Critical Droplets and Phase Transitions in Two Dimensions

In two space dimensions, the percolation point of the pure-site clusters of the Ising model coincides with the critical point T_c of the thermal transition and the percolation exponents belong to a special universality class. By introducing a bond probability p_B<1, the corresponding site-bond clusters keep on percolating at T_c and the exponents do not change, until p_B=p_CK=1-exp(-2J/kT): for this special expression of the bond weight the critical percolation exponents switch to the 2D Ising universality class. We show here that the result is valid for a wide class of bidimensional models with a continuous magnetization transition: there is a critical bond probability p_c such that, for any p_B>=p_c, the onset of percolation of the site-bond clusters coincides with the critical point of the thermal transition. The percolation exponents are the same for p_c<p_B<=1 but, for p_B=p_c, they suddenly change to the thermal exponents, so that the corresponding clusters are critical droplets of the phase transition. Our result is based on Monte Carlo simulations of various systems near criticality.Comment: Final version for publication, minor changes, figures adde

Interview with Laura Fortunato, Winner of the 2011 Gabriel W. Lasker Prize

An international jury composed of Michael Crawford (University of Kansas, USA), Dennis O\u27Rourke (University of Utah, USA), and Stephen Shennan (University College London, UK) has awarded the Gabriel Ward Lasker Prize 2011 to Dr. Laura Fortunato for her articles entitled Reconstructing the History of Residence Strategies in Indo-European–Speaking Societies and Reconstructing the History of Marriage Strategies in Indo-European–Speaking Societies considered as the best contribution to the 83rd volume of Human Biology (2011). Laura Fortunato is an Omidyar Fellow at the Santa Fe Institute in Santa Fe, New Mexico. She received her Ph.D. in anthropology from University College London in 2009; her doctoral research focused on the evolution of kinship and marriage systems. In particular, she has investigated the evolution of marriage strategies, wealth transfers at marriage, residence strategies, and inheritance strategies. Laura\u27s current research activities apply conceptual and methodological tools developed in evolutionary biology to a diverse range of topics in anthropology, from matrilineal kinship organization to cultural evolution

Two-neutron transfer in nuclei close to the dripline

We investigate the two-neutron transfer modes induced by (t,p) reactions in neutron-rich oxygen isotopes. The nuclear response to the pair transfer is calculated in the framework of continuum-Quasiparticle Random Phase Approximation (cQRPA). The cQRPA allows a consistent determination of the residual interaction and an exact treatment of the continuum coupling. The (t,p) cross sections are calculated within the DWBA approach and the form factors are evaluated by different methods : macroscopically, following the Bayman and Kallio method, and fully microscopically. The largest cross section corresponds to a high-lying collective mode built entirely upon continuum quasiparticle states.Comment: 12 pages, 7 figure

Considerations about multistep community detection

The problem and implications of community detection in networks have raised a huge attention, for its important applications in both natural and social sciences. A number of algorithms has been developed to solve this problem, addressing either speed optimization or the quality of the partitions calculated. In this paper we propose a multi-step procedure bridging the fastest, but less accurate algorithms (coarse clustering), with the slowest, most effective ones (refinement). By adopting heuristic ranking of the nodes, and classifying a fraction of them as `critical', a refinement step can be restricted to this subset of the network, thus saving computational time. Preliminary numerical results are discussed, showing improvement of the final partition.Comment: 12 page

Experimental application of decoherence-free subspaces in a quantum-computing algorithm

For a practical quantum computer to operate, it will be essential to properly manage decoherence. One important technique for doing this is the use of "decoherence-free subspaces" (DFSs), which have recently been demonstrated. Here we present the first use of DFSs to improve the performance of a quantum algorithm. An optical implementation of the Deutsch-Jozsa algorithm can be made insensitive to a particular class of phase noise by encoding information in the appropriate subspaces; we observe a reduction of the error rate from 35% to essentially its pre-noise value of 8%.Comment: 11 pages, 4 figures, submitted to PR

Effects of time window size and placement on the structure of aggregated networks

