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Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Product-Congruence Games: A Unified Impartial-Game Framew...
Satyam Tyagi · 2025-07-27 · via cs.IT updates on arXiv.org

RSA exponent reduction and AES S-box inversion share a hidden commonality: both are governed by the same impartial combinatorial principle, which we call a Product-Congruence Game (PCG). A Product-Congruence Game tracks play via the modular or finite-field product of heap values, providing a single invariant that unifies the algebraic cores of these two ubiquitous symmetric and asymmetric cryptosystems. We instantiate this framework with two companion games. First, $φ$-MuM, in which a left-associated "multi-secret" RSA exponent chain compresses into the game of Multiplicative Modular Nim, PCG($k,\{1\}$), where $k = ord_N(g)$. The losing predicate then factorizes via the Chinese remainder theorem, mirroring RSA's structure. Second, poly-MuM, our model for finite-field inversion such as the AES S-box. For poly-MuM we prove the single-hole property inside its threshold region, implying that the Sprague-Grundy values are multiplicative under disjunctive sums in that region. Beyond these instances, we establish four structural theorems for a general Product-Congruence Game PCG($m,R$): (i) single-heap repair above the modulus, (ii) ultimate period $m$ per coordinate, (iii) exact and asymptotic losing densities, and (iv) confinement of optimal play to a finite indeterminacy region. An operation-alignment collapse principle explains why some variants degenerate to a single aggregate while MuM, $φ$-MuM and poly-MuM retain rich local structure. All ingredients (multiplicative orders, the Chinese remainder theorem, finite fields) are classical; the contribution is the unified aggregation-compression viewpoint that embeds both RSA and AES inside one impartial-game framework, together with the structural and collapse theorems.