activity
20222026
most citedDissipation as a resource for Quantum Reservoir Computing

40 citations · 71 across the 8 of their papers we have counts for

collaborators

9 papers

quant-ph2026

Temporal information processing on a 4,500-qubit quantum annealer

Antonio Sannia, Roberto Menta, Pratik Sathe +7

Quantum machine learning could uncover statistical structure beyond the reach of classical models, but this requires quantum models large and expressive enough to be useful and che…

quant-ph2026

A Reservoir Computing Approach to Quantum Gate Synthesis

Francesco Caravelli, Roberto Menta, Antonio Sannia

Quantum gate synthesis is essential for implementing quantum algorithms on real hardware, yet existing methods are often computationally demanding. Here, we introduce a novel appro…

quant-ph2025

Uncovering and Circumventing Noise in Quantum Algorithms via Metastability

Antonio Sannia, Pratik Sathe, Luis Pedro García-Pintos

The presence of noise is the primary challenge in realizing fault-tolerant quantum computers. In this work, we introduce and experimentally validate a novel strategy to circumvent…

quant-ph2025

From quantum feature maps to quantum reservoir computing: perspectives and applications

Casper Gyurik, Filip Wudarski, Evan Philip +5

We explore the interplay between two emerging paradigms: reservoir computing and quantum computing. We observe how quantum systems featuring beyond-classical correlations and vast…

quant-ph2025

Exponential concentration and symmetries in Quantum Reservoir Computing

Antonio Sannia, Gian Luca Giorgi, Roberta Zambrini

Quantum reservoir computing (QRC) is an emerging framework for near-term quantum machine learning that offers in-memory processing, platform versatility across analogue and digital…

quant-ph2025

Non-Markovianity and memory enhancement in Quantum Reservoir Computing

Antonio Sannia, Ricard Ravell Rodríguez, Gian Luca Giorgi +1

Featuring memory of past inputs is a fundamental requirement for machine learning models processing time-dependent data. In quantum reservoir computing, all architectures proposed…

quant-ph2024★ 5 cited

Liouvillian skin effect in quantum neural networks

Antonio Sannia, Gian Luca Giorgi, Stefano Longhi +1

In the field of dissipative systems, the non-Hermitian skin effect has generated significant interest due to its unexpected implications. A system is said to exhibit a skin effect…

quant-ph2023★ 26 cited

Engineered dissipation to mitigate barren plateaus

Antonio Sannia, Francesco Tacchino, Ivano Tavernelli +2

Variational quantum algorithms represent a powerful approach for solving optimization problems on noisy quantum computers, with a broad spectrum of potential applications ranging f…

quant-ph2022★ 40 cited

Dissipation as a resource for Quantum Reservoir Computing

Antonio Sannia, Rodrigo Martínez-Peña, Miguel C. Soriano +2

Dissipation induced by interactions with an external environment typically hinders the performance of quantum computation, but in some cases can be turned out as a useful resource.…