Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Accelerating Large-Scale Linear Algebra Using Variational Quantum Imaginary Time Evolution
Willie Aboumrad, Daiwei Zhu, Claudio Girotto +6 more·Mar 17, 2025
The solution of large sparse linear systems via factorization methods such as LU or Cholesky decomposition, can be computationally expensive due to the introduction of non-zero elements, or “fill-in.” Graph partitioning can be used to reduce the “fil...
Enhancing Circuit Trainability with Selective Gate Activation Strategy
Jeihee Cho, Junyong Lee, Daniel Justice +1 more·Mar 17, 2025
Hybrid quantum-classical computing relies heavily on Variational Quantum Algorithms (VQAs) to tackle challenges in diverse fields like quantum chemistry and machine learning. However, VQAs face a critical limitation: the balance between circuit train...
Quantum Simulations of Chemical Reactions: Achieving Accuracy with NISQ Devices
Maitreyee Sarkar, Lisa Roy, Akash Gutal +2 more·Mar 15, 2025
Quantum computing is viewed as a promising technology because of its potential for polynomial growth in complexity, in contrast to the exponential growth observed in its classical counterparts. In the current Noisy Intermediate-Scale Quantum (NISQ) e...
Noise-strength-adapted approximate quantum codes inspired by machine learning
Shuwei Liu, Shiyu Zhou, Zi-Wen Liu +1 more·Mar 14, 2025
We demonstrate that machine learning provides a powerful tool for discovering new approximate quantum error-correcting (AQEC) codes beyond conventional algebraic frameworks. Building upon direct observations through hybrid quantum-classical learning,...
Floquet-ADAPT-VQE: A Quantum Algorithm to Simulate Non-Equilibrium Physics in Periodically Driven Systems
Abhishek Kumar, Karunya Shirali, N. Mayhall +2 more·Mar 14, 2025
Periodically driven quantum systems exhibit many fascinating phenomena absent in equilibrium systems, but their simulation is more challenging than that of static systems. Consequently, quantum simulation of these systems offers greater opportunity f...
Computing band gaps of periodic materials via sample-based quantum diagonalization
Alan Duriez, Pamela C. Carvalho, Marco Antonio Barroca +7 more·Mar 13, 2025
A key objective of computational solid state physics is to predict electronic properties of periodic materials. However, electronic structure simulations based on density functional theory fail to predict experimental results if correlations are not ...
Coherence of a hole spin flopping-mode qubit in a circuit quantum electrodynamics environment
L'eo Noirot, C. X. Yu, J. C. Abadillo-Uriel +5 more·Mar 13, 2025
The entanglement of microwave photons and spin qubits in silicon represents a pivotal step forward for quantum information processing utilizing semiconductor quantum dots. Such hybrid spin circuit quantum electrodynamics (cQED) has been achieved by g...
Finding Hidden Numbers with Majorana-based Topological Quantum Algorithms: Simulation of the Bernstein-Vazirani Algorithm
Jasmin Bedow, D. Morr·Mar 13, 2025
Executing quantum algorithms using Majorana zero modes - a major milestone for the field of topological quantum computing - requires a platform that can be scaled to large quantum registers, can be controlled in real time and space, and a braiding pr...
Fusion Dynamics of Majorana Zero Modes
Themba Hodge, Tuan Kieu, Jasmin Bedow +3 more·Mar 12, 2025
Braiding and fusion of Majorana zero modes are key elements of any future topological Majorana-based quantum computer. Here, we investigate the fusion dynamics of Majorana zero modes in the spinless Kitaev model, as well as in a spinful model describ...
Single-qudit quantum neural networks for multiclass classification
Leandro C. Souza, Renato Portugal·Mar 12, 2025
This paper proposes a single-qudit quantum neural network for multiclass classification by using the enhanced representational capacity of high-dimensional qudit states. Our design employs a d-dimensional unitary operator, where d corresponds to the ...
