Enabling Quantum Computer Simulation under Minimal Precision Floating-Point using Irrational Value Decomposition

Quantum computing holds immense promise for solving complex problems beyond the reach of classical computers. However, the realization of practical quantum computers faces significant challenges, including its inherent noise and error rates. To address these challenges and explore the capabilities of quantum computers, accurate and efficient quantum computer simulations are essential. This paper presents a novel quantum computer simulation framework designed to accommodate a wide range of custom reduced precision floating-point formats. Leveraging our proposed quantum computation algorithm, our framework enables the quantum computer simulations using exceptionally low precision floating-point numbers, while maintaining high accuracy levels. Through a systematic analysis, we explore the impact of floating-point precision on the accuracy of the quantum computer simulation, providing optimized bit-widths tailored for floating-point numbers. Particularly, using our proposed quantum computation algorithm, our framework achieves quantum state vector outcomes comparable to full-precision quantum simulations, even with extremely low precision floating-point formats ranging from 4 to 6 bits. Overall, these findings highlight the viability of precision reduction techniques in enhancing the efficiency of quantum computer simulations.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/mascots64422.2024.10786505
Citations
3
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
1.04

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enabling Quantum Computer Simulation under Minimal Precision Floating-Point using Irrational Value Decomposition

Hyoju Seo, Yongtae Kim
3 citations
Quantum Computing Algorithms and Architecture
1.04
article

Enabling Quantum Computer Simulation under Minimal Precision Floating-Point using Irrational Value Decomposition

Hyoju Seo, Yongtae Kim
article en
3 citations

Abstract

Quantum computing holds immense promise for solving complex problems beyond the reach of classical computers. However, the realization of practical quantum computers faces significant challenges, including its inherent noise and error rates. To address these challenges and explore the capabilities of quantum computers, accurate and efficient quantum computer simulations are essential. This paper presents a novel quantum computer simulation framework designed to accommodate a wide range of custom reduced precision floating-point formats. Leveraging our proposed quantum computation algorithm, our framework enables the quantum computer simulations using exceptionally low precision floating-point numbers, while maintaining high accuracy levels. Through a systematic analysis, we explore the impact of floating-point precision on the accuracy of the quantum computer simulation, providing optimized bit-widths tailored for floating-point numbers. Particularly, using our proposed quantum computation algorithm, our framework achieves quantum state vector outcomes comparable to full-precision quantum simulations, even with extremely low precision floating-point formats ranging from 4 to 6 bits. Overall, these findings highlight the viability of precision reduction techniques in enhancing the efficiency of quantum computer simulations.

Kyungpook National University (KR)
National Research Foundation
Openalex Percentile: Top 18%
Quantum Computing Algorithms and Architecture
1.04
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.

Enabling Quantum Computer Simulation under Minimal Precision Floating-Point using Irrational Value Decomposition — Hyoju Seo, Yongtae Kim · (2024) | TGRS Research Map | TGRS