Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2608.09509

Gate-based emulation of boson sampling using photonic qubits

Aastha P. Zalone, S. P. Dinesh, C. M. Chandrashekar

quant-phSubmitted Aug 10, 2026• Announced Aug 11, 2026• 0 citations
arXivHTMLPDF

Abstract

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 $N+1$ qubits for a two-photon $N$-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 $n-$photons in $m-$mode will be useful to solve a broad class of sampling complexity problem on a gate-based quantum computers.

Comments
19 pages 14 figures

Related papers

Quantum Interference Dynamics in Chip-Scale Photonic Boson Sampling Circuit

Gaurav Kumar Yadav, S K Satish Kumar, Chandan Pathak +1 more

Boson sampling is a leading platform for exploring many-body quantum interference in linear optical systems. However, identifying circuit-level operating regimes where quantum signatures remain robust under realistic conditions remains challenging. In this work, multimode photonic boson sampling is investigated using a programmable six mode integrated photonic circuit composed of cascaded beam splitters and tunable phase shifters. Each beam splitter is realized through directional couplers combined with local phase control, enabling arbitrary unitary transformations within the linear optical circuit. The circuit is modeled using a tight-binding Hamiltonian allowing controlled manipulation of optical phases and inter-mode coupling that directly governs multiphoton interference pathways. This set up is utilised to do the analysis of Heavy Output Generation (HOG), Total Variation Distance (TVD) and Linear Cross-Entropy Benchmarking (XEB), together with configuration-resolved probability differences, for up to five photons. Distinct dynamic regimes associated with coherent evolution, optimal interference and phase dispersion induced mixing is identified. The results further reveal a photon number dependent complexity–fragility trade-off and demonstrate the robustness of TVD to symmetric photon loss under post-selection. Overall, this work establishes a circuit-relevant validation framework linking programmable interferometer parameters, phase control and quantum interference metrics, providing guidance for scalable photonic boson-sampling implementations in the NISQ regime.

IEEE Journal of Quantum Electronics•May 20, 2026•0 citations

Non-linear Boson Sampling

Nicolò Spagnolo, Daniel J. Brod, Ernesto F. Galvão +1 more

Abstract Boson Sampling is a task that is conjectured to be computationally hard for a classical computer, but which can be efficiently solved by linear-optical interferometers with Fock state inputs. Significant advances have been reported in the last few years, with demonstrations of small- and medium-scale devices, as well as implementations of variants such as Gaussian Boson Sampling. Besides the relevance of this class of computational models in the quest for unambiguous experimental demonstrations of quantum advantage, recent results have also proposed the first applications for hybrid quantum computing. Here, we introduce the adoption of non-linear photon–photon interactions in the Boson Sampling framework, and analyze the enhancement in complexity via an explicit linear-optical simulation scheme. By extending the computational expressivity of Boson Sampling, the introduction of non-linearities promises to disclose novel functionalities for this class of quantum devices. Hence, our results are expected to lead to new applications of near-term, restricted photonic quantum computers.

arXiv:2110.13788•npj Quantum Information•Jan 9, 2023•24 citations

Logarithmic-depth quantum simulation of boson sampling

Changhun Oh

We show that boson sampling with an arbitrary $m$-mode interferometer and $n\le m$ single-photon inputs can be simulated to inverse-polynomial total-variation error by a logarithmic-depth qubit circuit with polynomially many qubits. The circuit uses Clifford+$T$ gates, arbitrary qubit connectivity, and a single final measurement, and its family is logspace uniform. The key idea is to enlarge the optical system, decompose the resulting transformation into six quadratic shears, and distribute each mode over many submodes. This redistribution permits a fixed local occupation cutoff, after which local basis changes and parallel phase gates give the qubit circuit. Consequently, our result places boson sampling within shallow quantum computation.

