Periodic Reporting for period 2 - QFreC (Smart protonic quantum frequency circuits)
Reporting period: 2022-11-01 to 2024-04-30
Machine learning empowers computers to solve complex tasks such as pattern identification and strategy optimization with applications in, e.g. financial trading, fraud detection, medical diagnosis, and self-driving vehicles. The required computing power is, however, pushing existing computational resources to their limits (hardware and power requirements), restraining their further advancement. QFreC targets the realization of photonic frequency-based quantum co-processors, specifically tailor-made to solve machine learning problems with capabilities commensurate with today’s high-power, yet energy-efficient processing needs. In particular, QFreC explores a high-dimensional photonic quantum frequency comb approach, where photons have hundreds to thousands of discrete and equidistantly spaced frequency modes, giving access to large, scalable information capacity. QFreC thus strategically combines i) the investigation of photonic frequency domain processing by the adaptation of existing and exploration of new qubit learning concepts, ii) the realization of efficiency-enhanced and novel integrated quantum frequency comb sources and iii) the development of reconfigurable, fast, and broadband control schemes via electro-optical and all-optical nonlinear processes.
Within the project, the exploration and development of different algorithms/models for their implementation in frequency-domain photonic circuits has been pursued. Hybrid generative adversarial networks on frequency circuits have been introduced and simulated, which show a fast convergence. Experimentally the project explored and developed a novel hybrid quantum frequency comb source, where the laser and parametric frequency-bin entangled state generation stage is integrated into a single device. Experiments showed the realization of high-dimensional entangled states with exceptionally high generation rates and fidelities, demonstrating the first fully integrated entangled photon pair source. Additionally, the realization and enhanced generation of frequency-bin product states as quantum resources for photonic networks was demonstrated by exploiting a pulsed-drive lithium niobate waveguide as well as a bi-chromatically excited integrated photonic cavity.
Building on this, the realization of a quantum random walk within the frequency domain was achieved, where the previously realized product-state generation introduced for the first time the control of a photonic random walk. Moreover, a frequency-to-time mapping technique for the fast readout of frequency-entangled states has been developed and demonstrated.
Building on this, the realization of a quantum random walk within the frequency domain was achieved, where the previously realized product-state generation introduced for the first time the control of a photonic random walk. Moreover, a frequency-to-time mapping technique for the fast readout of frequency-entangled states has been developed and demonstrated.
Progress beyond the state of the art includes the demonstration of a fully laser-integrated entangled quantum light source of two- and high-dimensional states. While previous systems exploited bulky laser systems next to an integrated chip, the source here directly integrates the laser into the chip platform, making it compact, scalable and stable.
The following work will further explore photonic frequency domain processing and push advancements in the modification and control concepts of frequency quantum circuits.
The following work will further explore photonic frequency domain processing and push advancements in the modification and control concepts of frequency quantum circuits.