An AI model informed by calculations from a quantum computer can better predict the behavior of a complex physical system ...

Overview: Today's high-performance cloud simulators surpass previous limits in handling qubits and accurately replicate ...

Analogue engineering still relies heavily on manual intervention, but that is changing with the growing use of AI/ML.

Manufacturing is entering a new era where AI interacts directly with the physical world. Through robotics, sensors, ...

It is important to consider the use of artificial intelligence (AI) for analog test and measurement, as well as other electrical engineering activities, as it helps ensure that critical electrical ...

Learn how to create a Python simulation of a tipping stick! In this video, we guide you step by step through coding a physics-based simulation that models tipping motion, friction, and torque. Perfect ...

Radio-Frequency (RF) Electronic Design Automation (EDA) is at a turning point. Historically, engineers adapted their workflows to rigid software tools, often sacrificing flexibility and efficiency.

Abstract: We introduce the QARN (Quantum Accelerated and Reconfigurable, Noisy) simulator, an efficient and scalable state vector based quantum circuit simulator. Implemented in Python, QARN delivers ...

ScaleQsim is a distributed full-state quantum circuit simulator based on Google's Qsim. It is designed to support extreme-scale HPC systems such as Perlmutter@NERSC while utilizing existing efficient ...

Reconfigurable lumped elements of resonant structures significantly impact resonant behavior. Full-wave simulations are expensive and time-consuming. Electromagnetic co-simulation provides an ...