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In this article, we propose the realization of conformal manifolds, which are smooth manifolds of scale-conformal invariant interacting Hamiltonians in two-dimensional quantum many-body systems. Such phenomena can occur in various…

Strongly Correlated Electrons · Physics 2026-01-23 Saran Vijayan , Fei Zhou

Transmission switching (TS) has gained significant attention recently. However, barriers still remain and must be overcome before the technology can be adopted by the industry. The state of the art challenges include AC feasibility and…

Finite dimensional truncations and the single field approximation have thus far played dominant roles in investigations of asymptotic safety for quantum gravity. This thesis is devoted to exploring asymptotic safety in infinite dimensional,…

High Energy Physics - Theory · Physics 2016-05-31 Juergen Dietz

Quantum computing has the potential to revolutionize quantum chemistry and material science by offering solutions to complex problems unattainable with classical computers. However, the development of efficient quantum algorithms that are…

The Renormalisation Group is a versatile tool for the study of many systems where scale-dependent behaviour is important. Its functional formulation can be cast into the form of an exact flow equation for the scale-dependent effective…

High Energy Physics - Theory · Physics 2015-12-14 Jan M. Pawlowski , Michael M. Scherer , Richard Schmidt , Sebastian J. Wetzel

We consider perturbations of unitary minimal models by boundary fields. Initially we consider the models in the limit as c -> 1 and find that the relevant boundary fields all have simple interpretations in this limit. This interpretation…

High Energy Physics - Theory · Physics 2009-11-07 K. Graham , I. Runkel , G. M. T Watts

Density estimation and reliable prediction regions for outputs are crucial in supervised and unsupervised learning. While conformal prediction effectively generates coverage-guaranteed regions, it struggles with multi-dimensional outputs…

Machine Learning · Statistics 2026-05-12 Zhenhan Fang , Aixin Tan , Jian Huang

A highly anticipated use of quantum computers is the simulation of complex quantum systems including molecules and other many-body systems. One promising method involves directly applying a linear combination of unitaries (LCU) to…

Quantum Physics · Physics 2022-02-02 Richard Meister , Simon C. Benjamin , Earl T. Campbell

We present a renormalization group (RG) method which allows for an analytical study of the transient dynamics of open quantum systems on all time scales. Whereas oscillation frequencies and decay rates of exponential time evolution follow…

Strongly Correlated Electrons · Physics 2013-05-23 Oleksiy Kashuba , Herbert Schoeller

The supersymmetric reformulation of physical observables in the Chalker-Coddington model (CC) for the plateau transition in the integer quantum Hall effect leads to a reformulation of its critical properties in terms of a 2D non-compact…

Statistical Mechanics · Physics 2019-03-27 Romain Couvreur , Eric Vernier , Jesper Lykke Jacobsen , Hubert Saleur

There is a wide literature on change point tests, but the case of variables with infinite variances is essentially unexplored. In this paper we address this problem by studying the asymptotic behavior of trimmed CUSUM statistics. We show…

Statistics Theory · Mathematics 2012-01-06 István Berkes , Lajos Horváth , Johannes Schauer

This work is an attempt to develop an approximate scheme for estimating the volume-based truncation errors in the finite volume analysis of laminar flows. The volume-based truncation error is the net flow error across the faces of a control…

Computational Physics · Physics 2019-04-04 Amir Reza Baserinia

In previous works, the projected truncation approximation (PTA) was developed as a systematic and controlled method to truncate the equation of motion of Green's functions (GFs) for a given quantum or classical many-body Hamiltonian. The…

Strongly Correlated Electrons · Physics 2026-05-20 Kou-Han Ma , Yue-Hong Wu , Ning-Hua Tong

Completely random measures (CRMs) and their normalizations are a rich source of Bayesian nonparametric priors. Examples include the beta, gamma, and Dirichlet processes. In this paper we detail two major classes of sequential CRM…

Statistics Theory · Mathematics 2020-05-11 Trevor Campbell , Jonathan H. Huggins , Jonathan P. How , Tamara Broderick

Tensor canonical correlation analysis (TCCA) has garnered significant attention due to its effectiveness in capturing high-order correlations in multi-view learning. However, existing TCCA methods often underemphasize the characterization…

Optimization and Control · Mathematics 2025-12-10 Yanjiao Zhu , Wanquan Liu , Xianchao Xiu , Jianqin Sun

Tensor Robust Principal Component Analysis (TRPCA) is a fundamental technique for decomposing multi-dimensional data into a low-rank tensor and an outlier tensor, yet existing methods relying on sparse outlier assumptions often fail under…

Numerical Analysis · Mathematics 2025-04-28 Yangyang Xu , Kexin Li , Li Yang , You-Wei Wen

An accurate description of the nonequilibrium dynamics of systems with coupled spin and bosonic degrees of freedom remains theoretically challenging, especially for large system sizes and in higher than one dimension. Phase space methods…

Quantum Gases · Physics 2017-09-13 A. Piñeiro Orioli , A. Safavi-Naini , M. L. Wall , A. M. Rey

Total Internal Reflection Fluorescence Cross Correlation Spectroscopy (TIR-FCCS) has recently (S. Yordanov et al., Optics Express 17, 21149 (2009)) been established as an experimental method to probe hydrodynamic flows near surfaces, on…

Soft Condensed Matter · Physics 2015-05-30 R. Schmitz , S. Yordanov , H. J. Butt , K. Koynov , B. Duenweg

Quantum simulations of bosonic field theories require a truncation in field space to map the theory onto finite quantum registers. Ideally, the truncated theory preserves the symmetries of the original model and has a critical point in the…

High Energy Physics - Lattice · Physics 2023-02-22 Andrei Alexandru , Paulo F. Bedaque , Andrea Carosso , Michael J. Cervia , Andy Sheng

This work presents a new algorithm for empirical risk minimization. The algorithm bridges the gap between first- and second-order methods by computing a search direction that uses a second-order-type update in one subspace, coupled with a…

Optimization and Control · Mathematics 2020-06-09 Majid Jahani , Mohammadreza Nazari , Rachael Tappenden , Albert S. Berahas , Martin Takáč