• Corpus ID: 252596132

Quantum neuromorphic approach to efficient sensing of gravity-induced entanglement

@inproceedings{Krisnanda2022QuantumNA,
  title={Quantum neuromorphic approach to efficient sensing of gravity-induced entanglement},
  author={Tanjung Krisnanda and Tomasz Paterek and Mauro Paternostro and Timothy C. H. Liew},
  year={2022}
}

• T. Krisnanda, T. Paterek, +1 author T. Liew
• Published 29 September 2022
• Physics

The detection of entanglement provides a definitive proof of quantumness. Its ascertainment might be challenging for hot or macroscopic objects, where entanglement is typically weak, but nevertheless present. Here we propose a platform for measuring entanglement by connecting the objects of interest to an uncontrolled quantum network, whose emission (readout) is trained to learn and sense the entanglement of the former. First, we demonstrate the platform and its features with generic quantum systems. As the network effectively learns to recognise quantum states, it is possible to sense the amount of entanglement after training with only non-entangled states. Furthermore, by taking into account measurement errors, we demonstrate entanglement sensing with precision that scales beyond the standard quantum limit and outperforms measurements performed directly on the objects. Finally, we utilise our platform for sensing gravity-induced entanglement between two masses and predict an improvement of two orders of magnitude in the precision of entanglement estimation compared to existing techniques. K n , 2 P } ∈ [1 , 2]Γ. As the readout, we take the mean excitation of the QN node (cid:104) ˆ b † ˆ b (cid:105) with time-multiplexing at T different times, i.e., τ = { 1 , 2 , · · · , T } π/ 10Γ. We tested this architecture for 10 different realisations of the parameters, where in each we performed training with N tr = 50 and testing with N te = 100. Our simulations show a transition to low entanglement estimation error ∆ E ∼ 10 − 8 for T ≥ 15. Again, this is because it requires at least 15 different parameters to characterise two-qubit input states.