Recovery of optical losses with the Petz recovery map

• URL: http://arxiv.org/abs/2511.05941v1
• Date: Sat, 08 Nov 2025 09:24:26 GMT
• Title: Recovery of optical losses with the Petz recovery map
• Authors: Jinyan Chen, Minjeong Song, Valerio Scarani,
• Abstract summary: We construct the Petz recovery of single mode losses and its implementations.<n>We show that the recovery performance of Petz recovery map is better than the recovery protocol that replaces the noisy state with the belief state.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Optical systems are a main platform for quantum information processing, while a hidden challenge in these systems is information loss due to scattering into unmonitored modes, typically modeled as state-independent beam-splitter interactions. While such losses simply erase information encoded across modes, they directly degrade information encoded in the quantum state of a mode. Perfect correction of these Gaussian lossy channels with Gaussian operations alone is known to be impossible. In this work, we investigate the Petz recovery map as an approximate recovery. We construct the Petz recovery of single mode losses and its implementations. In particular, we show that the recovery performance of Petz recovery map is better than the recovery protocol that replaces the noisy state with the belief state. Also, when the reference state is far from the true state, it is better not to use the Petz recovery map but to leave the noisy state instead. We discuss the physical intuition of Petz recovery map and finally shows that it is near-optimal among the considered recovery protocols.

Related papers

• Universal syndrome-based recovery for noise-adapted quantum error correction [0.9591164070876688]
  We propose an algorithmic approach to identifying error syndromes for arbitrary codes and noise processes.<n>We then use our algorithm to develop a variant of the Petz recovery map -- a syndrome-based Petz recovery map -- which can then be implemented via syndrome measurements.<n>We execute our recovery circuits on IBM quantum hardware to successfully demonstrate break-even performance of a noise-adapted QEC protocol.
  arXiv  Detail & Related papers  (2025-10-09T18:27:22Z)
• Realizing the Petz Recovery Map on an NMR Quantum Processor [0.0]
  We experimentally implement the Petz recovery map on a nuclear magnetic resonance (NMR) quantum processor using the duality quantum computing (DQC) algorithm.<n>Our results validate the feasibility of the Petz-based recovery map in current quantum platforms and highlight its relevance for near-term error mitigation strategies.
  arXiv  Detail & Related papers  (2025-08-12T15:07:20Z)
• APHQ-ViT: Post-Training Quantization with Average Perturbation Hessian Based Reconstruction for Vision Transformers [71.2294205496784]
  We propose textbfAPHQ-ViT, a novel PTQ approach based on importance estimation with Average Perturbation Hessian (APH)<n>We show that APHQ-ViT using linear quantizers outperforms existing PTQ methods by substantial margins in 3-bit and 4-bit across different vision tasks.
  arXiv  Detail & Related papers  (2025-04-03T11:48:56Z)
• A Memory-Based Reinforcement Learning Approach to Integrated Sensing and Communication [52.40430937325323]
  We consider a point-to-point integrated sensing and communication (ISAC) system, where a transmitter conveys a message to a receiver over a channel with memory.<n>We formulate the capacity-distortion tradeoff for the ISAC problem when sensing is performed in an online fashion.
  arXiv  Detail & Related papers  (2024-12-02T03:30:50Z)
• Petz map recovery for long-range entangled quantum many-body states [0.0]
  We study the infidelity of the rotated Petz map on several physically-relevant long-range entangled quantum states. Our result indicates that recovery fidelity of the Petz map is a useful diagnostic of quantum phases of matter.
  arXiv  Detail & Related papers  (2024-08-01T18:11:17Z)
• Noise-adapted recovery circuits for quantum error correction [1.8799303827638123]
  We present quantum circuits for a universal, noise-adapted recovery map, often referred to as the Petz map. We also present circuits that can directly estimate the fidelity between the encoded state and the recovered state. The efficacy of our noise-adapted recovery circuits is then demonstrated through ideal and noisy simulations.
  arXiv  Detail & Related papers  (2023-05-18T16:29:49Z)
• DifFace: Blind Face Restoration with Diffused Error Contraction [62.476329680424975]
  DifFace is capable of coping with unseen and complex degradations more gracefully without complicated loss designs. It is superior to current state-of-the-art methods, especially in cases with severe degradations.
  arXiv  Detail & Related papers  (2022-12-13T11:52:33Z)
• Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging [142.11622043078867]
  We propose a principled Degradation-Aware Unfolding Framework (DAUF) that estimates parameters from the compressed image and physical mask, and then uses these parameters to control each iteration. By plugging HST into DAUF, we establish the first Transformer-based deep unfolding method, Degradation-Aware Unfolding Half-Shuffle Transformer (DAUHST) for HSI reconstruction.
  arXiv  Detail & Related papers  (2022-05-20T11:37:44Z)
• Approximating Invertible Maps by Recovery Channels: Optimality and an Application to Non-Markovian Dynamics [68.8204255655161]
  We investigate the problem of reversing quantum dynamics, specifically via optimal Petz recovery maps. We focus on typical decoherence channels, such as dephasing, depolarizing and amplitude damping. We extend this idea to explore the use of recovery maps as an approximation of inverse maps, and apply it in the context of non-Markovian dynamics.
  arXiv  Detail & Related papers  (2021-11-04T16:16:45Z)
• Low to High Dimensional Modality Hallucination using Aggregated Fields of View [48.32515709424962]
  We argue modality hallucination as one effective way to ensure consistent modality availability. We present a novel hallucination architecture that aggregates information from multiple fields of view of the local neighborhood. We also conduct extensive classification and segmentation experiments on UWRGBD and NYUD datasets and demonstrate that hallucination allays the negative effects of the modality loss.
  arXiv  Detail & Related papers  (2020-07-13T03:13:48Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.