Quantum federated learning(QFL)enables collaborative training of a quantum machine learning(QML)model among multiple clients possessing quantum computing capabilities,without the need to share their respective local d...Quantum federated learning(QFL)enables collaborative training of a quantum machine learning(QML)model among multiple clients possessing quantum computing capabilities,without the need to share their respective local data.However,the limited availability of quantum computing resources poses a challenge for each client to acquire quantum computing capabilities.This raises a natural question:Can quantum computing capabilities be deployed on the server instead?In this paper,we propose a QFL framework specifically designed for classical clients,referred to as CC-QFL,in response to this question.In each iteration,the collaborative training of the QML model is assisted by the shadow tomography technique,eliminating the need for quantum computing capabilities of clients.Specifically,the server constructs a classical representation of the QML model and transmits it to the clients.The clients encode their local data onto observables and use this classical representation to calculate local gradients.These local gradients are then utilized to update the parameters of the QML model.We evaluate the effectiveness of our framework through extensive numerical simulations using handwritten digit images from the MNIST dataset.Our framework provides valuable insights into QFL,particularly in scenarios where quantum computing resources are scarce.展开更多
This research aims to review the developments in the field of quantum private query(QPQ), a type of practical quantum cryptographic protocol. The primary protocol, as proposed by Jacobi et al., and the improvements in...This research aims to review the developments in the field of quantum private query(QPQ), a type of practical quantum cryptographic protocol. The primary protocol, as proposed by Jacobi et al., and the improvements in the protocol are introduced.Then, the advancements made in sability, theoretical security, and practical security are summarized. Additionally, we describe two new results concerning QPQ security. We emphasize that a procedure to detect outside adversaries is necessary for QPQ, as well as for other quantum secure computation protocols, and then briefly propose such a strategy. Furthermore, we show that the shift-and-addition or low-shift-and-addition technique can be used to obtain a secure real-world implementation of QPQ, where a weak coherent source is used instead of an ideal single-photon source.展开更多
In this study, we examine how the quantum circuit of the Advanced Encryption Standard(AES) can be optimized from two aspects, i.e., number of qubits and T-depth. To reduce the number of qubits, we present three kinds ...In this study, we examine how the quantum circuit of the Advanced Encryption Standard(AES) can be optimized from two aspects, i.e., number of qubits and T-depth. To reduce the number of qubits, we present three kinds of improved quantum circuits of S-box for different phases in the AES. We found that the number of qubits in the round function can be decreased by introducing the circuit sending |a> to |S(a)>. As a result, compared with the previous quantum circuits where 400/640/768 qubits are required,our circuits of AES-128/-192/-256 only require 270/334/398 qubits. To reduce the T-depth, we propose a new circuit of AES's S-box with a T-depth of 4. Accordingly, the T-depth of our AES-128/-192/-256 quantum circuits become 80/80/84 instead of120/120/126 in a previous study.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.62371069,62272056,and 62372048)Beijing Natural Science Foundation(Grant No.4222031)China Scholarship Council(Grant No.202006470011)。
文摘Quantum federated learning(QFL)enables collaborative training of a quantum machine learning(QML)model among multiple clients possessing quantum computing capabilities,without the need to share their respective local data.However,the limited availability of quantum computing resources poses a challenge for each client to acquire quantum computing capabilities.This raises a natural question:Can quantum computing capabilities be deployed on the server instead?In this paper,we propose a QFL framework specifically designed for classical clients,referred to as CC-QFL,in response to this question.In each iteration,the collaborative training of the QML model is assisted by the shadow tomography technique,eliminating the need for quantum computing capabilities of clients.Specifically,the server constructs a classical representation of the QML model and transmits it to the clients.The clients encode their local data onto observables and use this classical representation to calculate local gradients.These local gradients are then utilized to update the parameters of the QML model.We evaluate the effectiveness of our framework through extensive numerical simulations using handwritten digit images from the MNIST dataset.Our framework provides valuable insights into QFL,particularly in scenarios where quantum computing resources are scarce.
基金supported by the National Natural Science Foundation of China(Grant Nos.61672110,61572081,61671082,61702469,and61771439)
文摘This research aims to review the developments in the field of quantum private query(QPQ), a type of practical quantum cryptographic protocol. The primary protocol, as proposed by Jacobi et al., and the improvements in the protocol are introduced.Then, the advancements made in sability, theoretical security, and practical security are summarized. Additionally, we describe two new results concerning QPQ security. We emphasize that a procedure to detect outside adversaries is necessary for QPQ, as well as for other quantum secure computation protocols, and then briefly propose such a strategy. Furthermore, we show that the shift-and-addition or low-shift-and-addition technique can be used to obtain a secure real-world implementation of QPQ, where a weak coherent source is used instead of an ideal single-photon source.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61972048, and 61976024)Beijing Natural Science Foundation (Grant No. 4222031)。
文摘In this study, we examine how the quantum circuit of the Advanced Encryption Standard(AES) can be optimized from two aspects, i.e., number of qubits and T-depth. To reduce the number of qubits, we present three kinds of improved quantum circuits of S-box for different phases in the AES. We found that the number of qubits in the round function can be decreased by introducing the circuit sending |a> to |S(a)>. As a result, compared with the previous quantum circuits where 400/640/768 qubits are required,our circuits of AES-128/-192/-256 only require 270/334/398 qubits. To reduce the T-depth, we propose a new circuit of AES's S-box with a T-depth of 4. Accordingly, the T-depth of our AES-128/-192/-256 quantum circuits become 80/80/84 instead of120/120/126 in a previous study.