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Register a new userSpecification of photonic circuits using Quantum Hardware Description Language
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Following the simple observation that the interconnection of a set of quantum optical input-output devices can be specified using structural mode VHSIC Hardware Description Language (VHDL), we demonstrate a computer-aided schematic capture workflow for modeling and simulating multi-component photonic circuits. We describe an algorithm for parsing circuit descriptions to derive quantum equations of motion, illustrate our approach using simple examples based on linear and cavity-nonlinear optical components, and demonstrate a computational approach to hierarchical model reduction.
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Topological photonics has been introduced as a powerful platform for integrated optics, since it can deal with robust light transport, and be further extended to the quantum world. Strikingly, valley-contrasting physics in topological photonic structures contributes to valley-related edge states, their unidirectional coupling, and even valley-dependent wave-division in topological junctions. Here, we design and fabricate nanophotonic topological harpoon-shaped beam splitters (HSBSs) based on $120$-deg-bending interfaces and demonstrate the first on-chip valley-dependent quantum information process. Two-photon quantum interference, namely, HongOu-Mandel (HOM) interference with a high visibility of $0.956 pm 0.006$, is realized with our 50/50 HSBS, which is constructed by two topologically distinct domain walls. Cascading this kind of HSBS together, we also demonstrate a simple quantum photonic circuit and generation of a path-entangled state. Our work shows that the photonic valley state can be used in quantum information processing, and it is possible to realize more complex quantum circuits with valley-dependent photonic topological insulators, which provides a novel method for on-chip quantum information processing.
The scaling up of quantum hardware is the fundamental challenge ahead in order to realize the disruptive potential of quantum technology in information science. Among the plethora of hardware platforms, photonics stands out by offering a modular approach, where the main challenge is to construct sufficiently high-quality building blocks and develop methods to efficiently interface them. Importantly, the subsequent scaling-up will make full use of the mature integrated photonic technology provided by photonic foundry infrastructure to produce small foot-print quantum processors of immense complexity. A fully coherent and deterministic photon-emitter interface is a key enabler of quantum photonics, and can today be realized with solid-state quantum emitters with specifications reaching the quantitative benchmark referred to as Quantum Advantage. This light-matter interaction primer realizes a range of quantum photonic resources and functionalities, including on-demand single-photon and multi-photon entanglement sources, and photon-photon nonlinear quantum gates. We will present the current state-of-the-art in single-photon quantum hardware and the main photonic building blocks required in order to scale up. Furthermore, we will point out specific promising applications of the hardware building blocks within quantum communication and photonic quantum computing, laying out the road ahead for quantum photonics applications that could offer a genuine quantum advantage.
The Majorization Principle is a fundamental statement governing the dynamics of information processing in optimal and efficient quantum algorithms. While quantum computation can be modeled to be reversible, due to the unitary evolution undergone by the system, these quantum algorithms are conjectured to obey a quantum arrow of time dictated by the Majorization Principle: the probability distribution associated to the outcomes gets ordered step-by-step until achieving the result of the computation. Here we report on the experimental observation of the effects of the Majorization Principle for two quantum algorithms, namely the quantum fast Fourier transform and a recently introduced validation protocol for the certification of genuine many-boson interference. The demonstration has been performed by employing integrated 3-D photonic circuits fabricated via femtosecond laser writing technique, which allows to monitor unambiguously the effects of majorization along the execution of the algorithms. The measured observables provide a strong indication that the Majorization Principle holds true for this wide class of quantum algorithms, thus paving the way for a general tool to design new optimal algorithms with a quantum speedup.
We propose a machine learning method to characterize photonic states via a simple optical circuit and the data processing of photon number distributions as photonic patterns. The input states consist of two coherent states used as references and a two-mode unknown state to be studied. We successfully trained a supervised learning algorithm to predict the degree of entanglement in the two-mode state and to perform the full tomography of one photonic mode, obtaining good accuracy and an $r$-factor performance of our algorithm $r > 0.75$.
Integrated photonics is a leading platform for quantum technologies including nonclassical state generation cite{Vergyris:2016-35975:SRP, Solntsev:2014-31007:PRX, Silverstone:2014-104:NPHOT, Solntsev:2016:RPH}, demonstration of quantum computational complexity cite{Lamitral_NJP2016} and secure quantum communications cite{Zhang:2014-130501:PRL}. As photonic circuits grow in complexity, full quantum tomography becomes impractical, and therefore an efficient method for their characterization cite{Lobino:2008-563:SCI, Rahimi-Keshari:2011-13006:NJP} is essential. Here we propose and demonstrate a fast, reliable method for reconstructing the two-photon state produced by an arbitrary quadratically nonlinear optical circuit. By establishing a rigorous correspondence between the generated quantum state and classical sum-frequency generation measurements from laser light, we overcome the limitations of previous approaches for lossy multimode devices cite{Liscidini:2013-193602:PRL, Helt:2015-1460:OL}. We applied this protocol to a multi-channel nonlinear waveguide network, and measured a 99.28$pm$0.31% fidelity between classical and quantum characterization. This technique enables fast and precise evaluation of nonlinear quantum photonic networks, a crucial step towards complex, large-scale, device production.
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