FTPrimitiveBench: A Benchmark Suite For Logical Computation Under Hardware-Motivated and Biased Noise Models

Fault-tolerant quantum computing hinges on understanding the performance of error-correcting codes on various physical hardware, which is typically evaluated through noisy stabilizer simulation of logical circuits. To better assess this performance, researchers have introduced FTPrimitiveBench, a benchmark suite designed to test logical computation under hardware-motivated and biased noise models¹. This suite moves beyond the standard uniform depolarizing model, which assumes homogeneous error rates, to account for more realistic noise scenarios. By simulating logical circuits at scale, FTPrimitiveBench provides a more nuanced understanding of how error-correcting codes behave under different noise conditions. The development of such benchmarking tools is crucial for advancing quantum computing, as it enables more accurate predictions of logical error rates and informs the design of more robust quantum systems. This matters to practitioners because it can help them develop more effective quantum error correction strategies, ultimately shaping the future of quantum computing and its potential impact on cryptography.