collaborators

6 papers

quant-ph2026

Heterogeneously Integrated Squeezed-Light Generation and Detection on a Single Photonic Chip

Haoran Chen, Benjamin Westcott, Fatemehsadat Tabatabaei +10

Squeezed light underpins quantum-enhanced sensing and continuous-variable quantum information processing, and integrated photonics offers a route to producing it at scale. Universa…

quant-ph2026

Photon-Conditioned Squeezed States for Directional Displacement Response in Continuous-Variable Photonics

Boris Kiefer, Olivier Pfister

Squeezed Fock states, photon-subtracted squeezed states, and optical cat states are established non-Gaussian resources in continuous-variable quantum optics. Here we compare these…

physics.optics2026

Laser interferometry as a robust neuromorphic platform for machine learning

Amanuel Anteneh, Kyungeun Kim, J. M. Schwarz +2

We present a method for implementing an optical neural network using only linear optical resources, namely field displacement and interferometry applied to coherent states of light…

quant-ph2026

Gradient-descent methods for scalable quantum detector tomography

Amanuel Anteneh, Olivier Pfister

We present a technique for performing quantum detector tomography (QDT) of phase insensitive quantum detectors, a category under which many detectors of interest fall under, using…

quant-ph2025

Implementing the Koopman-von Neumann approach on continuous-variable photonic quantum computers

Xinfeng Gao, Olivier Pfister, Stefan Bekiranov

The Koopman-von Neumann (KvN) formalism recasts classical mechanics in a Hilbert space framework using complex wavefunctions and linear operators, akin to quantum mechanics. Instea…

quant-ph2025

Deep reinforcement learning for near-deterministic preparation of cubic- and quartic-phase gates in photonic quantum computing

Amanuel Anteneh, Léandre Brunel, Carlos González-Arciniegas +1

Cubic-phase states are a sufficient resource for universal quantum computing over continuous variables. We present results from numerical experiments in which deep neural networks…