Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Quantum simulation of Helmholtz equations via Schr{ö}dingerization
Anjiao Gu, Shi Jin, Chuwen Ma·Jul 31, 2025
The Helmholtz equation is a prototypical model for time-harmonic wave propagation. Numerical solutions become increasingly challenging as the wave number $k$ grows, due to the equation's elliptic yet noncoercive character and the highly oscillatory n...
Field digitization scaling in a $\mathbb{Z}_N \subset U(1)$ symmetric model
Gabriele Calliari, Robert Ott, Hannes Pichler +1 more·Jul 30, 2025
The simulation of quantum field theories, both classical and quantum, requires regularization of infinitely many degrees of freedom. However, in the context of field digitization (FD) -- a truncation of the local fields to $N$ discrete values -- a co...
Operational interpretation of the Stabilizer Entropy
Lennart Bittel, Lorenzo Leone·Jul 30, 2025
Magic-state resource theory is a fundamental framework with far-reaching applications in quantum error correction and the classical simulation of quantum systems. Recent advances have significantly deepened our understanding of magic as a resource ac...
On the Trotter Error in Many-body Quantum Dynamics with Coulomb Potentials
Di Fang, Xiaoxu Wu, Avy Soffer·Jul 30, 2025
Efficient simulation of many-body quantum systems is central to advances in physics, chemistry, and quantum computing, with a key question being whether the simulation cost scales polynomially with the system size. In this work, we analyze many-body ...
Reducing Circuit Depth in Lindblad Simulation via Step-Size Extrapolation
Pegah Mohammadipour, Xiantao Li·Jul 30, 2025
We study algorithmic error mitigation via Richardson-style extrapolation for quantum simulations of open quantum systems modelled by the Lindblad equation. Focusing on two specific first-order quantum algorithms, we perform a backward-error analysis ...
Toward Practical Quantum Phase Estimation: A Modular, Scalable, and Adaptive Approach
Alok Shukla, P. Vedula·Jul 30, 2025
Quantum Phase Estimation (QPE) is a cornerstone algorithm in quantum computing, with applications ranging from integer factorization to quantum chemistry simulations. However, the resource demands of standard QPE, which require a large number of cohe...
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...
Single‐ and Two‐Mode Squeezing by Modulated Coupling to a Rabi Driven Qubit
E. Blumenthal, Nir Gutman, I. Kaminer +1 more·Jul 30, 2025
Advanced bosonic quantum computing architectures demand nonlocal Gaussian operations such as two‐mode squeezing to unlock universal control, enable entanglement generation, and implement logical operations across distributed modes. This work presents...
Quantum Krylov Subspace Diagonalization via Time Reversal Symmetries
Nicola Mariella, Enrique Rico, Adam Byrne +1 more·Jul 30, 2025
Krylov quantum diagonalization methods have emerged as a promising use case for quantum computers. However, many existing implementations rely on controlled operations, which pose challenges to near-term quantum hardware. We introduce a novel protoco...
Analysis of Quantum Image Representations for Supervised Classification
Marco Parigi, Mehran Khosrojerdi, Filippo Caruso +1 more·Jul 29, 2025
In the era of big data and artificial intelligence, the increasing volume of data and the demand to solve more and more complex computational challenges are two driving forces for improving the efficiency of data storage, processing and analysis. Qua...
Sampling (noisy) quantum circuits through randomized rounding
Victor Martinez, Omar Fawzi, Daniel Stilck França·Jul 29, 2025
The present era of quantum processors with hundreds to thousands of noisy qubits has sparked interest in understanding the computational power of these devices and how to leverage it to solve practically relevant problems. For applications that requi...
Data-driven quantum Koopman method for simulating nonlinear dynamics
Baoyang Zhang, Zhen Lu, Yaomin Zhao +1 more·Jul 29, 2025
Quantum computation offers potential exponential speedups for simulating certain physical systems, but its application to nonlinear dynamics is inherently constrained by the requirement of unitary evolution. We propose the quantum Koopman method (QKM...
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...
Quantum generative modeling for financial time series with temporal correlations
David Dechant, Eliot Schwander, Lucas van Drooge +4 more·Jul 29, 2025
Quantum generative adversarial networks (QGANs) have been investigated as a method for generating synthetic data with the goal of augmenting training data sets for neural networks. This is especially relevant for financial time series, since we only ...
Evaluation of Noise and Crosstalk in Neutral Atom Quantum Computers
Pranet Sharma, Yizhuo Tan, K. Papadopoulos +1 more·Jul 29, 2025
This work explores and evaluates noise and crosstalk in neutral atom quantum computers. Neutral atom quantum computers are a promising platform for analog Hamiltonian simulations, which rely on a sequence of time-dependent Hamiltonians to model the d...
Embedding-Aware Quantum-Classical SVMs for Scalable Quantum Machine Learning
S. A. C. Ord'onez, Luis Fernando Torres Torres, Mario Bifulco +3 more·Jul 28, 2025
Quantum Support Vector Machines face scalability challenges due to high-dimensional quantum states and hardware limitations. We propose an embedding-aware quantum-classical pipeline combining class-balanced k-means distillation with pretrained Vision...
Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware
Djamil Lakhdar-Hamina, Xingxin Liu, Richard Barney +4 more·Jul 28, 2025
We implement a quantum generalization of a neural network on trapped-ion and IBM superconducting quantum computers to classify MNIST images, a common benchmark in computer vision. The network feedforward involves qubit rotations whose angles depend o...
Efficient Gaussian State Preparation in Quantum Circuits
Yichen Xie, Nadav Ben-Ami·Jul 27, 2025
Gaussian states hold a fundamental place in quantum mechanics, quantum information, and quantum computing. Many subfields, including quantum simulation of continuousvariable systems, quantum chemistry, and quantum machine learning, rely on the abilit...
Circuit simulation of readout process toward large-scale superconducting quantum circuits
T. Tanamoto, Hiroshi Fuketa, T. Ishikawa +1 more·Jul 27, 2025
The rapid scaling of superconducting quantum computers has highlighted the impact of device-level variability on overall circuit fidelity. In particular, fabrication-induced fluctuations in device parameters such as capacitance and Josephson critical...
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...