Mitigating Phase Error Accumulation in Programming MZI-Based Optical Processors
Bibliographic record
Abstract
The practical implementation of reconfigurable interferometric-based optical processors requires complicated and time-consuming calibration and programming schemes to address errors induced by fabrication process variations. Among the various prevalent mesh topologies, the presence of a diagonal path inherently provides independent access to calibrate, monitor, and program each phase shifter, regardless of any existing dynamic errors in the bias of other blocks. In other words, the phase error of MZIs do not accumulate along a diagonal path. This attribute of the diagonal path has been experimentally validated in a 4×4 Bokun mesh topology by introducing phase distortion in the previous Mach-Zehnder interferometer block along the same diagonal path. Measurements demonstrate that the same phase distortion in a mesh topology lacking this attribute can lead to accumulating calibration and programming errors. The Bokun mesh topology, with its inherent beneficial attributes, supports the realization of significantly superior performance in the case of on-chip weight optimization, referred to as in-situ programming, due to enabling an error-free, faster, and easier programming scheme.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".