Quantum Digital Twins for Uncertainty Quantification

Kavli Affiliate: Elise Jennings

| First 5 Authors: Soronzonbold Otgonbaatar, Elise Jennings, , ,

| Summary:

Modern supercomputers can handle resource-intensive computational and
data-driven problems in various industries and academic fields. These
supercomputers are primarily made up of traditional classical resources
comprising CPUs and GPUs. Integrating quantum processing units with
supercomputers offers the potential to accelerate and manage computationally
intensive subroutines currently handled by CPUs or GPUs. However, the presence
of noise in quantum processing units limits their ability to provide a clear
quantum advantage over conventional classical resources. Hence, we develop and
construct "quantum digital twins," virtual versions of quantum processing
units. To demonstrate the potential benefit of quantum digital twins, we create
and deploy hybrid quantum ensembles on five quantum digital twins that emulate
parallel quantum computers since hybrid quantum ensembles are suitable for
distributed computing. Our study demonstrates that quantum digital twins assist
in analyzing the actual quantum device noise on real-world use cases and
emulate parallel quantum processing units for distributed computational tasks
to obtain quantum advantage as early as possible.

| Search Query: ArXiv Query: search_query=au:”Elise Jennings”&id_list=&start=0&max_results=3

Read More