Adversarially Robust Quantum State Learning and Testing | NSF Public Access Repository

skip to main content

An official website of the United States government Here's how you know

Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Citation Details

This content will become publicly available on December 14, 2026

Adversarially Robust Quantum State Learning and Testing

Award ID(s):: 2339116 2243659

PAR ID:: 10677738

Author(s) / Creator(s):: Aliakbarpour, Maryam ; Braverman, Vladimir ; Chia, Nai-Hui ; Liu, Yuhan

Publisher / Repository:: IEEE

Date Published:: 2025-12-14

ISBN:: 979-8-3315-7132-0

Page Range / eLocation ID:: 186 to 204

Format(s):: Medium: X

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
This content will become publicly available on December 14, 2026
Conference Paper:
https://doi.org/10.1109/FOCS63196.2025.00013