One of the challenges facing current noisy-intermediate-scale-quantum devices is achieving
efficient quantum circuit measurement or readout. The process of extracting classical data …

Contemporary quantum computers face many critical challenges that limit their usefulness
for practical applications. A primary limiting factor is classical-to-quantum (C2Q) data …

Convolutional neural networks (CNNs) have proven to be a very efficient class of machine
learning (ML) architectures for handling multidimensional data by maintaining data locality …

Noisy Intermediate-Scale Quantum (NISQ) devices face many critical challenges that limit
their usefulness for practical applications. A primary challenge is classical-to-quantum (C2Q) …

A critical challenge for Noisy Intermediate-Scale Quantum (NISQ) devices is achieving time-
efficient quantum state measurement or readout. Generally in quantum applications, data is …

With the rapid advancement of quantum computing technology, there is a strong motivation
to explore suitable practical applications for quantum algorithms and quantum computers …

Noisy Intermediate-Scale Quantum (NISQ) devices face many critical challenges that limit
their usefulness for practical applications. A primary challenge is classical-to-quantum (C2Q) …