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arXiv:2610.28349

COΦΦΦ - COmpiling PHotonics into dIgital quantum circuits

Grzegorz Czelusta, Marcin Markiewicz, Jakub Mielczarek, Artur Miroszewski

quant-phSubmitted Oct 20, 2026• Announced Oct 21, 2026• 0 citations
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Abstract

Photonic and qubit-based (digital) approaches to quantum computing are largely regarded as separate paradigms. This article aims to bridge these paradigms by developing a method for mapping quantum-optical systems onto qubit-based quantum circuits. The key ingredient enabling this mapping is the introduction of a truncation of the Fock space describing single-mode optical states. Within this framework, representations of basic photonic operations are developed, including the phase-rotation operator, the displacement operator, the squeezing operator, and the beam splitter. Explicit quantum circuit constructions are provided for Fock-space truncations of dimension $N=2$ and $N=4$. We discuss benchmarking of the implemented operations and identify the regime of applicability and the limitations of the proposed method. The presented results can be used to simulate quantum optical circuits on qubit-based quantum computers, with special relevance to Gaussian Boson Sampling in the low-photon-number regime. To demonstrate the practical applicability of this approach, we complement the theoretical framework with a Python-based quantum programming tool CO$Φ$ that compiles Blackbird quantum-optics programs into qubit-based OpenQASM circuits using a truncated Fock-space encoding. The compiler is available on GitHub at https://github.com/Quantum-Cosmos-Lab/cophi.

Comments
38 pages, 16 figures, GitHub repository: https://github.com/Quantum-Cosmos-Lab/cophi

