This article gives an overview and a perspective of recent theoretical proposals and their experimental implementations in the field of quantum machine learning. Without an aim to being exhaustive, the article reviews specific high-impact topics such as quantum reinforcement learning, quantum autoencoders, and quantum memristors, and their experimental realizations in the platforms of quantum photonics and superconducting circuits. The field of quantum machine learning could be among the first quantum technologies producing results that are beneficial for industry and, in turn, to society. Therefore, it is necessary to push forward initial quantum implementations of this technology, in Noisy Intermediate-Scale Quantum Computers, aiming for achieving fruitful calculations in machine learning that are better than with any other current or future computing paradigm.
We propose a scheme to implement quantum controlled NOT gate and quantum phase gate in an optomechanical system based on phonon blockade. For appropriate choices of system parameters, fidelities of both the quantum gate operations are very close to unity in the absence of dissipation. Using recently achieved experimental values in a mechanical resonator coupled to a microwave cavity, we show that the quantum gate can be realized experimentally with very high fidelity.
Fault-tolerant quantum computation with cluster states
由Raussendorf和Briegel引入的单向量子计算模型[Phys. Rev. Lett. 86（22），5188-5191（2001）]表明可以仅使用被称为簇态的固定纠缠资源和自适应单量子比特测量来进行量子计算。这个模型是几个实用的量子计算方案的基础，包括一个有希望的基于团簇态的光量子计算方案[M。A. Nielsen，arXiv：quant-ph/0402005，accepted to appear in Phys. Rev. Lett.].一个重要的开放问题是，这种建议是否是可扩展的存在物理现实的噪音。在本文中，我们证明了两个阈值定理，这表明，可扩展的容错量子计算可以实现基于集群状态的实现，提供的实现中的噪声是低于某个恒定的阈值。我们的第一个阈值定理适用于一类实现中，纠缠门应用确定性，但有少量的噪音。我们希望这个阈值能够适用于各种各样的物理系统。我们的第二个阈值定理是专门适应的建议，如光学集群状态的建议，其中使用非确定性纠缠门。一个关键的技术组成部分，我们的证明是两个强大的定理，关系到性能的噪音单一的操作限制作用于状态空间的子空间，这些操作的扩展作用于整个状态空间。
Theoretical study of a new method for the quantum computer implementation based on self-organizing structures: the essence of new proposals and argumentation
Kernel methods are used extensively in classical machine learning, especially in the field of pattern analysis. In this paper, we propose a kernel-based quantum machine learning algorithm that can be implemented on a near-term, intermediate scale quantum device. Our proposal is based on estimating classically intractable kernel functions, using a restricted quantum model known as deterministic quantum computing with one qubit. Our method provides a framework for studying the role of quantum correlations other than quantum entanglement for machine learning applications.
We have implemented a gated-based quantum version of a restricted Boltzmann machine for approximating the ground state of a Pauli-decomposed qubit Hamiltonian. During the implementation and evaluation, we have noticed a variety of unexpected topics. It starts from limitations due to the structure of the algorithm itself and continues with constraints induced by specific quantum software development kits, which did not (yet) support necessary features for an efficient implementation. In this paper we systematically summarize our findings and categorize them according to their relevance for the …
Universal quantum gates are the core elements in quantum information processing. We design two schemes to realize more general (SWAP)$^{1/m}$ and controlled--(swap)$^{1/m}$ gates (for integer $m\geq1$) by directing flying single photons to solid--state quantum dots. The parameter $m$ is easily controlled by adjusting two quarter--wave plates and one half--wave plate. Additional computational qubits are not required to construct the two gates. Evaluations of the gates indicate that our proposals are feasible with current experimental technology.
Shanghai University（上海大学）；University of the Basque Country UPV/EHU（巴斯克地区大学）；IKERBASQUE, Basque Foundation for Science（巴斯克科学基金会）
Quantum autoencoders allow for reducing the amount of resources in a quantum computation by mapping the original Hilbert space onto a reduced space with the relevant information. Recently, it was proposed to employ approximate quantum adders to implement quantum autoencoders in quantum technologies. Here, we carry out the experimental implementation of this proposal in the Rigetti cloud quantum computer employing up to three qubits. The experimental fidelities are in good agreement with the theoretical prediction, thus proving the feasibility to realize quantum autoencoders via quantum adders …
Quantum machine learning algorithms, the extensions of machine learning to quantum regimes, are believed to be more powerful as they leverage the power of quantum properties. Quantum machine learning methods have been employed to solve quantum many-body systems and have demonstrated accurate electronic structure calculations of lattice models, molecular systems, and recently periodic systems. A hybrid approach using restricted Boltzmann machines and a quantum algorithm to obtain the probability distribution that can be optimized classically is a promising method due to its efficiency and ease …
We devise an all-optical scheme for the generation of entangled multimode photonic states encoded in temporal modes of light. The scheme employs a nonlinear down-conversion process in an optical loop to generate one- and higher-dimensional tensor network states of light. We illustrate the principle with the generation of two different classes of entangled tensor network states and report on a variational algorithm to simulate the ground-state physics of many-body systems. We demonstrate that state-of-the-art optical devices are capable of determining the ground-state properties of the spin-1/2…
We adopt a geometric approach to describe the performance of adiabatic quantum machines, operating under slow time-dependent driving and in contact to two or more reservoirs with a temperature bias during all the cycle. We show that the problem of optimizing the power generation of a heat engine and the efficiency of both the heat engine and refrigerator operational modes is reduced to an isoperimetric problem with non-trivial underlying metrics and curvature. This corresponds to the maximization of the ratio between the area enclosed by a closed curve and its corresponding length. We illustra…
We propose an experiment to test the Weak Equivalence Principle (WEP) with a test mass consisting of two entangled atoms of different species. In the proposed experiment, a coherent measurement of the differential gravity acceleration between the two atomic species is considered, by entangling two atom interferometers operating on the two species. The entanglement between the two atoms is heralded at the initial beam splitter of the interferometers through the detection of a single photon emitted by either of the atoms, together with the impossibility of distinguishing which atom emitted the p…