quant-pharXiv:2609.18907•Sep 17, 2026•0 citations

Quantum machine learning with Adaptive Boson Sampling via post-selection

Francesco Hoch, Eugenio Caruccio, Giovanni Rodari +18 more

The implementation of large-scale universal quantum computation represents a challenging and ambitious task on the road to quantum processing of information. In recent years, an intermediate approach has been pursued to demonstrate quantum computational advantage via non-universal computational models. A relevant example for photonic platforms has been provided by the Boson Sampling paradigm and its variants, which are known to be computationally hard while requiring at the same time only the manipulation of the generated photonic resources via linear optics and detection. Beside quantum computational advantage demonstrations, a promising direction towards possibly useful applications can be found in the field of quantum machine learning, considering the currently almost unexplored intermediate scenario between non-adaptive linear optics and universal photonic quantum computation. Here, we report the experimental implementation of quantum machine learning protocols by adding adaptivity via post-selection to a Boson Sampling platform based on universal programmable photonic circuits fabricated via femtosecond laser writing. Our experimental results demonstrate that Adaptive Boson Sampling is a viable route towards dimension-enhanced quantum machine learning with linear optical devices. Extending quantum photonics’ capabilities from simple linear-optics-based schemes to universal quantum computing presents several challenges, but intermediate regimes with some degree of adaptivity might already bring practical advantages. Here, the authors experimentally emulate an adaptive Boson Sampling scheme using post-selection, and apply it to a data classification task.

arXiv:2502.20305•Nature Communications•Jan 21, 2025•34 citations

COΦΦΦ - COmpiling PHotonics into dIgital quantum circuits

Grzegorz Czelusta, Marcin Markiewicz, Jakub Mielczarek +1 more

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.

quant-pharXiv:2610.28349•Oct 21, 2026•0 citations

Single photons in linear optics: quantum computing and quantum simulations

Malaquias Correa Anguita

This dissertation explores the use of single photons in integrated photonic circuits as a platform for quantum computation and quantum simulation. In the noisy intermediate-scale quantum (NISQ) era, photonic implementations of boson sampling provide one of the most promising routes to demonstrating quantum advantage, while also enabling insight-driven experiments that probe many-body interference and computational complexity. The first part of the thesis is devoted to the hardware development and characterization of programmable silicon nitride photonic processors. We demonstrate large-scale multi-photon interference in a 20-mode universal processor, establishing the potential of integrated photonics for scaling up boson sampling experiments. In parallel, we introduce a validation protocol based on detector binning, implemented on a 12-mode predecessor of the device. Together, these studies advance the photonic platform itself, focusing on scalability, versatility, and benchmarking, rather than direct applications. The second part turns to quantum simulation. We first present a photonic simulation of a spin-foam amplitude from loop quantum gravity, illustrating how multi-photon interference can provide a testbed for problems in fundamental physics. We then implement a particle-number-difference Maxwell demon using conditional operations on photon subsets in a multi-mode interferometer. This experiment probes the link between thermodynamics and information theory, showing how a photonic platform with single-photon resolution and quantum interference can be used to explore information-driven control of physical systems. The final part addresses quantum computation, where we demonstrate a boson-sampling-accelerated Monte Carlo integrator. This hybrid quantum–classical algorithm represents one of the few proposals to extend boson sampling toward practical applications while plausibly retaining its computational hardness. We validate the method in a proof-of-principle experiment reproducing perturbative corrections in a model inspired by Efimov physics. Altogether, the results presented in this thesis position integrated photonics as both a scalable hardware platform for multi-photon experiments and a versatile tool for advancing quantum simulation and computation.

