Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Efficient mutual magic and magic capacity with matrix product states
P. S. Tarabunga, Tobias Haug·Apr 9, 2025
Stabilizer Rényi entropies (SREs) probe the non-stabilizerness (or “magic”) of many-body systems and quantum computers. Here, we introduce the mutual von-Neumann SRE and magic capacity, which can be efficiently computed in time O(N\chi^3)O(Nχ3) for m...
Trapped ion quantum hardware demonstration of energy calculations using a multireference unitary coupled cluster ansatz: application to the BeH2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs}
Palak Chawla, Disha Shetty, Peniel Bertrand Tsemo +5 more·Apr 9, 2025
In this study, we employ the variational quantum eigensolver algorithm with a multireference unitary coupled cluster ansatz to report the ground state energy of the BeH2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepacka...
Noise-aware entanglement generation protocols for superconducting qubits with impedance-matched FBAR transducers
Erin Sheridan, M. Senatore, Samuel Schwab +8 more·Apr 9, 2025
Connecting superconducting quantum processors to telecommunications-wavelength quantum networks is critically necessary to enable distributed quantum computing, secure communications, and other applications. Optically-mediated entanglement heralding ...
When Federated Learning Meets Quantum Computing: Survey and Research Opportunities
Aakar Mathur, Ashish Gupta, Sajal K. Das·Apr 9, 2025
Quantum Federated Learning (QFL) is an emerging field that harnesses advances in Quantum Computing (QC) to improve the scalability and efficiency of decentralized Federated Learning (FL) models. This paper provides a systematic and comprehensive surv...
Variational quantum machine learning with quantum error detection
Eromanga Adermann, Hajime Suzuki, Muhammad Usman·Apr 9, 2025
Quantum machine learning (QML) is an emerging field that promises advantages such as faster training, improved reliability and superior feature extraction over classical counterparts. However, its implementation on quantum hardware is challenging due...
Characterising the failure mechanisms of error-corrected quantum logic gates
Robin Harper, C. Lain'e, Evan T. Hockings +4 more·Apr 9, 2025
Mid-circuit measurements used in quantum error correction are essential in quantum computer architecture, as they read out syndrome data and drive logic gates. Here, we use a heavy-hex code prepared on a superconducting qubit array to investigate how...
Optimizing Multi-Hop Quantum Communication using Bidirectional Quantum Teleportation Protocol
N. Ikken, P. Kumar, A. Slaoui +4 more·Apr 9, 2025
In this paper, we introduce a new method for Bidirectional Quantum Teleportation called Bidirectional Quantum Teleportation using the Modified Dijkstra Algorithm and Quantum Walk (BQT-MDQW). This method uses different types of entangled states, such ...
Machine Learning Approach towards Quantum Error Mitigation for Accurate Molecular Energetics
Srushti Patil, D. Mondal, Rahul Maitra·Apr 9, 2025
Despite significant efforts, the realization of the hybrid quantum-classical algorithms has predominantly been confined to proof-of-principles, mainly due to the hardware noise. With fault-tolerant implementation being a long-term goal, going beyond ...
A quantum algorithm for linear autonomous differential equations via Padé approximation
Dekuan Dong, Yingzhou Li, Jungong Xue·Apr 9, 2025
We propose a novel quantum algorithm for solving linear autonomous ordinary differential equations (ODEs) using the Padé approximation. For linear autonomous ODEs, the discretized solution can be represented by a product of matrix exponentials. The p...
Evaluating Parameter-Based Training Performance of Neural Networks and Variational Quantum Circuits
Michael Kolle, Alexander Feist, Jonas Stein +2 more·Apr 9, 2025
In recent years, neural networks (NNs) have driven significant advances in machine learning. However, as tasks grow more complex, NNs often require large numbers of trainable parameters, which increases computational and energy demands. Variational q...
Assumption-free fidelity bounds for hardware noise characterization
Nicolò Colombo·Apr 9, 2025
In the Quantum Supremacy regime, quantum computers may overcome classical machines on several tasks if we can estimate, mitigate, or correct unavoidable hardware noise. Estimating the error requires classical simulations, which become unfeasible in t...
Low-latency control system for feedback experiments with optical tweezer arrays
Amir H. Dadpour, Timur Khayrullin, Fouad Afiouni +4 more·Apr 9, 2025
We present and characterize a modular, open-source system to perform feedback control experiments on configurations of atoms and molecules in arrays of optical tweezers. The system features a modular, cost-effective computer architecture with a mothe...
Consensus-based qubit configuration optimization for variational algorithms on neutral atom quantum systems
R. D. de Keijzer, Luke Visser, O. Tse +1 more·Apr 9, 2025
We report an algorithm that is able to tailor qubit interactions for individual variational quantum algorithm problems. The algorithm leverages the unique ability of a neutral atom tweezer platform to realize arbitrary qubit position configurations. ...
Successive randomized compression: A randomized algorithm for the compressed MPO-MPS product
Chris Camaño, Ethan N. Epperly, Joel A. Tropp·Apr 8, 2025
Tensor networks like matrix product states (MPSs) and matrix product operators (MPOs) are powerful tools for representing exponentially large states and operators, with applications in quantum many-body physics, machine learning, numerical analysis, ...
A Framework for Solving Continuous Energy and Power System Problems using Adiabatic Quantum Computing
Zeynab Kaseb, Matthias Moller, Peter Palensky +1 more·Apr 8, 2025
The increasing scale and nonlinearity of modern energy and power system problems pose significant challenges to classical numerical solvers. In parallel, advances in quantum and quantum-inspired hardware are expected to improve scalability and offer ...
Chernoff Information Bottleneck for Covert Quantum Target Sensing
Giuseppe Ortolano, Ivano Ruo-Berchera, Leonardo Banchi·Apr 8, 2025
The paradigm of quantum metrology and sensing aims to identify a quantum advantage in precision at a fixed energy of the probe state. However, in practice, employing high-energy classical probes is often simpler than leveraging the quantum regime. Th...
Can gravity mediate the transmission of quantum information?
Andrea Mari, Stefano Zippilli, David Vitali·Apr 8, 2025
We propose an experiment to test the non-classicality of the gravitational interaction. We consider two optomechanical systems that are perfectly isolated, except for a weak gravitational coupling. If a suitable resonance condition is satisfied, an o...
Pump-Threshold-Free Frequency Comb via Cavity Floquet Engineering
Sihan Wang, Cheng Wang, Matthijs H. J. de Jong +4 more·Apr 8, 2025
Frequency combs have revolutionized communication, metrology, and spectroscopy. Considerable efforts have been devoted to developing integrated combs, primarily leveraging Pockels or Kerr nonlinearities. Here, we demonstrate an alternative frequency ...
Functional matrix product state simulation of continuous variable quantum circuits
Andreas Bock Michelsen, Frederik K. Marqversen, Michael Kastoryano·Apr 8, 2025
We introduce a functional matrix product state (FMPS) based method for simulating the real-space representation of continuous-variable (CV) quantum computation. This approach efficiently simulates non-Gaussian CV systems by leveraging their functiona...
Transversal Fault Tolerant Distributed Quantum Computing Operations
John Stack, Ming Wang, Frank Mueller·Apr 8, 2025
Distributed architectures are a route to scalable quantum computing, but the performance of fault-tolerant operations across noisy inter-module links remains poorly characterized. We present circuit-level simulations of two key distributed primitives...