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We present a variational density matrix approach to the thermal properties of interacting fermions in the continuum. The variational density matrix is parametrized by a permutation equivariant many-body unitary transformation together with…

Strongly Correlated Electrons · Physics 2022-04-04 Hao Xie , Linfeng Zhang , Lei Wang

An emerging trend in approximate counting is to show that certain `low-temperature' problems are easy on typical instances, despite worst-case hardness results. For the class of regular graphs one usually shows that expansion can be…

Data Structures and Algorithms · Computer Science 2024-02-06 Charles Carlson , Ewan Davies , Alexandra Kolla

A novel physics-informed operator learning technique based on spectral methods is introduced to model the complex behavior of heterogeneous materials. The Lippmann-Schwinger operator in Fourier space is employed to construct physical…

Materials Science · Physics 2025-06-26 Ali Harandi , Hooman Danesh , Kevin Linka , Stefanie Reese , Shahed Rezaei

Stable partitioned techniques for simulating unsteady fluid-structure interaction (FSI) are known to be computationally expensive when high added-mass is involved. Multiple coupling strategies have been developed to accelerate these…

Computational Engineering, Finance, and Science · Computer Science 2025-02-18 Azzeddine Tiba , Thibault Dairay , Florian de Vuyst , Iraj Mortazavi , Juan-Pedro Berro Ramirez

In this work, we develop adaptive schemes using goal-oriented error control for a highly nonlinear flow temperature model with temperature dependent density. The dual-weighted residual method for computing error indicators to steer mesh…

Numerical Analysis · Mathematics 2024-04-03 Sven Beuchler , Ayhan Demircan , Bernhard Endtmayer , Uwe Morgner , Thomas Wick

In the field of Artificial Intelligence (AI) and Machine Learning (ML), the approximation of unknown target functions $y=f(\mathbf{x})$ using limited instances $S={(\mathbf{x^{(i)}},y^{(i)})}$, where $\mathbf{x^{(i)}} \in D$ and $D$…

Machine Learning · Computer Science 2023-08-14 Pablo Moscato , Mohammad Nazmul Haque , Kevin Huang , Julia Sloan , Jon C. de Oliveira

This paper aims to develop an efficient adaptive finite element method for the second-order elliptic problem. Although the theory for adaptive finite element methods based on residual-type a posteriori error estimator and bisection…

Numerical Analysis · Mathematics 2025-03-24 Jingjing Xiao , Ying Liu , Nianyu Yi

We establish rigorous \emph{a posteriori} error bounds for a space-time finite element method of arbitrary order discretising linear wave problems in second order formulation. The method combines standard finite elements in space and…

Numerical Analysis · Mathematics 2026-04-24 Zhaonan Dong , Emmanuil H. Georgoulis , Lorenzo Mascotto , Zuodong Wang

Accurately quantifying the increased risks of climate extremes requires generating large ensembles of climate realization across a wide range of emissions scenarios, which is computationally challenging for conventional Earth System Models.…

Computational Physics · Physics 2025-08-22 Mengze Wang , Benedikt Barthel Sorensen , Themistoklis Sapsis

We consider adaptive finite element methods for second-order elliptic PDEs, where the arising discrete systems are not solved exactly. For contractive iterative solvers, we formulate an adaptive algorithm which monitors and steers the…

Numerical Analysis · Mathematics 2021-07-14 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Stefan Schimanko

A methodology is proposed, which addresses the caveat that line-of-sight emission spectroscopy presents in that it cannot provide spatially resolved temperature measurements in nonhomogeneous temperature fields. The aim of this research is…

Machine Learning · Computer Science 2022-12-16 Ruiyuan Kang , Dimitrios C. Kyritsis , Panos Liatsis

In context of laser powder bed fusion (L-PBF), it is known that the properties of the final fabricated product highly depend on the temperature distribution and its gradient over the manufacturing plate. In this paper, we propose a novel…

Artificial Intelligence · Computer Science 2023-01-31 Ashkan Mansouri Yarahmadi , Michael Breuß , Carsten Hartmann

To prepare images for better segmentation, we need preprocessing applications, such as smoothing, to reduce noise. In this paper, we present an enhanced computation method for smoothing 2D object in binary case. Unlike existing approaches,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-31 Ramzi Mahmoudi , Mohamed Akil

We apply a generalization of the time-dependent DMRG to study finite temperature properties of several quantum spin chains, including the frustrated $J_1-J_2$ model. We discuss several practical issues with the method, including use of…

Strongly Correlated Electrons · Physics 2007-05-23 A. E. Feiguin , Steven R. White

We propose a numerical spectral reconstruction workflow for high-temperature gauge theories that incorporates elements of semi-classical real-time evolution directly into standard lattice QCD simulations via high-temperature dimensional…

High Energy Physics - Lattice · Physics 2025-12-30 P. V. Buividovich , B. Hind

Temperature evolution of the 2H-TaSe2 Fermi surface (FS) is studied by high-resolution angle-resolved photoemission spectroscopy (ARPES). High-accuracy determination of the FS geometry was possible after measuring electron momenta and…

Strongly Correlated Electrons · Physics 2009-03-20 D. S. Inosov , D. V. Evtushinsky , V. B. Zabolotnyy , A. A. Kordyuk , B. Buechner , R. Follath , H. Berger , S. V. Borisenko

The large variation of datasets is a huge barrier for image classification tasks. In this paper, we embraced this observation and introduce the finite temperature tensor network (FTTN), which imports the thermal perturbation into the matrix…

Machine Learning · Computer Science 2021-04-27 Haoxiang Lin , Shuqian Ye , Xi Zhu

We reinvestigate the large degeneracy solution of the multichannel Kondo problem, and show how in the universal regime the complicated integral equations simplifying the problem can be mapped onto a first order differential equation. This…

Strongly Correlated Electrons · Physics 2009-11-10 Serge Florens

In this paper, gradient-based optimization methods are combined with finite-element modeling for improving electric devices. Geometric design parameters are considered by affine decomposition of the geometry or by the design element…

The virial expansion provides a non-perturbative view into the thermodynamics of quantum many-body systems in dilute regimes. While powerful, the expansion is challenging as calculating its coefficients at each order $n$ requires analyzing…

Quantum Gases · Physics 2023-02-13 Aleks J. Czejdo , Joaquin E. Drut , Yaqi Hou , Kaitlyn J. Morrell