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DTSTAMP:20260730T152640Z
LOCATION:Exhibit Hall
DTSTART;TZID=America/Los_Angeles:20260728T172400
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UID:dac_DAC 2026_sess306_WIP3203@linklings.com
SUMMARY:Late Breaking Results: A Resource-Constrained Co-Design Framework 
 for Enabling Heterogeneous Quantum Chiplet Ensembles via Circuit Cutting
DESCRIPTION:Alberto Marchisio (New York University Abu Dhabi (NYUAD)); Muh
 ammad Kashif (eBrain Lab, Division of Engineering, New York University (NY
 U) Abu Dhabi, UAE); Nouhaila Innan and Walid El Maouaki (New York Universi
 ty Abu Dhabi); and Muhammad Shafique (New York University Abu Dhabi (NYUAD
 ))\n\nNear-term (NISQ) quantum processors are limited in qubit count, conn
 ectivity, and coherence, which constrains the size of quantum neural netwo
 rks (QNNs) that can run monolithically on a single device. We propose a he
 terogeneous chiplet \emph{ensemble} architecture that targets a realistic 
 setting with access to many small devices but no coherent interconnect: we
  assign one chiplet per model and use intra-model circuit cutting to decom
 pose each logical QNN into resource-feasible subcircuits. Cross-chip quant
 um dependencies are replaced by classical stitching and ensemble aggregati
 on, converting device heterogeneity into predictive diversity while avoidi
 ng coherent inter-chip communication. We further develop a resource-constr
 ained co-design flow that jointly selects cut locations, chiplet/model ass
 ignment, and sampling budgets under qubit and noise constraints. Across MN
 IST, Fashion-MNIST, and Digits, our framework scales to larger logical mod
 els under strict per-device limits and yields consistent accuracy improvem
 ents (up to 3-8%) in both ideal simulation and noise-calibrated backends, 
 motivating new CAD-style challenges in partitioning, mapping, and sampling
 -aware cost modeling for quantum chiplet systems.\n\nTrack: Student\n\n
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