Traditional encryption methods have long been vulnerable to quantum computers, but two new analyses suggest a capable enough ...

Engineering education faces a persistent tension: students eager to build real projects often view theoretical coursework as ...

Abstract: Deep neural networks (DNNs) have been widely used for learning various wireless communication policies. While DNNs have demonstrated the ability to reduce the time complexity of inference, ...

In this tutorial, we present an advanced, hands-on tutorial that demonstrates how we use Qrisp to build and execute non-trivial quantum algorithms. We walk through core Qrisp abstractions for quantum ...

The (Code-Analyzer) Chrome Extension is designed to help developers optimize their algorithms by providing instant insights into time and space complexity. Whether you are browsing coding platforms, ...

A woman sits behind a ring light and takes pictures of herself. “The camera eats first.” A decade ago, that phrase might have been a joke about influencers and their avocado toast. Now it’s a ...

One July afternoon in 2024, Ryan Williams set out to prove himself wrong. Two months had passed since he’d hit upon a startling discovery about the relationship between time and memory in computing.

Abstract: Discrete time-variant equation systems represent a typical and complex problem across various disciplines. With the increasing complexity of systems in various fields, traditional methods ...