This review provides a deep anatomical dissection of the core concepts, methodological innovations, strengths, limitations, comparative positioning, and philosophical underpinnings of Roncallo et al. (2026). The paper extends an inherently binary quantum optical classifier—based on the Hong-Ou-Mandel (HOM) interference effect—into the multiclass (multinomial) domain via classical post-processing strategies without altering the quantum architecture. Particular emphasis is placed on preserving quantum advantage through logarithmic overhead, specifically by leveraging binary decision trees to maintain the superexponential speedup inherent in the underlying optical hardware. By decomposing complex multiclass problems into structured binary sub-tasks, the authors demonstrate a pragmatic pathway for scaling NISQ-era quantum photonics to real-world categorical data without the need for increased qubit counts or circuit depth. Mamun, SM (2026)………………………………..1 Divide et impera: An Anatomical Review of Hybrid Multinomial Classifiers Derived from Quantum Binary Models (Vol-I) Also available on Academia.edu: https://www.academia.edu/attachments/132475514/download_file?s=portfolio
This review provides a deep anatomical dissection of the core concepts, methodological innovations, strengths, limitations, comparative positioning, and philosophical underpinnings of Roncallo et al. (2026). The paper extends an inherently binary quantum optical classifier—based on the Hong-Ou-Mandel (HOM) interference effect—into the multiclass (multinomial) domain via classical post-processing strategies without altering the quantum architecture. Particular emphasis is placed on preserving quantum advantage through logarithmic overhead, specifically by leveraging binary decision trees to maintain the superexponential speedup inherent in the underlying optical hardware. By decomposing complex multiclass problems into structured binary sub-tasks, the authors demonstrate a pragmatic pathway for scaling NISQ-era quantum photonics to real-world categorical data without the need for increased qubit counts or circuit depth. Mamun, SM (2026)………………………………..1 Divide et impera: An Anatomical Review of Hybrid Multinomial Classifiers Derived from Quantum Binary Models (Vol-I) Also available on Academia.edu: https://www.academia.edu/attachments/132475514/download_file?s=portfolio
This fourth volume in the series extends the epistemological critique initiated by Jung et al. (2026) and the architectural syntheses of Volumes II and III by introducing parameterized quantum adversary models. The research formally extends security proofs for lattice-based primitives to account for realistic constraints on quantum adversaries: bounded T-depth, noisy quantum oracles, and noisy intermediate-scale quantum (NISQ) devices. The analysis demonstrates that these parameterizations provide strong support for the "transient bottleneck" thesis: under current and near-term Mamun, SM (2026) ……………………………………….1 Theoretical and Physical Boundaries of Lattice-Based Post-Quantum Cryptography: An Anatomical Critique of Parameterized Quantum Adversary Models (Vol-IV) physical limits (T-depth , oracle noise , NISQ-scale qubit counts), quantum-sample attacks such as the Grilo-Kerenidis-Zijlstra (GKZ) algorithm remain computationally and thermodynamically infeasible, validating hybrid and QRAM-hard designs. However, the report also rigorously critiques the thesis by identifying critical loopholes—future fault-tolerant scaling, oracle de-noising techniques, and hybrid classical-quantum lifting theorems—that could render parameterized security temporary. Furthermore, emerging classical machine learning extractors (e.g., SALSA) demonstrate that reliance on quantum hardware constraints may be sidestepped entirely. Also available on Academia.edu: https://www.academia.edu/attachments/132761422/download_file?s=portfolio
We investigate how to combine a collection of quantum binary models into a multinomial classifier. We employ a hybrid approach, adopting strategies like one-vs-one, one-vs-rest and a binary decision tree. We benchmark each method, by emphasizing their computational overhead and their impact on the quantum advantage. By comparison against a classical binary model (generalized using the same approach), we show that the decision tree represents a cost-effective solution, achieving similar accuracies to other methods with an overhead at most logarithmic in the total number of classes.
