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Latent diffusion models have emerged as the dominant framework for high-fidelity and efficient image generation, owing to their ability to learn diffusion processes in compact latent spaces. However, while previous research has focused…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Qifan Li , Xingyu Zhou , Jinhua Zhang , Weiyi You , Shuhang Gu

How do transformer language models represent magnitude? Recent work disagrees: some find logarithmic spacing, others linear encoding, others per-digit circular representations. We apply the formal tools of psychophysics to resolve this.…

Computation and Language · Computer Science 2026-03-24 Jon-Paul Cacioli

We present a method to extract the phase shift of a scattering process using the real-time evolution in the early and intermediate stages of the collision in order to estimate the time delay of a wave packet. This procedure is convenient…

High Energy Physics - Lattice · Physics 2021-09-22 Erik Gustafson , Yingyue Zhu , Patrick Dreher , Norbert M. Linke , Yannick Meurice

The emergence of classical behavior from quantum mechanics as Planck's constant $\hbar$ approaches zero remains a fundamental challenge in physics [1-3]. This paper introduces a novel approach employing deep neural networks to directly…

Quantum Physics · Physics 2025-04-24 Kamran Majid

We focus on minimally coupled (multi)field quintessence models, of thawing type, and their realistic solutions. In a model-independent manner, we describe analytically these cosmological solutions throughout the universe history. Starting…

High Energy Physics - Theory · Physics 2025-05-26 David Andriot

We perform a systematic investigation of variational forms (wave function Ans\"atze), to determine the ground state energies and properties of two-dimensional model fermionic systems on triangular lattices (with and without periodic…

This paper introduces the Quantum Covariance Embedding, which embeds Positive Operator-Valued Measures into a tensor product of a Reproducing Kernel Hilbert Space and the quantum state space via a tensorized Bochner integral. This…

Statistics Theory · Mathematics 2026-05-26 Philipp Nikolas Mayer , Ho Yun

The Quantum Reverse Shannon Theorem has been a milestone in quantum information theory. It states that asymptotically reliable simulation of a quantum channel, assisted by unlimited shared entanglement, requires a rate of classical…

Quantum Physics · Physics 2025-02-18 Ke Li , Yongsheng Yao

Random measurements have been shown to induce a phase transition in an extended quantum system evolving under chaotic unitary dynamics, when the strength of measurements exceeds a threshold value. Below this threshold, a steady state with a…

Statistical Mechanics · Physics 2021-06-02 Ruihua Fan , Sagar Vijay , Ashvin Vishwanath , Yi-Zhuang You

Quantum Support Vector Machines face scalability challenges due to high-dimensional quantum states and hardware limitations. We propose an embedding-aware quantum-classical pipeline combining class-balanced k-means distillation with…

In this work, we study the tradeoffs between the error probabilities of classical-quantum channels and the blocklength $n$ when the transmission rates approach the channel capacity at a rate slower than $1/\sqrt{n}$, a research topic known…

Quantum Physics · Physics 2017-05-26 Hao-Chung Cheng , Min-Hsiu Hsieh

Reservoir computing leverages rich, non-linear dynamics to process temporal data. Quantum variants promise enhanced expressivity from high-dimensional Hilbert spaces, yet their practical applicability is hindered by hardware noise and…

In the study of weakly turbulent wave systems possessing incomplete self-similarity it is possible to use dimensional arguments to derive the scaling exponents of the Kolmogorov-Zakharov spectra, provided the order of the resonant wave…

Fluid Dynamics · Physics 2009-11-10 Colm Connaughton , Sergey Nazarenko , Alan C. Newell

Analog quantum simulation is emerging as a powerful tool for uncovering classically unreachable physics such as many-body real-time dynamics. A complete quantification of uncertainties is necessary in order to make precise predictions using…

Quantum Physics · Physics 2024-05-16 Nikita A. Zemlevskiy , Henry F. Froland , Stephan Caspar

Variational Autoencoders (VAEs) are powerful generative models capable of learning compact latent representations. However, conventional VAEs often generate relatively blurry images due to their assumption of an isotropic Gaussian latent…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Andrew Kiruluta

Quantum variational algorithms are one of the most promising applications of near-term quantum computers; however, recent studies have demonstrated that unless the variational quantum circuits are configured in a problem-specific manner,…

The Schwinger model (quantum electrodynamics in 1+1 dimensions) is a testbed for the study of quantum gauge field theories. We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and…

Quantum Physics · Physics 2020-08-12 Alexander F. Shaw , Pavel Lougovski , Jesse R. Stryker , Nathan Wiebe

The statistical objects characterizing turbulence in real turbulent flows differ from those of the ideal homogeneous isotropic model.They containcontributions from various 2d and 3d aspects, and from the superposition ofinhomogeneous and…

chao-dyn · Physics 2009-10-31 Susan Kurien , Victor S. L'vov , Itamar Procaccia , K. R. Sreenivasan

We propose coherent (`Schr\"odinger catlike') states adapted to the parity symmetry providing a remarkable variational description of the ground and first excited states of vibron models for finite-($N$)-size molecules. Vibron models…

Quantum Physics · Physics 2014-09-22 M. Calixto , E. Romera , R. del Real

We begin this thesis by expanding the technique of teleportation simulation, which adds noise to the entangled resource state to mimic channel effects. By introducing classical noise in the communication step, we show it is possible to…

Quantum Physics · Physics 2019-04-29 Thomas Cope