Papers
Live trends in quantum computing research, updated daily from arXiv.
Total Papers
27,548
This Month
1,041
Today
0
Research Volume
12,894 papers in 12 months (-5% vs prior quarter)
Research Focus Areas
Papers by research theme (12 months). Hover for details.
Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
From Reachability to Learnability: Geometric Design Principles for Quantum Neural Networks
Vishal S. Ngairangbam, Michael Spannowsky·Mar 3, 2026
Classical deep networks are effective because depth enables adaptive geometric deformation of data representations. In quantum neural networks (QNNs), however, depth or state reachability alone does not guarantee this feature-learning capability. We ...
Exact stabilizer scars in two-dimensional $U(1)$ lattice gauge theory
Sabhyata Gupta, Piotr Sierant, Luis Santos +1 more·Mar 3, 2026
The complexity of highly excited eigenstates is a central theme in nonequilibrium many-body physics, underpining questions of thermalization, classical simulability, and quantum information structure. In this work, considering the paradigmatic Rokhsa...
Scaling of silicon spin qubits under correlated noise
Juan S. Rojas-Arias, Leon C. Camenzind, Yi-Hsien Wu +8 more·Mar 3, 2026
The path to fault-tolerant quantum computing hinges on hardware that scales while remaining compatible with quantum error correction (QEC). Silicon spin qubits are a leading hardware candidate because they combine industrial fabrication compatibility...
Simulating a quantum sensor: quantum state tomography of NV-spin systems
Alberto López-García, Aikaterini Vasilakou, Javier Cerrillo·Mar 3, 2026
We employ a quantum computer to simulate the effect of spin impurities on nitrogen-vacancy (NV) centers in diamond. As these defects operate as nanoscale quantum sensors, modeling quantum noise is crucial to identify limitations in precision. The ana...
QFlowNet: Fast, Diverse, and Efficient Unitary Synthesis with Generative Flow Networks
Inhoe Koo, Hyunho Cha, Jungwoo Lee·Mar 3, 2026
Unitary Synthesis, the decomposition of a unitary matrix into a sequence of quantum gates, is a fundamental challenge in quantum compilation. Prevailing reinforcement learning (RL) approaches are often hampered by sparse reward signals, which necessi...
Motion-induced directionality of collective emission in a non-chiral waveguide
Yoan Spahn, Jens Hartmann, Benedikt Saalfrank +3 more·Mar 3, 2026
We report on the observation of motion-induced directionality in the collective emission of atoms confined within a hollow-core waveguide. Unlike in chiral waveguides, the atom-field coupling is here isotropic in the forward and backward direction. H...
Analytical Quantum Full-Wave Analysis of Few-Photon Transport Through a Superconducting Cavity Qubit
Soomin Moon, Thomas E. Roth·Mar 3, 2026
A promising way to scale up superconducting quantum computers is to link different devices together using propagating photons. Correspondingly, accurately modeling the quantum information transfer in such quantum interconnects is critical to advancin...
QAOA-Predictor: Forecasting Success Probabilities and Minimal Depths for Efficient Fixed-Parameter Optimization
Rodrigo Coelho, Georg Kruse, Jeanette Miriam Lorenz·Mar 3, 2026
Quantum Computing promises to solve complex combinatorial optimization problems more efficiently than classical methods, with the Quantum Approximate Optimization Algorithm (QAOA) being a leading candidate. Recent fixed-parameter variations of QAOA e...
Nuclear interference by electronic de-orthogonalisation
Matisse Wei-Yuan Tu, Angel Rubio, E. K. U. Gross·Mar 3, 2026
Interference is a universal consequence of superposition, yet in composite quantum systems it can encode correlations between subsystems. We show that in coupled electron-nuclear dynamics, interference in the nuclear density can arise dynamically eve...
