JFJoseph F. Fitzsimons

Joseph F. Fitzsimons

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Joseph F. Fitzsimons has a total of 157 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Experimental Quantum Homomorphic Encryption Using a Quantum Photonic Chip

    by Yuan Li, Lin Cao, Wei Luo, Hui Zhang, Hong Cai, Muhammad Faeyz Karim, Feng Gao, Joseph Fitzsimons, Qinghua Song, Ai-Qun Liu

    A fully homomorphic encryption system enables computation on encrypted data without the necessity for prior decryption. This facilitates the seamless establishment of a secure quantum channel, bridging the server and client components, and thereby providing the client with secure access to the server’s substantial computational capacity for executing quantum operations. However, traditional homomorphic encryption systems lack scalability, programmability, and stability. In this Letter, we experimentally demonstrate a proof-of-concept implementation of a homomorphic encryption scheme on a compact quantum chip, verifying the feasibility of using photonic chips for quantum homomorphic encryption. Our work not only provides a solution for circuit expansion, addressing the longstanding challenge of scalability while significantly reducing the size of quantum network infrastructure, but also lays the groundwork for the development of highly sophisticated quantum fully homomorphic encryption systems.


  • Open Access

    Cross-Verification of Independent Quantum Devices

    by C. Greganti, T. F. Demarie, M. Ringbauer, J. A. Jones, V. Saggio, I. Alonso Calafell, L. A. Rozema, A. Erhard, M. Meth, L. Postler, et al.

    Quantum computers are on the brink of surpassing the capabilities of even the most powerful classical computers, which naturally raises the question of how one can trust the results of a quantum computer when they cannot be compared to classical simulation Here, we present a cross-verification technique that exploits the principles of measurement-based quantum computation to link quantum circuits of different input size, depth, and structure. Our technique enables consistency checks of quantum computations between independent devices, as well as within a single device. We showcase our protocol by applying it to five state-of-the-art quantum processors, based on four distinct physical architectures: nuclear magnetic resonance, superconducting circuits, trapped ions, and photonics, with up to six qubits and up to 200 distinct circuits.


  • Compiling basic linear algebra subroutines for quantum computers

    by Liming Zhao, Zhikuan Zhao, Patrick Rebentrost, Joseph Fitzsimons


  • Open Access

    Experimental quantum homomorphic encryption

    by Jonas Zeuner, Ioannis Pitsios, Si-Hui Tan, Aditya N. Sharma, Joseph F. Fitzsimons, Roberto Osellame, Philip Walther

    Quantum computers promise not only to outperform classical machines for certain important tasks, but also to preserve privacy of computation. For example, the blind quantum computing protocol enables secure delegated quantum computation, where a client can protect the privacy of their data and algorithms from a quantum server assigned to run the computation. However, this security comes with the practical limitation that the client and server must communicate after each step of computation. A practical alternative is homomorphic encryption, which does not require any interactions, while providing quantum-enhanced data security for a variety of computations. In this scenario, the server specifies the computation to be performed, and the client provides only the input data, thus enabling secure noninteractive computation. Here, we demonstrate homomorphic-encrypted quantum computing with unitary transformations of individual qubits, as well as multi-qubit quantum walk computations using single-photon states and non-birefringent integrated optics. The client encrypts their input in the photons’ polarization state, while the server performs the computation using the path degree of freedom. Our demonstration using integrated quantum photonics underlines the applicability of homomorphic-encrypted quantum computations, and shows the potential for delegated quantum computing using photons.


  • Open Access

    Causal limit on quantum communication

    by Robert Pisarczyk, Zhikuan Zhao, Yingkai Ouyang, Vlatko Vedral, Joseph F. Fitzsimons

    The capacity of a channel is known to be equivalent to the highest rate at which it can generate entanglement. Analogous to entanglement, the notion of a causality measure characterises the temporal aspect of quantum correlations. Despite holding an equally fundamental role in physics, temporal quantum correlations have yet to find their operational significance in quantum communication. Here we uncover a connection between quantum causality and channel capacity. We show the amount of temporal correlations between two ends of the noisy quantum channel, as quantified by a causality measure, implies a general upper bound on its channel capacity. The expression of this new bound is simpler to evaluate than most previously known bounds. We demonstrate the utility of this bound by applying it to a class of shifted depolarizing channels, which results in improvement over previously calculated bounds for this class of channels.

