Papers
Live trends in quantum computing research, updated daily from arXiv.
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Universal Sample Complexity Bounds in Quantum Learning Theory via Fisher Information Matrix
Hyukgun Kwon, Seok Hyung Lie, Liang Jiang·Feb 25, 2026
In this work, we show that the sample complexity required in quantum learning theory within a general parametric framework, is fundamentally governed by the inverse Fisher information matrix. More specifically, we derive upper and lower bounds on the...
Unsupervised Discovery of Intermediate Phase Order in the Frustrated $J_1$-$J_2$ Heisenberg Model via Prometheus Framework
Brandon Yee, Wilson Collins, Maximilian Rutkowski·Feb 25, 2026
The spin-$1/2$ $J_1$-$J_2$ Heisenberg model on the square lattice exhibits a debated intermediate phase between Néel antiferromagnetic and stripe ordered regimes, with competing theories proposing plaquette valence bond, nematic, and quantum spin liq...
CQSA: Byzantine-robust Clustered Quantum Secure Aggregation in Federated Learning
Arnab Nath, Harsh Kasyap·Feb 25, 2026
Federated Learning (FL) enables collaborative model training without sharing raw data. However, shared local model updates remain vulnerable to inference and poisoning attacks. Secure aggregation schemes have been proposed to mitigate these attacks. ...
Deep Sequence Modeling with Quantum Dynamics: Language as a Wave Function
Ahmed Nebli, Hadi Saadatdoorabi, Kevin Yam·Feb 24, 2026
We introduce a sequence modeling framework in which the latent state is a complex-valued wave function evolving on a finite-dimensional Hilbert space under a learned, time-dependent Hamiltonian. Unlike standard recurrent architectures that rely on ga...
Phonon decoherence produced by two-level tunneling states
Ryan O. Behunin, Taylor Ray, Dylan Chapman +3 more·Feb 24, 2026
Phonon modes within pristine crystalline resonators now routinely reach the quantum ground state. Such systems are attractive for quantum information science applications, as advanced fabrication and processing can enable relatively long quantum cohe...
The Inverse Born Rule Fallacy: On the Informational Limits of Phase-Locked Amplitude Encoding
Sebastian Zając, Jacob L. Cybulski, Bartosz Dziewit +1 more·Feb 24, 2026
In Quantum Machine Learning (QML) and Quantum Finance, amplitude encoding is often motivated by its logarithmic storage capacity arXiv:1307.0411. This paradigm typically relies on the mapping $ψ= \sqrt{P}$, treating the quantum state as a derivative ...
Teleportation transition of surface codes on a superconducting quantum processor
Yiren Zou, Hong-Kuan Xia, Aosai Zhang +32 more·Feb 24, 2026
The topological surface code is a leading candidate for harnessing long-range entanglement to protect logical quantum information against errors, and teleportation of logical states is desirable for robust quantum information processing. Nevertheless...
Topological Floquet Green's function zeros
Elio J. König, Aditi Mitra·Feb 24, 2026
Motivated by recent advances in digital quantum emulation using noisy intermediate-scale quantum (NISQ) devices and an increased interest in topological Green's function zeros in condensed matter systems, we here study Green's function zeros in topol...
Quantum Approximate Optimization for Decoding of Low-Density Parity-Check Codes
Krishnakanta Barik, Goutam Paul·Feb 24, 2026
Decoding Low-Density Parity-Check (LDPC) codes is a fundamental problem in coding theory, and Belief Propagation (BP) is one of the most popular methods for LDPC code decoding. However, BP may encounter convergence issues and suboptimal performance, ...
Quantum-limited detection of arrival time and carrier frequency of time-dependent signals
Patrick Folge, Laura Serino, Ladislav Mišta +4 more·Feb 24, 2026
Precise measurements of both the arrival time and carrier frequency of light pulses are essential for time-frequency-encoded quantum technologies. Quantum mechanics, however, imposes fundamental limits on the simultaneous determination of these quant...
Adversarial Information Gain in Non-ideal Quantum Measurements
Andrés Muñoz-Moller, Leevi Leppäjärvi, Teiko Heinosaari·Feb 24, 2026
Performing a quantum measurement yields two different results: a classical outcome drawn from a probability distribution, according to Born's rule, and a quantum outcome corresponding to the post-measurement state. Quantum devices that provide both o...
Enhancing low-temperature quantum thermometry and magnetometry via quadratic interactions in optomechanical-like systems
Asghar Ullah, Özgür E. Müstecaplıoğlu·Feb 24, 2026
Standard optomechanical sensors operating in the low-temperature regime often face fundamental precision limits imposed by vacuum fluctuations. Here, we demonstrate that moving beyond conventional radiation-pressure interactions and exploiting quadra...
Simulating Microwave-Controlled Spin Imaging with Free-Space Electrons
Santiago Beltrán-Romero, Stefan Löffler, Dennis Rätzel +1 more·Feb 24, 2026
Coherent spin resonance techniques, such as nuclear and electron spin resonance spectroscopy, have revolutionized non-invasive imaging by providing spectrally resolved information about spin dynamics. Motivated by the recent emergence of electron mic...
Toward speedup without quantum coherent access
Nhat A. Nghiem·Feb 24, 2026
Along with the development of quantum technology, finding useful applications of quantum computers has been a central pursuit. Despite various quantum algorithms have been developed, many of them often require strong input assumptions, which is hardw...
Generative Deep Learning for the Two-Dimensional Quantum Rotor Model
Yanyang Wang, Feng Gao, Kui Tuo +1 more·Feb 24, 2026
The advancement of diverse generative deep learning models and their variants has furnished substantial insights for investigating quantum many-body problems. In this work, we design two models based on the foundational architecture of generative adv...
A note on entanglement detection via the generalized realignment moments
Xiaofen Huang, Xishun Zhu, Bin Chen +2 more·Feb 24, 2026
The experimental detection of quantum entanglement is of great importance in quantum information processing. We present two separability criteria based on the generalized realignment moments. By incorporating additional parameters, these criteria pro...
Quantum circuit design from a retraction-based Riemannian optimization framework
Zhijian Lai, Hantao Nie, Jiayuan Wu +1 more·Feb 24, 2026
Designing quantum circuits for ground state preparation is a fundamental task in quantum information science. However, standard Variational Quantum Algorithms (VQAs) are often constrained by limited ansatz expressivity and difficult optimization land...
Effect of atom-oscillator interaction on the aging transition in coupled oscillators
Huining Zhang, X. Z. Hao, X. X. Yi·Feb 24, 2026
Oscillators are often employed as a model of radiation fields, which may couple to an atom and play an important role for creating and manipulating nonclassical states in quantum metrology, quantum simulation, and quantum information. Aging transitio...
Measurement-Guided State Refinement for Shallow Feedback-Based Quantum Optimization Algorithm
Lucas A. M. Rattighieri, Pedro M. Prado, Marcos C. de Oliveira +1 more·Feb 23, 2026
Limited circuit depth remains a central constraint for quantum optimization in the noisy intermediate-scale quantum (NISQ) regime, where shallow unitary dynamics may fail to sufficiently concentrate probability on low-energy configurations. We introd...
Direct Variational Calculation of Two-Electron Reduced Density Matrices via Semidefinite Machine Learning
Luis H. Delgado-Granados, David A. Mazziotti·Feb 23, 2026
We introduce a data-driven framework for approximating the convex set of $N$-representable two-electron reduced density matrices (2-RDMs). Traditional approaches characterize this set through linear matrix inequalities that define its supporting hype...