Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Dynamic linear response quantum algorithm
A. Roggero, J. Carlson·Apr 4, 2018
The dynamic linear response of a quantum system is critical for understanding both the structure and dynamics of strongly interacting quantum systems, including neutron scattering from materials, photon and electron scattering from atomic systems, an...
From Symmetric Pattern-Matching to Quantum Control (Extended Version)
A. Sabry, Benoît Valiron, J. K. Vizzotto·Apr 3, 2018
One perspective on quantum algorithms is that they are classical algorithms having access to a special kind of memory with exotic properties. This perspective suggests that, even in the case of quantum algorithms, the control flow notions of sequenci...
Steering random spin systems to speed up the quantum adiabatic algorithm
A. B. Özgüler, R. Joynt, M. Vavilov·Apr 3, 2018
A general time-dependent quantum system can be driven fast from its initial ground state to its final ground state without generating transitions by adding a steering term to the Hamiltonian. We show how this technique can be modified to improve on t...
Controllable Photonic Time-Bin Qubits from a Quantum Dot
J. P. Lee, J. P. Lee, L. Wells +10 more·Apr 2, 2018
Photonic time bin qubits are well suited to transmission via optical fibres and waveguide circuits. The states take the form $\frac{1}{\sqrt{2}}(\alpha \ket{0} + e^{i\phi}\beta \ket{1})$, with $\ket{0}$ and $\ket{1}$ referring to the early and late t...
Channel fidelities for high-fidelity approach in KLM scheme
Kazuto Oshima·Apr 1, 2018
We study channel fidelity for the high-fidelity approach in the Knill-Laflamme-Milburn (KLM) scheme. We examine an optimal channel fidelity f_{opt} and identify the corresponding KLM ancilla state. In the limit of large n, where 2n is the number of t...
A note on state preparation for quantum machine learning
Zhikuan Zhao, V. Dunjko, Jack K. Fitzsimons +2 more·Apr 1, 2018
The intersection between the fields of machine learning and quantum information processing is proving to be a fruitful field for the discovery of new quantum algorithms, which potentially offer an exponential speed-up over their classical counterpart...
The Impact of Quantum Computing on Present Cryptography
Vasileios Mavroeidis, Kamer Vishi, Mateusz Zych +1 more·Mar 31, 2018
The aim of this paper is to elucidate the implications of quantum computing in present cryptography and to introduce the reader to basic post-quantum algorithms. In particular the reader can delve into the following subjects: present cryptographic sc...
Quantum Algorithm to Cubic Spline Interpolation
Changpeng Shao·Mar 31, 2018
HHL algorithm \cite{harrow} to solve linear system is a powerful and efficient quantum technique to deal with many matrix operations (such as matrix multiplication, powers and inversion). It inspires many applications in quantum machine learning \cit...
Performing fully parallel constraint logic programming on a quantum annealer
S. Pakin·Mar 30, 2018
Abstract A quantum annealer exploits quantum effects to solve a particular type of optimization problem. The advantage of this specialized hardware is that it effectively considers all possible solutions in parallel, thereby potentially outperforming...
An efficient high dimensional quantum Schur transform
H. Krovi·Mar 30, 2018
The Schur transform is a unitary operator that block diagonalizes the action of the symmetric and unitary groups on an n fold tensor product V⊗n of a vector space V of dimension d. Bacon, Chuang and Harrow [5] gave a quantum algorithm for this transf...
Towards quantum machine learning with tensor networks
W. Huggins, P. Patil, B. Mitchell +2 more·Mar 30, 2018
Machine learning is a promising application of quantum computing, but challenges remain for implementation today because near-term devices have a limited number of physical qubits and high error rates. Motivated by the usefulness of tensor networks f...
Quantum speedup in solving the maximal-clique problem
Weng-Long Chang, Qi Yu, Zhaokai Li +3 more·Mar 29, 2018
The maximal clique problem, to find the maximally sized clique in a given graph, is classically an NP-complete computational problem, which has potential applications ranging from electrical engineering, computational chemistry, bioinformatics to soc...
Barren plateaus in quantum neural network training landscapes
J. McClean, S. Boixo, V. Smelyanskiy +2 more·Mar 29, 2018
Many experimental proposals for noisy intermediate scale quantum devices involve training a parameterized quantum circuit with a classical optimization loop. Such hybrid quantum-classical algorithms are popular for applications in quantum simulation,...
Quantum algorithms for training Gaussian Processes
Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne +2 more·Mar 28, 2018
Gaussian processes (GPs) are important models in supervised machine learning. Training in Gaussian processes refers to selecting the covariance functions and the associated parameters in order to improve the outcome of predictions, the core of which ...
Glassy Phase of Optimal Quantum Control.
A. Day, M. Bukov, P. Weinberg +2 more·Mar 28, 2018
We study the problem of preparing a quantum many-body system from an initial to a target state by optimizing the fidelity over the family of bang-bang protocols. We present compelling numerical evidence for a universal spin-glasslike transition contr...
Controllable two-photon interference with versatile quantum frequency processor
Hsuan-Hao Lu, J. Lukens, N. Peters +3 more·Mar 28, 2018
Quantum information is the next frontier in information science, promising unconditionally secure communications, enhanced channel capacities, and computing capabilities far beyond their classical counterparts. And as quantum information processing d...
Using Gaussian Boson Sampling to Find Dense Subgraphs.
J. Arrazola, T. Bromley·Mar 28, 2018
Boson sampling devices are a prime candidate for exhibiting quantum supremacy, yet their application for solving problems of practical interest is less well understood. Here we show that Gaussian boson sampling (GBS) can be used for dense subgraph id...
Anomalous Joule law in the adiabatic dynamics of a normal-superconductor quantum dot
L. Arrachea, Rosa López·Mar 27, 2018
We formulate a general theory to study the time-dependent charge and energy transport of an adiabatically driven quantum dot in contact to normal and superconducting reservoirs at T = 0. This setup is a generalization of a quantum RC circuit, with ca...
Quantum machine learning for electronic structure calculations
Rongxin Xia, S. Kais·Mar 27, 2018
Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations—alongside impressive results using machine learning techniques for computation—hybridizing quantum computing with m...
Quantum Chemistry Calculations on a Trapped-Ion Quantum Simulator
Cornelius Hempel, C. Maier, J. Romero +10 more·Mar 27, 2018
Quantum-classical hybrid algorithms are emerging as promising candidates for near-term practical applications of quantum information processors in a wide variety of fields ranging from chemistry to physics and materials science. We report on the expe...