Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning
Hari Chittoor, P. Griffin, Ariel Neufeld +2 more·Dec 18, 2024
Long-term time series forecasting (LTSF) involves predicting a large number of future values of a time series based on the past values. This is an essential task in a wide range of domains including weather forecasting, stock market analysis and dise...
Assessing fault-tolerant quantum advantage for $k$-SAT with structure
Martijn Brehm, Jordi Weggemans·Dec 17, 2024
For many problems, quantum algorithms promise speedups over their classical counterparts. However, these results predominantly rely on asymptotic worst-case analysis, which overlooks significant overheads due to error correction and the fact that rea...
SentiQNF: A Novel Approach to Sentiment Analysis Using Quantum Algorithms and Neuro-Fuzzy Systems
Kshitij Dave, Nouhaila Innan, B. Behera +3 more·Dec 17, 2024
Sentiment analysis is an essential component of natural language processing, used to analyze sentiments, attitudes, and emotional tones in various contexts. It provides valuable insights into public opinion, customer feedback, and user experiences. R...
Factoring an integer with three oscillators and a qubit
Lukas Brenner, Libor Caha, Xavier Coiteux-Roy +1 more·Dec 17, 2024
A common starting point of traditional quantum algorithm design is the notion of a universal quantum computer with a scalable number of qubits. This convenient abstraction mirrors classical computations manipulating bits. It allows for a device-indep...
Hybrid of Gradient Descent and Semidefinite Programming for Certifying Multipartite Entanglement Structure
Kai Wu, Zhihua Chen, Zhen-Peng Xu +2 more·Dec 13, 2024
Multipartite entanglement is a crucial resource for a wide range of quantum information processing tasks, including quantum metrology, quantum computing, and quantum communication. The verification of multipartite entanglement, along with an understa...
Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning
Kuan-Cheng Chen, Samuel Yen-Chi Chen, Chen-Yu Liu +1 more·Dec 12, 2024
In this paper, we introduce Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning (Dist-QTRL), a novel approach to addressing the scalability challenges of traditional Reinforcement Learning (RL) by integrating quantum computing principl...
Application of quantum annealing for scalable robotic assembly line optimization: a case study
Moritz Willmann, Marcel Albus, Jan Schnabel +1 more·Dec 12, 2024
The even distribution and optimization of tasks across resources and workstations is a critical process in manufacturing aimed at maximizing efficiency, productivity, and profitability, known as Robotic Assembly Line Balancing (RALB). With the increa...
Minimizing resource overhead in fusion-based quantum computation using hybrid spin-photon devices
Stephen C. Wein, Timothée Goubault de Brugière, Luka Music +3 more·Dec 11, 2024
We present three schemes for constructing a (2,2)-Shor-encoded 6-ring photonic resource state for fusion-based quantum computing, each relying on a different type of photon source. We benchmark these architectures by analyzing their ability to achiev...
A quantum-classical reinforcement learning model to play Atari games
Dominik Freinberger, Julian Lemmel, R. Grosu +1 more·Dec 11, 2024
Recent advances in reinforcement learning have demonstrated the potential of quantum learning models based on parametrized quantum circuits as an alternative to deep learning models. On the one hand, these findings have shown the ultimate exponential...
A clustering aggregation algorithm on neutral-atoms and annealing quantum processors
Riccardo Scotti, Gabriella Bettonte, A. Costantini +3 more·Dec 10, 2024
This work presents a hybrid quantum-classical algorithm to perform clustering aggregation, designed for neutral-atoms quantum computers and quantum annealers. Clustering aggregation is a technique that mitigates the weaknesses of clustering algorithm...
Quantum Computing in Corrosion Modeling: Bridging Research and Industry
Juan Manuel Aguiar Hualde, Marek Kowalik, Lian Remme +7 more·Dec 10, 2024
Corrosion presents a major challenge to the longevity and reliability of products across various industries, particularly in the aerospace sector. Corrosion arises from chemical processes occurring on an atomistic scale, which lead to macroscopic deg...
Towards Novel Tunability Schemes for Hybrid Ferromagnetic Transmon Qubits
H. G. Ahmad, R. Ferraiuolo, G. Serpico +12 more·Dec 9, 2024
Flux tuning of qubit frequencies in superconducting quantum processors is fundamental for implementing single and multi-qubit gates in quantum algorithms. Typical architectures involve the use of DC or fast RF lines. However, these lines introduce si...
Cutting is All You Need: Execution of Large-Scale Quantum Neural Networks on Limited-Qubit Devices
Alberto Marchisio, Emman Sychiuco, Muhammad Kashif +1 more·Dec 6, 2024
The rapid advancement in Quantum Computing, particularly through Noisy-Intermediate Scale Quantum (NISQ) devices, has spurred significant interest in Quantum Machine Learning (QML) applications. Despite their potential, fully-quantum algorithms remai...
Computational Advantage in Hybrid Quantum Neural Networks: Myth or Reality?
Muhammad Kashif, Alberto Marchisio, Muhammad Shafique·Dec 6, 2024
Hybrid Quantum Neural Networks (HQNNs), under the umbrella of Quantum Machine Learning (QML), have garnered significant attention due to their potential to enhance computational performance by integrating quantum layers within traditional neural netw...
Generating graph states with a single quantum emitter and the minimum number of fusions
M. C. Löbl, Love A. Pettersson, Andrew Jena +3 more·Dec 5, 2024
Graph states are the key resources for measurement- and fusion-based quantum computing with photons, yet their creation is experimentally challenging. We optimize a hybrid graph-state generation scheme using a single quantum emitter and linear optics...
Lean Classical‐Quantum Hybrid Neural Network Model for Image Classification
A. Liu, Cuihong Wen, Jieci Wang·Dec 3, 2024
The integration of algorithms from quantum information with neural networks has enabled unprecedented advancements in various domains. Nonetheless, the application of quantum machine learning algorithms for image classification predominantly relies o...
A Quantum Computing Approach to Simulating Corrosion Inhibition
Karim Elgammal, Marc Maußner·Dec 1, 2024
This work demonstrates a systematic implementation of hybrid quantum-classical computational methods for investigating corrosion inhibition mechanisms on aluminum surfaces. We present an integrated workflow combining density functional theory (DFT) w...
Unitary-transformed projective squeezing: applications for circuit-knitting and state-preparation of non-Gaussian states
Keitaro Anai, Yasunari Suzuki, Yuuki Tokunaga +3 more·Nov 29, 2024
Continuous-variable (CV) quantum computing is a promising candidate for quantum computation because it can, even with one mode, utilize infinite-dimensional Hilbert spaces and can efficiently handle continuous values. Although photonic platforms have...
Training the parametric interactions in an analog bosonic quantum neural network with Fock basis measurement
Julien Dudas, Baptiste Carles, Elie Gouzien +2 more·Nov 28, 2024
Quantum neural networks promise to extend the power of machine learning into the quantum domain, with potential applications ranging from automatic recognition of quantum states to the control of quantum devices. However, their physical implementatio...
Toward a Quantum Computing Formulation of the Electron Nuclear Dynamics Method via Fukutome Unitary Representation
Juan C. Dom'inguez, Ismael de Farias, Jorge A. Morales·Nov 26, 2024
We present the first installment of the quantum computing (QC) formulation of the electron nuclear dynamics (END) method within the variational quantum simulator (VQS) scheme: END/QC/VQS. END is a time-dependent, variational, on-the-flight, and non-a...