Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Density of States (Gate) - Controlled Andreev Molecule and Sensor
Xiaofan Shi, Z. Dou, Guoan Li +19 more·Aug 6, 2025
Topological quantum computing typically relies on topological Andreev bound states (ABSs) engineered in hybrid superconductor-semiconductor devices, where gate control offers key advantages. While strong Zeeman fields can induce such states, an alter...
Advantages of Co-locating Quantum-HPC Platforms: A Survey for Near-Future Industrial Applications
D. Honda, Yuta Nishiyama, Junya Ishikawa +10 more·Aug 6, 2025
We conducted a systematic survey of emerging quantum-HPC platforms, which integrate quantum computers and High-Performance Computing (HPC) systems through co-location. Currently, it remains unclear whether such platforms provide tangible benefits for...
Hybrid Quantum-Classical Machine Learning Potential with Variational Quantum Circuits
S. Y. Willow, David ChangMo Yang, Chang Woo·Aug 6, 2025
Quantum algorithms for simulating large and complex molecular systems are still in their infancy, and surpassing state-of-the-art classical techniques remains an ever-receding goal post. A promising avenue of inquiry in the meanwhile is to seek pract...
Quantum Temporal Fusion Transformer
Krishnakanta Barik, Goutam Paul·Aug 6, 2025
The \textit{Temporal Fusion Transformer} (TFT), proposed by Lim \textit{et al.}, published in \textit{International Journal of Forecasting} (2021), is a state-of-the-art attention-based deep neural network architecture specifically designed for multi...
Path-Integral Formulation of Bosonic Markovian Open Quantum Dynamics with Monte Carlo stochastic trajectories using the Glauber-Sudarshan P, Wigner, and Husimi Q Functions and Hybrids
Toma Yoneya, Kazuya Fujimoto, Yuki Kawaguchi·Aug 4, 2025
The Monte Carlo (MC) trajectory sampling of stochastic differential equations (SDEs) based on the quasiprobabilities, such as the Glauber-Sudarshan P, Wigner, and Husimi Q functions, enables us to investigate bosonic open quantum many-body dynamics d...
Evaluating Angle and Amplitude Encoding Strategies for Variational Quantum Machine Learning: their impact on model's accuracy
A. Tudisco, Andrea Marchesin, Maurizio Zamboni +2 more·Aug 1, 2025
Recent advancements in Quantum Computing and Machine Learning have increased attention to Quantum Machine Learning (QML), which aims to develop machine learning models by exploiting the quantum computing paradigm. One of the widely used models in thi...
Swap Network Augmented Ansätze on Arbitrary Connectivity
Teodor Parella-Dilmé, Jakob S. Kottmann, Antonio Acín·Jul 31, 2025
Efficient parametrizations of quantum states are essential for trainable hybrid classical-quantum algorithms. A key challenge in their design consists in adapting to the available qubit connectivity of the quantum processor, which limits the capacity...
Search for $t\bar tt\bar tW$ Production at $\sqrt{s} = 13$ TeV Using a Modified Graph Neural Network at the LHC
Syed Haider Ali, A. Ahmad, Muhammad Saiel +1 more·Jul 31, 2025
The simultaneous production of four top quarks in association with a ($W$) boson at $(\sqrt{s} = 13)$ TeV is an rare SM process with a next-to-leading-order (NLO) cross-section of $(6.6^{+2.4}_{-2.6} {ab})$\cite{saiel}. Identifying this process in th...
Dynamical mean field theory with quantum computing
Thomas Ayral·Jul 31, 2025
Near-term quantum processors are limited in terms of the number of qubits and gates they can afford. They nevertheless give unprecedented access to programmable quantum systems that can efficiently, although imperfectly, simulate quantum time evoluti...
Dimension reduction with structure-aware quantum circuits for hybrid machine learning
A. Daskin·Jul 31, 2025
Schmidt decomposition of a vector can be understood as writing the singular value decomposition (SVD) in vector form. A vector can be written as a linear combination of tensor product of two dimensional vectors by recursively applying Schmidt decompo...
