ABSTRACT: Truncated singular value decomposition (TSVD) and Golub-Kahan diagonalization are two elementary techniques for solving a least squares problem from a linear discrete ill-posed problems. For ...

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 ...

This note examines the utility of pseudorandom variables (prv) in Global Search and Optimization (GSO) using Central Force Optimization (CFO) as an example. Most GSO metaheuristics are stochastic in ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

In this video, we explore why Spotify's shuffle feature isn't truly random and operates based on an algorithm. We discuss the reasons behind our preferences for non-random shuffle, the results of an ...

Researchers have successfully used a quantum algorithm to solve a complex century-old mathematical problem long considered impossible for even the most powerful conventional supercomputers. The ...

Here's the corrected and polished version: Implementation of randomized greedy algorithms for solving the Knapsack Problem and Traveling Salesman Problem in C++. Educational project demonstrating ...

Color prediction algorithms are widely used in gaming and probability-based applications, generating sequences based on mathematical models or randomness. Understanding their inner workings often ...