Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Best-approximation error for parametric quantum circuits
L. Funcke, T. Hartung, K. Jansen +3 more·Jul 15, 2021
In Variational Quantum Simulations, the construction of a suitable parametric quantum circuit is subject to two counteracting effects. The number of parameters should be small for the device noise to be manageable, but also large enough for the circu...
Divide and Conquer for Combinatorial Optimization and Distributed Quantum Computation
T. Tomesh, Zain Saleem, M. Perlin +3 more·Jul 15, 2021
Scaling the size of monolithic quantum computer systems is a difficult task. As the number of qubits within a device increases, a number of factors contribute to decreases in yield and performance. To meet this challenge, distributed architectures co...
Variational quantum simulation of thermal statistical states on a superconducting quantum processer
X. Guo 郭, S. Li 李, Xiao 骁 Xiao 效 +11 more·Jul 13, 2021
Quantum computers promise to solve finite-temperature properties of quantum many-body systems, which is generally challenging for classical computers due to high computational complexities. Here, we report experimental preparations of Gibbs states an...
Implementable hybrid quantum ant colony optimization algorithm
Mikel Garcia de Andoin, J. Echanobe·Jul 8, 2021
We propose a new hybrid quantum algorithm based on the classical Ant Colony Optimization algorithm to produce approximate solutions for NP-hard problems, in particular optimization problems. First, we discuss some previously proposed Quantum Ant Colo...
Quantum Local Search with the Quantum Alternating Operator Ansatz
T. Tomesh, Zain Saleem, Martin Suchara·Jul 8, 2021
We present a new hybrid, local search algorithm for quantum approximate optimization of constrained combinatorial optimization problems. We focus on the Maximum Independent Set problem and demonstrate the ability of quantum local search to solve larg...
Unbiasing fermionic quantum Monte Carlo with a quantum computer
W. Huggins, B. O’Gorman, N. Rubin +3 more·Jun 30, 2021
Interacting many-electron problems pose some of the greatest computational challenges in science, with essential applications across many fields. The solutions to these problems will offer accurate predictions of chemical reactivity and kinetics, and...
A hybrid algorithm to solve linear systems of equations with limited qubit resources
Fang Gao, Guojian Wu, Mingyu Yang +2 more·Jun 29, 2021
The solution of linear systems of equations is a very frequent operation and thus important in many fields. The complexity using classical methods increases linearly with the size of equations. The HHL algorithm proposed by Harrow et al. achieves exp...
Experimental Quantum Embedding for Machine Learning
I. Gianani, Ivana Mastroserio, L. Buffoni +6 more·Jun 25, 2021
The classification of big data usually requires a mapping onto new data clusters which can then be processed by machine learning algorithms by means of more efficient and feasible linear separators. Recently, Lloyd et al. have advanced the proposal t...
Overcoming Barriers to Scalability in Variational Quantum Monte Carlo
Tianchen Zhao, Saibal De, Brian Chen +2 more·Jun 24, 2021
The variational quantum Monte Carlo (VQMC) method received significant attention in the recent past because of its ability to overcome the curse of dimensionality inherent in many-body quantum systems. Close parallels exist between VQMC and the emerg...
Quantum-classical hybrid algorithm for the simulation of all-electron correlation.
Jan-Niklas Boyn, A. Lykhin, Scott E. Smart +2 more·Jun 22, 2021
While chemical systems containing hundreds to thousands of electrons remain beyond the reach of quantum devices, hybrid quantum-classical algorithms present a promising pathway toward a quantum advantage. Hybrid algorithms treat the exponentially sca...
QFCNN: Quantum Fourier Convolutional Neural Network
Feihong Shen, Jun Liu·Jun 19, 2021
The neural network and quantum computing are both significant and appealing fields, with their interactive disciplines promising for large-scale computing tasks that are untackled by conventional computers. However, both developments are restricted b...
Moving beyond the Transmon: Noise-Protected Superconducting Quantum Circuits
A. Gyenis, A. Di Paolo, J. Koch +3 more·Jun 18, 2021
Artificial atoms realized by superconducting circuits offer unique opportunities to store and process quantum information with high fidelity. Among them, implementations of circuits that harness intrinsic noise protection have been rapidly developed ...
Experimental Demonstrations of Native Implementation of Boolean Logic Hamiltonian in a Superconducting Quantum Annealer
D. Saida, Y. Yamanashi, M. Hidaka +4 more·Jun 16, 2021
Experimental demonstrations of quantum annealing with “native” implementation of Boolean logic Hamiltonians are reported. As a superconducting integrated circuit, a problem Hamiltonian whose set of ground states is consistent with a given truth table...
Photoluminescence spectra of point defects in semiconductors: Validation of first-principles calculations
Yu Jin, M. Govoni, G. Wolfowicz +4 more·Jun 16, 2021
Optically and magnetically active point defects in semiconductors are interesting platforms for the development of solid-state quantum technologies. Their optical properties are usually probed by measuring photoluminescence spectra, which provide inf...
Reconfigurable continuously-coupled 3D photonic circuit for Boson Sampling experiments
Francesco Hoch, S. Piacentini, Taira Giordani +10 more·Jun 15, 2021
Boson Sampling is a computational paradigm representing one of the most viable and pursued approaches to demonstrate the regime of quantum advantage. Recent results have shown significant technological leaps in single-photon generation and detection,...
Variational Quanvolutional Neural Networks with enhanced image encoding
Denny Mattern, Darya Martyniuk, Henri Willems +2 more·Jun 14, 2021
Image classification is an important task in various machine learning applications. In recent years, a number of classification methods based on quantum machine learning and different quantum image encoding techniques have been proposed. In this pape...
Slowing quantum decoherence of oscillators by hybrid processing
Kimin Park, Jacob Hastrup, Jonas S Neergaard-Nielsen +3 more·Jun 14, 2021
Quantum information encoded into the superposition of coherent states is an illustrative representation of practical applications of macroscopic quantum coherence possessing. However, these states are very sensitive to energy loss, losing their non-c...
Defect-Free Arbitrary-Geometry Assembly of Mixed-Species Atom Arrays.
Cheng Sheng, Jiayi Hou, Xiaodong He +8 more·Jun 11, 2021
Optically trapped mixed-species single atom arrays with arbitrary geometry are an attractive and promising platform for various applications, because tunable quantum systems with multiple components provide extra degrees of freedom for experimental c...
Matrix product state pre-training for quantum machine learning
J. Dborin, F. Barratt, V. Wimalaweera +2 more·Jun 10, 2021
Hybrid quantum–classical algorithms are a promising candidate for developing uses for NISQ devices. In particular, parametrised quantum circuits (PQCs) paired with classical optimizers have been used as a basis for quantum chemistry and quantum optim...
Variational Quantum-Neural Hybrid Eigensolver.
Shi-Xin Zhang, Z. Wan, Chee-Kong Lee +3 more·Jun 9, 2021
The variational quantum eigensolver (VQE) is one of the most representative quantum algorithms in the noisy intermediate-scale quantum (NISQ) era, and is generally speculated to deliver one of the first quantum advantages for the ground-state simulat...