Research Archive.

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The Science Behind the Platforms.

Before Fijishi’s moonshots became operational systems, they were rigorous theoretical models and experiments. Our peer-reviewed papers serve as the intellectual backbone of the sovereign stack — guiding how we build RIS-driven networks, quantum-secure PETs, self-evolving AI, and scientific discovery engines.

Highlights from Our Research.

Adaptive Quantum-Resilient Equivariant Homomorphic Computation (AQREHC)

Focus: Achieving scalable, post-quantum privacy with equivariant noise-adaptive re-encryption.

Federated Neuromorphic Acceleration for Secure Homomorphic Attribute Matching (HABC)

Focus: Neuromorphic co-processors that federate homomorphic tasks, reducing compute overhead by 90% in multi-party contexts.

Neuromorphic RIS for Autonomous 6G Environments

Focus: Spiking-field-controlled RIS that self-optimize electromagnetic propagation for cognitive network fabrics.

Noise-Adaptive Re-Encryption: A Paradigm Shift in Privacy-Preserving AI Execution

Focus: Defining entropic transformation layers to maintain rare data patterns under rigorous PET constraints.

Why This Archive Matters.

▸ Not marketing claims: Every platform we deploy traces back to published mathematical and experimental foundations.

▸ Cross-disciplinary proofs: Quantum optics, photonic AI, RIS control, privacy architectures, all under sovereign-first models.

▸ Driving standards: Our research informs global consortia, government policies, and next-generation compliance frameworks.