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PHOTONICS QUANTUM SAMPLING MACHINE

Periodic Reporting for period 1 - PHOQUSING (PHOTONICS QUANTUM SAMPLING MACHINE)

Reporting period: 2020-09-01 to 2021-08-31

Quantum theory provides a probabilistic description of nature, marking a departure from a classical picture. The intrinsic randomness of quantum processes has found applications in efficient probabilistic algorithms for simulation, integration, machine learning, and financial pricing, among other applications. Recently, a large research effort has been devoted to exploit quantum systems to generate probability distributions that are computationally hard for classical computers to obtain. In particular, several works reported the insight that devices exploiting quantum resources can generate probability distributions that are inaccessible with classical means. Hybrid Quantum Computational models combine classical processing with these quantum sampling machines to obtain computational advantage over standard classical means in some tasks. Moreover, NISQ (Noisy, Intermediate-Scale Quantum) technology may contribute to obtaining this advantage in the near term. The aim of this project is to implement PHOtonic Quantum SamplING (PHOQUSING) machines based on large, reconfigurable interferometers with active feedback.
Among the several objectives of this project, we will define the most suitable architectures enabling the generation of these hard-to-sample distributions using integrated photonics, optimizing the designs and studying the tolerance to errors. PHOQUSING aims to build working photonic quantum sampling machines, with first demonstrations of their algorithmic applications. This enables the implementation of Hybrid Quantum Computing (HQC) models that include quantum and classical elements for applications in machine learning and optimization. The results achieved within PHOQUSING will also have applications outside the scientific community. Several use cases will be addressed within the project, including development of new materials (for space technologies, surfactants, catalysts etc), financial services (portfolio optimization and management, assets scoring), computational fluid dynamics (for automotive, aeronautical) and pharma. Furthermore, we will envisage additional development of the machines to enable cloud-access, which will potentially attract interested end-users in the short term.
During the first reporting period, the PHOQUSING consortium has progressed several steps towards the final objective of the project. Theoretical work has been performed by implementing simulation software for processes based on a Boson Sampling architecture. This software represents a fundamental step towards definition of the final applications, since it will enable testing different protocols in small-instance size classical simulations. Furthermore, the consortium has already identified optimized reconfigurable circuit designs for the first experiments to be performed with the quantum sampling machines. In particular, different architectures will be pursued for the integrated platforms employed within the project (femtosecond laser-written circuits in glass and lithographic circuits in silicon nitride), to fully exploit the advantages of each approach. Additionally, first results have been obtained on several methodologies for calibration and certification of both the intermediate components and the final hardware to be assembled. These obtained results have also started to define a first roadmap for applications of sampling processes.
From the hardware point of view, the first components have been fabricated, in particular a first generation of integrated reconfigurable photonic circuits. The assembly process of QOLOSSUS and QALCULUS is currently on-going. Furthermore, fundamental advances in the efficiency of single-photon sources based on quantum dots have been achieved. Until now, first experiments have been performed to address calibration and validation of the first components, with the additional benefit of providing a fundamental data-oriented feedback to improve the corresponding methodologies. Furthermore, the technological advances have enabled first scientific outcomes, including a Boson Sampling experiment based on the novel 3D reconfigurable architecture for femtosecond laser-written circuits.
Several results beyond state-of-the-art have been obtained in the first period of PHOQUSING project.
The implementation of software codes for computational analysis of different models and Boson sampling variations to be addressed represents an important stepping stone through the final vision of PHOQUSING. In the first year we have been able to correctly identify and design an integrated circuit for the implementation of a modular quantum Bernoulli factory on-chip, solving the concatenation problem in the current-state-of-the-art. A complete Boson sampling experiment on a 3D integrated/reconfigurable photonic chip was successfully performed, making a step forward in the complexity of reconfigurable circuits employed in this task.
From the hardware perspective, the assembling of both machines QOLOSSUS and QALCULUS has already started. In particular a Silicon-Nitride integrated device having 20 modes and 380 thermal phase-shifters has been already designed and sent to a foundry for its construction. Another important result obtained during the first reporting period is the improvement of the brightness of single-photon sources (>50%). This result represents an important progress beyond current-state-of-the-art in single-photon sources. Additionally, steps ahead have been done in the experimental demonstration of quantum superposition of single-photon states encoded in two frequencies.
We expect to construct and perform several cutting-edge experiments once the machines are assembled and characterized. The potentials of this project are tightly connected to the development of new quantum computing algorithms where the hybrid models play a crucial role. Hybrid Quantum Computing models combine quantum and classical information processing to obtain maximum benefit from architectures that do not yet enable universal quantum computation. As such, they are perfect fits for development in the NISQ (Noisy, Intermediate-Scale Quantum) era. Non-adaptive protocols using linear optics have been devised to solve graph-theoretical problems (isomorphism, finding dense subgraphs), for Monte Carlo integration, and verification of solutions of NP—complete problems. All these represent important algorithms with applications in bioinformatics, simulation and optimization of financial products, and brute-force search of intractable problems (even for full-blown, universal quantum computers) representing a clear impact on the socio-economic sector.
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