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By numerical exact diagonalization techniques, we obtain the quantum phase diagram of the lattice fractional quantum Hall (FQH) systems in the presence of quenched disorder. By implementing an array of local potential traps representing the…

Strongly Correlated Electrons · Physics 2012-05-16 Shuo Yang , Kai Sun , S. Das Sarma

Quantum computing experiments have made remarkable progress in demonstrating key components of quantum error correction, a prerequisite for scalable quantum computation. While we anticipate the arrival of early fault-tolerant quantum…

Helical trilayer graphene realizes a versatile moir\'e system for exploring correlated topological states emerging from high Chern bands. Motivated by recent experimental observations of anomalous Hall effects at fractional fillings of…

Strongly Correlated Electrons · Physics 2025-10-02 Sen Niu , Jason Alicea , D. N. Sheng , Yang Peng

Tunnelling measurements on fractional quantum Hall systems are continuing to increase in popularity since they provide a method to probe the non-Fermi liquid behaviour of fractionally charged excitations occupying the edge states of a…

Strongly Correlated Electrons · Physics 2014-10-27 S. Huntington , V. Cheianov

Graphene enables precise carrier-density control via gating, making it an ideal platform for studying electronic interactions. However, sample inhomogeneities often limit access to the low-density regimes where these interactions dominate.…

We present a rigorous theoretical framework for designing full-space spatial power dividers using metagratings. In our study, the current restrictions of spatial power dividing platforms such as reflection-only performance, operating at…

Applied Physics · Physics 2021-09-29 Hamid Rajabalipanah , Ali Abdolali

We present a methodology for designing metagratings for perfect anomalous refraction, based on multilayered loaded wire arrays. In recent work, it has been shown that such structures can implement perfect anomalous deflection and beam…

Applied Physics · Physics 2018-04-09 Ariel Epstein , Oshri Rabinovich

In this paper we present an architecture that enables the redesign of large-scale quantum circuits on quantum hardware based on the entangling quantum generative adversarial network (EQ-GAN). Specifically, by prepending a random quantum…

Quantum Physics · Physics 2025-05-19 Runhong He , Ji Guan , Xin Hong , Guolong Cui , Shengbin Wang , Shenggang Ying

Quantum Random Access Memory (QRAM) holds the promise of enabling several large scale applications of quantum computers. However, designing fault tolerant QRAMs for large scale applications is still an open problem due to the poor error and…

Quantum Physics · Physics 2025-12-09 Ansh Singal , Kaitlin N. Smith

We develop a hybrid Monte Carlo method to efficiently compute the physical observables from the samplings of the Laughlin and the Moore-Read wave functions of fractional quantum Hall (FQH) systems. With the advancements in methodology,…

Strongly Correlated Electrons · Physics 2026-02-20 Ting-Tung Wang , Ha Quang Trung , Qianhui Xu , Min Long , Bo Yang , Zi Yang Meng

Natural cellular materials, such as honeycombs, woods, foams, trabecular bones, plant parenchyma, and sponges, may benefit from the disorderliness within their internal microstructures to achieve damage tolerant behaviours. Inspired by…

Disordered Systems and Neural Networks · Physics 2022-07-21 Akash Singh Bhuwal , Yong Pang , Ian Ashcroft , Wei Sun , Tao Liu

We report a systematic study of the fractional quantum Hall effect (FQHE) using the density-matrix renormalization group (DMRG) method on two different geometries: the sphere and the cylinder. We provide convergence benchmarks based on…

Strongly Correlated Electrons · Physics 2015-06-04 Zi-Xiang Hu , Z. Papic , S. Johri , R. N. Bhatt , Peter Schmitteckert

Mechanical deformations of graphene induce a term in the Dirac Hamiltonian which is reminiscent of an electromagnetic vector potential. Strain gradients along particular lattice directions induce local pseudomagnetic fields and substantial…

Mesoscale and Nanoscale Physics · Physics 2020-01-22 Eran Sela , Yakov Bloch , Felix von Oppen , Moshe Ben Shalom

Recent experimental and theoretical development in the Quantum Hall effect in monolayer graphene showed that the previous model of the valley-anisotropy interaction is incomplete, as it was assumed to be ultra-short range (USR). In this…

Mesoscale and Nanoscale Physics · Physics 2025-01-28 Oleg Grigorev , Ankur Das

Engineered micro- and nanomechanical resonators with ultra-low dissipation constitute the ideal systems for applications ranging from high-precision sensing such as magnetic resonance force microscopy, to quantum transduction between…

Mesoscale and Nanoscale Physics · Physics 2021-10-27 Dennis Høj , Fengwen Wang , Wenjun Gao , Ulrich Busk Hoff , Ole Sigmund , Ulrik Lund Andersen

An arbitrarily reliable quantum computer can be efficiently constructed from noisy components using a recursive simulation procedure, provided that those components fail with probability less than the fault-tolerance threshold. Recent…

Quantum Physics · Physics 2013-04-03 K. M. Svore , A. W. Cross , I. L. Chuang , A. V. Aho

Millimeter-wave massive multiple-input multiple-output systems employ highly directional beamforming to overcome severe path loss, and their performance critically depends on accurate beam alignment. Conventional codebook-based methods…

Signal Processing · Electrical Eng. & Systems 2026-02-26 Weijie Jin , Jing Zhang , Hengtao He , Chao-Kai Wen , Xiao Li , Shi Jin

Quantum Hall (QH) states are arguably the most ubiquitous examples of nontrivial topological order, requiring no special symmetry and elegantly characterized by the first Chern number. Their higher dimension generalizations are particularly…

Strongly Correlated Electrons · Physics 2018-10-03 Ching Hua Lee , Yuzhu Wang , Youjian Chen , Xiao Zhang

Considering the noise level limit, one crucial aspect for quantum machine learning is to design a high-performing variational quantum circuit architecture with small number of quantum gates. As the classical neural architecture search…

Quantum Physics · Physics 2024-03-08 Jialin Chen , Zhiqiang Cai , Ke Xu , Di Wu , Wei Cao

The development of new materials typically involves a process of trial and error, guided by insights from past experimental and theoretical findings. The inverse design approach for soft-matter systems has the potential to optimize specific…