{"version":"1.0","provider_name":"Luiss Data Lab","provider_url":"https:\/\/datalab.luiss.it\/en\/","author_name":"ad-peco","author_url":"https:\/\/datalab.luiss.it\/en\/author\/ad-peco\/","title":"Connectivity of Poissonian inhomogeneous random multigraphs\u00a0 - Luiss Data Lab","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"LbldSKv3Lu\"><a href=\"https:\/\/datalab.luiss.it\/en\/ricerche\/connectivity-of-poissonian-inhomogeneous-random-multigraphs\/\">Connectivity of Poissonian inhomogeneous random multigraphs\u00a0<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/datalab.luiss.it\/en\/ricerche\/connectivity-of-poissonian-inhomogeneous-random-multigraphs\/embed\/#?secret=LbldSKv3Lu\" width=\"600\" height=\"338\" title=\"&#8220;Connectivity of Poissonian inhomogeneous random multigraphs\u00a0&#8221; &#8212; Luiss Data Lab\" data-secret=\"LbldSKv3Lu\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/*! This file is auto-generated *\/\n!function(c,d){\"use strict\";var e=!1,o=!1;if(d.querySelector)if(c.addEventListener)e=!0;if(c.wp=c.wp||{},!c.wp.receiveEmbedMessage)if(c.wp.receiveEmbedMessage=function(e){var t=e.data;if(t)if(t.secret||t.message||t.value)if(!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var r,a,i,s=d.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),n=d.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),o=0;o<n.length;o++)n[o].style.display=\"none\";for(o=0;o<s.length;o++)if(r=s[o],e.source===r.contentWindow){if(r.removeAttribute(\"style\"),\"height\"===t.message){if(1e3<(i=parseInt(t.value,10)))i=1e3;else if(~~i<200)i=200;r.height=i}if(\"link\"===t.message)if(a=d.createElement(\"a\"),i=d.createElement(\"a\"),a.href=r.getAttribute(\"src\"),i.href=t.value,i.host===a.host)if(d.activeElement===r)c.top.location.href=t.value}}},e)c.addEventListener(\"message\",c.wp.receiveEmbedMessage,!1),d.addEventListener(\"DOMContentLoaded\",t,!1),c.addEventListener(\"load\",t,!1);function t(){if(!o){o=!0;for(var e,t,r,a=-1!==navigator.appVersion.indexOf(\"MSIE 10\"),i=!!navigator.userAgent.match(\/Trident.*rv:11\\.\/),s=d.querySelectorAll(\"iframe.wp-embedded-content\"),n=0;n<s.length;n++){if(!(r=(t=s[n]).getAttribute(\"data-secret\")))r=Math.random().toString(36).substr(2,10),t.src+=\"#?secret=\"+r,t.setAttribute(\"data-secret\",r);if(a||i)(e=t.cloneNode(!0)).removeAttribute(\"security\"),t.parentNode.replaceChild(e,t);t.contentWindow.postMessage({message:\"ready\",secret:r},\"*\")}}}}(window,document);\n<\/script>\n","thumbnail_url":"https:\/\/datalab.luiss.it\/wp-content\/uploads\/2023\/04\/abstract-networking-concept-still-life-assortment-scaled.jpg","thumbnail_width":2560,"thumbnail_height":1707,"description":"In the study of complex networks, one of the most challenging tasks is to construct mathematical models that are flexible enough to reproduce phenomena observed in the real world, yet simple enough to be both simulated and studied analytically. This paper develops a highly general model of random networks in which connections appear with arbitrary [&hellip;]"}