Continuous-variable (CV) photonics can generate trillions of time-multiplexed modes, but the resource requirements of its classical control stack - particularly the real-time decoders-have not yet been quantified. Here we present the first co-design study that bridges CV-photonic measurement-based quantum computing (MBQC) with CMOS control hardware. We implement a Union-Find surface-code decoder targeting an ASIC and, by evaluating its error-correction performance, silicon area, and decoding time as functions of code distance, we derive insights that lay the groundwork for future system development.
Continuous-variable (CV) photonics can generate trillions of time-multiplexed modes, but the resource requirements of its classical control stack - particularly the real-time decoders-have not yet been quantified. Here we present the first co-design study that bridges CV-photonic measurement-based quantum computing (MBQC) with CMOS control hardware. We implement a Union-Find surface-code decoder targeting an ASIC and, by evaluating its error-correction performance, silicon area, and decoding time as functions of code distance, we derive insights that lay the groundwork for future system development.
Measurement-based quantum computation (MBQC) offers a promising paradigm for photonic quantum computing, but its implementation requires the generation of specific non-Gaussian resource states. While continuous-variable encodings such as the highly complex (GKP) states have been widely studied, the much simpler binomial codes offer an experimentally accessible alternative, though they demand a distinct set of operational tools. Here, we present a toolkit for MBQC using optical binomial codes, detailing a cavity-QED protocol for conditional generation of cluster states and the implementation of Pauli measurements. Our work proposes the first steps for existing optical atom-cavity architectures to lay the groundwork for their use in quantum computation.
Most of the architectural research on photonic implementations of measurement-based quantum computing (MBQC) has focused on the quantum resources involved in the problem with the implicit assumption that these will provide the main constraints on system scaling. However, the ‘flying-qubit’ architecture of photonic MBQC requires specific timing constraints that need to be met by the classical control system. This classical control includes, for example: the amplification of the signals from single-photon detectors to voltage levels compatible with digital systems; the implementation of a control system which converts measurement outcomes into basis settings for measuring subsequent cluster qubits, in accordance with the quantum algorithm being implemented; and the digital-to-analog converter (DAC) and amplifier systems required to set these measurement bases using a fast phase modulator. In this paper, we analyze the digital system needed to implement arbitrary one-qubit rotations and controlled-NOT (CNOT) gates in discrete-variable photonic MBQC, in the presence of an ideal cluster state generator, with the main aim of understanding the timing constraints imposed by the digital logic on the analog system and quantum hardware. We have verified that the design works using functional simulations, and have used static timing analysis of a Xilinx FPGA (7 series) to provide a practical upper bound on the speed at which the adaptive measurement processing can be performed, in turn constraining the photonic clock rate of the system. The design and testing system is freely available, for use as the basis of analysis of more complex designs, incorporating more recent proposals for photonic quantum computing.} Our work points to the importance of co-designing the classical control system in tandem with the quantum system in order to meet the challenging specifications of a photonic quantum computer.
Hybrid discrete- and continuous-variable (DV-CV) encodings have been developed to overcome operational drawbacks of each individual encoding, while fusion-based quantum computation (FBQC) has emerged to address the practical challenges of scalability toward fault-tolerant photonic quantum computation. Here we introduce hybrid FBQC using small optical DV-CV hybrid resource states connected through hybrid fusions, to combine the advantages of both approaches. We develop protocols for directly generating these resource states without requiring local hybrid logic such as the Hadamard gate, together with a tailored decoding strategy that exploits the error information contained in individual hybrid-fusion outcomes. We demonstrate that hybrid FBQC achieves a photon loss threshold of 2.231% while requiring only 12 hybrid fusions per surface-code unit cell, substantially improving upon the 0.89% threshold and 60-fusion requirement of previous hybrid measurement-based scheme. These results establish optical hybrid FBQC as a high-threshold resource-efficient route to scalable fault-tolerant photonic quantum computation.
The physical realization of scalable quantum processors is primarily limited by decoherence, which typically requires cryogenic conditions and complex error-correction protocols. In this paper, we present AṆU ASTRA, a room-temperature optical quantum co-processor capable of coherently simulating up to 1000 physical qubits. Unlike purely discrete-variable quantum computers that rely on fragile unitary gates for universal computation, the ASTRA architecture operates via a hybrid measurement-based quantum computation (MBQC) framework. It leverages continuous-variable (CV) macroscopic light intensity, utilizing Time-Division Multiplexing (TDM) through active Liquid Crystal Variable Retarders (LCVRs) driven by a digital Real-Time Operating System (RTOS). This allows for the manipulation of coherent optical states across discrete temporal bins, effectively emulating large-scale entanglement graphs without the exponential hardware overhead or cryogenic footprint of superconducting systems. We empirically validate the architecture's statistical quantum non-determinism, passing NIST SP 800-90B entropy tests for True Quantum Random Number Generation (QRNG). Furthermore, the practical computational utility of the co-processor is demonstrated through the physical execution of the Quantum Approximate Optimization Algorithm (QAOA), Quantum Support Vector Machine (QSVM) non-linear classification, and Grover's algorithm amplitude amplification. This architecture provides a highly scalable, low-cost, room-temperature pathway for applied quantum optimization and machine learning tasks.
Quantum computers, leveraging the principles of quantum mechanics, hold the potential to surpass classical computers in numerous applications, with implications across various domains. Besides the well-known gate model, Measurement-based Quantum Computation (MBQC) is another promising computational approach to achieve universal quantum computation. In MBQC, large ensembles of qubits are prepared in a highly entangled cluster state, forming the basis for executing quantum computations through sequential measurements. Cluster states are realized using both continuous variables (CV) and discrete variables (DV) techniques. In the CV-based methods, Frequency Domain Multiplexing (FDM), Time Domain Multiplexing (TDM), Spatial Domain Multiplexing (SDM), and hybrid schemes are employed. This paper thoroughly discusses and compares these approaches, elucidating their strengths and limitations. Additionally, the generation of photonic cluster states in DV is explored and some recent results are reported. Some recent state-of-the-art advancements in photonic and superconducting qubits entanglement, which can potentially serve as cluster states, are also presented. Finally, we highlight the approach that exhibits the most promising characteristics for achieving efficient cluster state realization in the context of MBQC.
Continuous-variable (CV) quantum light sources are the essential resource for quantum computation. Integrated CV quantum light sources offer a scalable pathway by harnessing low-loss nonlinear materials, versatile device architectures, and CMOS-compatible fabrication processes enabled by integrated photonics platforms. In this review, we briefly introduce recent progress on integrated CV quantum light sources, including single-mode squeezed states, two-mode squeezed states, and multimode entangled states. The key performance metrics of CV quantum light sources, such as the squeezing level, bandwidth, purity, and mode multiplexing, are analyzed. We highlight representative implementations of lithium niobate, silicon nitride, and silica platforms for CV quantum light sources and discuss major challenges for realizing integrated large-scale and fault-tolerant CV quantum computation.