Generalized Two-Qubit Hamiltonian Improves Quantum Feature Maps for Machine Learning
By
[Submitted on 11 Jun 2026]
Summary
This paper introduces a generalized two-qubit Hamiltonian-based Projected Quantum Feature Map (PQFM) that unifies encoding of classical features through local Pauli fields and pairwise two-qubit Pauli interactions. The approach increases information density in shallow quantum circuits while remaining hardware-compatible. The authors developed pqfmlib, a public Python library for building and benchmarking these methods. They tested the generalized Hamiltonian PQFMs against reference PQFMs on four biomedical classification datasets using IBM quantum processors (up to 156 qubits) and simulations. Results show the generalized two-qubit Hamiltonian family consistently outperforms matched classical baselines, though performance varies by dataset, encoding strategy, observables, and hardware conditions.
Source
bskyGeneralized Two-Qubit Hamiltonian Improves Quantum Feature Maps for Machine Learningarxiv.orgKey quotes
· 5 pulledProjected quantum feature maps provide a strategy for using quantum processors as feature generators for classical machine-learning models.
This construction allows distinct classical variables to be embedded along different Pauli axes of the same qubit, increasing the information density of shallow circuits while remaining compatible with hardware constraints.
Our results show that the generalized two-qubit Hamiltonian family provides the most consistent pattern of statistically supported gains over matched classical baselines.
These findings support generalized Hamiltonian PQFMs as a promising route toward near-term quantum utility.
We develop and implement these methods in pqfmlib, a publicly available Python library for constructing, executing, and benchmarking Hamiltonian-based PQFMs.
You might also wanna read
Embedding-Aware Quantum-Classical SVMs for Scalable Quantum Machine Learning
arxiv.org·10mo ago
Witness expansion: A unified framework for detecting quantum resources in mixed states
This paper proposes "witness expansion," a unified theoretical framework for constructing nonlinear criteria to detect quantum resources in
scirate.com·3d ago
Researchers build million-p-bit probabilistic computer by networking FPGAs, breaking single-chip limit
Researchers have built a programmable probabilistic computer using networked FPGAs that achieves one million p-bits (probabilistic bits), br
arxiv.org·17h ago
Comments
Sign in to join the conversation.
No comments yet. Be the first.