Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Quantum open system description of a hybrid plasmonic cavity
Marco Vallone·Dec 4, 2025
We present a unified quantum open system framework for lossy plasmonic cavities in which coherent dynamics, relaxation, dephasing, and irreversible absorption are treated on equal footing. The Dyson equation for the cavity photon propagator in the ra...
Operator Formalism for Laser-Plasma Wakefield Acceleration
Mostafa Behtouei, Carlos Salgado Lopez, Giancarlo Gatti·Dec 4, 2025
In this paper, we develop an operator-based framework for laser--plasma wakefield acceleration (LPWA) in capillary discharges, providing a compact and systematic description of the coupled dynamics of laser fields and plasma response. The formalism e...
Convergence of sample-based quantum diagonalization on a variable-length cuprate chain
L. Andrew Wray, Cheng-Ju Lin, Vincent Su +1 more·Dec 4, 2025
Sample-based quantum diagonalization (SQD) is an algorithm for hybrid quantum-classical molecular simulation that has been of broad interest for application with noisy intermediate scale quantum (NISQ) devices. However, SQD does not always converge o...
PVLS: A Learning-based Parameter Prediction Technique for Variational Quantum Linear Solvers
Youla Yang·Dec 4, 2025
Variational Quantum Linear Solvers (VQLS) are a promising method for solving linear systems on near-term quantum devices. However, their performance is often limited by barren plateaus and inefficient parameter initialization, which significantly hin...
Hybrid VQE-CVQE algorithm using diabatic state preparation
John P. T. Stenger, C. Stephen Hellberg, Daniel Gunlycke·Dec 4, 2025
We propose a hybrid variational quantum algorithm that has variational parameters used by both the quantum circuit and the subsequent classical optimization. Similar to the Variational Quantum Eigensolver (VQE), this algorithm applies a parameterized...
Optimal Scaling Quantum Interior Point Method for Linear Optimization
Mohammadhossein Mohammadisiahroudi, Zeguan Wu, Pouya Sampourmahani +2 more·Dec 4, 2025
The emergence of huge-scale, data-intensive linear optimization (LO) problems in applications such as machine learning has driven the need for more computationally efficient interior point methods (IPMs). While conventional IPMs are polynomial-time a...
Combined Quantum and Post-Quantum Security Performance Under Finite Keys
Aman Gupta, Ravi Singh Adhikari, Anju Rani +2 more·Dec 4, 2025
Recent advances in quantum-secure communication have highlighted the value of hybrid schemes that combine Quantum Key Distribution (QKD) with Post-Quantum Cryptography (PQC). Yet most existing hybrid designs omit realistic finite-key effects on QKD k...
Maestro: Intelligent Execution for Quantum Circuit Simulation
Oriol Bertomeu, Hamzah Ghayas, Adrian Roman +1 more·Dec 3, 2025
Quantum circuit simulation remains essential for developing and validating quantum algorithms, especially as current quantum hardware is limited in scale and quality. However, the growing diversity of simulation methods and software tools creates a h...
Towards Quantum Stochastic Optimization for Energy Systems under Uncertainty: Joint Chance Constraints with Quantum Annealing
David Ribes, Tatiana Gonzalez Grandon·Dec 3, 2025
Uncertainty is fundamental in modern power systems, where renewable generation and fluctuating demand make stochastic optimization indispensable. The chance constrained unit commitment problem (UCP) captures this uncertainty but rapidly becomes compu...
Laser-induced modulation of conductance in graphene with magnetic barriers
Rachid El Aitouni, Miloud Mekkaoui, Pablo Díaz +2 more·Dec 3, 2025
We study how electrons move across a graphene sheet when it encounters two magnetic barriers with a region in between that is continuously driven by laser light. Rather than acting as a static obstacle, this illuminated middle section becomes a Floqu...
Solution of the Electric Field Integral Equation Using a Hybrid Quantum-Classical Scheme: Investigation of Accuracy and Efficiency
Rui Chen, Teng-Yang Ma, Meng-Han Dou +1 more·Dec 3, 2025
Conventional classical solvers are commonly used for solving matrix equation systems resulting from the discretization of SIEs in computational electromagnetics (CEM). However, the memory requirement would become a bottleneck for classical computing ...
Complex Wigner entropy and Fisher control of negativity in an oval quantum billiard
Kyu-Won Park, Jongin Jeong·Dec 3, 2025
We develop a complex-entropy framework for Wigner negativity and apply it to avoided crossings in an oval quantum billiard. For a real Wigner function the Gibbs--Shannon functional becomes complex; its imaginary part, proportional to the Wigner-negat...
Hybridized-Mode Parametric Amplifier in Kinetic-Inductance Circuits
Danial Davoudi, Abdul Mohamed, Shabir Barzanjeh·Dec 3, 2025
Parametric amplification is essential for quantum measurement, enabling the amplification of weak microwave signals with minimal added noise. While Josephson-junction-based amplifiers have become standard in superconducting quantum circuits, their ma...
Sketch Tomography: Hybridizing Classical Shadow and Matrix Product State
Xun Tang, Haoxuan Chen, Yuehaw Khoo +1 more·Dec 3, 2025
We introduce Sketch Tomography, an efficient procedure for quantum state tomography based on the classical shadow protocol used for quantum observable estimations. The procedure applies to the case where the ground truth quantum state is a matrix pro...
Quantum Topological Graph Neural Networks for Detecting Complex Fraud Patterns
Mohammad Doost, Mohammad Manthouri·Dec 3, 2025
We propose a novel QTGNN framework for detecting fraudulent transactions in large-scale financial networks. By integrating quantum embedding, variational graph convolutions, and topological data analysis, QTGNN captures complex transaction dynamics a...
SDQC: Distributed Quantum Computing Architecture Utilizing Entangled Ion Qubit Shuttling
Seunghyun Baek, Seok-Hyung Lee, Dongmoon Min +1 more·Dec 2, 2025
We propose Shuttling-based Distributed Quantum Computing (SDQC), a hybrid architecture that combines the strengths of physical qubit shuttling and distributed quantum computing to enable scalable trapped-ion quantum computing. SDQC performs non-local...
Generative modeling using evolved quantum Boltzmann machines
Mark M. Wilde·Dec 2, 2025
Born-rule generative modeling, a central task in quantum machine learning, seeks to learn probability distributions that can be efficiently sampled by measuring complex quantum states. One hope is for quantum models to efficiently capture probability...
Hybrid Quantum State Preparation via Data Compression
Emad Rezaei Fard Boosari, Maryam Afsary·Dec 1, 2025
Quantum state preparation (QSP) for a general $n$-qubit state requires $O(2^n)$ CNOT gates and circuit depth, making exact amplitude encoding (EAE) impractical for near-term quantum hardware. We introduce an ancilla-free hybrid classical-quantum stra...
Resource Estimation for VQE on Small Molecules: Impact of Fermion Mappings and Hamiltonian Reductions
Anurag K. S. V., Ashish Kumar Patra, Vikas Dattatraya Ghevade +5 more·Dec 1, 2025
Accurate determination of ground-state energies for molecules remains a challenge in quantum chemistry and a cornerstone for progress in fields such as drug discovery and materials design. The Variational Quantum Eigensolver (VQE) represents a leadin...
QuantumCanvas: A Multimodal Benchmark for Visual Learning of Atomic Interactions
Can Polat, Erchin Serpedin, Mustafa Kurban +1 more·Dec 1, 2025
Despite rapid advances in molecular and materials machine learning, most models still lack physical transferability: they fit correlations across whole molecules or crystals rather than learning the quantum interactions between atomic pairs. Yet bond...