Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Hierarchical qubit maps and hierarchically implemented quantum error correction
N. Klco, M. Savage·Sep 5, 2021
We consider hierarchically implemented quantum error correction (HI-QEC), in which the fidelities of logical qubits are differentially optimized to enhance the capabilities of quantum devices in scientific applications. By employing qubit representat...
Towards a Larger Molecular Simulation on the Quantum Computer: Up to 28 Qubits Systems Accelerated by Point Group Symmetry
Changsu Cao, Jiaqi Hu, Wengang Zhang +7 more·Sep 5, 2021
The exact evaluation of the molecular ground state in quantum chemistry requires an exponentially increasing computational cost. Quantum computation is a promising way to overcome the exponential problem using polynomial-time quantum algorithms. A qu...
A review of Quantum Neural Networks: Methods, Models, Dilemma
Ren-Xin Zhao, Shi Wang·Sep 4, 2021
The rapid development of quantum computer hardware has laid the hardware foundation for the realization of QNN. Due to quantum properties, QNN shows higher storage capacity and computational efficiency compared to its classical counterparts. This art...
Medical image classification via quantum neural networks
Natansh Mathur, Jonas Landman, Yun Li +4 more·Sep 4, 2021
Machine Learning provides powerful tools for a variety of applications, including disease diagnosis through medical image classification. In recent years, quantum machine learning techniques have been put forward as a way to potentially enhance perfo...
Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability
V. Pascuzzi, M. Goli·Sep 3, 2021
High-performance computing (HPC) is a major driver accelerating scientific research and discovery, from quantum simulations to medical therapeutics. While the increasing availability of HPC resources is in many cases pivotal to successful science, ev...
Arnoldi-Lindblad time evolution: Faster-than-the-clock algorithm for the spectrum of time-independent and Floquet open quantum systems
F. Minganti, Dolf Huybrechts·Sep 3, 2021
The characterization of open quantum systems is a central and recurring problem for the development of quantum technologies. For time-independent systems, an (often unique) steady state describes the average physics once all the transient processes h...
Speed limits for two-qubit gates with weakly anharmonic qubits
S. Ashhab, F. Yoshihara, T. Fuse +3 more·Sep 3, 2021
We consider the implementation of two-qubit gates when the physical systems used to realize the qubits possess additional quantum states in the accessible energy range. We use optimal control theory to determine the maximum achievable gate speed for ...
Exploring finite temperature properties of materials with quantum computers
Connor Powers, Lindsay Bassman Oftelie, Daan Camps +1 more·Sep 3, 2021
Thermal properties of nanomaterials are crucial to not only improving our fundamental understanding of condensed matter systems, but also to developing novel materials for applications spanning research and industry. Since quantum effects arise at th...
Accelerating Variational Quantum Algorithms Using Circuit Concurrency
Salonik Resch, Anthony Gutierrez, J. Huh +5 more·Sep 3, 2021
Variational quantum algorithms (VQAs) provide a promising approach to achieve quantum advantage in the noisy intermediate-scale quantum era. In this era, quantum computers experience high error rates and quantum error detection and correction is not ...
omg blueprint for trapped ion quantum computing with metastable states
D. Allcock, W. C. Campbell, J. Chiaverini +7 more·Sep 3, 2021
Quantum computers, much like their classical counterparts, will likely benefit from flexible qubit encodings that can be matched to different tasks. For trapped ion quantum processors, a common way to access multiple encodings is to use multiple, co-...
Equation-of-Motion Theory to Calculate Accurate Band Structures with a Quantum Computer.
Yi-Wei Fan, Jie Liu, Zhenyu Li +1 more·Sep 3, 2021
Band structure is a cornerstone to understand the electronic properties of materials. Accurate band structure calculations using a high-level quantum chemistry theory can be computationally very expensive. It is promising to speed up such calculation...
High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware
J. Nelson, Marc Vuffray, A. Lokhov +2 more·Sep 3, 2021
Quantum Annealing (QA) was originally intended for accelerating the solution of combinatorial optimization tasks that have natural encodings as Ising models. However, recent experiments on QA hardware platforms have demonstrated that, in the operatin...
Data science and Machine learning in the Clouds: A Perspective for the Future
H. Barua·Sep 2, 2021
As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and astronomy...
Quantum design for advanced qubits: plasmonium
Feng-Ming Liu, Ming-Cheng Chen, Can Wang +8 more·Sep 2, 2021
: The increasingly complex quantum electronic circuits with a number of coupled quantum degrees of freedom will become intractable to be simulated on classical computers, and requires quantum computers for an efficient simulation. In turn, it will be...
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?
Samson Wang, Piotr Czarnik, A. Arrasmith +3 more·Sep 2, 2021
Variational Quantum Algorithms (VQAs) are often viewed as the best hope for near-term quantum advantage. However, recent studies have shown that noise can severely limit the trainability of VQAs, e.g., by exponentially flattening the cost landscape a...
Quantum algorithm for structure learning of Markov Random Fields
Liming Zhao, Siyi Yang, P. Rebentrost·Sep 2, 2021
Markov random fields (MRFs) appear in many problems in machine learning and statistics. From a computational learning theory point of view, a natural problem of learning MRFs arises: given samples from an MRF from a restricted class, learn the struct...
Exploring variational quantum eigensolver ansatzes for the long-range XY model
Jia-bin You, Dax Enshan Koh, J. Kong +3 more·Sep 1, 2021
Finding the ground state energy and wavefunction of a quantum many-body system is a key problem in quantum physics and chemistry. We study this problem for the long-range XY model by using the variational quantum eigensolver (VQE) algorithm. We consi...
Hexagonal boron nitride as a low-loss dielectric for superconducting quantum circuits and qubits
J. Wang, M. Yamoah, Qing Li +19 more·Aug 31, 2021
Dielectrics with low loss at microwave frequencies are imperative for high-coherence solid-state quantum computing platforms. Here we study the dielectric loss of hexagonal boron nitride (hBN) thin films in the microwave regime by measuring the quali...
Quantum Communication Using Semiconductor Quantum Dots
Daniel A. Vajner, L. Rickert, T. Gao +2 more·Aug 31, 2021
Worldwide, enormous efforts are directed toward the development of the so‐called quantum internet. Turning this long‐sought‐after dream into reality is a great challenge that will require breakthroughs in quantum communication and computing. To estab...
Quantum outage probability for time-varying quantum channels
Josu Etxezarreta Martinez, Patricio Fuentes, P. Crespo +1 more·Aug 31, 2021
Recent experimental studies have shown that the relaxation time, T1, and the dephasing time, T2, of superconducting qubits fluctuate considerably over time. Time-varying quantum channel (TVQC) models have been proposed in order to consider the time v...