Gepubliceerd op dinsdag 20 januari om 17:34

**Abstract:** This paper presents a novel design framework for hyper-efficient quantum heat engines leveraging tensor network optimization (TNO) and Bayesian calibration techniques within the interdisciplinary domain of quantum information and thermodynamics. Our approach, termed the Tensor-Network-Engine (TNE), dynamically optimizes engine configurations by iteratively refining a parameterized tensor network representation of the quantum system's Hamiltonian, achieving significantly enhanced work extraction compared to traditional designs while minimizing thermodynamic inefficiencies.

Nieuwe TNO-studie: Prijsschok fossiele energie tachtig procent kleiner bij een duurzaam energiesysteem. Als Nederland overschakelt op duurzame energie stijgen de energiekosten tachtig procent minder b...

Quobly and TNO have formed a collaboration to advance industrial-scale silicon quantum hardware by combining CMOS-compatible quantum chips with advanced materials and cryogenic characterization expertise. The partnership focuses on understanding how materials and defects affect qubit performance to enable faster...

Quobly (Grenoble, France) and TNO (Delft, Netherlands) have announced a research collaboration focused on accelerating the industrialization of silicon-based quantum computing. The partnership aims to bridge the gap between device engineering and materials

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