Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Student works
  4. Tighter lower bounds on teh conditional entropy for USD-Based QRNG
 
master thesis

Tighter lower bounds on teh conditional entropy for USD-Based QRNG

Brunet, Thomas
July 4, 2025

In this work, we study the security of a semi-device-independent Quantum Random Number Generator (QRNG) based on Unambiguous State Discrimination (USD). The original security proof relied on bounding the guessing probability of a classical adversary, which effectively corresponds to estimating the conditional min-entropy, leading to rather loose bounds. Thus, we present new tighter bounds on the conditional entropy directly, based on a converging sequence of optimization problems. We further extend the analysis to quantum adversaries by combining this approach with an SDP hierarchy which relies on the Gram matrix of the input states. Using numerical simulations, we investigate the protocol's robustness to both noise and finite-size effects, considering non-i.i.d. rounds of the protocol, in contrast to the assumptions made in the original proof. Finally, we propose an improvement to the protocol by introducing an input to Bob that determines his measurement, which allows us to certify security even in the quantum adversary model.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

MasterThesisThomasBrunet.pdf

Type

Main Document

Version

Accepted version

Access type

openaccess

License Condition

N/A

Size

1.36 MB

Format

Adobe PDF

Checksum (MD5)

b03f27a5fb47ff81fab7f84c6a905012

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés