Dynex remains at the forefront of innovation, dedicating itself to continuous research in the dynamic realm of n.quantum computing. Our commitment to pushing the boundaries of knowledge and technology is exemplified through ongoing exploration and experimentation. We take pride in contributing to the academic discourse by publishing cutting-edge research in esteemed scientific papers. This commitment not only underscores our passion for advancing the field of neuromorphic computing but also reflects our steadfast dedication to sharing insights and discoveries with the global scientific community. As we delve deeper into the complexities of neuromorphic computing, our aim is to pave the way for transformative breakthroughs that will shape the future of computing technology.
> Computing a Quantum Volume of 2^119 Using the Dynex Neuromorphic Quantum Computing Platform; Samer Rahmeh, Head of Quantum Solutions Architecture, Dynex; Adam Neumann, Dynex Developers; 124276903; Academia.edu; 2024
> Patent: Method and System for Large-Scale Computation of Quantum Algorithms; WIPO; International Application Number PCT/IB2024/059272; 24 Sep 2024; Abstract (EN): Current quantum computing technology, while promising, faces significant challenges that limit its scalability and practical application. These challenges primarily stem from the limited number of qubits available, the high susceptibility of qubits to errors, and the complexity of error correction protocols necessary to maintain coherence in quantum states. As quantum systems grow in size, the need for sophisticated error correction becomes increasingly critical, further complicating the development of reliable quantum computers. The invention described enables efficient, large-scale computation of quantum algorithms and circuits on traditional hardware, without sacrificing the fidelity or capabilities of quantum mechanics-based systems, thus bridging the gap between classical and quantum computing paradigms.
> Advancements in Unsupervised Learning: Mode-Assisted Quantum Restricted Boltzmann Machines Leveraging Neuromorphic Computing on the Dynex Platform; Adam Neumann, Dynex Developers; International Journal of Bioinformatics & Intelligent Computing. 2024; Volume 3(1):91- 103, ISSN 2816-8089
> Quantum Frontiers on Dynex: Elevating Deep Restricted Boltzmann Machines with Quantum Mode-Assisted Training; Adam Neumann, Dynex Developers; 116660843, Academia.edu; 2024
> HUBO & QUBO and Prime Factorization; Samer Rahmeh, Cali Technology Solutions, Dynex Developers; International Journal of Bioinformatics & Intelligent Computing. 2024; Volume 3(1):45-69, ISSN 2816-8089
> Framework for Solving Harrow-Hassidim-Lloyd Problems with Neuromorphic Computing using the Dynex Cloud Computing Platform; Samer Rahmeh, Cali Technology Solutions, Dynex Developers; 112871175; Academia.edu; 2023
> Neuromorphic Computing for Computer Scientists: A complete guide to Neuromorphic Computing on the Dynex Neuromorphic Cloud Computing Platform; Dynex Developers; Amazon; 2024; ISBN-13: 979-8874282196
> 计算机科学家的神经形态计算：在Dynex神经形态云计算平台上的神经形态计算完全指南, Dynex Developers; Amazon; 2024; ASIN: B0CSBPR9WL
> Patent: Distributed Neuromorphic Supercomputing Platform (分布式神经形态超级计算平台), Publication Number CN116384458A, Publication Date 2023.07.04, China National Intellectual Property Administration