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Phase transition in magic with random quantum circuits

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arXiv 2023年

作者： Niroula, Pradeep White, Christopher David Wang, Qingfeng Johri, Sonika Zhu, Daiwei Monroe, Christopher Noel, Crystal Gullans, Michael J. Joint Center for Quantum Information and Computer Science University of Maryland and NIST College ParkMD20742 United States Joint Quantum Institute University of Maryland and NIST College ParkMD20742 United States Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States IonQ Inc. College ParkMD20740 United States Duke Quantum Center Department of Electrical & Computer Engineering Department of Physics Duke University DurhamNC27701 United States

Magic is a property of quantum states that enables universal fault-tolerant quantum computing using simple sets of gate operations. Understanding the mechanisms by which magic is created or destroyed is, therefore, a crucial step towards efficient and practical fault-tolerant computation. We observe that a random stabilizer code subject to coherent errors exhibits a phase transition in magic, which we characterize through analytic, numeric and experimental probes. Below a critical error rate, stabilizer syndrome measurements remove the accumulated magic in the circuit, effectively protecting against coherent errors;above the critical error rate syndrome measurements concentrate magic. A better understanding of such rich behavior in the resource theory of magic could shed more light on origins of quantum speedup and pave pathways for more efficient magic state generation. © 2023, CC BY.

关键词： Random errors

Comparative study of quantum emitter fabrication in wide bandgap materials using localized electron irradiation

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arXiv 2023年

作者： Kumar, Anand Cholsuk, Chanaprom Mishuk, Mohammad N. Hazra, Mouli Pillot, Clotilde Matthes, Tjorben Shaik, Tanveer A. Çakan, Aslı Deckert, Volker Suwanna, Sujin Vogl, Tobias Department of Computer Engineering School of Computation Information and Technology Technical University of Munich Munich80333 Germany Abbe Center of Photonics Institute of Applied Physics Friedrich Schiller University Jena Jena07745 Germany Abbe Center of Photonics Friedrich Schiller University Jena Jena07743 Germany Jena07745 Germany Optical and Quantum Physics Laboratory Department of Physics Faculty of Science Mahidol University Bangkok10400 Thailand

Quantum light sources are crucial foundational components for various quantum technology applications. With the rapid development of quantum technology, there has been a growing demand for materials with the capability of hosting quantum emitters. One such material platform uses fluorescent defects in hexagonal boron nitride (hBN) that can host deep sub-levels within the band gap. The localized electron irradiation has shown its effectiveness in generating deep sub-levels to induce single emitters in hBN. The question is whether localized (electron beam) irradiation is a reliable tool for creating emitters in other wide bandgap materials and its uniqueness to hBN. Here, we investigate and compare the fabrication of quantum emitters in hBN and exfoliated muscovite mica flakes along with other 3D crystals, such as silicon carbide and gallium nitride, which are known to host quantum emitters. We use our primary fabrication technique of localized electron irradiation using a standard scanning electron microscope. To complement our experimental work, we employ density functional theory simulations to study the atomic structures of defects in mica. While our fabrication technique allows to create hBN quantum emitters with a high yield and high single photon purity, it is unable to fabricate single emitters in the other solid-state crystals under investigation. This allows us to draw conclusions on the emitter fabrication mechanism in hBN, which could rely on activating pre-existing defects by charge state manipulation. Therefore, we provide an essential step towards the identification of hBN emitters and their formation process. © 2023, CC BY.

关键词： Silicon carbide

Minimum Detection Efficiencies for Loophole-free Genuine Nonlocality Tests

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arXiv 2024年

作者： Ghosh, Subhendu B. Chowdhury, Snehasish Roy Adhikary, Ranendu Roy, Arup Guha, Tamal Physics and Applied Mathematics Unit Indian Statistical Institute 203 B.T. Road Kolkata700108 India Electronics and Communication Sciences Unit Indian Statistical Institute 203 B.T. Road Kolkata700108 India Department of Physics A B N Seal College Cooch Behar West Bengal 736101 India QICI Quantum Information and Computation Initiative Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong

