English
Related papers

Related papers: Growing quantum states with topological order

200 papers

A complex system with many interacting individuals can be represented by a network consisting of nodes and links representing individuals and pairwise interactions, respectively. However, real-world systems grow with time and include many…

Physics and Society · Physics 2024-11-12 Soo Min Oh , Yongsun Lee , Byungnam Kahng

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

We study the reduced fidelity between local states of lattice systems exhibiting topological order. By exploiting mappings to spin models with classical order, we are able to analytically extract the scaling behavior of the reduced fidelity…

Strongly Correlated Electrons · Physics 2009-06-11 Erik Eriksson , Henrik Johannesson

Learning faithful representations of quantum states is crucial to fully characterizing the variety of many-body states created on quantum processors. While various tomographic methods such as classical shadow and MPS tomography have shown…

We present an attention-based foundation model architecture for learning and predicting quantum states across Hamiltonian parameters, system sizes, and physical systems. Using only basis configurations and physical parameters as inputs, our…

Strongly Correlated Electrons · Physics 2025-12-16 Timothy Zaklama , Daniele Guerci , Liang Fu

Recently, tremendous progress has been made in the field of quantum science and technologies: different platforms for quantum simulation as well as quantum computing, ranging from superconducting qubits to neutral atoms, are starting to…

The composite fermion theory opened a new chapter in understanding many-body correlations through the formation of emergent particles. The formation of two-flux and four-flux composite fermions is well established. While there are limited…

Mesoscale and Nanoscale Physics · Physics 2024-02-21 Haoyun Huang , Waseem Hussain , S. A. Myers , L. N. Pfeiffer , K. W. West , K. W. Baldwin , G. A. Csáthy

Deciding if a given family of quantum states is topologically ordered is an important but nontrivial problem in condensed matter physics and quantum information theory. We derive necessary and sufficient conditions for a family of graph…

Quantum Physics · Physics 2022-09-09 Pengcheng Liao , Barry C. Sanders , David L. Feder

We show how to numerically calculate several quantities that characterize topological order starting from a microscopic fractional quantum Hall (FQH) Hamiltonian. To find the set of degenerate ground states, we employ the infinite density…

Strongly Correlated Electrons · Physics 2013-06-19 Michael P. Zaletel , Roger S. K. Mong , Frank Pollmann

Entanglement and its propagation are central to understanding a multitude of physical properties of quantum systems. Notably, within closed quantum many-body systems, entanglement is believed to yield emergent thermodynamic behavior.…

Higher-order topological phase as a generalization of Berry phase attracts an enormous amount of research. The current theoretical models supporting higher-order topological phases, however, cannot give the connection between lower and…

Quantum Physics · Physics 2021-12-22 Yao Wang , Yongguan Ke , Yi-Jun Chang , Yong-Heng Lu , Jun Gao , Chaohong Lee , Xian-Min Jin

An approach to analyse the properties of a particle system is to compare it with different processes to understand when one of them is larger than other ones. The main technique for that is coupling, which may not be easy to construct. We…

Probability · Mathematics 2011-02-22 Davide Borrello

Quantum phase transitions reveal deep insights into the behavior of many-body quantum systems, but identifying these transitions without well-defined order parameters remains a significant challenge. In this work, we introduce a novel…

We address the problem posed by the inhomogeneous trapping fields when using ultracold fermions to simulate strongly correlated electrons. As a starting point, we calculate the density of states for a single atom. Using semiclassical…

Statistical Mechanics · Physics 2007-05-23 C. Hooley , J. Quintanilla

Modern condensed matter physics relies on the concept of topology to classify matter, from quantum Hall systems to topological insulators. Engineered systems, benefiting from synthetic dimensions, can potentially give access to novel…

Topological features - global properties not discernible locally - emerge in systems from liquid crystals to magnets to fractional quantum Hall systems. Deeper understanding of the role of topology in physics has led to a new class of…

Mesoscale and Nanoscale Physics · Physics 2015-04-23 M. Hafezi , S. Mittal , J. Fan , A. Migdall , J. Taylor

Quantum computers promise to perform computations beyond the reach of modern computers with profound implications for scientific research. Due to remarkable technological advances, small scale devices are now becoming available for use. One…

Strongly Correlated Electrons · Physics 2022-05-20 Adam Smith , Bernhard Jobst , Andrew G. Green , Frank Pollmann

The circuit complexity of time-evolved pure quantum states grows linearly in time for an exponentially long time. This behavior has been proven in certain models, is conjectured to hold for generic quantum many-body systems, and is believed…

High Energy Physics - Theory · Physics 2025-10-22 Yale Fan , Nicholas Hunter-Jones , Andreas Karch , Shivan Mittal

Topological phases in two-dimensional quantum lattice models are often studied on cylinders for revealing different topological properties and making the problem numerically tractable. This makes a proper understanding of…

Strongly Correlated Electrons · Physics 2025-10-31 Felix A. Palm , Chloé Van Bastelaere , Laurens Vanderstraeten

Neural-network quantum states have shown great potential for the study of many-body quantum systems. In statistical machine learning, transfer learning designates protocols reusing features of a machine learning model trained for a problem…