The United States is facing a sharp increase in electricity demand, driven by the rapid growth of AI data centers and a resurgence in domestic manufacturing. Meeting this demand while sustaining U.S. leadership in innovation requires the reliable integration of all available electric generation sources into the national grid. Electromagnetic transients (EMT) studies are essential to this effort, as they capture system dynamics by continuously tracking the evolution of grid states. High-fidelity EMT simulations, mandated by regulatory and planning bodies, are critical for ensuring grid reliability and secure energy integration. Three challenges, however, make EMT studies prohibitively costly and difficult: 1) EMT simulations involve polynomial-time matrix computations at each step; 2) Capturing fast inverter-induced transients requires extremely small time steps, resulting in a vast number of calculations; and 3) Time- and frequency-domain contingency screening becomes prohibitively difficult when faced with massive contingencies and operational scenarios. Building on the PIs’ pioneering work on quantum grid analytics, this project aims to establish a scalable quantum EMT (QEMT) framework with ultra-fast screening capabilities in both time and frequency domains. The broader impacts of this project include: First, QEMT will be adopted by major independent system operators (ISOs) and power utilities, enabling the accelerated and reliable deployment of gigawatts of added generat