The certification of quantum nonlocality, which has immense significance in architecting device-independent technologies, confronts severe experimental challenges. Detection loophole, originating from the unavailability of perfect detectors, is one of the major issues amongst them. In the present study we focus on the minimum detection efficiency (MDE) required to detect various forms of genuine nonlocality, originating from the type of causal constraints imposed on the involved parties. In this context, we demonstrate that the MDE needed to manifest the recently suggested T2-type nonlocality deviates significantly from perfection. Additionally, we have computed the MDE necessary to manifest Svetlichny’s nonlocality, with state-independent approach markedly reducing the previously established bound. Finally, considering the inevitable existence of noise we demonstrate the robustness of the imperfect detectors to certify T2-type nonlocality. © 2024, CC BY.

关键词： Efficiency

Quantum Optics Applications of Hexagonal Boron Nitride Defects

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arXiv 2024年

作者： Çakan, Aslı Cholsuk, Chanaprom Gale, Angus Kianinia, Mehran Paçal, Serkan Ateş, Serkan Aharonovich, Igor Toth, Milos Vogl, Tobias Department of Computer Engineering TUM School of Computation Information and Technology Technical University of Munich Munich80333 Germany Munich80799 Germany Abbe Center of Photonics Institute of Applied Physics Friedrich Schiller University Jena Jena07745 Germany School of Mathematical and Physical Sciences Faculty of Science University of Technology Sydney UltimoNSW2007 Australia University of Technology Sydney UltimoNSW2007 Australia Department of Physics Izmir Institute of Technology Izmir35430 Turkey

Hexagonal boron nitride (hBN) has emerged as a compelling platform for both classical and quantum technologies. In particular, the past decade has witnessed a surge of novel ideas and developments, which may be overwhelming for newcomers to the field. This review provides an overview of the fundamental concepts and key applications of hBN, including quantum sensing, quantum key distribution, quantum computing, and quantum memory. Additionally, we highlight critical experimental and theoretical advances that have expanded the capabilities of hBN, in a cohesive and accessible manner. The objective is to equip readers with a comprehensive understanding of the diverse applications of hBN, and provide insights into ongoing research efforts. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum computers

Complexity-constrained quantum thermodynamics

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arXiv 2024年

作者： Munson, Anthony Kothakonda, Naga Bhavya Teja Haferkamp, Jonas Halpern, Nicole Yunger Eisert, Jens Faist, Philippe Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Department of Physics University of Maryland College ParkMD20742 United States Physics Department Universitat Autònoma de Barcelona Bellaterra Barcelona08193 Spain Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany School of Engineering and Applied Sciences Harvard University MA02134 United States Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States

Quantum complexity measures the difficulty of realizing a quantum process, such as preparing a state or implementing a unitary. We present an approach to quantifying the thermodynamic resources required to implement a process if the process’s complexity is restricted. We focus on the prototypical task of information erasure, or Landauer erasure, wherein an n-qubit memory is reset to the all-zero state. We show that the minimum thermodynamic work required to reset an arbitrary state, via a complexity-constrained process, is quantified by the state’s complexity entropy. The complexity entropy therefore quantifies a trade-off between the work cost and complexity cost of resetting a state. If the qubits have a nontrivial (but product) Hamiltonian, the optimal work cost is determined by the complexity relative entropy. The complexity entropy quantifies the amount of randomness a system appears to have to a computationally limited observer. Similarly, the complexity relative entropy quantifies such an observer’s ability to distinguish two states. We prove elementary properties of the complexity (relative) entropy and determine the complexity entropy’s behavior under random circuits. Also, we identify information-theoretic applications of the complexity entropy. The complexity entropy quantifies the resources required for data compression if the compression algorithm must use a restricted number of gates. We further introduce a complexity conditional entropy, which arises naturally in a complexity-constrained variant of information-theoretic decoupling. Assuming that this entropy obeys a conjectured chain rule, we show that the entropy bounds the number of qubits that one can decouple from a reference system, as judged by a computationally bounded referee. Overall, our framework extends the resource-theoretic approach to thermodynamics to integrate a notion of time, as quantified by complexity. © 2024, CC BY.

