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Updated: May 28, 2026
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Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source
Published on: April 4, 2017
Evaluating Photonic Quantum Memristors in Noisy Environments
Jiachao Wang1,2, Wentao Mao1,2, Tengze Yang1,2
1School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China.
Entropy (Basel, Switzerland)
|May 26, 2026
Summary
Photon loss significantly degrades photonic quantum memristor (PQM) performance, impacting individual device dynamics and network-level neuromorphic computing tasks like time-series prediction. Loss-tolerant architectures are crucial for PQM deployment.
Area of Science:
- Quantum Computing
- Neuromorphic Engineering
- Photonics
Background:
- Photonic quantum memristors (PQMs) are promising for neuromorphic computing.
- Hardware noise, especially photon loss and phase fluctuations, limits PQM performance.
Purpose of the Study:
- To systematically investigate the impact of photon loss and phase fluctuations on PQM dynamics.
- To evaluate the system-level implications of photon loss in a PQM network for time-series prediction.
Main Methods:
- Employed the noisy gates approach to integrate dissipative effects into PQM evolution.
- Analyzed individual PQM hysteresis loops and simulated a two-PQM network for NARMA2 prediction.
Main Results:
- Photon loss deforms PQM hysteresis loops and degrades non-Markovian memory effects.
- Network prediction error (NMSE) increased from 0.0448 to 0.3056 with photon loss probabilities up to 0.5.
- Increased integration time did not mitigate, but worsened, errors at high photon loss.
Conclusions:
- Photon loss impairs both individual PQM dynamics and network-level processing capabilities.
- Highlights the critical need for developing loss-tolerant architectures for practical PQM applications.
