Abstract

As we scale quantum computers to even larger devices, creating highly detailed and accurate digital twins is essential for understanding unexpected experimental results and for improving the design and performance of the QPUs. Scalable simulations that faithfully replicate the actual behaviour and dynamics of the complete quantum system including all classical surrounding infrastructure are necessary for the fast prototyping of new QPU designs that overcome the shortcomings of their predecessors. We present a modular software stack that conveniently simulates the open quantum dynamics of noisy systems - seamlessly modelling both the QPU and the control stack. A flexible domain specific language (DSL) allows for easy definition of complex QPU architectures. Applications include data-driven learning of system parameters using the differentiable digital twins, open loop optimisation for pulse shaping, and identification of next-generation QPU design parameters. We discuss demonstrative examples on various platforms - in flux tunable superconducting qubits studying the effects of leakage in fast CZ and iSWAP gates, in Rydberg atoms studying the effect of noise in gate fidelities and in Nitrogen vacancy centres designing optimal control pulses - showing how such an accurate digital twin of the system is critical for a quantitative breakdown of the contribution of different error generating factors to the bottomline benchmarks of a QPU's performance.

Slides are available online here.

Authors:
Shai Machnes (Qruise)
Yousof Mardoukhi (Qruise)
Ana Gramajo (Qruise)
Lorena Bianchet (Qruise)
Marco Rossignolo (Qruise)
Anurag Saha Roy (Qruise)