Selected work

Representative Papers

A Mathematical Framework for Reading the Autopsias' Meta - Compositional System

Jul 30, 2026

This study addresses the limited readability of dynamic music notation systems—such as Autopsias—which hinders effective communication between composers and performers. For the first time, it systematically introduces mathematical tools from topology to construct an analytical framework grounded in topological concepts, elucidating the transformation mechanism from static scores to dynamically computed reconstructions. Integrating pitch-class set theory, algorithmic reconstruction, and models of performative behavior, the work proposes an extended set of orthographic rules that go beyond traditional notation. The findings demonstrate that this mathematical approach effectively reveals the informational structure inherent in dynamic scores, thereby enhancing their readability and practical utility in human–computer collaborative performance, and laying a theoretical foundation for future developments in dynamic musical notation.

0 citationsRead paper

Revising price coordination in the classical and neoclassical economics based on elementary cellular automata

Jun 29, 2026

This study addresses the lack of a clear and predictable account of market price coordination in both classical and neoclassical economics. It introduces elementary cellular automata into economic modeling for the first time, employing Shannon entropy for exploratory analysis and assessing statistical significance through Monte Carlo simulations based on Spearman’s rank correlation coefficient. The framework systematically compares the dynamic performance of the two theoretical paradigms in generating coordinated price outcomes. Findings indicate that classical economics, by emphasizing rational interactions grounded in objective data, consistently produces stable coordination patterns, whereas the neoclassical approach, lacking a concrete coordination mechanism, tends to yield unstable results. This work thus offers a novel computational perspective and theoretical insight into the mechanisms underlying price formation.

0 citationsRead paper

On the Limits of Causal Observation in Shared-Memory Systems

Jun 12, 2026

This study addresses the problem of reliably observing causal order in shared-memory concurrent systems (COP), formalizing its observability limits and proving that strong consistency—defined as both completeness and reliability—is generally unattainable. The key insight is that the placement of monitoring instrumentation, rather than the choice of timestamp mechanism, fundamentally determines observability guarantees. To this end, the work proposes three non-blocking monitor implementations: FAInc (a centralized atomic counter), Striped (a decentralized counter), and Collect (an iterative register snapshot). Theoretically, all three provide equivalent COP guarantees. Experimental evaluation on a 64-core NUMA architecture demonstrates that Striped achieves throughput comparable to Collect while maintaining linearizability and substantially alleviating the cache contention bottleneck inherent in FAInc.

0 citationsRead paper

A Family of Quaternion-Valued Differential Evolution Algorithms for Numerical Function Optimization

May 12, 2026

This study addresses the slow convergence and performance limitations of conventional real-valued differential evolution (DE) algorithms in continuous optimization, as well as the underexplored potential of alternative number systems in intelligent optimization. The work proposes a novel family of quaternion-based differential evolution algorithms (QDE), which operate directly in quaternion space by integrating quaternion algebra into the DE framework for the first time. Several new mutation strategies are designed to leverage both the algebraic and geometric properties of quaternions. Evaluated on the BBOB benchmark suite, QDE variants demonstrate significant improvements over traditional real-valued DE in both convergence speed and solution accuracy, thereby expanding the mathematical foundations and application scope of bio-inspired optimization algorithms.

0 citationsRead paper

Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement

Apr 29, 2026

This work addresses the slow convergence of traditional self-consistent field (SCF) calculations caused by poor initial guesses. The authors propose an end-to-end approach based on the equivariant PhiSNet architecture that directly predicts the one-electron reduced density matrix (1-RDM) in an atomic orbital basis from molecular geometry. Physical constraints—such as electron number conservation and generalized idempotency—are enforced through a lightweight analytical module, enabling the simultaneous generation of high-quality SCF initial guesses, total energies, and Hellmann–Feynman forces without explicit force supervision. Evaluated on six closed-shell molecules, the method reduces SCF iteration counts by 49%–81%, substantially accelerating convergence while maintaining high accuracy.

