Dependable classical-quantum computing systems engineering

Increasing evidence suggests quantum computing (QC) complements traditional High-Performance Computing (HPC) by leveraging its unique capabilities, leading to the emergence of a new, hybrid paradigm, QHPC. However, this integration introduces new challenges, with dependability–defined by reproducibility, resiliency, and security and privacy–emerging as a central concern for building trustworthy systems that provide an advantage to the users. This paper proposes a framework for dependable QHPC system design, organized around these three pillars. We identify integration challenges, anticipate roadblocks, and highlight productive synergies across QC, HPC, cloud platforms, and network security. Drawing from both classical computing principles and quantum-specific insights, we present a roadmap for co-design that supports robust hybrid architectures. Our approach offers concrete metrics for assessing dependability, provides design guidance for engineers working at the QC-HPC interface, and surfaces new engineering questions around complexity, scale, and fault tolerance. Ultimately, designing for dependability is key to realizing practical, scalable QHPC systems and accelerating the broader quantum ecosystem capable of translating quantum promises into actual application delivery.

Authors

Institutions

Publication Details

Journal
Frontiers in Computer Science
Published
2025-07-16
DOI
https://doi.org/10.3389/fcomp.2025.1520903
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dependable classical-quantum computing systems engineering

Bartolomeo Montrucchio, Kaitlin N. Smith, Flavio Vella, Weiwen Jiang et al.
Frontiers in Computer Science
Quantum Computing Algorithms and Architecture
article

Dependable classical-quantum computing systems engineering

Bartolomeo Montrucchio, Kaitlin N. Smith, Flavio Vella, Weiwen Jiang, Shuai Xu, Samudra Dasgupta, Ed Younis, Santiago Núñez-Corrales, Betis Baheri, Paolo Rech, Edoardo Giusto, Ravishankar K. Iyer, Alessandro Cilardo, Phuong Cao, Travis S. Humble
article en

Abstract

Increasing evidence suggests quantum computing (QC) complements traditional High-Performance Computing (HPC) by leveraging its unique capabilities, leading to the emergence of a new, hybrid paradigm, QHPC. However, this integration introduces new challenges, with dependability–defined by reproducibility, resiliency, and security and privacy–emerging as a central concern for building trustworthy systems that provide an advantage to the users. This paper proposes a framework for dependable QHPC system design, organized around these three pillars. We identify integration challenges, anticipate roadblocks, and highlight productive synergies across QC, HPC, cloud platforms, and network security. Drawing from both classical computing principles and quantum-specific insights, we present a roadmap for co-design that supports robust hybrid architectures. Our approach offers concrete metrics for assessing dependability, provides design guidance for engineers working at the QC-HPC interface, and surfaces new engineering questions around complexity, scale, and fault tolerance. Ultimately, designing for dependability is key to realizing practical, scalable QHPC systems and accelerating the broader quantum ecosystem capable of translating quantum promises into actual application delivery.

Frontiers in Computer ScienceVol. 7
Northwestern University (US), Lawrence Berkeley National Laboratory (US), Kent State University (US), University of Illinois Urbana-Champaign (US), George Mason University (US), Politecnico di Torino (IT), University of Trento (IT), National Center for Supercomputing Applications (US), Quantum Science Center (US), Case Western Reserve University (US), University of Naples Federico II (IT)
National Science Foundation, National Research Centre, University of Illinois at Urbana-Champaign
Openalex Percentile: Top 91%
Quantum Computing Algorithms and Architecture
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.