  • Open Access

    Cross-verification of independent quantum devices

    by C. Greganti, T. F. Demarie, M. Ringbauer, J. A. Jones, V. Saggio, I. A. Calafell, L. A. Rozema, A. Erhard, M. Meth, L. Postler, et al.

    Quantum computers are on the brink of surpassing the capabilities of even the most powerful classical computers. This naturally raises the question of how one can trust the results of a quantum computer when they cannot be compared to classical simulation. Here we present a verification technique that exploits the principles of measurement-based quantum computation to link quantum circuits of different input size, depth, and structure. Our approach enables consistency checks of quantum computations within a device, as well as between independent devices. We showcase our protocol by applying it to five state-of-the-art quantum processors, based on four distinct physical architectures: nuclear magnetic resonance, superconducting circuits, trapped ions, and photonics, with up to 6 qubits and 200 distinct circuits.

  • Client-friendly continuous-variable blind and verifiable quantum computing

    by Nana Liu, Tommaso F. Demarie, Si-Hui Tan, Leandro Aolita, Joseph F. Fitzsimons

    We present a verifiable and blind protocol for assisted universal quantum computing on continuous-variable (CV) platforms. This protocol is experimentally friendly to the client, as it only requires Gaussian-operation capabilities from the latter. Moreover, the server does not require universal quantum-computational power either, its only function being to supply the client with copies of a single-mode non-Gaussian state. Universality is attained based on state injection of the server's non-Gaussian supplies. The protocol is automatically blind because the non-Gaussian resource requested to the server is always the same, regardless of the specific computation. Verification, in turn, is possible thanks to an efficient non-Gaussian state fidelity test where we assume identical state preparation by the server. It is based on Gaussian measurements by the client on the injected states, which is potentially interesting on its own. The division of quantum hardware between client and server assumed here is in agreement with the experimental constraints expected in realistic schemes for CV cloud quantum computing.


  • Causal Limit on Quantum Communication

    by Robert Pisarczyk, Zhikuan Zhao, Yingkai Ouyang, Vlatko Vedral, Joseph F. Fitzsimons

    The capacity of a channel is known to be equivalent to the highest rate at which it can generate entanglement. Analogous to entanglement, the notion of a causality measure characterizes the temporal aspect of quantum correlations. Despite holding an equally fundamental role in physics, temporal quantum correlations have yet to find their operational significance in quantum communication. Here we uncover a connection between quantum causality and channel capacity. We show the amount of temporal correlations between two ends of the noisy quantum channel, as quantified by a causality measure, implies a general upper bound on its channel capacity. The expression of this new bound is simpler to evaluate than most previously known bounds. We demonstrate the utility of this bound by applying it to a class of shifted depolarizing channels, which results in improvement over previously known bounds for this class of channels.


  • Measurement-driven analog of adiabatic quantum computation for frustration-free Hamiltonians

    by Liming Zhao, Carlos A. Pérez-Delgado, Simon C. Benjamin, Joseph F. Fitzsimons

    The adiabatic quantum algorithm has drawn intense interest as a potential approach to accelerating optimization tasks using quantum computation. The algorithm is most naturally realized in systems which support Hamiltonian evolution rather than discrete gates. We explore an alternative approach in which slowly varying measurements are used to mimic adiabatic evolution. We show that, for certain Hamiltonians, which remain frustration free all along the adiabatic path, the necessary measurements can be implemented through the measurement of random terms from the Hamiltonian. This offers a potentially more viable method of realizing adiabatic evolution in gate-based quantum computer architectures.


  • Quantum algorithms for training Gaussian processes

    by Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons

    Gaussian processes (GPs) are important models in supervised machine learning. Training in Gaussian processes refers to selecting the covariance functions and the associated parameters in order to improve the outcome of predictions, the core of which amounts to evaluating the logarithm of the marginal likelihood (LML) of a given model. The LML gives a concrete measure of the quality of prediction that a GP model is expected to achieve. The classical computation of the LML typically carries a polynomial time overhead with respect to the input size. We propose a quantum algorithm that computes the logarithm of the determinant of a Hermitian matrix, which runs in logarithmic time for sparse matrices. This is applied in conjunction with a variant of the quantum linear system algorithm that allows for logarithmic-time computation of the form yTA−1y, where y is a dense vector and A is the covariance matrix. We hence show that quantum computing can be used to estimate the LML of a GP with exponentially improved efficiency under certain conditions.