Quantum Machine Learning in Multi-Qubit Phase-Space Part I: Foundations

2025-07-16 · Timothy Heightman, Edward Jiang, Ruth Mora-Soto, Maciej Lewenstein, Marcin Płodzień arxiv

Quantum machine learning (QML) seeks to exploit the intrinsic properties of quantum mechanical systems, including superposition, coherence, and quantum entanglement for classical data processing. However, due to the exponential growth of the Hilbert space, QML faces practical limits in classical simulations with the state-vector representation of quantum system. On the other hand, phase-space methods offer an alternative by encoding quantum states as quasi-probability functions. Building on prior work in qubit phase-space and the Stratonovich-Weyl (SW) correspondence, we construct a closed, composable dynamical formalism for one- and many-qubit systems in phase-space. This formalism replaces the operator algebra of the Pauli group with function dynamics on symplectic manifolds, and recasts the curse of dimensionality in terms of harmonic support on a domain that scales linearly with the number of qubits. It opens a new route for QML based on variational modelling over phase-space.

📄 PDF Abstract BibTeX arXiv:2507.12117

Code (0)

등록된 구현이 없습니다.

Tasks

Quantum Machine Learning

Machine-learning based three-qubit gate for realization of a Toffoli gate with cQED-based transmon systems

2019-08-02 · Sahar Daraeizadeh, Shavindra P. Premaratne, Xiaoyu Song, Marek Perkowski 외

We use machine learning techniques to design a 50 ns three-qubit flux-tunable controlled-controlled-phase gate with fidelity of >99.99% for nearest-neighbor coupled transmons in circuit quantum electrodynamics architectu…

BIG-bench Machine Learning

eXplainable AI for Quantum Machine Learning

2022-11-02 · Patrick Steinmüller, Tobias Schulz, Ferdinand Graf, Daniel Herr

Parametrized Quantum Circuits (PQCs) enable a novel method for machine learning (ML). However, from a computational point of view they present a challenge to existing eXplainable AI (xAI) methods. On the one hand, measur…

Explainable Artificial Intelligence (XAI)Quantum Machine Learning

Machine Learning for Quantum Noise Reduction

2025-09-17 · Karan Kendre arxiv

Quantum noise fundamentally limits the utility of near-term quantum devices, making error mitigation essential for practical quantum computation. While traditional quantum error correction codes require substantial qubit…

Machine learning applied to quantum synchronization-assisted probing

2019-01-16 · Gabriel Garau Estarellas, Gian Luca Giorgi, Miguel C. Soriano, Roberta Zambrini

A probing scheme is considered with an accessible and controllable qubit, used to probe an out-of equilibrium system consisting of a second qubit interacting with an environment. Quantum spontaneous synchronization betwe…

BIG-bench Machine Learning

Designing high-fidelity multi-qubit gates for semiconductor quantum dots through deep reinforcement learning

2020-06-15 · Sahar Daraeizadeh, Shavindra P. Premaratne, A. Y. Matsuura

In this paper, we present a machine learning framework to design high-fidelity multi-qubit gates for quantum processors based on quantum dots in silicon, with qubits encoded in the spin of single electrons. In this hardw…

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning (RL)