This seventh volume of the series establishes the first formal post-post-quantum taxonomy—a three-tier ontological and epistemological hierarchy that reclassifies all post-quantum cryptographic schemes according to the fundamental nature and justification of their security. The hierarchy progresses from computational (algorithmic hardness assumptions) through physical (thermodynamic, noise-engineered, and hardware-constrained irreversibility) to device-independent (information-theoretic guarantees independent of device implementation). Building directly upon the anatomical critiques, hybrid primitives (Vol II), QRAM-hardness (Vol III), parameterized adversary models (Vol IV), GKP-resistant countermeasures (Vol V), and NISQ empirical validation (Vol VI), we provide a complete reclassification of NIST PQC standards, hybrid protocols, and the novel primitives introduced across the series. Dedicated Mamun, SM (2026) ……………………………….1 Theoretical and Physical Boundaries of Lattice-Based Post-Quantum Cryptography: An Anatomical Critique of Post-Post-Quantum Taxonomy (Vol-VII) sections dissect the ontology (what security is) and epistemology (how security claims are known and justified) of each tier. K S C The taxonomy reveals that current lattice-based schemes remain anchored in the provisional computational tier, while the countermeasures developed in Vols III–VI elevate them into the physical tier. True device-independent security remains an aspirational frontier. Also available on Academia.edu: https://www.academia.edu/attachments/132771868/download_file?s=portfolio
The transition to post-quantum cryptography (PQC) based on the Learning with Errors (LWE) problem suffers from a critical epistemological gap: its security is predicated on transient computational bottlenecks, not information-theoretic permanence, making it vulnerable to mature quantum algorithms like Gottesman-Kitaev-Preskill (GKP) error correction. This critique argues that absolute quantum resilience requires a pivot to inherently hybrid architectures that systematically combine LWE's computational efficiency with the absolute, physics-bound security of Quantum Key Distribution (QKD) and Physical Random Oracles (PROs), such as Physical Unclonable Functions (PUFs). This volume details these hybrid primitives, addressing structural vulnerabilities in standard PQC and QKD. Key architectural syntheses include the Lattice PUF, which provably binds ML-modeling resistance to the LWE problem hardness using PAC theory, and Quantum-Locked Physical Mamun, SM (2026) …………………………………….1 Theoretical and Physical Boundaries of Lattice-Based Post-Quantum Cryptography: An Anatomical Critique of Hybrid Info-Theoretic and Computational Primitives (Vol-II) K S C Primitives (HLPUF, HEPUF), which utilize conjugate coding and entanglement to provide authentication guarantees independent of algorithmic hardness. Also available on Academia.edu: https://www.academia.edu/attachments/132761055/download_file?s=portfolio
Quantum-AI hybrid algorithms represent the most practical near-term pathway for leveraging quantum computing's probabilistic power alongside classical AI's scalability and optimization strengths. In the noisy intermediate-scale quantum (NISQ) era, these hybrids—primarily variational quantum algorithms (VQAs) such as the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA)—delegate hard subproblems (e.g., high-dimensional sampling, optimization under quantum constraints, or feature extraction in entangled spaces) to quantum processors while classical optimizers or neural networks handle parameter tuning, error mitigation, and large-scale data processing (Ferguson et al., 2026; Acampora, 2026). This exploration builds on the 2025 NSF AI+MPS community paper by integrating accelerated timelines: mass deployment of utility-scale quantum computing by August 2027 and AGI substantially before 2030. Hybrid approaches become critical enablers for MPS grand challenges in Mamun, SM (2026)…………………………………………1 Quantum-AI Hybrid Algorithms: Bridging Classical Intelligence, Quantum Acceleration, and Scientific Discovery in the MPS Domains (Vol-I) chemistry (molecular ground states), materials (inverse design), physics (many-body simulation), and astronomy (anomaly detection under uncertainty). Also available on Academia.edu: https://www.academia.edu/attachments/132469868/download_file?s=portfolio
This sixth volume of the anatomical critique systematically deconstructs the purely mathematical paradigm of lattice-based post-quantum cryptography (PQC), proposing that cryptographic security in the quantum era is fundamentally a thermodynamic property of information systems. The work validates this 'transient bottleneck thesis' through comprehensive empirical quantum simulations of Learning with Errors (LWE) extraction on 2026-era Mamun, SM (2026) ………………………………………….1 Theoretical and Physical Boundaries of Lattice-Based Post-Quantum Cryptography: An Anatomical Critique of Empirical Quantum Simulation on NISQ and Analog Devices (Vol-VI) K S C Noisy Intermediate-Scale Quantum (NISQ) gate-based processors (IBM, IonQ, Rigetti), neutral-atom analog platforms (QuEra), and photonic continuous-variable systems. Empirical results confirm that standard Gaussian LWE is protected against heuristic Variational Quantum Algorithm (VQA) attacks by the exponential thermodynamic overhead required for deep circuit transpilation and error mitigation. However, experiments on analog and photonic hardware physically prove the structural equivalence between LWE noise and continuous-variable displacement errors, confirming that Gottesman-Kitaev-Preskill (GKP) error correction can function as a physical decryption mechanism. Also available on Academia.edu: https://www.academia.edu/attachments/132771797/download_file?s=portfolio