Layer-wise QUBO-Based Training of CNN Classifiers for Quantum Annealing
Mostafa Atallah, Rebekah Herrman·Mar 3, 2026
Variational quantum circuits for image classification suffer from barren plateaus, while quantum kernel methods scale quadratically with dataset size. We propose an iterative framework based on Quadratic Unconstrained Binary Optimization (QUBO) for t...
Improved Grid-Based Simulation of Coulombic Dynamics
Xiaoning Feng, Hans Hon Sang Chan, David P. Tew·Mar 3, 2026
Accurate time-dependent quantum dynamics of Coulombic systems on grid-based representations remains computationally demanding due to the singularity of the Coulomb potential, which necessitates extremely fine spatial grids to mitigate discretisation ...
Fingerprint Recognition of Partial Discharge Signals in Deep Learning Enhanced Rydberg Atomic Sensors
Yi-Ming Yin, Qi-Feng Wang, Yu Ma +16 more·Mar 3, 2026
Partial discharge originates from microscopic insulation imperfections in high-voltage apparatus and is widely considered a critical marker of incipient deterioration. Conventional partial discharge detection methods are typically constrained by limi...
Toward multi-purpose quantum communication networks: from theory to protocol implementation
Lucas Hanouz, Marc Kaplan, Jean-Sébastien Kersaint Tournebize +2 more·Mar 3, 2026
Most quantum communication networks around the world are used for a single task: quantum key distribution. In order to initiate the transition to multi-purpose quantum communication networks, we demonstrate the implementation of two different tasks o...
Learning Hamiltonians for solid-state quantum simulators
Jarosław Pawłowski, Mateusz Krawczyk·Mar 3, 2026
We introduce a generalizable framework for learning to identify effective Hamiltonians directly from experimental data in solid-state quantum systems. Our approach is based on a physics-informed neural network architecture that embeds physical constr...
Discrete-modulation continuous-variable quantum key distribution with probabilistic amplitude shaping over a linear quantum channel
Emanuele Parente, Michele N. Notarnicola, Stefano Olivares +3 more·Mar 3, 2026
The practical implementation difficulties arising from the Gaussian modulation of the GG02 protocol lead us to investigate the possibilities offered by the combination of probabilistic amplitude shaping technique and quadrature amplitude modulation f...
An Extensible Quantum Network Simulator Built on ns-3: Q2NS Design and Evaluation
Adam Pearson, Francesco Mazza, Marcello Caleffi +1 more·Mar 3, 2026
As quantum networking hardware remains costly and not yet widely accessible, simulation tools are essential for the design and evaluation of quantum network architectures and protocols. However, designing a scalable and computationally efficient quan...
Identification of quantum generative circuits with parallel quantum neural network
Zheping Wu, Xiaopeng Huang, Hengyue Jia +2 more·Mar 3, 2026
The rapid emergence of quantum technology has raised new challenges in distinguishing various quantum circuits of similar functions. In this work, we propose parallel quantum embedding neural network (ParaQuanNet) for the efficient identification of ...
Charging power enhancement at the phase transition of a non-integrable quantum battery
D. Farina, M. Sassetti, V. Cataudella +2 more·Mar 3, 2026
Exploiting many-body interaction and critical phenomena to improve the performance of quantum batteries is an emerging and promising line of research. A central question in this direction is whether quantum phase transitions can enhance the charging ...
Merged amplitude encoding for Chebyshev quantum Kolmogorov--Arnold networks: trading qubits for circuit executions
Hikaru Wakaura·Mar 3, 2026
Quantum Kolmogorov--Arnold networks based on Chebyshev polynomials (CCQKAN) evaluate each edge activation function as a quantum inner product, creating a trade-off between qubit count and the number of circuit executions per forward pass. We introduc...
Fast and memory-efficient classical simulation of quantum machine learning via forward and backward gate fusion
Yoshiaki Kawase·Mar 3, 2026
While real quantum devices have been increasingly used to conduct research focused on achieving quantum advantage or quantum utility in recent years, executing deep quantum circuits or performing quantum machine learning with large-scale data on curr...