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Photonic and qubit-based (digital) approaches to quantum computing are largely regarded as separate paradigms. This article aims to bridge these paradigms by developing a method for mapping quantum-optical systems onto qubit-based quantum circuits.
The key ingredient enabling this mapping is the introduction of a truncation of the Fock space describing single-mode optical states. Within this framework, representations of basic photonic operations are developed, including the phase-rotation operator, the displacement operator, the squeezing operator, and the beam splitter. Explicit quantum circuit constructions are provided for Fock-space truncations of dimension N=2N=2N=2 and N=4N=4N=4. We discuss benchmarking of the implemented operations and identify the regime of applicability and the limitations of the proposed method.
The presented results can be used to simulate quantum optical circuits on qubit-based quantum computers, with special relevance to Gaussian Boson Sampling in the low-photon-number regime. To demonstrate the practical applicability of this approach, we complement the theoretical framework with a Python-based quantum programming tool COΦΦΦ that compiles Blackbird quantum-optics programs into qubit-based OpenQASM circuits using a truncated Fock-space encoding. The compiler is available on GitHub at https://github.com/Quantum-Cosmos-Lab/cophi.
Boson sampling arising from multiphoton interference in linear-optical networks is a prominent non-universal model for quantum computation. Here, by encoding the multi-qubit state to bosonic Fock state, we present a scalable quantum-circuit framework for simulating boson sampling on a universal quantum computing platform. Beginning with balanced beam-splitter transformations on the single- and two-photon sectors, we derive equivalent quantum-circuit implementations and unify them within a common Hilbert-space representation using an ancilla-assisted encoding. This construction is then generalized to arbitrary interferometers by replacing each optical beam splitter with a repeating quantum-circuit unit that selectively acts only within the relevant local interference subspace, requiring N+1N+1N+1 qubits for a two-photon NNN-mode interferometer and a linear-overhead subspace-identification procedure. Using this framework, gate-based quantum circuit for a four-mode boson-sampling circuit is developed and experimentally implemented on a four-qubit gate-based photonic qubit system. The qubit framework for emulating boson sampling of n−n-n−photons in m−m-m−mode will be useful to solve a broad class of sampling complexity problem on a gate-based quantum computers.
We introduce a framework for simulating hybrid oscillator-qubit quantum processors on qubit-only systems through position encoding. By encoding continuous-variable position and momentum wave functions into qubit amplitudes, our method efficiently simulates all Gaussian and conditional Gaussian operations -- encompassing the phase-space instruction set (beam splitter, single-qubit rotation, conditional displacement) and extending to squeezing, conditional squeezing, conditional rotation, and conditional beam splitter -- using O ⁣(log⁡2 ⁣(Γ+log⁡(1/ε)))O\!\left(\log^2\!\left(Γ+ \log(1/ε)\right)\right)O(log2(Γ+log(1/ε))) qubit gates per hybrid gate, where ΓΓΓ is the Fock-level bound and εεε is the target precision. This polylogarithmic per-gate complexity represents an exponential improvement over Fock basis encoding approaches, which require exponential quantum or classical resources in the number of qubits per mode. We provide rigorous numerical characterization of quantum Fourier transform errors for Fock-bounded states, enabling precise resource estimation for practical implementations. This work establishes that hybrid oscillator-qubit algorithms can be implemented on qubit processors with polynomial overhead, providing new insights into the computational power trade-offs between discrete-variable and hybrid continuous-discrete-variable quantum computing.
Abstract Quantum photonic simulators are pivotal for designing and analyzing quantum photonic circuits that utilize both continuous-variable (CV) and discrete-variable (DV) encodings. This review critically examines the transition from Gaussian to non-Gaussian photonic models and the computational overhead that emerges from simulating systems with more than 20 modes or photon numbers exceeding 10 per mode. Gaussian states; such as coherent and squeezed states, are modeled efficiently using first-moment vectors and covariance matrices of dimension 2n×2n2n \times 2n2n×2n 2 n × 2 n , where n is the number of modes. Non-Gaussian elements like the cubic phase gate U=exp⁡(iγx^3)U = \exp (i \gamma \hat{x}^{3})U=exp(iγx^3) U = exp ( i γ x ˆ 3 ) and photon-subtracted states demand full Fock space representations and scale exponentially with photon number d2d^{2}d2 d 2 , where d is the Hilbert space dimension. We analyze simulators including , , and , benchmarking their support for tensor networks (bond dimension D >100), GPU acceleration, thus NVIDIA A100 with 1555 GB/s bandwidth, and SoC implementations such as Edge TPU with 8 TFLOPS. Special focus is given to noise models such as photon loss with transmissivity η , thermal noise modeled with nˉ=1.5\bar{n} = 1.5nˉ=1.5 n ¯ = 1.5 , and dark count Poisson distributions ( λ=0.1\lambda = 0.1λ=0.1 λ = 0.1 ). The review underscores scalable techniques and hybrid quantum-classical workflows vital for near-term photonic quantum computing.
We introduce coherent-state propagation, a computational framework for simulating bosonic systems. We focus on bosonic circuits composed of displaced linear optics augmented by Kerr nonlinearities, a universal model of bosonic quantum computation that is also physically motivated by driven Bose-Hubbard dynamics. The method works in the Schrödinger picture representing the evolving state as a sparse superposition of coherent states. We develop approximation strategies that keep the simulation cost tractable in physically relevant regimes, notably when the number of Kerr gates is small or the Kerr nonlinearities are weak, and prove rigorous guarantees for both observable estimation and sampling. In particular, bosonic circuits with logarithmically many Kerr gates admit quasi-polynomial-time classical simulation at exponentially small error in trace distance. We further identify a weak-nonlinearity regime in which the runtime is polynomial for arbitrarily small constant precision. We complement these results with numerical benchmarks on the Bose-Hubbard model with all-to-all connectivity. The method reproduces Fock-basis and matrix-product-state reference data, suggesting that it offers a useful route to the classical simulation of bosonic systems.
This work presents a developed Wolfram Mathematica software tool based on the Quantum extension package. This tool is able to simulate the output state for any linear optical circuit based on Beam Splitters (BSs) and Phase Sifters (PSs) by using as input, quantum states of light. The input of the software is described via the use of photon number states capable of emulating Fock states or coherent states, whereas the output provides the probability of detecting a photon at each output port. This photonic circuit may include any number of linear optical elements, including beam splitters with variable splitting ratios, as well as phase shifters. By using the unitary transformation of any photonic circuit (e.g., photonic chip), the output states can be computed, and detection probabilities of the chip can be obtained. The unitary transformation of the Controlled NOT (CNOT) quantum gate through a linear optical layout is presented, validating the functionality of the proposed software tool. In conclusion, the proposed software aims to enable testing of simple photonic circuits in the quantum regime.
Parametrized quantum optical circuits are a class of quantum circuits in which the carriers of quantum information are photons and the gates are optical transformations. Classically optimizing these circuits is challenging due to the infinite dimensionality of the photon number vector space that is associated to each optical mode. Truncating the space dimension is unavoidable, and it can lead to incorrect results if the gates populate photon number states beyond the cutoff. To tackle this issue, we present an algorithm that is orders of magnitude faster than the current state of the art, to recursively compute the exact matrix elements of Gaussian operators and their gradient with respect to a parametrization. These operators, when augmented with a non-Gaussian transformation such as the Kerr gate, achieve universal quantum computation. Our approach brings two advantages: first, by computing the matrix elements of Gaussian operators directly, we don't need to construct them by combining several other operators; second, we can use any variant of the gradient descent algorithm by plugging our gradients into an automatic differentiation framework such as TensorFlow or PyTorch. Our results will find applications in quantum optical hardware research, quantum machine learning, optical data processing, device discovery and device design.