Back to News
quantum-computing

A Universal Entanglement Witness Generator

Aiden R. Rosebush, Alexander C. B. Greenwood, Andi Shahaj, Li Qian
Loading...
4 min read
0 likes
⚡ Quantum Brief
Our witnesses achieve perfect accuracy across both physical experimental test states and large numerical sets of separable mixed states-including 30 million test states for a 3-qubit W-state witness and 10 million for a 4-qubit hy Quantum Physics arXiv:2608.07806 (quant-ph) [Submitted on 7 Aug 2026] Title:A Universal Entanglement Witness Generator Authors:Aiden R. For N qudits of dimension d, we train on the fully-separable eigenstates of each qudit's SU(d) generators to find a prototype witness, then tune the witness's bias term via gradient descent to maximize noise tolerance.
Why it matters

This advance signals a leap in practical quantum verification, reducing experimental overhead while improving reliability, a critical step for scaling quantum technologies beyond proof-of-concept stages.

AI Audio Summary
0:00 / 0:00
Click to play
pexels-thisisengineering-3861969 (1).jpg
Quantum News · Media Library

Quantum Physics arXiv:2608.07806 (quant-ph) [Submitted on 7 Aug 2026] Title:A Universal Entanglement Witness Generator Authors:Aiden R. Rosebush, Alexander C. B. Greenwood, Andi Shahaj, Li Qian View a PDF of the paper titled A Universal Entanglement Witness Generator, by Aiden R. Rosebush and 3 other authors View PDF HTML (experimental) Abstract:Entanglement witnesses are essential for certifying entanglement, yet constructing ones that are both noise-robust and economical in measurement settings remains challenging - particularly beyond qubits and for non-stabilizer ("magic") states. We present a machine-learning method that, given a target state and a user-specified number of measurement settings, generates an entanglement witness optimized for noise tolerance in the neighborhood of that state, requiring only local measurements. The approach is fully general, applying to multipartite qubit and qudit systems alike, including non-stabilizer states. For N qudits of dimension d, we train on the fully-separable eigenstates of each qudit's SU(d) generators to find a prototype witness, then tune the witness's bias term via gradient descent to maximize noise tolerance. Adversarial training further strengthens the witnesses, delivering greater noise tolerance with even fewer settings; critically, under this scheme the required training-set size becomes independent of system size. We package the entire pipeline as an automated script that, in every case we tested, produces witnesses surpassing all existing methods in noise tolerance and/or number of measurement settings. We demonstrate the method on Bell, GHZ, W, and hypergraph states, along with a range of qudit states, spanning 2-6 qubits, bipartite qudits up to d=10, and tripartite qutrits. Our witnesses achieve perfect accuracy across both physical experimental test states and large numerical sets of separable mixed states-including 30 million test states for a 3-qubit W-state witness and 10 million for a 4-qubit hypergraph-state witness-and we experimentally confirm the noise tolerance of Bell- and hypergraph state witnesses on both photonic and superconducting platforms, respectively. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.07806 [quant-ph] (or arXiv:2608.07806v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2608.07806 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Aiden Rosebush [view email] [v1] Fri, 7 Aug 2026 23:05:13 UTC (639 KB) Full-text links: Access Paper: View a PDF of the paper titled A Universal Entanglement Witness Generator, by Aiden R. Rosebush and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-08 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark 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?) 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?)

Read Original

Tags

quantum-hardware

Source Information

Source: arXiv Quantum Physics

Discussion

0 professional contributions

Sign in to join this professional discussion.

Be the first to add a constructive contribution.