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Mode connectivity in the QCBM loss landscape

2021-11-09 18:31:12
Kathleen E. Hamilton, Emily Lynn, Vicente Leyton-Ortega, Swarnadeep Majumder, Raphael C. Pooser
arXiv_CV
       
Abstract

Quantum circuit Born machines (QCBMs) and training via variational quantum algorithms (VQAs) are key applications for near-term quantum hardware. QCBM ansätze designs are unique in that they do not require prior knowledge of a physical Hamiltonian. Many ansätze are built from fixed designs. In this work, we train and compare the performance of QCBM models built using two commonly employed parameterizations and two commonly employed entangling layer designs. In addition to comparing the overall performance of these models, we look at features and characteristics of the loss landscape -- connectivity of minima in particular -- to help understand the advantages and disadvantages of each design choice. We show that the rotational gate choices can improve loss landscape connectivity.

Abstract (translated)

URL

https://arxiv.org/abs/2111.05312

PDF

https://arxiv.org/pdf/2111.05312.pdf

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