ADAPT-VQE Sampling Noise w/VTech
By Akansha, Marina, Sophia, Kade
ADAPT-VQE is a Variational Quantum Eigensolver (VQE) for solving quantum chemistry simulations and optimization problems. However, in the real world, we can only use a finite number of measurement shots to estimate expectation values, limiting the performance of the algorithm. This is known as sampling noise, which impacts the accuracy of energy evaluations and the gradients for variational parameter optimization. In this work, we analyze the performance of ADAPT-VQE under realistic noise conditions to compare multiple classical optimizers such as gradient descent, quasi-Newton methods, and simplex-based approaches. We hope that our findings contribute to the development of more accurate and efficient variational algorithms with fewer measurements.
Files and Resources
Files are coming soon!
Photo Gallery
