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Live trends in quantum computing research, updated daily from arXiv.
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Weighted Approximate Quantum Natural Gradient for Variational Quantum Eigensolver
Chenyu Shi, Vedran Dunjko, Hao Wang·Apr 7, 2025
The variational quantum eigensolver (VQE) is one of the most prominent algorithms using near-term quantum devices, designed to find the ground state of a Hamiltonian. In VQE, a classical optimizer iteratively updates the parameters in the quantum cir...
Markov Gap and Bound Entanglement in Haar Random State
Tian-Ren Jin, Shang Liu, Heng Fan·Apr 7, 2025
Bound entanglement refers to entangled states that cannot be distilled into maximally entangled states and therefore cannot directly be used in many quantum information processing protocols. We identify a relationship between bound entanglement and t...
Unified speed limits in classical and quantum dynamics via temporal Fisher information
Tomohiro Nishiyama, Yoshihiko Hasegawa·Apr 7, 2025
The importance of Fisher information is increasing in nonequilibrium thermodynamics, as it has played a fundamental role in trade-off relations such as thermodynamic uncertainty relations and speed limits. In this work, we investigate temporal Fisher...
Quantum circuits for high-dimensional absolutely maximally entangled states
Berta Casas, Grzegorz Rajchel-Mieldzio'c, Suhail Ahmad Rather +4 more·Apr 7, 2025
Absolutely maximally entangled (AME) states of multipartite quantum systems exhibit maximal entanglement across all possible bipartitions. These states lead to teleportation protocols that surpass standard teleportation schemes, determine quantum err...
Measuring the Oscillation Frequency Beyond the Diffraction Limit
Chao-Ning Hu, Jun Xin, Xiao-Ming Lu·Apr 6, 2025
High-resolution array detectors are widely used in single-particle tracking, but their performance is limited by excess noise from background light and dark current. As pixel resolution increases, the diminished signal per pixel exacerbates susceptib...
Quantum parallel information exchange (QPIE) hybrid network with transfer learning
Ziqing Guo, Alex Khan, Victor Sheng +2 more·Apr 5, 2025
Quantum machine learning (QML) has emerged as an innovative framework that has the potential to uncover complex patterns by leveraging the ability of quantum systems to simulate and exploit high-dimensional latent spaces, particularly in learning tas...
Experiment indicates that Realism, not Locality, is false in Quantum Mechanics
Mónica Agüero, Juliana Bordieu, Alejandro Hnilo +2 more·Apr 4, 2025
The interpretation of the meaning of Quantum Mechanics has faced controversy since its inception. Bell's inequalities are a touchstone in this controversy. Their observed violation demonstrates that at least one of the hypotheses involved in their de...
Reducing quantum error correction overhead using soft information
Joonas Majaniemi, Elisha S. Matekole·Apr 4, 2025
Imperfect measurements are a prevalent source of error across quantum computing platforms, significantly degrading the logical error rates achievable on current hardware. To mitigate this issue, rich measurement data referred to as soft information h...
Quantum conditional mutual information as a probe of measurement-induced entanglement phase transitions
Yuichi Otsuka, Kazuhiro Seki, Seiji Yunoki·Apr 4, 2025
We propose that the quantum conditional mutual information (QCMI), computed with a suitably chosen partition of the system, serves as a powerful probe for detecting measurement-induced entanglement phase transitions in monitored quantum circuits. To ...
Dynamically stable two-mode squeezing in cavity optomechanics
Chen Wang, Shi-fan Qi·Apr 4, 2025
Bosonic two-mode squeezed states are paradigmatic entangled states with broad applications in quantum information processing and quantum metrology. In this work, we propose a two-mode squeezing scheme in a hybrid three-mode cavity optomechanical syst...
Tracking and Distinguishing Slime Mold Solutions to the Traveling Salesman Problem through Synchronized Amplification in the Non-Equilibrium Steady State
Suyash Bajpai, M. Aono, Philip Kurian·Apr 4, 2025
The plasmodium of the true slime mold Physarum polycephalum serves as a platform to study information processing in non-equilibrium active matter, showing complex oscillations and computation despite its simple morphology. Past experiments used Physa...
Monitored Fluctuating Hydrodynamics
Sarang Gopalakrishnan, Ewan McCulloch, Romain Vasseur·Apr 3, 2025
We introduce a hydrodynamic framework for describing monitored classical stochastic processes. We study the conditional ensembles for these monitored processes -- i.e., we compute spacetime correlation functions conditioned on a fixed, typical measur...
HQViT: Hybrid Quantum Vision Transformer for Image Classification
Hui Zhang, Qinglin Zhao, MengChu Zhou +1 more·Apr 3, 2025
Transformer-based architectures have revolutionized the landscape of deep learning. In computer vision domain, Vision Transformer demonstrates remarkable performance on par with or even surpassing that of convolutional neural networks. However, the q...
Quantum Gibbs states are locally Markovian
Chi-Fang Chen, Cambyse Rouz'e·Apr 3, 2025
The Markov property entails the conditional independence structure inherent in Gibbs distributions for general classical Hamiltonians, a feature that plays a crucial role in inference, mixing time analysis, and algorithm design. However, much less is...
General channel capacities from quantum channel-state duality
Y.-D. Liu, D.-S. Wang·Apr 2, 2025
The quantum channel-state duality permits the characterization of a quantum process through a quantum state, referred to as a Choi state. This characteristic serves as the impetus for the quantum computing paradigm that utilizes Choi states as inform...
Bayesian critical points in classical lattice models
Adam Nahum, J. Jacobsen·Apr 2, 2025
The Boltzmann distribution encodes our subjective knowledge of the configuration in a classical lattice model, given only its Hamiltonian. If we acquire further information about the configuration from measurement, our knowledge is updated accordin...
Output Prediction of Quantum Circuits based on Graph Neural Networks
Yuxiang Liu, Fanxu Meng, Lu Wang +3 more·Apr 1, 2025
The output prediction of quantum circuits is a formidably challenging task imperative in developing quantum devices. Motivated by the natural graph representation of quantum circuits, this paper proposes a Graph Neural Networks (GNNs)-based framework...
Quantum Resetting Protocols Based on Synchronizing Words
Jkedrzej Stempin, Jan W'ojcik, Andrzej Grudka +3 more·Apr 1, 2025
Resetting a system's state plays a fundamental role in physics, engineering, computer science, and many other fields. Here we focus on a method originally proposed in automata theory. The state of an automaton evolves according to a set of rules. The...
Operating two exchange-only qubits in parallel
Mateusz T. Mkadzik, F. Luthi, G. Guerreschi +38 more·Apr 1, 2025
Semiconductors are among the most promising platforms to implement large-scale quantum computers, as advanced manufacturing techniques allow fabrication of large quantum dot arrays1. Various qubit encodings can be used to store and manipulate quantum...
Deterministic quantum trajectory via imaginary time evolution
Shivan Mittal, Bin Yan·Mar 31, 2025
Stochastic quantum trajectories, such as pure state evolutions under unitary dynamics and random measurements, offer a crucial ensemble description of many-body open system dynamics. Recent studies have highlighted that individual quantum trajectorie...