Quick Navigation
Topics
Quantum Simulation
Quantum Chemistry
Fragmentation of Virtual Orbitals for Quantum Computing: Reducing Qubit Requirements through Many-Body Expansion
arXiv
Authors: Federico Zahariev, Mark S. Gordon
Year
2025
Paper ID
50816
Status
Preprint
Abstract Read
~2 min
Abstract Words
156
Citations
N/A
Abstract
The development of quantum computing for molecular simulations is constrained by the limited number of qubits available on current Noisy Intermediate-Scale Quantum (NISQ) devices. The present work introduces the Virtual Orbital Fragmentation (FVO) method, a systematic approach that reduces qubit requirements by 40--66% while maintaining chemical accuracy. The method partitions the virtual orbital space into chemically intuitive fragments and employs many-body expansion techniques analogous to spatial fragmentation methods. Applications to six molecular systems demonstrate that the 2-body FVO expansion achieves errors below 3 kcal/mol, while the 3-body expansion provides sub-kcal/mol accuracy. When integrated with the Variational Quantum Eigensolver (VQE) and combined with the Effective Fragment Molecular Orbital (EFMO) method for multi-molecular systems, the hierarchical Q-EFMO-FVO approach achieves 96--100% accuracy relative to full calculations. The method provides a practical pathway for quantum chemical calculations on current 50--100 qubit processors and establishes virtual orbital fragmentation as a complementary strategy to spatial fragmentation for managing quantum computational complexity.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- The development of quantum computing for molecular simulations is constrained by the limited number of qubits available on current Noisy Intermediate-Scale Quantum (NISQ) devices.
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
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
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.