A team led by Prof Vito Latora has used mathematical mapping to understand the mechanisms behind creating and innovating.
Higher-order Heaps’ exponents in real-world data sets
Ever wondered how we stumble upon new discoveries? Scientists have long studied how we explore the world, looking for novelties, those exciting first-time encounters with something new. Traditionally, a novelty was simply defined as the very first time we saw or experienced something. But what about those “aha!” moments when we connect familiar ideas in a completely new way?
A team of researchers led by Prof Vito Latora (QMUL) is now exploring these “higher-order novelties” – the moments when we combine existing knowledge to create something truly innovative. Think of it like combining ingredients you've used before to bake a completely new kind of cake. This new study introduces a way to measure how quickly these higher-order novelties are discovered, using something called "higher-order Heaps' exponents."
By analysing real-world data, they have found that even when two exploration processes seem to be uncovering novelties at the same rate, they can be vastly different when it comes to these higher-order, combined discoveries. To explain this, they developed a computer model that simulates exploration as a kind of random walk on a constantly changing network of ideas. This model successfully reproduced the patterns they saw in the real-world data, showing how the very structure of what we're exploring evolves as we explore it. This research helps us better understand the complex mechanisms behind discovery and innovation.
The recently published paper was featured in this week’s Nature Communications Editors’ Highlights for Applied physics and mathematics.