https://arxiv.org/abs/2506.14272

Skip to main content
Cornell University
We gratefully acknowledge support from the Simons Foundation, member
institutions, and all contributors. Donate
 
arxiv logo > physics > arXiv:2506.14272
[                    ]

Help | Advanced Search

[All fields        ]
Search
arXiv logo
Cornell University Logo
[                    ] GO
quick links

  * Login
  * Help Pages
  * About

Physics > Optics

arXiv:2506.14272 (physics)
[Submitted on 17 Jun 2025]

Title:GHz spiking neuromorphic photonic chip with in-situ training

Authors:Jinlong Xiang, Xinyuan Fang, Jie Xiao, Youlve Chen, An He,
Yaotian Zhao, Zhenyu Zhao, Yikai Su, Min Gu, Xuhan Guo
View a PDF of the paper titled GHz spiking neuromorphic photonic chip
with in-situ training, by Jinlong Xiang and 9 other authors
View PDF

    Abstract:Neuromorphic photonic computing represents a paradigm
    shift for next-generation machine intelligence, yet critical gaps
    persist in emulating the brain's event-driven, asynchronous
    dynamics,a fundamental barrier to unlocking its full potential.
    Here, we report a milestone advancement of a photonic spiking
    neural network (PSNN) chip, the first to achieve full-stack
    brain-inspired computing on a complementary metal oxide
    semiconductor-compatible silicon platform. The PSNN features
    transformative innovations of gigahertz-scale nonlinear spiking
    dynamics,in situ learning capacity with supervised synaptic
    plasticity, and informative event representations with
    retina-inspired spike encoding, resolving the long-standing
    challenges in spatiotemporal data integration and
    energy-efficient dynamic processing. By leveraging its
    frame-free, event-driven working manner,the neuromorphic
    optoelectronic system achieves 80% accuracy on the KTH video
    recognition dataset while operating at ~100x faster processing
    speeds than conventional frame-based approaches. This work
    represents a leap for neuromorphic computing in a scalable
    photonic platform with low latency and high throughput, paving
    the way for advanced applications in real-time dynamic vision
    processing and adaptive decision-making, such as autonomous
    vehicles and robotic navigation.

Comments: 18 pages, 4 figures
Subjects: Optics (physics.optics)
Cite as:  arXiv:2506.14272 [physics.optics]
          (or arXiv:2506.14272v1 [physics.optics] for this version)
          https://doi.org/10.48550/arXiv.2506.14272
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Xuhan Guo [view email]
[v1] Tue, 17 Jun 2025 07:37:25 UTC (4,396 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled GHz spiking neuromorphic photonic
    chip with in-situ training, by Jinlong Xiang and 9 other authors
  * View PDF
  * Other Formats

license icon view license
Current browse context:
physics.optics
< prev   |   next >
new | recent | 2025-06
Change to browse by:
physics

References & Citations

  * NASA ADS
  * Google Scholar
  * Semantic Scholar

a export BibTeX citation Loading...

BibTeX formatted citation

x
[loading...          ]
Data provided by:

Bookmark

BibSonomy logo Reddit logo
(*) Bibliographic Tools

Bibliographic and Citation Tools

[ ] Bibliographic Explorer Toggle
Bibliographic Explorer (What is the Explorer?)
[ ] Connected Papers Toggle
Connected Papers (What is Connected Papers?)
[ ] Litmaps Toggle
Litmaps (What is Litmaps?)
[ ] scite.ai Toggle
scite Smart Citations (What are Smart Citations?)
( ) Code, Data, Media

Code, Data and Media Associated with this Article

[ ] alphaXiv Toggle
alphaXiv (What is alphaXiv?)
[ ] Links to Code Toggle
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
[ ] DagsHub Toggle
DagsHub (What is DagsHub?)
[ ] GotitPub Toggle
Gotit.pub (What is GotitPub?)
[ ] Huggingface Toggle
Hugging Face (What is Huggingface?)
[ ] Links to Code Toggle
Papers with Code (What is Papers with Code?)
[ ] ScienceCast Toggle
ScienceCast (What is ScienceCast?)
( ) Demos

Demos

[ ] Replicate Toggle
Replicate (What is Replicate?)
[ ] Spaces Toggle
Hugging Face Spaces (What is Spaces?)
[ ] Spaces Toggle
TXYZ.AI (What is TXYZ.AI?)
( ) Related Papers

Recommenders and Search Tools

[ ] Link to Influence Flower
Influence Flower (What are Influence Flowers?)
[ ] Core recommender toggle
CORE Recommender (What is CORE?)

  * Author
  * Venue
  * Institution
  * Topic

( ) About arXivLabs

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and
share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have
embraced and accepted our values of openness, community, excellence,
and user data privacy. arXiv is committed to these values and only
works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community?
Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is
MathJax?)

  * About
  * Help

  * Click here to contact arXiv Contact
  * Click here to subscribe Subscribe

  * Copyright
  * Privacy Policy

  * Web Accessibility Assistance
  * arXiv Operational Status
    Get status notifications via email or slack