Sigma Publishinq

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Quantum Software for Your Business We deliver quantum optimization solutions using QAOA: for Budgeting, Next Best Action, and Recommender Systems, leveraging Superposition and Entanglement with an increase in target metrics by 10-30% Sigma PublishinQ’s hyper-innovative QAOA approaches: 🔹Full complex-valued computation: complex numbers for all components enable precise quantum state modeling, enhancing superposition and entanglement, unlike real-valued QOKit implementations. 🔹Non-diagonal cost Hamiltonians: non-diagonal terms boost entanglement, offering a novel approach absent in standard QAOA. 🔹Probabilistic superposition: powerful frequency regularization and optimization of probability distributions. 🔹MLMVN optimization: multilayer multivalued neural networks analytically optimize QAOA parameters, minimizing local minima and outperforming traditional gradient descent. 🔹High adaptability through TaskEvaluator: dynamic selection of methods (non-diagonal cost Hamiltonian, probabilistic superposition, robust optimization, quantum walks) based on metrics like energy and stability, adding a unique intelligent layer to QAOA. We implement QAOA, ADAPT-QAOA, bDA-QAOA, and DQAOA for tasks like optimization of functionals on discrete structures in Hilbert spaces with combinatorial and spectral constraints, for tasks of finding extrema and minimizing energy in high-dimensional spaces with discrete topology and functional measures. Quantum Reinforcement Learning (QRL) for DeepTech: we create Qiskit-based PoC projects and Solution Showcases, demonstrating quantum solutions for your investors. Our prototypes optimize quantum materials like graphene and NV centers, achieving exponential speedup (O(log(n)) vs. O(2^n)). Using QRL and QFT, we enable adaptive control of quantum systems, such as graphene spectroscopy. Quantum Prototypes - for your investors and clients. Quantum Optimization - for your business processes.
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