{"ID":6267152,"CreatedAt":"2026-07-10T01:11:38.759438437Z","UpdatedAt":"2026-07-13T01:02:08.706470581Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.08360","arxiv_id":"2607.08360","title":"Inverse-designed meta processing units for multi-task near-field photonic computing","abstract":"Integrated photonic neural networks require optical operators that are simultaneously compact, matrix-general and compatible with task-level reconfigurability. Here we introduce a meta processing unit (MPU), an inverse-designed near-field photonic device that implements local complex matrix transformations within a shallow-etched silicon region. Each 2x2 operator occupies 9.6 umx4.8 um and is designed as a reusable passive matrix primitive that can be combined with reconfigurable MZI neurons. We demonstrate a 3-bit quantized MZI-equivalent unitary device library with an effective reconstruction precision of 3.32 bits. Beyond unitary operators, we validate arbitrary complex 2x2 matrix fitting and a cascaded 4x4 matrix operation with 92.7% fidelity. We further integrate the MPU with active photonic components and hardware-in-the-loop training, achieving test accuracies of 83.5% and 80.9% on dual-task vowel recognition. In large-scale EMNIST simulations, a fine-grained neuron-level MPU replacement strategy reaches 87.64% average accuracy at 90% shared-MPU replacement, outperforming a layer-level baseline by 7.26 percentage points. These results establish inverse-designed MPUs as compact passive matrix operators for heterogeneous, hardware-adaptive photonic neural networks.","short_abstract":"Integrated photonic neural networks require optical operators that are simultaneously compact, matrix-general and compatible with task-level reconfigurability. Here we introduce a meta processing unit (MPU), an inverse-designed near-field photonic device that implements local complex matrix transformations within a sha...","url_abs":"https://arxiv.org/abs/2607.08360","url_pdf":"https://arxiv.org/pdf/2607.08360v1","authors":"[\"Chu Wu\",\"Zeyu Cai\",\"Songtao Yang\",\"Ruoyu Shen\",\"Yinan Zhao\",\"Haiou Zhang\",\"Wei Chu\",\"Xing Lin\"]","published":"2026-07-09T11:20:00Z","proceeding":"physics.optics","tasks":"[\"physics.optics\",\"eess.SP\"]","methods":"[]","has_code":false}