Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Estimation of one-dimensional discrete-time quantum walk parameters by using machine learning algorithms
Parth Rajauria, Prateek Chawla, C. M. Chandrashekar·Jul 9, 2020
Estimation of the coin parameter(s) is an important part of the problem of implementing more robust schemes for quantum simulation using quantum walks. We present the estimation of the quantum coin parameter used for one-dimensional discrete-time qua...
Quantum Fan-out: Circuit Optimizations and Technology Modeling
P. Gokhale, S. Koretsky, Shilin Huang +4 more·Jul 8, 2020
Instruction scheduling is a key compiler optimization in quantum computing, just as it is for classical computing. Current schedulers optimize for data parallelism by allowing simultaneous execution of instructions, as long as their qubits do not ove...
Stabilizer extent is not multiplicative
Arne Heimendahl, Felipe Montealegre-Mora, F. Vallentin +1 more·Jul 8, 2020
The Gottesman-Knill theorem states that a Clifford circuit acting on stabilizer states can be simulated efficiently on a classical computer. Recently, this result has been generalized to cover inputs that are close to a coherent superposition of loga...
A Quantum Finite Automata Approach to Modeling the Chemical Reactions
A. Bhatia, Shenggen Zheng·Jul 8, 2020
In recent years, the modeling interest has increased significantly from molecular level to atomic and quantum levels. Computational chemistry plays a significant role in designing computational models for the operation and simulation of systems rangi...
Adiabatic quantum state transfer in a semiconductor quantum-dot spin chain
Y. Kandel, Haifeng Qiao, S. Fallahi +3 more·Jul 8, 2020
Semiconductor quantum-dot spin qubits are a promising platform for quantum computation, because they are scalable and possess long coherence times. In order to realize this full potential, however, high-fidelity information transfer mechanisms are re...
Wishart and random density matrices: Analytical results for the mean-square Hilbert-Schmidt distance
Santosh Kumar·Jul 6, 2020
Hilbert-Schmidt distance is one of the prominent distance measures in quantum information theory which finds applications in diverse problems, such as construction of entanglement witnesses, quantum algorithms in machine learning, and quantum-state t...
Quantum State Learning via Single-Shot Measurements.
Sang Min Lee, H. Park, Jinhyoung Lee +2 more·Jul 6, 2020
A novel machine-learning algorithm based on single-shot measurements, named single-shot measurement learning, is demonstrated achieving the theoretical optimal accuracy. The method is at least as efficient as existing tomographic schemes and computat...
Preparing symmetry broken ground states with variational quantum algorithms
N. Vogt, S. Zanker, Jan-Michael Reiner +3 more·Jul 3, 2020
One of the most promising applications for near term quantum computers is the simulation of physical quantum systems, particularly many-electron systems in chemistry and condensed matter physics. In solid state physics, finding the correct symmetry b...
Quantum Simulation with Hybrid Tensor Networks.
Xiao Yuan, Jinzhao Sun, Junyu Liu +2 more·Jul 2, 2020
Tensor network theory and quantum simulation are, respectively, the key classical and quantum computing methods in understanding quantum many-body physics. Here, we introduce the framework of hybrid tensor networks with building blocks consisting of ...
Boltzmann machine learning with a variational quantum algorithm
Yuta Shingu, Yuya Seki, S. Watabe +5 more·Jul 2, 2020
Boltzmann machine is a powerful tool for modeling probability distributions that govern the training data. A thermal equilibrium state is typically used for Boltzmann machine learning to obtain a suitable probability distribution. The Boltzmann machi...
Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
Z. Cai·Jul 2, 2020
Noise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large q...
Just Like the Real Thing: Fast Weak Simulation of Quantum Computation
S. Hillmich, I. Markov, R. Wille·Jul 1, 2020
Quantum computers promise significant speedups in solving problems intractable for conventional computers but, despite recent progress, remain limited in scaling and availability. Therefore, quantum software and hardware development heavily rely on s...
Quantum spectral clustering
Iordanis Kerenidis, Jonas Landman·Jul 1, 2020
Spectral clustering is a powerful unsupervised machine learning algorithm for clustering data with non convex or nested structures. With roots in graph theory, it uses the spectral properties of the Laplacian matrix to project the data in a low dimen...
Quantum optimal control with quantum computers: A hybrid algorithm featuring machine learning optimization
D. Castaldo, Marta Rosa, S. Corni·Jul 1, 2020
We develop a hybrid quantum-classical algorithm to solve an optimal population transfer problem for a molecule subject to a laser pulse. The evolution of the molecular wave function under the laser pulse is simulated on a quantum computer, while the ...
Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer
Elijah Pelofske, Georg Hahn, H. Djidjev·Jun 29, 2020
NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search ...
Reinforcement Learning for Digital Quantum Simulation.
Adrien Bolens, M. Heyl·Jun 29, 2020
Digital quantum simulation on quantum computers provides the potential to simulate the unitary evolution of any many-body Hamiltonian with bounded spectrum by discretizing the time evolution operator through a sequence of elementary quantum gates. A ...
Faster Digital Quantum Simulation by Symmetry Protection
Minh C. Tran, Yuan Su, D. Carney +1 more·Jun 29, 2020
Simulating the dynamics of quantum systems is an important application of quantum computers and has seen a variety of implementations on current hardware. We show that by introducing quantum gates implementing unitary transformations generated by the...
Quantum simulation of the qubit-regularized O(3)-sigma model
Alex Buser, T. Bhattacharya, L. Cincio +1 more·Jun 28, 2020
Recently, Singh and Chandrasekharan showed that fixed points of the non-linear $O(3)$ sigma model can be reproduced near a quantum phase transition of a spin model with just two qubits per lattice site. In this paper, we demonstrate how to prepare th...
Efficient 2D Tensor Network Simulation of Quantum Systems
Yuchen Pang, Tianyi Hao, Annika Dugad +2 more·Jun 26, 2020
Simulation of quantum systems is challenging due to the exponential size of the state space. Tensor networks provide a systematically improvable approximation for quantum states. 2D tensor networks such as Projected Entangled Pair States (PEPS) are w...
Quantum Computing for Finance: State-of-the-Art and Future Prospects
D. Egger, Claudio Gambella, Jakub Marecek +6 more·Jun 25, 2020
This article outlines our point of view regarding the applicability, state-of-the-art, and potential of quantum computing for problems in finance. We provide an introduction to quantum computing as well as a survey on problem classes in finance that ...