Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Quantum-classical simulation of two-site dynamical mean-field theory on noisy quantum hardware
Trevor Keen, T. Maier, S. Johnston +1 more·Oct 21, 2019
We report on a quantum–classical simulation of the single-band Hubbard model using two-site dynamical mean-field theory (DMFT). Our approach uses IBM’s superconducting qubit chip to compute the zero-temperature impurity Green’s function in the time d...
A simple approach to design quantum neural networks and its applications to kernel-learning methods
Changpeng Shao·Oct 19, 2019
We give an explicit simple method to build quantum neural networks (QNNs) to solve classification problems. Besides the input (state preparation) and output (amplitude estimation), it has one hidden layer which uses a tensor product of $\log M$ two-d...
Quantum locally linear embedding for nonlinear dimensionality reduction
Xi He, Li Sun, Chufan Lyu +1 more·Oct 17, 2019
Reducing the dimension of nonlinear data is crucial in data processing and visualization. The locally linear embedding algorithm (LLE) is specifically a representative nonlinear dimensionality reduction method with maintaining well the original manif...
Precise measurement of quantum observables with neural-network estimators
G. Torlai, G. Mazzola, Giuseppe Carleo +1 more·Oct 16, 2019
The measurement precision of modern quantum simulators is intrinsically constrained by the limited set of measurements that can be efficiently implemented on hardware. This fundamental limitation is particularly severe for quantum algorithms where co...
Variational fast forwarding for quantum simulation beyond the coherence time
Cristina Cîrstoiu, Zoe Holmes, Joseph Iosue +3 more·Oct 9, 2019
Trotterization-based, iterative approaches to quantum simulation (QS) are restricted to simulation times less than the coherence time of the quantum computer (QC), which limits their utility in the near term. Here, we present a hybrid quantum-classic...
Robust and efficient algorithms for high-dimensional black-box quantum optimization
Z. Leng, Pranav S. Mundada, Saeed Ghadimi +1 more·Oct 8, 2019
Hybrid quantum-classical optimization using near-term quantum technology is an emerging direction for exploring quantum advantage in high-dimensional systems. However, precise characterization of all experimental parameters is often impractical and c...
Quantum Hamiltonian-Based Models and the Variational Quantum Thermalizer Algorithm
Guillaume Verdon, Jacob A. Marks, Sasha Nanda +2 more·Oct 4, 2019
We introduce a new class of generative quantum-neural-network-based models called Quantum Hamiltonian-Based Models (QHBMs). In doing so, we establish a paradigmatic approach for quantum-probabilistic hybrid variational learning, where we efficiently ...
Stochastic gradient descent for hybrid quantum-classical optimization
R. Sweke, Frederik Wilde, Johannes Jakob Meyer +4 more·Oct 2, 2019
Within the context of hybrid quantum-classical optimization, gradient descent based optimizers typically require the evaluation of expectation values with respect to the outcome of parameterized quantum circuits. In this work, we explore the conseque...
Nonunitary Operations for Ground-State Calculations in Near-Term Quantum Computers.
G. Mazzola, Pauline J. Ollitrault, P. Barkoutsos +1 more·Sep 27, 2019
We introduce a quantum Monte Carlo inspired reweighting scheme to accurately compute energies from optimally short quantum circuits. This effectively hybrid quantum-classical approach features both entanglement provided by a short quantum circuit, an...
On the need for large Quantum depth
Nai-Hui Chia, Kai-Min Chung, C. Lai·Sep 23, 2019
Near-term quantum computers are likely to have small depths due to short coherence time and noisy gates. A natural approach to leverage these quantum computers is interleaving them with classical computers. Understanding the capabilities and limits o...
Hybrid kernel polynomial method
M. Irfan, Sathish R. Kuppuswamy, D. Varjas +4 more·Sep 20, 2019
The kernel polynomial method allows to sample overall spectral properties of a quantum system, while sparse diagonalization provides accurate information about a few important states. We present a method combining these two approaches without loss of...
Efficient evaluation of Pauli strings with entangled measurements
Ikko Hamamura, T. Imamichi·Sep 19, 2019
The advent of cloud quantum computing accelerates development of quantum algorithms. In particular, it is essential to study variational quantum-classical hybrid algorithms, which are executable on Noisy Intermediate-Scale Quantum (NISQ) computers. E...
An Adaptive Optimizer for Measurement-Frugal Variational Algorithms
Jonas M. Kübler, A. Arrasmith, L. Cincio +1 more·Sep 19, 2019
Variational hybrid quantum-classical algorithms (VHQCAs) have the potential to be useful in the era of near-term quantum computing. However, recently there has been concern regarding the number of measurements needed for convergence of VHQCAs. Here, ...
Hybrid quantum error correction in qubit architectures
L. B. Kristensen, M. Kjaergaard, C. K. Andersen +1 more·Sep 19, 2019
Noise and errors are inevitable parts of any practical implementation of a quantum computer. As a result, large-scale quantum computation will require ways to detect and correct errors on quantum information. Here, we present such a quantum error cor...
Adiabatic Quantum Kitchen Sinks for Learning Kernels Using Randomized Features.
M. Noori, Seyed Shakib Vedaie, Inderpreet Singh +4 more·Sep 17, 2019
Quantum information processing is likely to have far-reaching impact in the field of artificial intelligence. While the race to build an error-corrected quantum computer is ongoing, noisy, intermediate-scale quantum (NISQ) devices provide an immediat...
Learning adiabatic quantum algorithms for solving optimization problems
D. Pastorello, E. Blanzieri·Sep 15, 2019
An adiabatic quantum algorithm is essentially given by three elements: An initial Hamiltonian with known ground state, a problem Hamiltonian whose ground state corresponds to the solution of the given problem and an evolution schedule such that the a...
Nondestructive classification of quantum states using an algorithmic quantum computer
D. Babukhin, A. Zhukov, W. Pogosov·Sep 12, 2019
Methods of processing quantum data become more important as quantum computing devices improve their quality towards fault tolerant universal quantum computers. These methods include discrimination and filtering of quantum states given as an input to ...
Dimensional tuning of Majorana fermions and real space counting of the Chern number
Eric Mascot, S. Cocklin, S. Rachel +1 more·Sep 12, 2019
Chiral superconductors have the ability to host topologically protected Majorana zero modes which have been proposed as future qubits for topological quantum computing. The recently introduced magnet--superconductor hybrid (MSH) systems consisting of...
Variational Quantum Linear Solver
Carlos Bravo-Prieto, Ryan Larose, M. Cerezo +3 more·Sep 12, 2019
Previously proposed quantum algorithms for solving linear systems of equations cannot be implemented in the near term due to the required circuit depth. Here, we propose a hybrid quantum-classical algorithm, called Variational Quantum Linear Solver (...
Parallel in time dynamics with quantum annealers
Konrad Jalowiecki, A. Więckowski, P. Gawron +1 more·Sep 11, 2019
Recent years have witnessed an unprecedented increase in experiments and hybrid simulations involving quantum computers. In particular, quantum annealers. There exist a plethora of algorithms promising to outperform classical computers in the near-te...