Nanostructured surfaces with quasi-random geometries can manipulate light over broadband wavelengths and wide ranges of angles. Optimization and realization of stochastic patterns have typically relied on serial, direct-write fabrication methods combined with real-space design. However, this approach is not suitable for customizable features or scalable nanomanufacturing. Moreover, trial-and-error processing cannot guarantee fabrication feasibility because processing-structure relations are not included in conventional designs. Here, we report wrinkle lithography integrated with concurrent design to produce quasi-random nanostructures in amorphous silicon at wafer scales that achieved over 160% light absorption enhancement from 800 to 1,200 nm. The quasi-periodicity of patterns, materials filling ratio, and feature depths could be independently controlled. We statistically represented the quasi-random patterns by Fourier spectral density functions (SDFs) that could bridge the processing-structure and structure-performance relations. Iterative search of the optimal structure via the SDF representation enabled concurrent design of nanostructures and processing.wrinkles | light trapping | silicon photonics | spectral density function | pattern transfer Q uasi-random structures with neither periodic nor fully disordered geometries are useful in the design of superhydrophobic substrates (1, 2), stretchable electronics (3-6), and sensors (7,8). In particular, these nanostructured systems support rich Fourier spectra that enable light manipulation over broadband wavelengths and over wide collection angles (9, 10). Independent control over the relative degree of order vs. disorder, materials filling ratio, and feature size is critical to generate patterns with a diverse range of optical responses (11). For example, quasi-random nanostructures in photonic materials such as amorphous silicon (a-Si) are being increasingly used in photovoltaics and light-emitting diodes (9, 12-18). To enhance device performance from the patterns, optimization of nanoscale structure is crucial. However, most efforts to control quasirandom patterns have relied on serial processes such as electron-beam lithography (9,12,16,18,19). Although such approaches enable precise pattern placement and maximum control over the nanostructured features, the tools are not scalable and are cost prohibitive for large-area fabrication (>1 cm 2 ). Furthermore, most work has focused on the traditional, sequential strategy for pattern generation: (i) design nanostructures in real space for a target performance and then (ii) fabricate structures by trial-and-error processing optimization (9, 20). Without considering the fabrication conditions as part of the overall design strategy, however, conventional methods cannot ensure manufacturing feasibility of the optimized nanostructures. Trial-and-error experiments to achieve optimal designs are usually time-consuming. Hence, development of a concurrent design approach can establish the phase space of target quasi-rand...