17 citations · 45 across the 29 of their papers we have counts for
11 papers · 1 filter
Investigating Different Barren Plateaus Mitigation Strategies in Variational Quantum Eigensolver
Mostafa Atallah, Nouhaila Innan, Muhammad Kashif +1
Variational Quantum Eigensolver (VQE) algorithms suffer from barren plateaus, where gradients vanish with system size and circuit depth. Although many mitigation strategies exist,…
FAQNAS: FLOPs-aware Hybrid Quantum Neural Architecture Search using Genetic Algorithm
Muhammad Kashif, Shaf Khalid, Alberto Marchisio +2
Hybrid Quantum Neural Networks (HQNNs), which combine parameterized quantum circuits with classical neural layers, are emerging as promising models in the noisy intermediate-scale…
Evaluating Quantum Amplitude Estimation for Pricing Multi-Asset Basket Options
Muhammad Kashif, Shaf Khalid, Nouhaila Innan +2
Accurate and efficient pricing of multi-asset basket options poses a significant challenge, especially when dealing with complex real-world data. In this work, we investigate the r…
QUAV: Quantum-Assisted Path Planning and Optimization for UAV Navigation with Obstacle Avoidance
Nouhaila Innan, Muhammad Kashif, Alberto Marchisio +3
The growing demand for drone navigation in urban and restricted airspaces requires real-time path planning that is both safe and scalable. Classical methods often struggle with the…
Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy
Nouhaila Innan, Muhammad Kashif, Alberto Marchisio +2
This paper provides an integrated perspective on addressing key challenges in developing reliable and secure Quantum Neural Networks (QNNs) in the Noisy Intermediate-Scale Quantum…
PennyCoder: Efficient Domain-Specific LLMs for PennyLane-Based Quantum Code Generation
Abdul Basit, Minghao Shao, Muhammad Haider Asif +4
The growing demand for robust quantum programming frameworks has unveiled a critical limitation: current large language model (LLM) based quantum code assistants heavily rely on re…
QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges
Abdul Basit, Minghao Shao, Muhammad Haider Asif +4
Recent advances in Large Language Models (LLMs) have demonstrated strong potential in code generation, yet their effectiveness in quantum computing remains underexplored. This pape…
Noisy HQNNs: A Comprehensive Analysis of Noise Robustness in Hybrid Quantum Neural Networks
Tasnim Ahmed, Alberto Marchisio, Muhammad Kashif +1
Hybrid Quantum Neural Networks (HQNNs) offer promising potential of quantum computing while retaining the flexibility of classical deep learning. However, the limitations of Noisy…
A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG
Abdul Basit, Nouhaila Innan, Muhammad Haider Asif +4
Large Language Models (LLMs) offer powerful capabilities in code generation, natural language understanding, and domain-specific reasoning. Their application to quantum software de…
NRQNN: The Role of Observable Selection in Noise-Resilient Quantum Neural Networks
Muhammad Kashif, Muhammad Shafique
This paper explores the complexities associated with training Quantum Neural Networks (QNNs) under noisy conditions, a critical consideration for Noisy Intermediate-Scale Quantum (…
Quantum Neural Networks: A Comparative Analysis and Noise Robustness Evaluation
Tasnim Ahmed, Muhammad Kashif, Alberto Marchisio +1
In current noisy intermediate-scale quantum (NISQ) devices, hybrid quantum neural networks (HQNNs) offer a promising solution, combining the strengths of classical machine learning…