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From the 1 of 8 linked papers with an AI index.

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8 papers

quant-ph2026

Enabling Hybrid HPCQC Workflows with a Heterogeneous Software Stack

Muhammad Nufail Farooqi, Minh Chung, Burak Mete +5

In this work, we demonstrate hybrid High Performance Computing-Quantum Computing (HPCQC) workflows on a production petascale system. The demonstration combines three components: th…

cs.ET2026

MQSS Client: Interface for Decoupling Quantum Programming Interfaces

Ercüment Kaya, Muhammad Nufail Farooqi, Minh Chung +3

MQSS Client is a context‑aware access layer and library that abstracts resources, jobs, and results to decouple quantum programming interfaces from the underlying compilation and r…

physics.flu-dyn2026

Explainable quantum-compressed machine learning for complex fluid flows

Xiao Xue, Maida Wang, Mingyang Gao +2

Machine-learning surrogates of physical systems face a paradox: explainable models facing the challenge of expressivity to capture complex nonlinear flows, whereas expressive deep…

quant-ph2026

Practical Quantum Advantage before Fault Tolerance via Quantum-Informed Machine Learning

Maida Wang, Xiao Xue, Minh Chung +1

Early quantum devices can deliver a practical advantage before fault tolerance. The role we identify is a statistical module within a classical scientific workflow: a compressed me…

quant-ph2026

Evaluating System-Level Fidelity with Peaked Random Circuits

Martin Brieger, Florian Krötz, Minh Chung +1

Quantum computing is transitioning from experimental prototypes to commercially available turnkey systems, making architecture-agnostic performance metrics essential for cross-plat…

quant-ph2026

The Munich Quantum Software Stack: Connecting End Users, Integrating Diverse Quantum Technologies, Accelerating HPC

Lukas Burgholzer, Jorge Echavarria, Patrick Hopf +11

Quantum computing is advancing rapidly in hardware and algorithms, but broad accessibility demands a comprehensive, efficient, unified software stack. Such a stack must flexibly sp…