关键词： Entropy

HiPoNet: A Topology-Preserving Multi-View Neural Network For High Dimensional Point Cloud and Single-Cell Data

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arXiv 2025年

作者： Viswanath, Siddharth Madhu, Hiren Bhaskar, Dhananjay Kovalic, Jake Johnson, Dave Ying, Rex Tape, Christopher Adelstein, Ian Perlmutter, Michael Krishnaswamy, Smita Department of Computer Science Yale University New Haven United States Department of Genetics Yale University New Haven United States Department of Applied Physics Yale University New Haven United States Program in Computing Boise State University Idaho United States Cell Communication Lab Department of Oncology University College London Cancer Institute London United Kingdom Department of Mathematics Yale University New Haven United States Department of Mathematics Boise State University Idaho United States Computational Biology and Bioinformatics Program Yale University New Haven United States Wu-Tsai Institute Yale University New Haven United States Program for Applied Math Yale University New Haven United States

In this paper, we propose HiPoNet, an end-to-end differentiable neural network for regression, classification, and representation learning on high-dimensional point clouds. Single-cell data can have high dimensionality exceeding the capabilities of existing methods for point clouds which are tailored for 3D data. Moreover, modern single-cell and spatial experiments now yield entire cohorts of datasets (i.e. one on every patient), necessitating models that can process large, high-dimensional point clouds at scale. Most current approaches build a single nearest-neighbor graph, discarding important geometric information. In contrast, HiPoNet forms higher-order simplicial complexes through learnable feature reweighting, generating multiple data views that disentangle distinct biological processes. It then employs simplicial wavelet transforms to extract multiscale features—capturing both local and global topology. We empirically show that these components preserve topological information in the learned representations, and that HiPoNet significantly outperforms state-of-the-art point-cloud and graph-based models on single cell. We also show an application of HiPoNet on spatial transcriptomics datasets using spatial co-ordinates as one of the views. Overall, HiPoNet offers a robust and scalable solution for high-dimensional data analysis. © 2025, CC BY.

关键词： Network topology

Observation of the dual quantum spin Hall insulator by density-tuned correlations in a van der Waals monolayer

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arXiv 2024年

作者： Tang, Jian Ding, Thomas Siyuan Chen, Hongyu Gao, Anyuan Qian, Tiema Huang, Zumeng Sun, Zhe Han, Xin Strasser, Alex Li, Jiangxu Geiwitz, Michael Shehabeldin, Mohamed Belosevich, Vsevolod Wang, Zihan Wang, Yiping Watanabe, Kenji Taniguchi, Takashi Bell, David C. Wang, Ziqiang Fu, Liang Zhang, Yang Qian, Xiaofeng Burch, Kenneth S. Shi, Youguo Ni, Ni Chang, Guoqing Xu, Su-Yang Ma, Qiong Department of Physics Boston College Chestnut HillMA United States Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore Singapore Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Department of Physics and Astronomy and California NanoSystems Institute University of California Los Angeles Los AngelesCA United States Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing China Department of Materials Science and Engineering Texas A&M University College StationTX United States Department of Physics and Astronomy University of Tennessee KnoxvilleTN United States Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN United States Research Center for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science Tsukuba Japan Harvard John A. Paulson School of Engineering and Applied Sciences The Center for Nanoscale system Harvard University CambridgeMA United States Department of Physics Massachusetts Institute of Technology CambridgeMA United States CIFAR Azrieli Global Scholars program CIFAR Toronto Canada