On the Simulation of Conical Intersections in Water and Methanimine Molecules Via Variational Quantum Algorithms
Samir Belaloui, N. Belaloui, Achour Benslama·Jul 30, 2025
We investigate the electronic structure of methanimine (CH2NH) and water (H2O) molecules in an effort to locate conical intersections (CIs) using variational quantum algorithms. Our approach implements and compares a range of hybrid quantum-classical...
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model
A. Ambainis, J. F. Doriguello, Debbie Lim·Jul 30, 2025
We propose novel classical and quantum online algorithms for learning finite-horizon and infinite-horizon average-reward Markov Decision Processes (MDPs). Our algorithms are based on a hybrid exploration-generative reinforcement learning (RL) model w...
Hybrid Quantum Classical Surrogate for Real Time Inverse Finite Element Modeling in Digital Twins
A. Alavi, Sanduni Jayasinghe, M. Mahmoodian +3 more·Jul 30, 2025
Large-scale civil structures, such as bridges, pipelines, and offshore platforms, are vital to modern infrastructure, where unexpected failures can cause significant economic and safety repercussions. Although finite element (FE) modeling is widely u...
Structured quantum learning via em algorithm for Boltzmann machines
Takeshi Kimura, Kohtaro Kato, Masahito Hayashi·Jul 29, 2025
Quantum Boltzmann machines (QBMs) are generative models with potential advantages in quantum machine learning, yet their training is fundamentally limited by the barren plateau problem, where gradients vanish exponentially with system size. We introd...
Quantum Solvers: Predictive Aeroacoustic&Aerodynamic modeling
Nis-Luca van Hulst, Theofanis Panagos, Greta Sophie Reese +2 more·Jul 29, 2025
This technical report presents our winning contribution to the 2024 Airbus and BMW Group Quantum Computing Challenge under the category'Quantum Solvers'. This submission addresses efficient simulation in industrial CFD using (i) quantum-inspired algo...
Robust qubit interactions mediated by photonic topological edge states
Boris Gurevich, Weihua Xie, Mohsen Yarmohammadi +1 more·Jul 28, 2025
We investigate the coupling of two spatially separated qubits via topologically protected edge states in a two-dimensional Hofstadter lattice. In this hybrid platform, the qubits are coupled to distinct edge sites of the lattice, enabling long-range ...
Quantum Reinforcement Learning by Adaptive Non-Local Observables
Hsin-Yi Lin, Samuel Yen-Chi Chen, H. Tseng +1 more·Jul 25, 2025
Hybrid quantum-classical frameworks leverage quantum computing for machine learning; however, variational quantum circuits (VQCs) are limited by local measurements. We introduce an adaptive non-local observable (ANO) paradigm within VQCs for quantum ...
Towards System-Level Quantum-Accelerator Integration
Ralf Ramsauer, Wolfgang Mauerer·Jul 25, 2025
Quantum computers are often treated as experimental add-ons that are loosely coupled to classical infrastructure through high-level interpreted languages and cloud-like orchestration. However, future deployments in both, high-performance computing (H...
Quantum-Efficient Convolution through Sparse Matrix Encoding and Low-Depth Inner Product Circuits
Mohammad Rasoul Roshanshah, Payman Kazemikhah, Hossein Aghababa·Jul 25, 2025
Convolution operations are foundational to classical image processing and modern deep learning architectures, yet their extension into the quantum domain has remained algorithmically and physically costly due to inefficient data encoding and prohibit...
FD4QC: Application of Classical and Quantum-Hybrid Machine Learning for Financial Fraud Detection A Technical Report
Matteo Cardaioli, Luca Marangoni, Giada Martini +5 more·Jul 25, 2025
The increasing complexity and volume of financial transactions pose significant challenges to traditional fraud detection systems. This technical report investigates and compares the efficacy of classical, quantum, and quantum-hybrid machine learning...