arXiv subjects

Christiano M. S. Nascimento

Publications and source records attributed to Christiano M. S. Nascimento.

4 recordsLinked to original sources

arXiv2026

Demonstration of an LLO CV-QKD system over 12 km of optical fiber

Continuous-variable quantum key distribution (CV-QKD) promises high rates and seamless integration with classical beams within a single optical fiber. Over the years, implementations have been performed by transmitting a local oscillator reference along with the quantum channel, opening security loopholes for eavesdroppers and limiting potential applications. Here, we report on a Gaussian CV-QKD implementation using fully independent transmitter and receiver lasers (local-oscillator sources) over a 12 km fiber spool. The system was experimentally evaluated using logical frames containing approximately $10^7$ coherent states, each composed of ten independently processed subframes of approximately $10^6$ states, and security was assessed in both asymptotic and finite-size regimes under a trusted-device model. The full-fledged classical post-processing is capable of recovering the channel parameters and extracting secret key rates of 5.11 Mbit/s in the asymptotic regime and 4.67 Mbit/s in the finite-size regime, showing good agreement with theoretical predictions. This work establishes the foundation for metropolitan fiber deployment of CV-QKD under strict security constraints.

quant-ph↗

arXiv2025

Towards a point-to-point CV-QKD system: Implementation challenges and perspectives

This article presents an analysis of the practical challenges and implementation perspectives of point-to-point continuous-variable quantum key distribution (CV-QKD) systems over optical fiber. The study addresses the physical layer, including the design of transmitters, quantum channels, and receivers, with emphasis on impairments such as attenuation, chromatic dispersion, polarization fluctuations, and coexistence with classical channels. We further examine the role of digital signal processing (DSP) as the bridge between quantum state transmission and classical post-processing, highlighting its impact on excess noise mitigation, covariance matrix estimation, and reconciliation efficiency. The post-processing pipeline is detailed with a focus on parameter estimation in the finite-size regime, information reconciliation using LDPC-based codes optimized for low-SNR conditions, and privacy amplification employing large-block universal hashing. From a hardware perspective, we discuss modular digital architectures that integrate dedicated accelerators with programmable processors, supported by a reference software framework (CV-QKD-ModSim) for algorithm validation and hardware co-design. Finally, we outline perspectives for the deployment of CV-QKD in Brazil, starting from metropolitan testbeds and extending toward hybrid fiber/FSO and space-based infrastructures. The work establishes the foundations for the first point-to-point CV-QKD system in Brazil, while providing a roadmap for scalable and interoperable quantum communication networks.

quant-ph↗

arXiv2025

Exploring Quantum Machine Learning for Weather Forecasting

Weather forecasting plays a crucial role in supporting strategic decisions across various sectors, including agriculture, renewable energy production, and disaster management. However, the inherently dynamic and chaotic behavior of the atmosphere presents significant challenges to conventional predictive models. On the other hand, introducing quantum computing simulation techniques to the forecasting problems constitutes a promising alternative to overcome these challenges. In this context, this work explores the emerging intersection between quantum machine learning (QML) and climate forecasting. We present the implementation of a Quantum Neural Network (QNN) trained on real meteorological data from NASA's Prediction of Worldwide Energy Resources (POWER) database. The results show that QNN has the potential to outperform a classical Recurrent Neural Network (RNN) in terms of accuracy and adaptability to abrupt data shifts, particularly in wind speed prediction. Despite observed nonlinearities and architectural sensitivities, the QNN demonstrated robustness in handling temporal variability and faster convergence in temperature prediction. These findings highlight the potential of quantum models in short and medium term climate prediction, while also revealing key challenges and future directions for optimization and broader applicability.

quant-ph↗

arXiv2025

Passive polarization and phase stabilization scheme for Twin-Field QKD

Twin-Field Quantum Key Distribution requires first-order interference between coherent states sent by Alice and Bob in a mid-station Charlie. In order to obtain stable operation and maximum interferometric visibility, not only phase stabilization but also polarization control is required, especially in optical-fiber setups. In this paper, we propose an experimental setup that simultaneously provides passive stabilization of phase and polarization fluctuations by combining a Sagnac-like interferometer with a "Plug-and-Play" configuration employing Faraday mirrors. Experimental results show a net interferometric visibility maintained around 95.3% during 72 hours of continuous operation, with a standard deviation of 0.47%. The setup can be straightforwardly adapted to a multi-user scenario employing either a star network, a bus topology, or a combination of both.

quant-ph↗