ComputingNotes

What are electromagnetic waves?

by ComputingNotes
Further, electromagnetic waves are different from mechanical wave which need medium to travel. What is an Electromagnetic Wave? Most waves we encounter like sound or water ripples are mechanical. They need matter (a “medium”) to travel, bumping molecules together like falling dominoes. But Electromagnetic (EM) waves are different. They don’t need a medium at all, ... Read More

How Data or Information travel wirelessly?

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Wireless communication relies on invisible electromagnetic waves that carry information through the air by altering their size or speed. By precisely manipulating these wave properties, using techniques like Amplitude Modulation (AM), Frequency Modulation (FM), and digital Frequency Shift Keying (FSK), devices can seamlessly transmit everything from analog radio broadcasts to high-speed Wi-Fi data. How Wireless ... Read More

Quantum Perceptron

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To understand Variational Quantum Circuits, we can have analogy with Classical Neural Networks. NN vs. QNN Classical Perceptrons (Left) vs. Quantum Gates (Right) Mapping to Hilbert Space R U Classical NN Quantum QNN Classical: Data flows through fixed layers of neurons. Quantum: Data is encoded into qubits and transformed via Rotational Gates. Non-Linearity: In QNNs, ... Read More

Asymptotic Lower Bound – Omega

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Resources: What is Asymptotic Lower Bound? In the world of algorithm analysis, Asymptotic Lower Bound, denoted by the Greek letter Omega ($\omega$), is used to describe the “best-case” or the minimum rate of growth for a function as the input size n approaches infinity. Think of it as a guarantee. If an algorithm has a ... Read More

Big Oh Expressions Reference

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Big-O Time Complexity O(1) Constant time — stays the same regardless of input size. O(log n) Logarithmic — grows very slowly (e.g., binary search). O((log n)2) Log-squared — slightly faster growth than log n. O(√n) Square root — moderate growth, better than linear. O(n) Linear — grows directly with input size. O(n log n) Efficient ... Read More

2025 ACM A.M. Turing Award Honors Quantum Pioneers

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2025 ACM A.M. Turing Award Honors Quantum Pioneers Recipients: Charles H. Bennett & Gilles Brassard ACM has named Charles H. Bennett (IBM Research) and Gilles Brassard (Université de Montréal) as the recipients of the 2025 A.M. Turing Award. Often called the “Nobel Prize of Computing,” the award includes a $1 million prize for their foundational ... Read More

Tactical MANETs – Node Mobility, Tx Range, Routing Schemes

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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

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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

Inner or Dot Products – Linear Algebra

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In linear algebra, the dot product (or inner product) is specifically used for vectors. It takes two vectors of the same dimension and results in a single scalar value (a number). 1. Geometric Definition Geometrically, the dot product measures the overlap or projection of one vector onto another. a · b = ||a|| ||b|| cos(θ) ... Read More
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