Papers
Live trends in quantum computing research, updated daily from arXiv.
Total Papers
27,980
This Month
1,396
Today
0
Research Volume
13,215 papers in 12 months (+3% vs prior quarter)
Research Focus Areas
Papers by research theme (12 months). Hover for details.
Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Beam-splitter-free, high-rate quantum key distribution inspired by intrinsic quantum mechanical spatial randomness of entangled photons
Ayan Kumar Nai, Gopal Prasad Sahu, Rutuj Gharate +2 more·Sep 12, 2025
Quantum key distribution (QKD) using entangled photon sources (EPS) is a cornerstone of secure communication. Despite rapid advances in QKD, conventional protocols still employ beam splitters (BSs) for passive random basis selection. However, BSs int...
Wafer-Scale Squeezed-Light Chips
Shuai Liu, Kailu Zhou, Yuheng Zhang +4 more·Sep 12, 2025
Squeezed-light generation in photonic integrated circuits (PICs) is essential for scalable continuous-variable (CV) quantum information processing. By suppressing quantum fluctuations below the shot-noise limit, squeezed states enable quantum-enhance...
Enhancing Optical Imaging via Quantum Computation
Aleksandr Mokeev, Babak Saif, Mikhail D. Lukin +1 more·Sep 11, 2025
Extracting information from weak optical signals is a critical challenge across a broad range of technologies. Conventional imaging techniques, constrained to integrating over detected signals and classical post-processing, are limited in signal-to-n...
Attributed-graphs kernel implementation using local detuning of neutral-atoms Rydberg Hamiltonian
Mehdi Djellabi, Matthias Hecker, Shaheen Acheche·Sep 11, 2025
We extend the quantum-feature kernel framework, which relies on measurements of graph-dependent observables, along three directions. First, leveraging neutral-atom quantum processing units (QPUs), we introduce a scheme that incorporates attributed gr...
Quantum-Enhanced Forecasting for Deep Reinforcement Learning in Algorithmic Trading
Jun-Hao Chen, Yu-Chien Huang, Yun-Cheng Tsai +1 more·Sep 11, 2025
The convergence of quantum-inspired neural networks and deep reinforcement learning offers a promising avenue for financial trading. We implemented a trading agent for USD/TWD by integrating Quantum Long Short-Term Memory (QLSTM) for short-term trend...
A hybrid quantum walk model unifying discrete and continuous quantum walks
Tianen Chen, Y. Shang·Sep 11, 2025
Quantum walks, both discrete and continuous, serve as fundamental tools in quantum information processing with diverse applications. This work introduces a hybrid quantum walk model that integrates the coin mechanism of discrete walks with the Hamilt...
Retrocausal capacity of a quantum channel
Kaiyuan Ji, Seth Lloyd, Mark M. Wilde·Sep 10, 2025
We study the capacity of a quantum channel for retrocausal communication, where messages are transmitted backward in time, from a sender in the future to a receiver in the past, through a noisy postselected closed timelike curve (P-CTC) mathematicall...
Power and limitations of distributed quantum state purification
Benchi Zhao, Yu-Ao Chen, Xuanqiang Zhao +3 more·Sep 10, 2025
Quantum state purification protocols, which mitigate noise by converting multiple copies of noisy quantum states into fewer copies with a lower noise level, have applications in quantum communication and computation with imperfect devices. Here, we s...
Comparing quantum incompatibility of device sets from an operational perspective
Kensei Torii, Ryo Takakura, Ryotaro Imamura·Sep 10, 2025
To effectively utilize quantum incompatibility as a resource in quantum information processing, it is crucial to evaluate how incompatible a set of devices is. In this study, we propose an ordering to compare incompatibility and reveal its various pr...
Quantum Fisher information matrix via its classical counterpart from random measurements
Jianfeng Lu, Kecen Sha·Sep 10, 2025
Preconditioning with the quantum Fisher information matrix (QFIM) is a popular approach in quantum variational algorithms. Yet the QFIM is costly to obtain directly, usually requiring more state preparation than its classical counterpart: the classic...
Quantum Error Correction in Adversarial Regimes
Rahul Arvind, Nikhil Bansal, Dax Enshan Koh +2 more·Sep 10, 2025
In adversarial settings, where attackers can deliberately and strategically corrupt quantum data, standard quantum error correction reaches its limits. It can only correct up to half the code distance and must output a unique answer. Quantum list dec...
Adaptive Quantum Computers: decoding and state preparation
Niels M. P. Neumann·Sep 10, 2025
Interacting with a standard computer can enhance the capabilities of current quantum computers already today, particularly by offloading certain computations to the standard computer. Quantum computers that interact with standard computers to perform...
Machine learning the effects of many quantum measurements
W. Hou, Samuel J. Garratt, N. Eassa +4 more·Sep 10, 2025
Measurements are essential for the processing and protection of information in quantum computers. They can also induce long-range entanglement between unmeasured qubits. However, when post-measurement states depend on many non-deterministic measureme...
Measuring the non-Abelian Quantum Phase with the Algorithm of Quantum Phase Estimation
Seng Ghee Tan, Son-Hsien Chen, Ying-Cheng Yang +3 more·Sep 9, 2025
We propose an approach to measure the quantum phase of an electron in a non-Abelian system using the algorithm of Quantum Phase Estimation (QPE). The discrete-path systems were previously studied in the context of square or rectangular rings. Present...
The thermodynamics of readout devices and semiclassical gravity
Samuel Fedida, Adrian Kent·Sep 8, 2025
We analyse the common claim that nonlinear modifications of quantum theory necessarily violate the second law of thermodynamics. We focus on hypothetical extensions of quantum theory that contain readout devices. These black boxes provide a classical...
Entanglement and Classical Simulability in Quantum Extreme Learning Machines
A. De Lorenzis, M. P. Casado, N. Lo Gullo +3 more·Sep 8, 2025
Quantum Machine Learning (QML) has emerged as a promising framework for exploring how quantum dynamics may enhance data processing tasks. Here we investigate Quantum Extreme Learning Machines (QELMs), a quantum analogue of classical Extreme Learning ...
Demonstrating an unconditional separation between quantum and classical information resources
William Kretschmer, Sabee Grewal, M. DeCross +8 more·Sep 8, 2025
A longstanding goal in quantum information science is to demonstrate quantum computations that cannot be feasibly reproduced on a classical computer. Such demonstrations mark major milestones: they showcase fine control over quantum systems and are p...
Super-Quadratic Quantum Speed-ups and Guessing Many Likely Keys
Timo Glaser, Alexander May, Julian Nowakowski·Sep 8, 2025
We study the fundamental problem of guessing cryptographic keys, drawn from some non-uniform probability distribution $D$, as e.g. in LPN, LWE or for passwords. The optimal classical algorithm enumerates keys in decreasing order of likelihood. The op...
Density Matrix-based Dynamics for Quantum Robotic Swarms
Maria Mannone, Mahathi Anand, Peppino Fazio +1 more·Sep 7, 2025
In a robotic swarm, parameters such as position and proximity to the target can be described in terms of probability amplitudes. This idea led to recent studies on a quantum approach to the definition of the swarm, including a block-matrix representa...
A brain-inspired paradigm for scalable quantum vision
Chenghua Duan, Xiuxing Li, Wending Zhao +6 more·Sep 7, 2025
One of the fundamental tasks in machine learning is image classification, which serves as a key benchmark for validating algorithm performance and practical potential. However, effectively processing high-dimensional, detail-rich images, a capability...