Quantum machine learning via continuous-variable cluster states and teleportation

• DOI: 10.1140/epjqt/s40507-025-00352-3
• ArXiv number: 2411.06907

We propose a new approach for a photonic platform suitable for distributed quantum machine learning and exhibiting memory. This measurement-based quantum reservoir computing takes advantage of continuous variable cluster states as the main quantum resource. Cluster states are key to several photonic quantum technologies, enabling universal quantum computing as well as quantum communication protocols. The proposed measurement-based quantum reservoir computing is based on a neural network of cluster states and local operations, where input data are encoded through measurement, thanks to quantum teleportation. In this design, measurements enable input injections, information processing and continuous monitoring for time series processing. The architecture’s power and versatility are tested by performing a set of benchmark tasks showing that the protocol displays internal memory and is suitable for both static and temporal information processing without hardware modifications. This design opens the way to distributed machine learning.

• Artículo completo

Related research projects

QNet

Transport, metastability, and neuromorphic applications in quantum networks

I.P.: Gian Luca Giorgi, Roberta Zambrini

QNet is a European project funded under the call Quantera 2023. The consortium is coordinated by Ticijana Ban from the Institute of Physics, Zagreb, and is also composed of IFISC, Universität des …

CoQuSy

Complex Quantum Systems: machine learning, thermodynamics, and emergent phenomena

I.P.: Gian Luca Giorgi, Gonzalo Manzano, Roberta Zambrini

CoQuSy is a coordinated project and joins all the researchers at IFISC (belonging either to CSIC or UIB) working in the common line of complex quantum systems. The coordination is motivated by …

INFOLANET

Information processing with coupled laser networks

I.P.: Apostolos Argyris, Miguel C. Soriano

In the INFOLANET project, we will combine the expertise of the PIs on dynamical systems and machine learning to advance information processing concepts, based on a high-speed photonic implementation. We anticipate that …

Quantum Spain

Quantum Spain

I.P.: Roberta Zambrini

Reserach topic: QUANTUM MACHINE LEARNING Convenio en el BOE: https://www.boe.es/diario_boe/txt.php?id=BOE-A-2023-18333 IFISC participation both as UIB and as CSIC (2 separate budgets)

MdM-IFISC-2

Maria de Maeztu 2023-2026

I.P.: Ernesto Estrada, Ingo Fischer, Emilio Hernández-García, Rosa Lopez, Claudio Mirasso, Jose Javier Ramasco, Raúl Toral, Roberta Zambrini

After 15 years of its existence, IFISC can point to a proven track record of impactful research. The previous 2018-2022 MdM award has significantly enhanced the institute's capabilities, as demonstrated by an …