0 citationsRead paper

Recent publications

Latest Papers

A Mathematical Framework for Reading the Autopsias' Meta - Compositional System

Jul 30, 2026

This study addresses the limited readability of dynamic music notation systems—such as Autopsias—which hinders effective communication between composers and performers. For the first time, it systematically introduces mathematical tools from topology to construct an analytical framework grounded in topological concepts, elucidating the transformation mechanism from static scores to dynamically computed reconstructions. Integrating pitch-class set theory, algorithmic reconstruction, and models of performative behavior, the work proposes an extended set of orthographic rules that go beyond traditional notation. The findings demonstrate that this mathematical approach effectively reveals the informational structure inherent in dynamic scores, thereby enhancing their readability and practical utility in human–computer collaborative performance, and laying a theoretical foundation for future developments in dynamic musical notation.

0 citationsRead paper

Revising price coordination in the classical and neoclassical economics based on elementary cellular automata

Jun 29, 2026

This study addresses the lack of a clear and predictable account of market price coordination in both classical and neoclassical economics. It introduces elementary cellular automata into economic modeling for the first time, employing Shannon entropy for exploratory analysis and assessing statistical significance through Monte Carlo simulations based on Spearman’s rank correlation coefficient. The framework systematically compares the dynamic performance of the two theoretical paradigms in generating coordinated price outcomes. Findings indicate that classical economics, by emphasizing rational interactions grounded in objective data, consistently produces stable coordination patterns, whereas the neoclassical approach, lacking a concrete coordination mechanism, tends to yield unstable results. This work thus offers a novel computational perspective and theoretical insight into the mechanisms underlying price formation.

0 citationsRead paper

On the Limits of Causal Observation in Shared-Memory Systems

Jun 12, 2026

This study addresses the problem of reliably observing causal order in shared-memory concurrent systems (COP), formalizing its observability limits and proving that strong consistency—defined as both completeness and reliability—is generally unattainable. The key insight is that the placement of monitoring instrumentation, rather than the choice of timestamp mechanism, fundamentally determines observability guarantees. To this end, the work proposes three non-blocking monitor implementations: FAInc (a centralized atomic counter), Striped (a decentralized counter), and Collect (an iterative register snapshot). Theoretically, all three provide equivalent COP guarantees. Experimental evaluation on a 64-core NUMA architecture demonstrates that Striped achieves throughput comparable to Collect while maintaining linearizability and substantially alleviating the cache contention bottleneck inherent in FAInc.

0 citationsRead paper

A Family of Quaternion-Valued Differential Evolution Algorithms for Numerical Function Optimization

May 12, 2026

This study addresses the slow convergence and performance limitations of conventional real-valued differential evolution (DE) algorithms in continuous optimization, as well as the underexplored potential of alternative number systems in intelligent optimization. The work proposes a novel family of quaternion-based differential evolution algorithms (QDE), which operate directly in quaternion space by integrating quaternion algebra into the DE framework for the first time. Several new mutation strategies are designed to leverage both the algebraic and geometric properties of quaternions. Evaluated on the BBOB benchmark suite, QDE variants demonstrate significant improvements over traditional real-valued DE in both convergence speed and solution accuracy, thereby expanding the mathematical foundations and application scope of bio-inspired optimization algorithms.

0 citationsRead paper

Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement

Apr 29, 2026

This work addresses the slow convergence of traditional self-consistent field (SCF) calculations caused by poor initial guesses. The authors propose an end-to-end approach based on the equivariant PhiSNet architecture that directly predicts the one-electron reduced density matrix (1-RDM) in an atomic orbital basis from molecular geometry. Physical constraints—such as electron number conservation and generalized idempotency—are enforced through a lightweight analytical module, enabling the simultaneous generation of high-quality SCF initial guesses, total energies, and Hellmann–Feynman forces without explicit force supervision. Evaluated on six closed-shell molecules, the method reduces SCF iteration counts by 49%–81%, substantially accelerating convergence while maintaining high accuracy.

0 citationsRead paper