Explainable Quantum Machine Learning for Multispectral Images Segmentation: Case Study
Tomasz Rybotycki, Manish K. Gupta, Piotr Gawron·Mar 11, 2025
The emergence of Big Data changed how we approach information systems engineering. Nowadays, when we can use remote sensing techniques for Big Data acquisition, the issues such data introduce are as important as ever. One of those concerns is the pro...
QUIET-SR: Quantum Image Enhancement Transformer for Single Image Super-Resolution
Siddhant Dutta, Nouhaila Innan, Khadijeh Najafi +2 more·Mar 11, 2025
Recent advancements in Single-Image Super-Resolution (SISR) using deep learning have significantly improved image restoration quality. However, the high computational cost of processing high-resolution images due to the large number of parameters in ...
H3PIMAP: A Heterogeneity-Aware Multi-Objective DNN Mapping Framework on Electronic-Photonic Processing-in-Memory Architectures
Ziang Yin, Aashish Poonia, Ashish Reddy Bommana +7 more·Mar 10, 2025
The future of artificial intelligence (AI) acceleration demands a paradigm shift beyond the limitations of purely electronic or photonic architectures. Photonic analog computing delivers unmatched speed and parallelism but struggles with data movemen...
Hybrid Quantum Surface Acoustic Wave with Skyrmion Qubit for Quantum Information Processing.
Yu-Yuan Chen, Zhihui Peng, Yu-xi Liu·Mar 10, 2025
Surface acoustic wave (SAW) devices are key components of classical communication systems and recently studied for quantum information processing. We here propose and study a hybrid quantum system composed of skyrmion qubit and a SAW cavity, which su...
Driven Magnon-Photon System as a Tunable Quantum Heat Rectifier
C. O. Edet, K. Słowik, N. Ali +2 more·Mar 8, 2025
Controlling heat flow at the quantum level is a key challenge for next-generation quantum technologies, including thermal management and quantum information processing. Here, we investigate quantum heat transport in an asymmetrically driven hybrid ma...
HIVQE: Handover Iterative Variational Quantum Eigensolver for Efficient Quantum Chemistry Calculations
Aidan Pellow-Jarman, Shane McFarthing Doo, Hyung Kang +6 more·Mar 8, 2025
A novel hybrid quantum-classical approach has been developed to efficiently address the multireference quantum chemistry problem. The Handover Iterative Variational Quantum Eigensolver (HiVQE) is designed to accurately estimate ground-state wavefunct...
Seismic inversion using hybrid quantum neural networks
Divakar Vashisth, Rohan Sharma, T. Mukerji +1 more·Mar 6, 2025
Seismic inversion-including post-stack, pre-stack, and full waveform inversion is compute and memory-intensive. Recently, several approaches, including physics-informed machine learning, have been developed to address some of these limitations. Motiv...
Interpolation-based coordinate descent method for parameterized quantum circuits
Zhijian Lai, Jiang Hu, Taehee Ko +2 more·Mar 6, 2025
Parameterized quantum circuits (PQCs) are fundamental to many hybrid quantum-classical algorithms. However, existing structure-based optimizers for the training of PQCs, such as Rotosolve and sequential minimal optimization, rely on heuristic node se...
CQ CNN: A Hybrid Classical Quantum Convolutional Neural Network for Alzheimer's Disease Detection Using Diffusion Generated and U Net Segmented 3D MRI
Mominul Islam, Mohammad Junayed Hasan, M.R.C. Mahdy·Mar 4, 2025
The detection of Alzheimer disease (AD) from clinical MRI data is an active area of research in medical imaging. Recent advances in quantum computing, particularly the integration of parameterized quantum circuits (PQCs) with classical machine learni...
The carbon nanotube gatemon qubit
H. Riechert, S. Annabi, A. Peugeot +8 more·Mar 3, 2025
Gate-tunable transmon qubits are based on quantum conductors used as weak links within hybrid Josephson junctions. These gatemons have been implemented in just a handful of systems, all relying on extended conductors, namely epitaxial semiconductors ...