions decay exponentially. In three dimensions our data strongly support the absence of spontaneous magnetization in the infinite-volume limit

Persistence of Rumours and Hate Speech Over the Years: the Manchester Arena Bombing

Following the 2017 Manchester Arena bombing, the ensuing discussions in the media and on social platforms highlighted the potential of terrorism to deepen societal divisions. This study investigates the dynamics of rumors on social media and in the press after the attack, as well as the subsequent discourse on migration policies. We compiled a dataset comprising 3,184 press articles and 89,148 tweets pertaining to the Manchester Arena bombing. The research aims to identify prevalent rumors, assess their short- and long-term effects on user engagement, analyze the sentiment in tweets related to each rumor, and scrutinize perceptions of terrorism threats and migration policies among both the press and Twitter users. The findings reveal that Twitter acted as an echo chamber for misinformation, amplifying specific rumors related to the attack, while the press demonstrated fact-checking practices and offered nuanced perspectives. Notably, one rumor suggesting the attacker was a refugee gained traction over time, reflecting a surge in anti-immigrant sentiments. Emotional responses on Twitter varied from a neutral tone to heightened distress and anger, underscoring the significant impact of social media narratives on public sentiment. The research highlights the polarization of views on social media, influenced by the concise format of tweets and the rapid production cycle, with Twitter users predominantly expressing very negative attitudes toward immigration. This study emphasizes the crucial role of the media in dispelling misinformation and cultivating a nuanced public understanding in complex socio-political contexts