Quick Navigation

Topics

Quantum Chemistry

Efficient variational quantum eigensolver methodologies on quantum processors

arXiv
Authors: Tushar Pandey, Jason Saroni, Abdullah Kazi, Kartik Sharma

Year

2024

Paper ID

65085

Status

Preprint

Abstract Read

~2 min

Abstract Words

83

Citations

N/A

Abstract

We compare the performance of different methodologies for finding the ground state of the molecule BeH2. We implement adaptive, tetris-adaptive variational quantum eigensolver (VQE), and entanglement forging to reduce computational resource requirements. We run VQE experiments on IBM quantum processing units and use error mitigation, including twirled readout error extinction (TREX) and zero-noise extrapolation (ZNE) to reduce noise. Our results affirm the usefulness of VQE on noisy quantum hardware and pave the way for the usage of VQE related methods for large molecules.

Why This Paper Matters

  • This paper contributes to the Quantum Chemistry research area in the Quantum Articles archive.
  • It adds a 2024 reference point for readers tracking recent quantum research.
  • We compare the performance of different methodologies for finding the ground state of the molecule BeH2.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #65085 #69978 Distribution Complexity of Elec... #69971 Quantum-enhanced estimation of ... #69966 Schur--Horn bound on field-free... #69943 The moving Fermi polaron

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.