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Quantum tunneling in a many-body system is much more non-trivial than that in a one-body system. The most characteristic phenomenon is the mixed tunneling, which has been studied in many fields for decades. For instance, let us consider a…

高能物理 - 理论 · 物理学 2023-05-11 Yutaro Shoji

Feynman's path integral approach is studied in the framework of the Wigner-Dunkl deformation of quantum mechanics. We start with reviewing some basics from Dunkl theory and investigate the time evolution of a Gaussian wave packet, which…

数学物理 · 物理学 2024-01-30 Georg Junker

The curse of dimensionality in the realm of association rules is twofold. Firstly, we have the well known exponential increase in computational complexity with increasing item set size. Secondly, there is a \emph{related curse} concerned…

人工智能 · 计算机科学 2018-05-16 Tom Hanika , Friedrich Martin Schneider , Gerd Stumme

Feynman's path integrals in ordinary, p-adic and adelic quantum mechanics are considered. The corresponding probability amplitudes $ K(x^{"},t^{"};x',t')$ for two-dimensional systems with quadratic Lagrangians are evaluated analytically and…

数学物理 · 物理学 2010-12-01 Branko Dragovich

Gradient-based (a.k.a. `first order') optimization algorithms are routinely used to solve large scale non-convex problems. Yet, it is generally hard to predict their effectiveness. In order to gain insight into this question, we revisit the…

概率论 · 数学 2024-12-10 Andrea Montanari , Eliran Subag

The classical Feynman-Kac identity builds a bridge between stochastic analysis and partial differential equations (PDEs) by providing stochastic representations for classical solutions of linear Kolmogorov PDEs. This opens the door for the…

概率论 · 数学 2021-10-25 Christian Beck , Martin Hutzenthaler , Arnulf Jentzen

We study the costs and benefits of different quantum approaches to finding approximate solutions of constrained combinatorial optimization problems with a focus on Maximum Independent Set. In the Lagrange multiplier approach we analyze the…

量子物理 · 物理学 2024-08-13 Zain H. Saleem , Teague Tomesh , Bilal Tariq , Martin Suchara

Quantum machine learning, which involves running machine learning algorithms on quantum devices, may be one of the most significant flagship applications for these devices. Unlike its classical counterparts, the role of data in quantum…

量子物理 · 物理学 2024-08-20 Kaining Zhang , Junyu Liu , Liu Liu , Liang Jiang , Min-Hsiu Hsieh , Dacheng Tao

The complexity of matrix multiplication is a central topic in computer science. While the focus has traditionally been on exact algorithms, a long line of literature also considers randomized algorithms, which return an approximate solution…

量子物理 · 物理学 2025-10-10 Simon Apers , Arjan Cornelissen , Samson Wang

Most problems in uncertainty quantification, despite its ubiquitousness in scientific computing, applied mathematics and data science, remain formidable on a classical computer. For uncertainties that arise in partial differential equations…

量子物理 · 物理学 2022-09-29 Francois Golse , Shi Jin , Nana Liu

We realize constant-space quantum computation by measure-many two-way quantum finite automata and evaluate their language recognition power by analyzing patterns of their exotic behaviors and by exploring their structural properties. In…

形式语言与自动机理论 · 计算机科学 2016-06-29 Tomoyuki Yamakami

We investigate the complexity of integration and derivative for multivariate polynomials in the standard computation model. The integration is in the unit cube $[0,1]^d$ for a multivariate polynomial, which has format $f(x_1,\cdots,…

计算复杂性 · 计算机科学 2010-12-13 Bin Fu

Quantum computing involving physical systems with continuous degrees of freedom, such as the quantum states of light, has recently attracted significant interest. However, a well-defined quantum complexity theory for these bosonic…

量子物理 · 物理学 2026-05-20 Ulysse Chabaud , Michael Joseph , Saeed Mehraban , Arsalan Motamedi

Parametrized families of PDEs arise in various contexts such as inverse problems, control and optimization, risk assessment, and uncertainty quantification. In most of these applications, the number of parameters is large or perhaps even…

偏微分方程分析 · 数学 2015-03-04 Albert Cohen , Ronald Devore

The frequent interactions between quantum computing and machine learning revolutionize both fields. One prototypical achievement is the quantum auto-encoder (QAE), as the leading strategy to relieve the curse of dimensionality ubiquitous in…

量子物理 · 物理学 2024-10-03 Yuxuan Du , Dacheng Tao

We investigate the limitations of quantum computers for solving nonlinear dynamical systems. In particular, we tighten the worst-case bounds of the quantum Carleman linearisation (QCL) algorithm [Liu et al., PNAS 118, 2021] answering one of…

量子物理 · 物理学 2024-10-30 Dylan Lewis , Stephan Eidenbenz , Balasubramanya Nadiga , Yiğit Subaşı

The vast and complicated large-qubit state space forbids us to comprehensively capture the dynamics of modern quantum computers via classical simulations or quantum tomography. Recent progress in quantum learning theory prompts a crucial…

量子物理 · 物理学 2025-09-22 Yuxuan Du , Min-Hsiu Hsieh , Dacheng Tao

A critical milestone on the path to useful quantum computers is quantum supremacy - a demonstration of a quantum computation that is prohibitively hard for classical computers. A leading near-term candidate, put forth by the Google/UCSB…

量子物理 · 物理学 2020-11-13 Adam Bouland , Bill Fefferman , Chinmay Nirkhe , Umesh Vazirani

The wave-particle duality and its probabilistic interpretation are at the heart of quantum mechanics. Here we show that, in some standard contexts like the double slit experiment, a deterministic interpretation can be provided. This…

数学物理 · 物理学 2024-01-09 Winfried Lohmiller , Jean-Jacques Slotine

Rydberg atom arrays are among the leading contenders for the demonstration of quantum speedups. Motivated by recent experiments with up to 289 qubits [Ebadi et al., Science 376, 1209 (2022)] we study the maximum independent set problem on…