Complex networks are often constructed by aggregating empirical data over time, such that a link represents the existence of interactions between the endpoint nodes and the link weight represents the intensity of such interactions within the aggregation time window. The resulting networks are then often considered static. More often than not, the aggregation time window is dictated by the availability of data, and the effects of its length on the resulting networks are rarely considered. Here, we address this question by studying the structural features of networks emerging from aggregating empirical data over different time intervals, focussing on networks derived from time-stamped, anonymized mobile telephone call records. Our results show that short aggregation intervals yield networks where strong links associated with dense clusters dominate; the seeds of such clusters or communities become already visible for intervals of around one week. The degree and weight distributions are seen to become stationary around a few days and a few weeks, respectively. An aggregation interval of around 30 days results in the stablest similar networks when consecutive windows are compared. For longer intervals, the effects of weak or random links become increasingly stronger, and the average degree of the network keeps growing even for intervals up to 180 days. The placement of the time window is also seen to affect the outcome: for short windows, different behavioural patterns play a role during weekends and weekdays, and for longer windows it is seen that networks aggregated during holiday periods are significantly different.Comment: 19 pages, 11 figure

A Method for Modeling Decoherence on a Quantum Information Processor

We develop and implement a method for modeling decoherence processes on an N-dimensional quantum system that requires only an $N^2$-dimensional quantum environment and random classical fields. This model offers the advantage that it may be implemented on small quantum information processors in order to explore the intermediate regime between semiclassical and fully quantum models. We consider in particular $\sigma_z\sigma_z$ system-environment couplings which induce coherence (phase) damping, though the model is directly extendable to other coupling Hamiltonians. Effective, irreversible phase-damping of the system is obtained by applying an additional stochastic Hamiltonian on the environment alone, periodically redressing it and thereby irreversibliy randomizing the system phase information that has leaked into the environment as a result of the coupling. This model is exactly solvable in the case of phase-damping, and we use this solution to describe the model's behavior in some limiting cases. In the limit of small stochastic phase kicks the system's coherence decays exponentially at a rate which increases linearly with the kick frequency. In the case of strong kicks we observe an effective decoupling of the system from the environment. We present a detailed implementation of the method on an nuclear magnetic resonance quantum information processor.Comment: 12 pages, 9 figure

Combining exposure indicators and predictive analytics for threats detection in real industrial IoT sensor networks

We present a framework able to combine exposure indicators and predictive analytics using AI-tools and big data architectures for threats detection inside a real industrial IoT sensors network. The described framework, able to fill the gaps between these two worlds, provides mechanisms to internally assess and evaluate products, services and share results without disclosing any sensitive and private information. We analyze the actual state of the art and a possible future research on top of a real case scenario implemented into a technological platform being developed under the H2020 ECHO project, for sharing and evaluating cybersecurity relevant informations, increasing trust and transparency among different stakeholders

Rigidity percolation in a field

Rigidity Percolation with g degrees of freedom per site is analyzed on randomly diluted Erdos-Renyi graphs with average connectivity gamma, in the presence of a field h. In the (gamma,h) plane, the rigid and flexible phases are separated by a line of first-order transitions whose location is determined exactly. This line ends at a critical point with classical critical exponents. Analytic expressions are given for the densities n_f of uncanceled degrees of freedom and gamma_r of redundant bonds. Upon crossing the coexistence line, n_f and gamma_r are continuous, although their first derivatives are discontinuous. We extend, for the case of nonzero field, a recently proposed hypothesis, namely that the density of uncanceled degrees of freedom is a ``free energy'' for Rigidity Percolation. Analytic expressions are obtained for the energy, entropy, and specific heat. Some analogies with a liquid-vapor transition are discussed. Particularizing to zero field, we find that the existence of a (g+1)-core is a necessary condition for rigidity percolation with g degrees of freedom. At the transition point gamma_c, Maxwell counting of degrees of freedom is exact on the rigid cluster and on the (g+1)-rigid-core, i.e. the average coordination of these subgraphs is exactly 2g, although gamma_r, the average coordination of the whole system, is smaller than 2g. gamma_c is found to converge to 2g for large g, i.e. in this limit Maxwell counting is exact globally as well. This paper is dedicated to Dietrich Stauffer, on the occasion of his 60th birthday.Comment: RevTeX4, psfig, 16 pages. Equation numbering corrected. Minor typos correcte