QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting

• URL: http://arxiv.org/abs/2605.18333v1
• Date: Mon, 18 May 2026 12:49:46 GMT
• Title: QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting
• Abstract summary: This work adapts the Quantum Leaky Integrate-and-Fire spiking neural network for time-series regression tasks.<n>QLIF-CAST encodes excitation neuron states as single-qubit quantum superpositions, driven by Rx rotation gates and T1 relaxation decay.<n> Hardware verification on IBM Marrakesh confirms reliable circuit execution with only 1.2% average deviation from simulation.
• Score: 2.1702673021505245
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Accurate and efficient time-series forecasting remains a challenging problem for both classical and quantum neural architectures, particularly in multivariate environmental settings. This work adapts the Quantum Leaky Integrate-and-Fire (QLIF) spiking neural network for time-series regression tasks, specifically short-term multivariate weather forecasting. We extend QLIF beyond classification and demonstrate its applicability to continuous-valued prediction problems. The QLIF-CAST model encodes neuron excitation states as single-qubit quantum superpositions, driven by Rx rotation gates and T1 relaxation decay, and is embedded within a hybrid quantum-classical recurrent architecture. We conduct two distinct evaluations. First, a controlled comparison against a parameter-matched classical LIF baseline on a multivariate weather dataset shows that QLIF-CAST achieves 15.4% lower MSE and 4.4% lower MAE, demonstrating that quantum neuronal dynamics reduce prediction error over classical equivalents. Second, a cross-domain comparative analysis with state-of-the-art quantum LSTM (QLSTM) and quantum neural network (QNN) models on air quality and wind speed benchmarks reveals that QLIF-CAST converges in up to 94% less training time, occupying a distinct position in the speed-error trade-off space. Hardware verification on IBM Marrakesh (156-qubit QPU) confirms reliable circuit execution with only 1.2% average deviation from simulation.

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