Suche: quantum advantage

16 Paper gefunden.

• Foundations of Practical Quantum Advantage in Quantum-Informed Machine Learning for Predicting Chaos

  Maida Wang, Xiao Xue, Minh Chung, Peter V. Coveney · 24. Juni 2026 · Quantum many-body systems

  We develop theoretical foundations for a practical quantum-advantage mechanism in quantum-informed machine learning for chaotic dynamical systems. A family of $k$-indexed higher-order quantum statistical priors (Q-Priors) hosts the $k$-point marginal of the invariant measure on $n_q = kq$ qubits, ex…

• Exponential quantum advantage in processing massive classical data

  Haimeng Zhao, Alexander Zlokapa, Hartmut Neven, Ryan Babbush, John Preskill, Jarrod R. McClean, Hsin-Yuan Huang · 2. Oktober 2026 · Quantum Computing Algorithms and Architecture

  Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In this work, we prove that a small quantum computer of polylogarithmic size can perform large-scale classification and dimension reduction on massive classical …

• An Irreducible Quantum Advantage in Aligning World Models with Reality

  Josep Lumbreras, Hailan Ma, Jayne Thompson, Mile Gu · 21. August 2026 · Quantum Mechanics and Applications

  World models provide digital simulacra of the true world, allowing agents to be trained and tested before costly real-world deployment. At each time step, they receive an action and generate an observation and reward matching the statistics of the true world. In complex environments where present ou…

• Exponential quantum advantage for learning signals with a single qubit

  Ishaan Kannan, Sridhar Prabhu, Saeed A. Khan, Mandar M. Sohoni, Xingrui Song, Saswata Roy, Alen Senanian, Valla Fatemi, Peter L. McMahon, Jordan Cotler · 14. August 2026 · Quantum Information and Cryptography

  Quantum technology has the potential to transform scientific discovery, but quantum advantages often require processing capabilities well beyond the reach of experimental platforms. We show that coupling a single controllable qubit to an otherwise conventional sensor can exponentially reduce the num…

• One Qubit Can Beat One Bit: Quantum Advantage for Post-Training Quantization

  Yuma Ichikawa, Moeto Mishima · 7. August 2026 · Quantum Computing Algorithms and Architecture

  One-bit post-training quantization represents each weight using only its sign, requiring all deployment contexts to share the same binary weight matrix even when their activation statistics favor different sign patterns. We study this shared-sign constraint and introduce Quantum Random Access Quanti…

• Quantum Advantage in Multi Agent Reinforcement Learning

  Simranjeet Singh Dahia, Claudia Szabo · 15. Mai 2026 · Quantum Computing Algorithms and Architecture

  We present an empirical evaluation of quantum entanglement in agent coordination within quantum multi agent reinforcement learning (QMARL). While QMARL has attracted growing interest recently, most prior work evaluates quantum policies without provable baselines, making it impossible to rigorously d…

• Quantum-Informed Machine Learning for Predicting Spatiotemporal Chaos with Practical Quantum Advantage

  Maida Wang, Xiao Xue, Mingyang Gao, Peter V. Coveney · 16. März 2026 · Neural Networks and Applications

  We introduce a quantum-informed machine learning (QIML) framework for modelling the long-term behaviour of high-dimensional chaotic systems. QIML combines a one-time, offline-trained quantum generative model with a classical autoregressive predictor for spatiotemporal field generation. The quantum m…

• Quantum advantage for learning shallow neural networks with natural data distributions

  Laura Lewis, Dar Gilboa, Jarrod R. McClean · 11. Februar 2026 · Quantum Computing Algorithms and Architecture

  Without large quantum computers to empirically evaluate performance, theoretical frameworks such as the quantum statistical query (QSQ) are a primary tool to study quantum algorithms for learning classical functions and search for quantum advantage in machine learning tasks. However, we only underst…

• Prospects for quantum advantage in machine learning from the representability of functions

