Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Learning-Based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing
Minrui Xu, D. Niyato, Jiawen Kang +2 more·Nov 12, 2022
In this paper, a novel paradigm of mobile edgequantum computing (MEQC) is proposed, which brings quantum computing capacities to mobile edge networks that are closer to mobile users (i.e., edge devices). First, we propose an MEQC system model where m...
Quantum Algorithm for Estimating Largest Eigenvalues
Nhat A. Nghiem, T. Wei·Nov 11, 2022
A majority of numerical scientific computation relies heavily on handling and manipulating matrices, such as solving linear equations, finding eigenvalues and eigenvectors, and so on. Many quantum algorithms have been developed to advance these compu...
Quantum power flows: from theory to practice
Junyu Liu, Hang Zheng, M. Hanada +2 more·Nov 10, 2022
The high-level integration of spatial-dispersed renewable energies can greatly enlarge future smart grid size and complicate system operations. Existing numerical methods based on classical computational oracles may be challenged to fulfill efficienc...
Hybrid Quantum Neural Network for Drug Response Prediction
A. Sagingalieva, Mohammad Kordzanganeh, Nurbolat Kenbayev +3 more·Nov 10, 2022
Simple Summary This work successfully employs a novel approach in processing patient and drug data to predict the drug response for cancer patients. The approach uses a deep quantum computing circuit as part of a machine learning architecture to simu...
Ising formulation of integer optimization problems for utilizing quantum annealing in iterative improvement strategy
Shuntaro Okada, Masayuki Ohzeki·Nov 8, 2022
Quantum annealing is a heuristic algorithm for searching the ground state of an Ising model. Heuristic algorithms aim to obtain near-optimal solutions with a reasonable computation time. Accordingly, many algorithms have so far been proposed. In gene...
Analytical Formulation of the Second-Order Derivative of Energy for the Orbital-Optimized Variational Quantum Eigensolver: Application to Polarizability.
Yuya O. Nakagawa, Jiabao Chen, Shotaro Sudo +2 more·Nov 7, 2022
We develop a quantum-classical hybrid algorithm to calculate the analytical second-order derivative of the energy for the orbital-optimized variational quantum eigensolver (OO-VQE), which is a method to calculate eigenenergies of a given molecular Ha...
Toward Neural Network Simulation of Variational Quantum Algorithms
Oliver Knitter, J. Stokes, S. Veerapaneni·Nov 5, 2022
Variational quantum algorithms (VQAs) utilize a hybrid quantum–classical architecture to recast problems of high-dimensional linear algebra as ones of stochastic optimization. Despite the promise of leveraging near- to intermediate-term quantum resou...
Analog Quantum Variational Embedding Classifier
Rui Yang, Samuel Bosch, B. Kiani +2 more·Nov 4, 2022
Quantum machine learning has the potential to provide powerful algorithms for artificial intelligence. The pursuit of quantum advantage in quantum machine learning is an active area of research. For current noisy, intermediate-scale quantum (NISQ) co...
Faster variational quantum algorithms with quantum kernel-based surrogate models
Alistair W. R. Smith, A. Paige, Myungshik S. Kim·Nov 2, 2022
We present a new optimization strategy for small-to-intermediate scale variational quantum algorithms (VQAs) on noisy near-term quantum processors which uses a Gaussian process surrogate model equipped with a classically-evaluated quantum kernel. VQA...
Time-optimal control of driven oscillators by variational circuit learning
Tangyou Huang, Yongcheng Ding, L. Dupays +4 more·Nov 1, 2022
The simulation of quantum dynamics on a digital quantum computer with parameterized circuits has widespread applications in fundamental and applied physics and chemistry. In this context, using the hybrid quantum-classical algorithm, combining classi...
Rotation-inspired circuit cut optimization
G. Uchehara, T. Aamodt, Olivia Di Matteo·Nov 1, 2022
Recent works have demonstrated that large quantum circuits can be cut and decomposed into smaller clusters of quantum circuits with fewer qubits that can be executed independently on a small quantum computer. Classical post-processing then combines t...
Tierkreis: a Dataflow Framework for Hybrid Quantum-Classical Computing
Seyon Sivarajah, Lukas Heidemann, A. Lawrence +1 more·Nov 1, 2022
We present Tierkreis, a higher-order dataflow graph program representation and runtime designed for compositional, quantum-classical hybrid algorithms. The design of the system is motivated by the remote nature of quantum computers, the need for hybr...
Quantum Natural Language Generation on Near-Term Devices
Amin Karamlou, Marcel Pfaffhauser, James R. Wootton·Nov 1, 2022
The emergence of noisy medium-scale quantum devices has led to proof-of-concept applications for quantum computing in various domains. Examples include Natural Language Processing (NLP) where sentence classification experiments have been carried out,...
QNet: A Quantum-Native Sequence Encoder Architecture
Wei-Yen Day, Hao Chen, Min Sun·Oct 31, 2022
This work proposes QNet, a novel sequence encoder model that entirely inferences on the quantum computer using a minimum number of qubits. Let n and $d$ represent the length of the sequence and the embedding size, respectively. The dot-product attent...
Classical ensemble of Quantum-classical ML algorithms for Phishing detection in Ethereum transaction networks
Anupama Ray, Sai Sakunthala Guddanti, Vishnu Ajith +1 more·Oct 30, 2022
Ethereum is one of the most valuable blockchain networks in terms of the total monetary value locked in it, and arguably been the most active network where new blockchain innovations in research and applications are demonstrated. But, this also leads...
Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry
Po-Yu Kao, Ya-Chu Yang, Wei-Yin Chiang +3 more·Oct 30, 2022
De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time- and resource-consuming, and it has a low probability of success. Recent advances in machine learni...
Classification of Hybrid Quantum-Classical Computing
F. Phillipson, N. Neumann, R. Wezeman·Oct 27, 2022
As quantum computers mature, the applicability in practice becomes more important. Many uses of quantum computers will be hybrid, with classical computers still playing an important role in operating and using the quantum computer. The term hybrid is...
Universal robust quantum gates by geometric correspondence of noisy quantum evolution
Yong-Ju Hai, Junning Li, Junkai Zeng +2 more·Oct 26, 2022
A key to the next leap in quantum technologies and quantum computing relies on precise and robust control over noisy quantum systems. For the first time, our theory uncovers an essential correspondence between the driven noisy quantum evolution and m...
Implementation of Trained Factorization Machine Recommendation System on Quantum Annealer
Chen-Yu Liu, Hsin-Yu Wang, Pei-Yen Liao +2 more·Oct 24, 2022
Factorization Machine (FM) is the most commonly used model to build a recommendation system since it can incorporate side information to improve performance. However, producing item suggestions for a given user with a trained FM is time-consuming. To...
Track reconstruction at the LUXE experiment using quantum algorithms
Arianna Crippa, L. Funcke, T. Hartung +8 more·Oct 24, 2022
LUXE (Laser Und XFEL Experiment) is a proposed experiment at DESY which will study Quantum Electrodynamics (QED) in the strong-field regime, where QED becomes non-perturbative. Measuring the rate of created electron-positron pairs using a silicon pix...