Investigating parameter trainability in the SNAP-Displacement protocol of a qudit system.

Conference · Fri Dec 15 04:00:00 EST 2023

DOI:https://doi.org/10.2172/2246726· OSTI ID:2246726

Ogunkoya, Oluwadara ^[1]; Morris, Kirsten ^[2]; Kurkcuoglu, Doga ^[1]

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1. Fermilab
2. Nebraska U.

Our main focus is to investigate the sensitivity of training any of the SNAP parameters in the SNAP-Displacement protocol. We analyze conditions that could potentially lead to the Barren Plateau problem in a qudit system and draw comparisons with multi-qubit systems. The parameterized ansatz we consider consists of SNAP -Displacement blocks. We utilize techniques similar to those in [8] and [2] along with the concept of $t-$design. Through this analysis, we make the following key observations: (a) The trainability of a SNAP-parameter does not exhibit a preference for any particular direction within our cost function landscape, (b) using Haar measure properties, we establish new lemmas concerning the expectation of certain polynomial functions, and (c) utilizing these new lemmas, we identify a general condition that indicates an expected trainability advantage in a qudit system when compared to multi-qubit systems.

• Research Organization: Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
• DOE Contract Number: AC02-07CH11359
• OSTI ID: 2246726
• Report Number(s): FERMILAB-POSTER-23-311-SQMS; oai:inspirehep.net:2737236
• Country of Publication: United States
• Language: English

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