Blind quantum computation with a client performing different single-qubit gates

In the field of single-server blind quantum computation(BQC), a major focus is to make the client as classical as possible. To achieve this goal, we propose two single-server BQC protocols to achieve verifiable universal quantum computation. In these two protocols, the client only needs to perform either the gate T(in the first protocol) or the gates H and X(in the second protocol). With assistance from a single server, the client can utilize his quantum capabilities to generate some single-qubit states while keeping the actual state of these qubits confidential from others. By using these single-qubit states, the verifiable universal quantum computation can be achieved.

Analysis and improvement of verifiable blind quantum computation

In blind quantum computation(BQC),a client with weak quantum computation capabilities is allowed to delegate its quantum computation tasks to a server with powerful quantum computation capabilities,and the inputs,algorithms and outputs of the quantum computation are confidential to the server.Verifiability refers to the ability of the client to verify with a certain probability whether the server has executed the protocol correctly and can be realized by introducing trap qubits into the computation graph state to detect server deception.The existing verifiable universal BQC protocols are analyzed and compared in detail.The XTH protocol(proposed by Xu Q S,Tan X Q,Huang R in 2020),a recent improvement protocol of verifiable universal BQC,uses a sandglass-like graph state to further decrease resource expenditure and enhance verification capability.However,the XTH protocol has two shortcomings:limitations in the coloring scheme and a high probability of accepting an incorrect computation result.In this paper,we present an improved version of the XTH protocol,which revises the limitations of the original coloring scheme and further improves the verification ability.The analysis demonstrates that the resource expenditure is the same as for the XTH protocol,while the probability of accepting the wrong computation result is reduced from the original minimum(0.866)^(d*)to(0.819)^(d^(*)),where d;is the number of repeated executions of the protocol.

Quantum federated learning through blind quantum computing

Private distributed learning studies the problem of how multiple distributed entities collaboratively train a shared deep network with their private data unrevealed. With the security provided by the protocols of blind quantum computation, the cooperation between quantum physics and machine learning may lead to unparalleled prospect for solving private distributed learning tasks.In this paper, we introduce a quantum protocol for distributed learning that is able to utilize the computational power of the remote quantum servers while keeping the private data safe. For concreteness, we first introduce a protocol for private single-party delegated training of variational quantum classifiers based on blind quantum computing and then extend this protocol to multiparty private distributed learning incorporated with diferential privacy. We carry out extensive numerical simulations with diferent real-life datasets and encoding strategies to benchmark the efectiveness of our protocol. We find that our protocol is robust to experimental imperfections and is secure under the gradient attack after the incorporation of diferential privacy. Our results show the potential for handling computationally expensive distributed learning tasks with privacy guarantees, thus providing a valuable guide for exploring quantum advantages from the security perspective in the field of machine learning with real-life applications.