The convergence of topology and correlations represents a highly coveted realm in the pursuit of novel quantum states of matter [1, 2]. Introducing electron correlations to a quantum spin Hall (QSH) insulator can lead to the emergence of a fractional topological insulator and other exotic time-reversal-symmetric topological order [3- 10], not possible in quantum Hall and Chern insulator systems. However, the QSH insulator with quantized edge conductance remains rare, let alone that with significant correlations. In this work, we report a novel dual QSH insulator within the intrinsic monolayer crystal of TaIrTe4, arising from the interplay of its single-particle topology and density-tuned electron correlations. At charge neutrality, monolayer TaIrTe4 demonstrates the QSH insulator that aligns with single-particle band structure calculations, manifesting enhanced nonlocal transport and quantized helical edge conductance. Interestingly, upon introducing electrons from charge neutrality, TaIrTe4 only shows metallic behavior in a small range of charge densities but quickly goes into a new insulating state, entirely unexpected based on TaIrTe4's single-particle band structure. This insulating state could arise from a strong electronic instability near the van Hove singularities (VHS), likely leading to a charge density wave (CDW). Remarkably, within this correlated insulating gap, we observe a resurgence of the QSH state, marked by the revival of nonlocal transport and quantized helical edge conduction. Our observation of helical edge conduction in a CDW gap could bridge spin physics and charge orders. The discovery of a dual QSH insulator introduces a new method for creating topological flat minibands via CDW superlattices, which offer a promising platform for exploring time-reversal-symmetric fractional phases and electromagnetism [3-5, 11, 12]. Copyright © 2024, The Authors. All rights reserved.

关键词： Charge density waves

Bounding and Computing Obstacle Numbers of Graphs

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arXiv 2022年

作者： Balko, Martin Chaplick, Steven Ganian, Robert Gupta, Siddharth Hoffmann, Michael Valtr, Pavel Wolff, Alexander Department of Applied Mathematics Faculty of Mathematics and Physics Charles University Czech Republic Maastricht University Netherlands Institute of Logic and Computation Technische Universität Wien Austria Department of Computer Science & Information Systems BITS Pilani Goa Campus India Department of Computer Science ETH Zürich Switzerland Institut für Informatik Universität Würzburg Germany

An obstacle representation of a graph G consists of a set of pairwise disjoint simply-connected closed regions and a one-to-one mapping of the vertices of G to points such that two vertices are adjacent in G if and only if the line segment connecting the two corresponding points does not intersect any obstacle. The obstacle number of a graph is the smallest number of obstacles in an obstacle representation of the graph in the plane such that all obstacles are simple polygons. It is known that the obstacle number of each n-vertex graph is O(nlog n) [Balko, Cibulka, and Valtr, 2018] and that there are n-vertex graphs whose obstacle number is Ω(n/(log log n)2) [Dujmović and Morin, 2015]. We improve this lower bound to Ω(n/log log n) for simple polygons and to Ω(n) for convex polygons. To obtain these stronger bounds, we improve known estimates on the number of n-vertex graphs with bounded obstacle number, solving a conjecture by Dujmović and Morin. We also show that if the drawing of some n-vertex graph is given as part of the input, then for some drawings Ω(n2) obstacles are required to turn them into an obstacle representation of the graph. Our bounds are asymptotically tight in several instances. We complement these combinatorial bounds by two complexity results. First, we show that computing the obstacle number of a graph G is fixed-parameter tractable in the vertex cover number of G. Second, we show that, given a graph G and a simple polygon P, it is NP-hard to decide whether G admits an obstacle representation using P as the only obstacle. © 2022, CC BY.

关键词： Graph theory

NMR Spectra Denoising with Vandermonde Constraints

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arXiv 2023年

作者： Guo, Di Xu, Runmin Wu, Jinyu Lin, Meijin Du, Xiaofeng Qu, Xiaobo School of Computer and Information Engineering Fujian Engineering Research Center for Medical Data Mining and Application Xiamen University of Technology Xiamen361024 China Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen361102 China Department of Applied Marine Physics and Engineering Xiamen University Xiamen361102 China

Nuclear magnetic resonance (NMR) spectroscopy serves as an important tool to analyze chemicals and proteins in bioengineering. However, NMR signals are easily contaminated by noise during the data acquisition, which can affect subsequent quantitative analysis. Therefore, denoising NMR signals has been a long-time concern. In this work, we propose an optimization model-based iterative denoising method, CHORD-V, by treating the time-domain NMR signal as damped exponentials and maintaining the exponential signal form with a Vandermonde factorization. Results on both synthetic and realistic NMR data show that CHORD-V has a superior denoising performance over typical Cadzow and rQRd methods, and the state-of-the-art CHORD method. CHORD-V restores low-intensity spectral peaks more accurately, especially when the noise is relatively high. © 2023, CC BY.

关键词： Nuclear magnetic resonance spectroscopy