Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Quantum circuit compilation and hybrid computation using Pauli-based computation
F. C. R. Peres, E. Galvão·Mar 3, 2022
Pauli-based computation (PBC) is driven by a sequence of adaptively chosen, non-destructive measurements of Pauli observables. Any quantum circuit written in terms of the Clifford+T gate set and having tT gates can be compiled into a PBC on t qubits....
Quantum Deep Reinforcement Learning for Robot Navigation Tasks
Hans Hohenfeld, D. Heimann, Felix Wiebe +1 more·Feb 24, 2022
We utilize hybrid quantum deep reinforcement learning to learn navigation tasks for a simple, wheeled robot in simulated environments of increasing complexity. For this, we train parameterized quantum circuits (PQCs) with two different encoding strat...
Hybrid Quantum-classical Search Algorithms
A. Rosmanis·Feb 23, 2022
Search is one of the most commonly used primitives in quantum algorithm design. It is known that quadratic speedups provided by Grover’s algorithm are optimal, and no faster quantum algorithms for Search exist. While it is known that at least some qu...
An LLVM-based C++ Compiler Toolchain for Variational Hybrid Quantum-Classical Algorithms and Quantum Accelerators
Pradnya Khalate, Xin-Chuan Wu, S. Premaratne +6 more·Feb 22, 2022
Variational algorithms are a representative class of quantum computing workloads that combine quantum and classical computing. This paper presents an LLVM-based C++ compiler toolchain to efficiently execute variational hybrid quantum-classical algori...
Improved Variational Quantum Eigensolver Via Quasidynamical Evolution
M. Jattana, F. Jin, H. Raedt +1 more·Feb 21, 2022
The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There are proble...
Quantum Computing of Schwarzschild-de Sitter Black Holes and Kantowski-Sachs Cosmology
Amy Joseph, Tristen White, V. Chandra +1 more·Feb 20, 2022
The quantum mechanics of Schwarzschild-de Sitter black holes is of great recent interest because of their peculiar thermodynamic properties as well as their realization in modern dark energy cosmology which indicates the presence of a small positive ...
Study of Feature Importance for Quantum Machine Learning Models
Aaron K. Baughman, Kavitha Yogaraj, Rajat Hebbar +3 more·Feb 18, 2022
Feature or predictor importance is a crucial part of data preprocessing pipelines in classical machine learning. Since classical data is used in many quantum machine learning models, feature importance is equally important for quantum machine learnin...
Pulse based Variational Quantum Optimal Control for hybrid quantum computing
R. Keijzer, O. Tse, S. Kokkelmans·Feb 17, 2022
This work studies pulse based variational quantum algorithms (VQAs), which are designed to determine the ground state of a quantum mechanical system by combining classical and quantum hardware. In contrast to more standard gate based methods, pulse b...
The Platypus of the Quantum Channel Zoo
Felix Leditzky, D. Leung, Vikesh Siddhu +2 more·Feb 16, 2022
Understanding quantum channels and the strange behavior of their capacities is a key objective of quantum information theory. Here we study a remarkably simple, low-dimensional, single-parameter family of quantum channels with exotic quantum informat...
Towards AutoQML: A Cloud-Based Automated Circuit Architecture Search Framework
Ra'ul Berganza G'omez, Corey O’Meara, G. Cortiana +2 more·Feb 16, 2022
The learning process of classical machine learning algorithms is tuned by hyperparameters that need to be customized to best learn and generalize from an input dataset. In recent years, Quantum Machine Learning (QML) has been gaining traction as a po...
Quantum Neuron with Separable-State Encoding
London Cavaletto, L. Candelori, A. Matos-Abiague·Feb 16, 2022
The use of advanced quantum neuron models for pattern recognition applications requires fault tolerance. Therefore, it is not yet possible to test such models on a large scale in currently available quantum processors. As an alternative, we propose a...
Range dependent Hamiltonian algorithms for numerical QUBO formulation
Hyunju Lee, Kyungtaek Jun·Feb 15, 2022
With the advent and development of quantum computers, various quantum algorithms that can solve linear equations and eigenvalues faster than classical computers have been developed. In particular, a hybrid solver provided by D-Wave’s Leap quantum clo...
High-frequency traveling-wave phononic cavity with sub-micron wavelength
Xin-Biao Xu, Jia-Qi Wang, Yuancai Yang +7 more·Feb 15, 2022
Thin-film gallium nitride (GaN) is a promising platform for phononic integrated circuits that hold great potential for scalable information processing processors. Here, an unsuspended traveling phononic resonator based on a high-acoustic-index-contra...
Uncovering Instabilities in Variational-Quantum Deep Q-Networks
Maja Franz, Luca Wolf, Maniraman Periyasamy +5 more·Feb 10, 2022
Deep Reinforcement Learning (RL) has considerably advanced over the past decade. At the same time, state-of-the-art RL algorithms require a large computational budget in terms of training time to converge. Recent work has started to approach this pro...
An Evolutionary Pathway for the Quantum Internet Relying on Secure Classical Repeaters
G. Long, Dong Pan, Yu‐Bo Sheng +3 more·Feb 8, 2022
Until quantum repeaters become mature, quantum networks remain restricted either to limited areas of directly connected nodes or to nodes connected to a common node. We circumvent this limitation by conceiving quantum networks using secure classical ...
Hybrid Quantum Annealing for Larger-than-QPU Lattice-structured Problems
Jack Raymond, R. Stevanovic, William Bernoudy +6 more·Feb 7, 2022
Quantum processing units (QPUs) executing annealing algorithms have shown promise in optimization and simulation applications. Hybrid algorithms are a natural bridge to larger applications. We present a simple greedy method for solving larger-than-QP...
Classically optimized variational quantum eigensolver with applications to topological phases
K. Okada, Keita Osaki, K. Mitarai +1 more·Feb 7, 2022
Variational quantum eigensolver (VQE) is regarded as a promising candidate of hybrid quantum-classical algorithm for the near-term quantum computers. Meanwhile, VQE is confronted with a challenge that statistical error associated with the measurement...
Parallel quantum chemistry on noisy intermediate-scale quantum computers
Robert Schade, C. Bauer, Konstantin Tamoev +3 more·Feb 4, 2022
A novel parallel hybrid quantum-classical algorithm for the solution of the quantum-chemical ground-state energy problem on gate-based quantum computers is presented. This approach is based on the reduced density-matrix functional theory (RDMFT) form...
Observation of Wave-Packet Branching through an Engineered Conical Intersection
Christopher S. Wang, N. Frattini, Benjamin J. Chapman +4 more·Feb 4, 2022
In chemical reactions, the interplay between coherent evolution and dissipation is central to determining key properties such as the rate and yield. Of particular interest are cases where two potential energy surfaces cross at features known as conic...
Hybrid Quantum-Classical Algorithm for Hydrodynamics
Julien Zylberman, G. Molfetta, M. Brachet +2 more·Feb 2, 2022
A new model of nonlinear charged quantum relativistic fluids is presented. This model can be discretized into Discrete Time Quantum Walks (DTQWs), and a new hybrid (quantum-classical) algorithm for implementing these walks on NISQ devices is proposed...