基于无序结构的计算光谱仪已成为满足集成光谱仪需求的有前景解决方案，提供高性能并提高对制造变化和温度波动的抵抗力。然而，当前的计算光谱仪由于依赖蛮力随机设计无序结构而变得不切实际，导致无法控制、不可复制且性能不佳。在这项研究中，我们通过引入一种创新的逆向设计方法彻底改变了现有范式。通过利用逆向设计的强大功能，我们成功地将其适用于优化由多个相关组件组成的复杂系统，这些组件具有复杂的光谱响应。该方法可应用于广泛的结构。我们通过实现一种基于干涉效应的新型无序结构的光谱仪验证了这一点，该结构表现出可忽略的损耗和高灵敏度。对于给定结构，我们的方法在光谱分辨率上提高了12倍，并将滤波器间的交叉相关性减少了四倍。最终的光谱仪展现了可靠和可复制的性能，能够精确确定结构参数。

Computational spectrometers utilizing disordered structures have emerged as promising solutions for meeting the imperative demand for integrated spectrometers, offering high performance and improved resilience to fabrication variations and temperature fluctuations. However, the current computational spectrometers are impractical because they rely on a brute-force random design approach for disordered structures. This leads to an uncontrollable, non-reproducible, and suboptimal spectrometer performance. In this study, we revolutionize the existing paradigm by introducing a novel inverse design approach for computational spectrometers. By harnessing the power of inverse design, which has traditionally been applied to optimize single devices with simple performance, we successfully adapted it to optimize a complex system comprising multiple correlated components with intricate spectral responses. This approach can be applied to a wide range of structures. We validated this by realizing a spectrometer utilizing a new type of disordered structure based on interferometric effects that exhibits negligible loss and high sensitivity. For a given structure, our approach yielded a remarkable 12-times improvement in the spectral resolution and a four-fold reduction in the cross-correlation between the filters. The resulting spectrometer demonstrated reliable and reproducible performance with the precise determination of structural parameters.