From the 2 of 8 linked papers with an AI index.
8 papers
Let the Qudit Do the Jacobi: A Structured Quantum Algorithm for Spectral Decomposition
A. Mandilara
The paper presents a qudit-native quantum version of the Jacobi diagonalization algorithm that iteratively finds the spectral decomposition of unknown unitary operators using varia…
A Scalable Cloud-Orchestrated and Service-Oriented Multi-Domain QKD Network with PQC Integration
Konstantinos Krilakis, Antonia Tsili, Aikaterini Mandilara +1
The paper proposes a cloud‑orchestrated, service‑oriented architecture that combines vendor‑agnostic quantum key distribution with software‑defined networking and post‑quantum cryp…
Parameterized Quantum Circuits as Feature Maps: Representation Quality and Readout Effects in Multispectral Land-Cover Classification
Ralntion Komini, Aikaterini Mandilara, Georgios Maragkopoulos +1
We investigate variational quantum classifiers (VQCs) for land-cover classification from multispectral satellite imagery, adopting a feature-map perspective in which the quantum ci…
Quantum-Inspired Unitary Pooling for Multispectral Satellite Image Classification
Georgios Maragkopoulos, Aikaterini Mandilara, Ralntion Komini +1
Multispectral satellite imagery poses significant challenges for deep learning models due to the high dimensionality of spectral data and the presence of structured correlations ac…
Feature Ranking in Credit-Risk with Qudit-Based Networks
Georgios Maragkopoulos, Lazaros Chavatzoglou, Aikaterini Mandilara +1
In finance, predictive models must balance accuracy and interpretability, particularly in credit risk assessment, where model decisions carry material consequences. We present a qu…
Learning kernels with quantum optical circuits
A. Mandilara, A. D. Papadopoulos, D. Syvridis
Support Vector Machines (SVMs) are a cornerstone of supervised learning, widely used for data classification. A central component of their success lies in kernel functions, which e…