Bounding quantum uncommon information with quantum neural estimators
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915603466420224 |
|---|---|
| author | Ji, Donghwa Lee, Junseo Shin, Myeongjin Sohn, IlKwon Jeong, Kabgyun |
| author_facet | Ji, Donghwa Lee, Junseo Shin, Myeongjin Sohn, IlKwon Jeong, Kabgyun |
| contents | In classical information theory, uncommon information refers to the amount of information that is not shared between two messages, and it admits an operational interpretation as the minimum communication cost required to exchange the messages. Extending this notion to the quantum setting, quantum uncommon information is defined as the amount of quantum information necessary to exchange two quantum states. While the value of uncommon information can be computed exactly in the classical case, no direct method is currently known for calculating its quantum analogue. Prior work has primarily focused on deriving upper and lower bounds for quantum uncommon information. In this work, we propose a new approach for estimating these bounds by utilizing the quantum Donsker-Varadhan representation and implementing a gradient-based optimization method. Our results suggest a pathway toward efficient approximation of quantum uncommon information using variational techniques grounded in quantum neural architectures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_06091 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Bounding quantum uncommon information with quantum neural estimators Ji, Donghwa Lee, Junseo Shin, Myeongjin Sohn, IlKwon Jeong, Kabgyun Quantum Physics Information Theory In classical information theory, uncommon information refers to the amount of information that is not shared between two messages, and it admits an operational interpretation as the minimum communication cost required to exchange the messages. Extending this notion to the quantum setting, quantum uncommon information is defined as the amount of quantum information necessary to exchange two quantum states. While the value of uncommon information can be computed exactly in the classical case, no direct method is currently known for calculating its quantum analogue. Prior work has primarily focused on deriving upper and lower bounds for quantum uncommon information. In this work, we propose a new approach for estimating these bounds by utilizing the quantum Donsker-Varadhan representation and implementing a gradient-based optimization method. Our results suggest a pathway toward efficient approximation of quantum uncommon information using variational techniques grounded in quantum neural architectures. |
| title | Bounding quantum uncommon information with quantum neural estimators |
| topic | Quantum Physics Information Theory |
| url | https://arxiv.org/abs/2507.06091 |