A Unified Framework of Parameter-shift Rule Based on Heisenberg Picture

We propose a framework of parameter-shift rule for variational quantum algorithms that provides a unified description of previous extensions, together with unexplored use cases such as adaptive circuits, quantum state engineering, and CV-DV hybrid systems.

Authors

Institutions

Publication Details

Published
2025-01-01
DOI
https://doi.org/10.1364/quantum.2025.qtu3a.10
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Unified Framework of Parameter-shift Rule Based on Heisenberg Picture

H. Nagayoshi, Warit Asavanant, Ryuhoh Ide, Akira Furusawa
Neural Networks and Applications
article

A Unified Framework of Parameter-shift Rule Based on Heisenberg Picture

H. Nagayoshi, Warit Asavanant, Ryuhoh Ide, Akira Furusawa
article en

Abstract

We propose a framework of parameter-shift rule for variational quantum algorithms that provides a unified description of previous extensions, together with unexplored use cases such as adaptive circuits, quantum state engineering, and CV-DV hybrid systems.

Rikkyo University (JP), RIKEN Center for Advanced Photonics (JP), RIKEN Center for Quantum Computing, The University of Tokyo (JP)
Openalex Percentile: Top 91%
Neural Networks and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.