Despite the great progress in photonics over the past few decades, we are nowhere near the level of integration and complexity in photonic systems that would be comparable to those of electronic circuits, which prevents the use of photonics in many applications. This lag in integration scale is largely a result of how we traditionally design photonics: by combining building blocks from a limited library of known designs and manually tuning a few parameters. Unfortunately, the resulting photonic circuits are very sensitive to errors in manufacturing and to environmental instabilities, bulky, and often inefficient. The departure from this old-fashioned approach can lead to optimal photonic designs that are much better than state of the art on many metrics (smaller, more efficient, more robust). Such a departure is enabled by development of inverse design approach which efficiently searches through all possible combinations of realistic parameters and geometries for photonics using a combination of fast electromagnetic solvers and optimization algorithms. 

The inverse design approach can also enable new functionalities for photonics, including compact particle accelerators on chip which are 10000 times smaller than traditional accelerators, chip-to-chip and on-chip optical interconnects with error free communication rates exceeding terabit per second, and scaling of quantum systems (beyond present modest scale demonstrations, such as 3 node quantum networks and two dozens of maximally entangled qubits). In particular, platforms based on color centers in wide band gap semiconductors such as diamond and silicon carbide would be suitable for implementing scalable quantum systems, based on excellent spin quantum memories with direct photonic interfaces, the possibility to perform high speed and high fidelity quantum gates on spin qubits, combined with expertise in scaling semiconductor circuits. However, there are outstanding challenges, including color centers integration into optical structures while preserving their coherence and homogeneity, their spectral and spatial control, and implementation of efficient connections between spin qubits. Novel computational techniques such as photonics inverse design, along with new nanofabrication approaches, play a crucial role in addressing these challenges.