quantum noise
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SNS V11.28: Quantum Noise in Spiking Neural Networks
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The SNS V11.28 introduces a novel approach to computation by leveraging physical entropy, including thermal noise and quantum effects, as a computational feature rather than a limitation. This architecture utilizes memristors for analog in-memory computing and quantum dot single-electron transistors to inject true randomness into the learning process, validated by the NIST SP 800-22 Suite. Instead of traditional backpropagation, it employs biologically plausible learning rules such as active inference and e-prop, aiming to operate at the edge of chaos for maximum information transmission. The architecture targets significantly lower energy consumption compared to GPUs, with aggressive efficiency goals, though it's currently in the simulation phase with no hardware yet available. This matters because it presents a potential path to more energy-efficient and scalable neural network architectures by harnessing the inherent randomness of quantum processes.
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Advanced Quantum Simulation with cuQuantum SDK v25.11
Read Full Article: Advanced Quantum Simulation with cuQuantum SDK v25.11
Simulating large-scale quantum computers is increasingly challenging as quantum processing units (QPUs) improve, necessitating advanced techniques to validate results and generate datasets for AI models. The cuQuantum SDK v25.11 introduces new components to accelerate workloads like Pauli propagation and stabilizer simulations using NVIDIA GPUs, crucial for simulating quantum circuits and managing quantum noise. Pauli propagation efficiently simulates observables in large-scale circuits by dynamically discarding insignificant terms, while stabilizer simulations leverage the Gottesman-Knill theorem for efficient classical simulation of Clifford group gates. These advancements are vital for quantum error correction, verification, and algorithm engineering, offering significant speedups over traditional CPU-based methods. Why this matters: Enhancing quantum simulation capabilities is essential for advancing quantum computing technologies and ensuring reliable, scalable quantum systems.