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Tactical MANETs – Node Mobility, Tx Range, Routing Schemes

Tactical MANETs Tactical Mobile Ad-Hoc Networks (MANETs) provide dynamic, infrastructure-less connectivity in environments without traditional networks. Live Simulation: Full Network Packet Routing 1. Node Mobility Tactical devices are constantly moving. Military units travel in swarms or platoons, requiring the network to predict group mobility patterns to maintain stable connections as topology shifts. Simulation: Platoon Movement ... Read More

Quantum Feature Map

Resources: The Concept: Quantum Feature Maps In classical machine learning, a “kernel trick” is often used to map data into a higher-dimensional space. Quantum computers provide a natural way to do this: Feature Map The process of encoding a classical input vector \( \vec{x} \) into a quantum state \( |\Phi(\vec{x})\rangle \) acts as a ... Read More

Probability – Conditional Probability and Independence

Resource: What is Conditional Probability? Conditional Probability Conditional probability is the likelihood of an event occurring, given that another event has already happened. It allows us to update our understanding of an outcome based on new information or specific “conditions.” The Formula P(A|B) = P(A ∩ B) P(B) • P(A|B): The probability of event A ... Read More

Paper Highlight – Quantum Inspired classical algorithm for recommendation systems

E. Tang, “A quantum-inspired classical algorithm for recommendation systems,” in Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, Jun. 2019, pp. 217–228. doi: 10.1145/3313276.3316310.\ “Introduction | IBM Quantum Learning,” IBM Quantum Learning, 2021. https://quantum.cloud.ibm.com/learning/en/courses/quantum-machine-learning/introduction (accessed Feb. 20, 2026). Paper Summary: Classical Analogue to Quantum Recommendation Systems Author: Ewin Tang Key Finding: The ... Read More

IBM Course: Introduction to Quantum Machine Learning

Resources: Introduction to Quantum Machine Learning A Comprehensive Course Overview The Classical-Quantum Intersection Quantum Machine Learning (QML) is a symbiotic cycle where quantum and classical systems push each other’s limits. The current focus remains on applying quantum algorithms to classical datasets to complement existing workflows where classical systems already excel. Feature Mapping & Kernels A ... Read More
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