Pasqal Holding SAS has published application-level hardware research comparing the performance of logical and physical qubits executing a machine learning algorithm. Conducted in collaboration with the Université Paris-Saclay and the Institut d’Optique, the benchmark evaluated a quantum kernel-based differential equation solver. The experiment represents a transition for neutral-atom hardware from executing isolated code subroutines to processing end-to-end applications on an error-detecting architecture. The publication follows the company’s disclosure of a definitive business combination agreement to list on the public markets via a merger with Bleichroeder Acquisition Corp. II (Nasdaq: BBCQ). Technical Architecture & Specifications / Operational Implementation The computation was executed [...]

Kipu Quantum has released an off-line Digitized Quantum Feature Extraction (DQFE) pipeline that allows quantum-enhanced machine learning models to execute inference operations…

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A neutral-atom quantum processor outperformed conventional physical-qubit approaches when solving differential equations on real hardware.

Pasqal Holding SAS has published application-level hardware research comparing the performance of logical and physical qubits executing a machine learning algorithm. Conducted in…