  Sergi Masot-Llima, Elies Gil-Fuster, Carlos Bravo-Prieto, Jens Eisert, and Tommaso Guaita · 18. Dezember 2025 · Quantum Computing Algorithms and Architecture

  Demonstrating quantum advantage in machine learning tasks requires navigating a complex landscape of proposed models and algorithms. To bring clarity to this search, we introduce a framework that connects the structure of parametrized quantum circuits to the mathematical nature of the functions they…

• Limitations of Quantum Advantage in Unsupervised Machine Learning

  Apoorva D. Patel · 18. November 2025 · Quantum Computing Algorithms and Architecture

  Machine learning models are used for pattern recognition analysis of big data, without direct human intervention. The task of unsupervised learning is to find the probability distribution that would best describe the available data, and then use it to make predictions for observables of interest. Cl…

• Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings

  Sebastian Cajas Ord\'o\~nez, Felipe Ocampo Osorio, Dax Enshan Koh, Rafi Al Attrach, Aldo Marzullo, Ariel Guerra-Adames, J. Alejandro Andrade, Siong Thye Goh, Chi-Yu Chen, Rahul Gorijavolu, Xue Yang, Noah Dane Hebdon, Leo Anthony Celi · 29. April 2026 · Quantum Computing Algorithms and Architecture

  We provide evidence of quantum kernel advantage under noiseless simulation in binary insurance classification on MIMIC-CXR chest radiographs using quantum support vector machines (QSVM) with frozen embeddings from three medical foundation models (MedSigLIP-448, RAD-DINO, ViT-patch32). We propose a t…

• How Quantum Is the Advantage? A Fair, Calibration- and Noise-Aware Benchmark and Attribution Audit of Quantum Machine Learning for Network Intrusion Detection

  Syeda Anshrah Gillani, Mirza Samad Ahmed Baig, Shahid Munir Shah, Asher Ali, Hamzah Siddiqui · 20. August 2026 · Network Security and Intrusion Detection

  Quantum machine learning (QML) for network intrusion detection (NIDS) is routinely reported to reach near-perfect accuracy, yet the most rigorous studies find that well-tuned classical models remain competitive, and that apparent quantum gains may be artefacts of classical dimensionality reduction a…

• Quantum entanglement provides a competitive advantage in adversarial games

  Peiyong Wang, Kieran Hymas, James Quach · 12. März 2026 · Quantum Computing Algorithms and Architecture

  Whether uniquely quantum resources confer advantages in fully classical, competitive environments remains an open question. Competitive zero-sum reinforcement learning is particularly challenging, as success requires modelling dynamic interactions between opposing agents rather than static state-act…

• Hybrid Quantum-Classical Mixture of Experts: Unlocking Topological Advantage via Interference-Based Routing

  Reda Heddad, Lamiae Bouanane · 30. Dezember 2025 · Quantum Computing Algorithms and Architecture

  The Mixture-of-Experts (MoE) architecture has emerged as a powerful paradigm for scaling deep learning models, yet it is fundamentally limited by challenges such as expert imbalance and the computational complexity of classical routing mechanisms. This paper investigates the potential of Quantum Mac…

• Quantum ring all-reduce: communication and privacy advantages for distributed learning

  Mar\'ia Gragera Garc\'es, Lirand\"e Pira · 19. Juni 2026 · Quantum Information and Cryptography

  Machine learning models have scaled to unprecedented sizes, making training across distributed devices the de facto standard in the field. In this work, we explore how quantum communications can make distributed training both more communication-efficient and information-theoretically private, for bo…

• Practical advantage beyond the quadratic speedup limit with fully-quantum walks

  Massimiliano Incudini, Guglielmo Mazzola · 28. Juli 2026 · Quantum Computing Algorithms and Architecture

  We introduce a new class of fully-quantum Metropolis walks in which both the proposal and acceptance steps are intrinsically quantum. Unlike standard quantum walks obtained by quantizing classically efficient Markov chains, our algorithm employs Hamiltonian simulation as a quantum-native proposal me…