Wide-angle spectral filter for energy-saving windows designed by quantum annealing-enhanced active learning

Multi-band spectral filters that can transmit visible light but block UV and infrared light in the solar spectrum are applicable to energy-saving windows. However, such filters are usually designed to consider normal incident light only. Here, we report photonic structures allowing selective solar spectrum transmission in wide angles using a quantum-computing-enhanced active learning scheme, which includes machine learning, quantum annealing, and wave-optics simulation in an iterative loop. We experimentally demonstrate the optical characteristics of the photonic structure and its capability to reduce the temperature rise in an enclosure when combined with a thermal radiation layer (temperature reduction of 5.4°C–7.2°C and annual energy saving of ∼97.5 MJ/m2). This structure can be incorporated into existing windows in buildings or automobiles to reduce cooling energy consumption, and the active learning scheme can be applied to design materials with complex properties in general.