PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
October 2, 2025Physical Review Research4 citationsOpen Access

Ultrafast all-optical measurement of squeezed vacuum in a lithium niobate nanophotonic circuit

View Full Paper
JWJames WilliamsESElina SendonarisRNRajveer Nehra

Key Points

  • All-optical measurement enables real-time analysis of squeezed vacuum, pushing the limits of traditional electronic systems.
  • This work achieved a theoretical maximum clock speed of 6.5 THz, significantly improving measurement speeds.
  • Using dispersion engineering, femtosecond pulses can now propagate without distortion within a nanophotonic circuit.
  • The use of thin-film lithium niobate provides compatibility with diverse photonic components, enhancing practical applications.

Abstract

Squeezed vacuum, a fundamental resource for continuous-variable quantum information processing, has been used to demonstrate quantum advantages in sensing, communication, and computation. While most experiments use homodyne detection to characterize squeezing and are therefore limited to electronic bandwidths, recent experiments have shown optical parametric amplification (OPA) to be a viable measurement strategy. Here, we realize OPA-based quantum state tomography in integrated photonics and demonstrate the generation and all-optical Wigner tomography of squeezed vacuum in a nanophotonic circuit. We employ dispersion engineering to enable the distortion-free propagation of femtosecond pulses and achieve ultrabroad operation bandwidths, effectively lifting the speed restrictions imposed by traditional electronics on quantum measurements with a theoretical maximum clock speed of 6.5 THz. We implement our circuit on thin-film lithium niobate, a platform compatible with a wide variety of active and passive photonic components. Our results chart a course for realizing all-optical ultrafast quantum information processing in an integrated room-temperature platform.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Williams et al. (2025) studied this question.

synapsesocial.com/papers/68de6f3a83cbc991d0a227b4https://doi.org/10.1103/rvmb-ljd3
Ask AI
Helpful
Bookmark
Share
View Full Paper