arXiv: Quantum Physics
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#1Yi-Cheng Wang (NTU: National Taiwan University)
#2Jhih-Shih YouH-Index: 10
Last. H. H. Jen
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Explorations of symmetry and topology have led to important breakthroughs in quantum optics, but much richer behaviour arise from the non-Hermitian nature of interactions of light with matter. Recently an optical mirror has been realized by using subwavelength arrays of atomic reflectors, which display the cooperative optical effects resulting from the photon-mediated dipole-dipole interactions. The loss processes associated with free space emission intrinsically endow the optical mirror with ca...
#1Hua YangH-Index: 7
#2J. Y. MaH-Index: 1
Last. Luming DuanH-Index: 57
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Trapped ions constitute one of the most promising systems for implementing quantum computing and networking. For large-scale ion-trap-based quantum computers and networks, it is critical to have two types of qubits, one for computation and storage, while the other for auxiliary operations like runtime qubit detection, sympathetic cooling, and repetitive entanglement generation through photon links. Dual-type qubits have previously been realized in hybrid systems using two ion species, which, how...
#1Mahdi Chehimi (Virginia Tech)H-Index: 1
#2Walid Saad (Virginia Tech)H-Index: 75
Quantum machine learning (QML) has emerged as a promising field that leans on the developments in quantum computing to explore large complex machine learning problems. Recently, some purely quantum machine learning models were proposed such as the quantum convolutional neural networks (QCNN) to perform classification on quantum data. However, all of the existing QML models rely on centralized solutions that cannot scale well for large-scale and distributed quantum networks. Hence, it is apropos ...
#1Samuel Yen-Chi Chen (BNL: Brookhaven National Laboratory)H-Index: 9
#2Shinjae Yoo (BNL: Brookhaven National Laboratory)H-Index: 19
Last. Yao-Lung L. Fang (BNL: Brookhaven National Laboratory)H-Index: 9
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Long short-term memory (LSTM) is a kind of recurrent neural networks (RNN) for sequence and temporal dependency data modeling and its effectiveness has been extensively established. In this work, we propose a hybrid quantum-classical model of LSTM, which we dub QLSTM. We demonstrate that the proposed model successfully learns several kinds of temporal data. In particular, we show that for certain testing cases, this quantum version of LSTM converges faster, or equivalently, reaches a better accu...
#1Sam KeramatiH-Index: 2
#2Will Brunner (UNL : University of Nebraska–Lincoln)
Last. Herman BatelaanH-Index: 19
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The statistical character of electron beams used in current technologies, as described by a stream of particles, is random in nature. Using coincidence measurements of femtosecond pulsed electron pairs, we report the observation of sub-Poissonian electron statistics that are non-random due to two-electron Coulomb interactions, and that exhibit an anti-bunching signal of 1 part in 4. This advancement is a fundamental step towards realizing a strongly quantum degenerate electron beam needed for ma...
#1Davide FerrariH-Index: 21
#2Michele AmorettiH-Index: 16
Quantum compilation is the problem of translating an input quantum circuit into the most efficient equivalent of itself, taking into account the characteristics of the device that will execute the computation. Compilation strategies are composed of sequential passes that perform placement, routing and optimization tasks. Noise-adaptive compilers do take the noise statistics of the device into account, for some or all passes. The noise statics can be obtained from calibration data, and updated af...
#1N.L. HarshmanH-Index: 1
#2A.C. KnappH-Index: 1
The standard topological approach to indistinguishable particles formulates exchange statistics by using the fundamental group to analyze the connectedness of the configuration space. Although successful in two and more dimensions, this approach gives only trivial or near trivial exchange statistics in one dimension because two-body coincidences are excluded from configuration space. Instead, we include these path-ambiguous singular points and consider configuration space as an orbifold. This or...
#1Lena FunckeH-Index: 8
#2Tobias HartungH-Index: 6
Last. Paolo StornatiH-Index: 3
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The design of parametric quantum circuits (PQCs) for efficient use in variational quantum simulations (VQS) is subject to two competing factors. On one hand, the set of states that can be generated by the PQC has to be large enough to contain the solution state. Otherwise, one may at best find the best approximation of the solution restricted to the states generated by the chosen PQC. On the other hand, the PQC should contain as few parametric quantum gates as possible to minimize noise from the...
#1Giovanni IannelliH-Index: 1
#2Karl JansenH-Index: 38
The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm used to find the ground state of a Hamiltonian using variational methods. In the context of this Lattice symposium, the procedure can be used to study lattice gauge theories (LGTs) in the Hamiltonian formulation. Bayesian optimization (BO) based on Gaussian process regression (GPR) is a powerful algorithm for finding the global minimum of a cost function, e.g. the energy, with a very low number of iterations using ...
#2Lena FunckeH-Index: 8
Last. Thomas WeberH-Index: 5
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Readout errors are among the most dominant errors on current noisy intermediate-scale quantum devices. Recently, an efficient and scaleable method for mitigating such errors has been developed, based on classical bit-flip correction. In this talk, we compare the performance of this method for IBM's and Rigetti's quantum devices, demonstrating how the method improves the noisy measurements of observables obtained on the quantum hardware. Moreover, we examine the variance amplification to the data...
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