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The search for artificial topological superconductivity has been limited by the stringent conditions required for its emergence. As exemplified by the recent discoveries of various correlated electronic states in twisted van der Waals…

Mesoscale and Nanoscale Physics · Physics 2022-01-14 Shawulienu Kezilebieke , Viliam Vaňo , Md N. Huda , Markus Aapro , Somesh Chandra Ganguli , Peter Liljeroth , Jose L. Lado

We investigate fully self-consistent multiscale quantum-classical algorithms on current generation superconducting quantum computers, in a unified approach to tackle the correlated electronic structure of large systems in both quantum…

Qubits strongly coupled to a photonic crystal give rise to many exotic physical scenarios, beginning with single and multi-excitation qubit-photon dressed bound states comprising induced spatially localized photonic modes, centered around…

Quantum Physics · Physics 2019-02-06 Neereja M. Sundaresan , Rex Lundgren , Guanyu Zhu , Alexey V. Gorshkov , Andrew A. Houck

The variety of correlated phenomena in moir\'e systems is incredibly rich, spanning effects such as superconductivity, a generalized form of ferromagnetism, or even charge fractionalization. This wide range of quantum phenomena is partly…

Mesoscale and Nanoscale Physics · Physics 2023-10-31 Michał Papaj , Guangxin Ni , Cyprian Lewandowski

The search for topological superconductors has recently become a key issue in condensed matter physics, because of their possible relevance to provide a platform for Majorana bound states, non-Abelian statistics, and fault-tolerant quantum…

Superconductivity · Physics 2015-09-29 Lars Elster , Christian Platt , Ronny Thomale , Werner Hanke , Ewelina M. Hankiewicz

Understanding quantum many-body systems is at the heart of condensed matter physics. The ability to control the underlying lattice geometry of a system, and thus its many-body interactions, would enable the realization of and transition…

Mesoscale and Nanoscale Physics · Physics 2023-08-09 Eric Anderson , Feng-Ren Fan , Jiaqi Cai , William Holtzmann , Takashi Taniguchi , Kenji Watanabe , Di Xiao , Wang Yao , Xiaodong Xu

Computing spectral functions in large, non-periodic super-moir\'e systems remains an open problem due to the exceptionally large system size that must be considered. Here, we establish a tensor network methodology that allows computing…

Strongly Correlated Electrons · Physics 2026-05-12 Anouar Moustaj , Yitao Sun , Tiago V. C. Antão , Jose L. Lado

The electronic and magnetic properties of many strongly-correlated systems are controlled by a limited number of states, located near the Fermi level and well isolated from the rest of the spectrum. This opens a formal way for combining the…

Strongly Correlated Electrons · Physics 2010-07-15 I. V. Solovyev

One important yet exceedingly rare property of the cuprate high-temperature superconductors is the presence of a single correlated $d$ band in the low-energy spectrum, leading to the one-band Hubbard model as the minimal description. In…

Strongly Correlated Electrons · Physics 2019-06-05 Eric B. Isaacs , Chris Wolverton

Quantum state tomography (QST) is the gold standard technique for obtaining an estimate for the state of small quantum systems in the laboratory. Its application to systems with more than a few constituents (e.g. particles) soon becomes…

Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproducing kernel Hilbert space. Beyond this classical setting,…

Numerical Analysis · Mathematics 2025-05-19 Toni Karvonen , Gabriele Santin , Tizian Wenzel

Inspired by recent advances in the chromosome capture techniques, a method is proposed to study the structural organization of systems of polymers rings with topological constraints.To this purpose, the system is divided into compartments…

Soft Condensed Matter · Physics 2024-03-08 Neda Abbasi Taklimi , Franco Ferrari , Marcin Radosław Piątek , Luca Tubiana

Strong electron-electron interaction can induce Mott insulating state, which is believed to host unusual correlated phenomena such as quantum spin liquid when quantum fluctuation dominates and unconventional superconductivity through…

Strongly Correlated Electrons · Physics 2025-04-24 Qiang Gao , Haiyang Chen , Wen-shin Lu , Yang-hao Chan , Zhenhua Chen , Yaobo Huang , Zhengtai Liu , Peng Chen

In this tutorial-style review we discuss basic concepts of coupled cluster theory and recent developments that increase its computational efficiency for calculations of molecules, solids and materials in general. We will touch upon the…

Materials Science · Physics 2020-04-15 Igor Ying Zhang , Andreas Grüneis

We introduce a high-performance linear-scaling electronic structure method that employs chromatic superposition states (CSS) as a low-dimensional, high-fidelity representation, which can be orders of magnitude smaller than the full Hilbert…

Materials Science · Physics 2026-05-21 Zhikang Jiang , Zhizhi Xiao , Mingfa Tang , Weiyu Li , Zhaoru Sun , Ke Xia , Youqi Ke

There are several important solid-state systems, such as defects in solids, superconducting circuits and molecular qubits, for attractive candidates of quantum computations. Molecular qubits, which benefit from the power of chemistry for…

Quantum Physics · Physics 2017-06-29 Yingqiu Dai , Zhifu Shi , Yue Fu , Xi Qin , Shiwei Mu , Yang Wu , Ji-Hu Su , Lei Qin , Yuan-Qi Zhai , Yi-Fei Deng , Xing Rong , Jiangfeng Du

This work explores the representation of univariate and multivariate functions as matrix product states (MPS), also known as quantized tensor-trains (QTT). It proposes an algorithm that employs iterative Chebyshev expansions and Clenshaw…

Layers of two-dimensional materials stacked with a small twist-angle give rise to beating periodic patterns on a scale much larger than the original lattice, referred to as a moir\'e superlattice. When the stacking involves more than two…

Mesoscale and Nanoscale Physics · Physics 2020-12-03 Kan-Ting Tsai , Xi Zhang , Ziyan Zhu , Yujie Luo , Stephen Carr , Mitchell Luskin , Efthimios Kaxiras , Ke Wang

While there have been many developments in computational probes of both strongly-correlated molecular systems and machine-learning accelerated molecular dynamics, there remains a significant gap in capabilities in simulating accurate…

Chemical Physics · Physics 2025-04-04 Yannic Rath , George H. Booth

In many instances one has to deal with parametric models. Such models in vector spaces are connected to a linear map. The reproducing kernel Hilbert space and affine- / linear- representations in terms of tensor products are directly…

Numerical Analysis · Mathematics 2018-11-26 Hermann G. Matthies , Roger Ohayon