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IEEE Access

A Software Platform for Programmable Linear Optical Quantum Computer

Yong Sung Kwon, Byung-Soo Choi

Published Jan 1, 2023• 3 citations
Publisher

Abstract

Optical quantum computers represent qubits as photons created by laser and implement arbitrary quantum operations through Mach-Zehnder interferometers (MZIs) which is called linear optical quantum computing (LOQC). Since the number of qubits and quantum system is getting bigger, we need a scalable and universal quantum computing platform based on LOQC. In this work, we propose a software framework which can support a universal programming with flexibility of LOQC hardware configuration. The framework consists of four parts such as decomposer, mapper, controller, and user-interface controller. As an example, we show a use case of this framework for Bell state generation on Recket al.’s MZI network.

DOI
10.1109/access.2023.3324048

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Optical quantum computers represent qubits as photons created by laser and implement arbitrary quantum operations through Mach-Zehnder interferometers (MZIs) which is called linear optical quantum computing (LOQC). Since the number of qubits and quantum system is getting bigger, we need a scalable and universal quantum computing platform based on LOQC. In this work, we propose a software framework which can support a universal programming with flexibility of LOQC hardware configuration. The framework consists of four parts such as decomposer, mapper, controller, and user-interface controller. As an example, we show a use case of this framework for Bell state generation on Recket al.’s MZI network.
Linear optical quantum computing (LOQC) offers a quantum computation paradigm based on well-established and robust technology and flexible environmental conditions following DiVincenzo's criteria. Within this framework, integrated photonics can be utilized to achieve gate-based quantum computing, defining qubits by path-encoding, quantum gates through the use of Mach-Zehnder interferometers (MZIs), and measurements through single-photon detectors. In particular, universal two-qubit gates can be achieved by suitable structures of MZIs together with post-selection or heralding. The most resource-efficient choice is given by the post-selected Controlled-Z (CZ) gate. However, this implementation is characterized by a design which has a non-regular structure and cannot be cascaded. This limits the implementation of large-scale LOQC. Starting from these issues, we suggest an approach to move toward a universal and scalable LOQC on the integrated photonic platform. First of all, choosing the post-selected CZ as a universal two-qubit gate, we extend the path-encoded dual-rail qubit to a triplet of waveguides, composed of an auxiliary waveguide and the pair of waveguides corresponding to the qubit basis states. Additionally, we introduce a swap photonic network that maps the regularly-labeled structure of the new path-encoded qubits to the structure needed for the post-selected CZ. We also discuss the optical swap gate that allows the connection of non-nearest neighbor path-encoded qubits. In this way, we can deterministically exchange the locations of the qubits and execute controlled quantum gates between any path-encoded qubits. Next, by truncating the auxiliary waveguides after any post-selected CZ, we find that it is possible to cascade this optical gate when it acts on different pairs that share only one qubit. Finally, we show the Bell state and the Greenberger-Horne-Zeilinger (GHZ) state generation circuits implementing the regular structure, the cascading procedure of post-selected CZ and the optical swap.
Photonic systems offer a promising platform for interconnecting quantum processors and enabling scalable, networked architectures. Designing and verifying such architectures requires a unified formalism that integrates linear algebraic reasoning with probabilistic and control-flow structures. In this work, we introduce a graphical framework for distributed quantum computing that brings together linear optics, the ZX-calculus, and dataflow programming. Our language supports the formal analysis and optimization of distributed protocols involving both qubits and photonic modes, with explicit interfaces for classical control and feedforward, all expressed within a synchronous dataflow model with discrete-time dynamics. Within this setting, we classify entangling photonic fusion measurements, show how their induced Pauli errors can be corrected via a novel flow structure for fusion networks, and establish correctness proofs for new repeat-until-success protocols enabling arbitrary fusions. Layer by layer, we construct qubit architectures incorporating practical optical components such as beam splitters, switches, and photon sources, with graphical proofs that they are deterministic and support universal quantum computation. Together, these results establish a foundation for verifiable compilation and automated optimization in networked quantum computing.
Universal quantum computing requires an architecture that supports both linear circuits and, crucially, strong nonlinear resources. For quantum photonic systems, integrating such nonlinearities with scalable linear circuitry has been a major bottleneck, leaving most optical experiments without nonlinear operations and, consequently, incapable of achieving universality. Here, we report an extensible photonic computer that supports a universal gate set by seamlessly combining fully programmable, scalable linear optical networks with integrated nonlinear modules. This platform enables a broad range of quantum computing and simulation tasks. We demonstrate the quasi-deterministic generation of optical Gottesman-Kitaev-Preskill states, which are essential resources for bosonic error correction, yet had previously been realized only probabilistically. Furthermore, we simulate complex many-body quantum dynamics, exemplified by the Bose-Hubbard model. Such quantum simulation tasks have long been considered beyond the reach of photonic hardware limited to linear operations. These capabilities, enabled by our extensible architecture, establish a viable route towards photonic quantum simulation and fault-tolerant quantum computing.
A software platform for quantum computing is required to run a complex algorithm on a real quantum device through automatically converting a quantum circuit level algorithm to a control sequence of target device. Moreover, the software platform must be tailored for the target quantum system by exploiting the properties of qubits and gates. In this work, we show how to implement a software platform for a photonic integrated circuit (PIC) platform with path-encoded photon qubits and quantum gates realized by means of interference in a mesh of tuneable Mach-Zehnder interferometers (MZIs). For universal and programmable quantum computing, the software platform consists of three standard modules: decomposer, mapper, and controller. To verify the software we runs example circuit through software and hardware integration platform and confirm each module generates correct output. Also the validation is done by comparing two results for conventionally used manual way and the software supported automatic way. These two points ensure that the implemented software works correctly when applied to the PIC.
Optical technology is a highly promising platform for quantum computing due to its enormous potential for large-scale, ultrafast computation. However, realizing a programmable and scalable system remains a significant challenge. Here, we present a high-speed programmable Gaussian quantum computing platform with one hundred inputs based on a continuous-variable full-stack architecture. Our system features a 100 MHz clock frequency and integrates a cloud-based interface with an open-source Python software development kit, mqc3, significantly enhancing accessibility and operational flexibility. We provide a comprehensive characterization of our system and its capabilities through multi-input and multi-step teleportation, as well as the programmable routing of quantum states across 101 input modes. This platform represents a critical milestone in scalable analog quantum information processing, offering a robust testbed for the future integration of non-Gaussian resources and the development of large-scale optical neural networks.