Fuelled by increasing computer power and algorithmic advances, machine learning
techniques have become powerful tools for finding patterns in data. Quantum systems …

Recent progress in applying complex network theory to problems in quantum information
has resulted in a beneficial cross-over. Complex network methods have successfully been …

The problem of finding a marked node in a graph can be solved by the spatial search
algorithm based on continuous-time quantum walks (CTQW). However, this algorithm is …

These are exciting times for quantum physics as new quantum technologies are expected to
soon transform computing at an unprecedented level. Simultaneously network science is …

Any physical system can be viewed from the perspective that information is implicitly
represented in its state. However, the quantification of this information when it comes to …

In many studies, it is common to use binary (ie, unweighted) edges to examine networks of
entities that are either adjacent or not adjacent. Researchers have generalized such binary …

Network theory has played a dominant role in understanding the structure of complex
systems and their dynamics. Recently, quantum complex networks, ie collections of quantum …

Predicting new links in physical, biological, social, or technological networks has a
significant scientific and societal impact. Path-based link prediction methods utilize the …

To investigate the performance of quantum information tasks on networks whose topology
changes in time, we study the spatial search algorithm by continuous time quantum walk to …

Networks are topological and geometric structures used to describe systems as different as
the Internet, the brain, or the quantum structure of space-time. Here we define complex …