•Sep 23, 2025•0 citations
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.
Boson sampling is a leading platform for exploring many-body quantum interference in linear optical systems. However, identifying circuit-level operating regimes where quantum signatures remain robust under realistic conditions remains challenging. In this work, multimode photonic boson sampling is investigated using a programmable six mode integrated photonic circuit composed of cascaded beam splitters and tunable phase shifters. Each beam splitter is realized through directional couplers combined with local phase control, enabling arbitrary unitary transformations within the linear optical circuit. The circuit is modeled using a tight-binding Hamiltonian allowing controlled manipulation of optical phases and inter-mode coupling that directly governs multiphoton interference pathways. This set up is utilised to do the analysis of Heavy Output Generation (HOG), Total Variation Distance (TVD) and Linear Cross-Entropy Benchmarking (XEB), together with configuration-resolved probability differences, for up to five photons. Distinct dynamic regimes associated with coherent evolution, optimal interference and phase dispersion induced mixing is identified. The results further reveal a photon number dependent complexity–fragility trade-off and demonstrate the robustness of TVD to symmetric photon loss under post-selection. Overall, this work establishes a circuit-relevant validation framework linking programmable interferometer parameters, phase control and quantum interference metrics, providing guidance for scalable photonic boson-sampling implementations in the NISQ regime.
Abstract Boson Sampling is a task that is conjectured to be computationally hard for a classical computer, but which can be efficiently solved by linear-optical interferometers with Fock state inputs. Significant advances have been reported in the last few years, with demonstrations of small- and medium-scale devices, as well as implementations of variants such as Gaussian Boson Sampling. Besides the relevance of this class of computational models in the quest for unambiguous experimental demonstrations of quantum advantage, recent results have also proposed the first applications for hybrid quantum computing. Here, we introduce the adoption of non-linear photon–photon interactions in the Boson Sampling framework, and analyze the enhancement in complexity via an explicit linear-optical simulation scheme. By extending the computational expressivity of Boson Sampling, the introduction of non-linearities promises to disclose novel functionalities for this class of quantum devices. Hence, our results are expected to lead to new applications of near-term, restricted photonic quantum computers.
We show that boson sampling with an arbitrary mmm-mode interferometer and n≤mn\le mn≤m single-photon inputs can be simulated to inverse-polynomial total-variation error by a logarithmic-depth qubit circuit with polynomially many qubits. The circuit uses Clifford+TTT gates, arbitrary qubit connectivity, and a single final measurement, and its family is logspace uniform. The key idea is to enlarge the optical system, decompose the resulting transformation into six quadratic shears, and distribute each mode over many submodes. This redistribution permits a fixed local occupation cutoff, after which local basis changes and parallel phase gates give the qubit circuit. Consequently, our result places boson sampling within shallow quantum computation.
The implementation of large-scale universal quantum computation represents a challenging and ambitious task on the road to quantum processing of information. In recent years, an intermediate approach has been pursued to demonstrate quantum computational advantage via non-universal computational models. A relevant example for photonic platforms has been provided by the Boson Sampling paradigm and its variants, which are known to be computationally hard while requiring at the same time only the manipulation of the generated photonic resources via linear optics and detection. Beside quantum computational advantage demonstrations, a promising direction towards possibly useful applications can be found in the field of quantum machine learning, considering the currently almost unexplored intermediate scenario between non-adaptive linear optics and universal photonic quantum computation. Here, we report the experimental implementation of quantum machine learning protocols by adding adaptivity via post-selection to a Boson Sampling platform based on universal programmable photonic circuits fabricated via femtosecond laser writing. Our experimental results demonstrate that Adaptive Boson Sampling is a viable route towards dimension-enhanced quantum machine learning with linear optical devices. Extending quantum photonics’ capabilities from simple linear-optics-based schemes to universal quantum computing presents several challenges, but intermediate regimes with some degree of adaptivity might already bring practical advantages. Here, the authors experimentally emulate an adaptive Boson Sampling scheme using post-selection, and apply it to a data classification task.
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.
This dissertation explores the use of single photons in integrated photonic circuits as a platform for quantum computation and quantum simulation. In the noisy intermediate-scale quantum (NISQ) era, photonic implementations of boson sampling provide one of the most promising routes to demonstrating quantum advantage, while also enabling insight-driven experiments that probe many-body interference and computational complexity. The first part of the thesis is devoted to the hardware development and characterization of programmable silicon nitride photonic processors. We demonstrate large-scale multi-photon interference in a 20-mode universal processor, establishing the potential of integrated photonics for scaling up boson sampling experiments. In parallel, we introduce a validation protocol based on detector binning, implemented on a 12-mode predecessor of the device. Together, these studies advance the photonic platform itself, focusing on scalability, versatility, and benchmarking, rather than direct applications. The second part turns to quantum simulation. We first present a photonic simulation of a spin-foam amplitude from loop quantum gravity, illustrating how multi-photon interference can provide a testbed for problems in fundamental physics. We then implement a particle-number-difference Maxwell demon using conditional operations on photon subsets in a multi-mode interferometer. This experiment probes the link between thermodynamics and information theory, showing how a photonic platform with single-photon resolution and quantum interference can be used to explore information-driven control of physical systems. The final part addresses quantum computation, where we demonstrate a boson-sampling-accelerated Monte Carlo integrator. This hybrid quantum–classical algorithm represents one of the few proposals to extend boson sampling toward practical applications while plausibly retaining its computational hardness. We validate the method in a proof-of-principle experiment reproducing perturbative corrections in a model inspired by Efimov physics. Altogether, the results presented in this thesis position integrated photonics as both a scalable hardware platform for multi-photon experiments and a versatile tool for advancing quantum simulation and computation.