主题图谱 / disordered systems and neural networks

disordered systems and neural networks

GeneTech 知识引擎共收录 84 篇相关科研实体，横跨 14 个垂直领域。数据来自 OpenAlex、arXiv、Crossref、PubMed、Europe PMC 等公开学术源，全部可溯源到原文。

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代表性文献（按质量分排序，前 60 条）

• Fluctuation-dissipation of the Kuramoto model on fruit-fly connectomes
  2025 · 脑科学 · We investigate the distance from equilibrium using the Kuramoto model via the degree of fluctuation-dissipation violation as the consequence of different levels of edge weight anisotropies. This is achieved by solving th…
• Impact of Clifford operations on non-stabilizing power and quantum chaos
  2025 · 量子计算 · Non-stabilizerness, alongside entanglement, is a crucial ingredient for fault-tolerant quantum computation and achieving a genuine quantum advantage. Despite recent progress, a complete understanding of the generation an…
• Large positive magnetoconductance in carbon nanoscrolls
  2024 · 碳中和与 CCUS · We theoretically demonstrate that carbon nanoscrolls -- spirally wrapped graphene layers with open endpoints -- can be characterized by a large positive magnetoconductance. We show that when a carbon nanoscroll is subjec…
• Hedgehog topological defects in 3D amorphous solids
  2024 · 量子计算 · The underlying structural disorder renders the concept of topological defects in amorphous solids difficult to apply and hinders a first-principle identification of the microscopic carriers of plasticity and of the regio…
• Robust teleportation of a surface code and cascade of topological quantum phase transitions
  2024 · 量子材料 · Teleportation is a facet where quantum measurements can act as a powerful resource in quantum physics, as local measurements allow to steer quantum information in a non-local way. While this has long been established for…
• Embracing Disorder in Quantum Materials Design
  2024 · 量子材料 · Many of the most exciting materials discoveries in fundamental condensed matter physics are made in systems hosting some degree of intrinsic disorder. While disorder has historically been regarded as something to be avoi…
• Neural Network Solutions of Bosonic Quantum Systems in One Dimension
  2023 · AI 安全与对齐 · Neural networks have been proposed as efficient numerical wavefunction ansatze which can be used to variationally search a wide range of functional forms for ground state solutions. These neural network methods are also …
• Quantum Next Generation Reservoir Computing: An Efficient Quantum Algorithm for Forecasting Quantum Dynamics
  2023 · 量子计算 · Next Generation Reservoir Computing (NG-RC) is a modern class of model-free machine learning that enables an accurate forecasting of time series data generated by dynamical systems. We demonstrate that NG-RC can accurate…
• A brief review of evolutionary game dynamics in the reinforcement learning paradigm
  2026 · AI 安全与对齐 · Cooperation, fairness, trust, and resource coordination are cornerstones of modern civilization, yet their emergence remains inadequately explained by the persistent discrepancies between theoretical predictions and beha…
• Criticality in Neural Network Function Space through Wilsonian Fixed Points and Finite-Width Corrections
  2026 · AI 安全与对齐 · Neural networks can be studied not only as parameterized computational models but also as probability distributions over functions. In this paper we develop a Wilsonian interpretation of criticality in the neural network…
• Computing frustration and near-monotonicity in deep neural networks
  2025 · AI 安全与对齐 · For the signed graph associated to a deep neural network, one can compute the frustration level, i.e., test how close or distant the graph is to structural balance. For all the pretrained deep convolutional neural networ…
• Connectivity determines the capability of sparse neural network quantum states
  2025 · AI 安全与对齐 · The Lottery Ticket Hypothesis (LTH) posits that within overparametrized neural networks, there exist sparse subnetworks that are capable of matching the performance of the original model when trained in isolation from th…
• Microscopic and collective signatures of feature learning in neural networks
  2025 · AI 安全与对齐 · Feature extraction - the ability to identify relevant properties of data - is a key factor underlying the success of deep learning. Yet, it has proved difficult to elucidate its nature within existing predictive theories…
• Ecosystems as adaptive living circuits
  2025 · 生物计算 · Unlike many physical nonequilibrium systems, in biological systems, the coupling to external energy sources is not a fixed parameter but adaptively controlled by the system itself. We do not have theoretical frameworks t…
• Learning and criticality in a self-organizing model of connectome growth
  2025 · 脑科学 · The exploration of brain networks has reached an important milestone as relatively large and reliable information has been gathered for connectomes of different species. Analyses of connectome data sets reveal that the s…
• Percolation thresholds and connectivity in quantum networks
  2025 · 量子材料 · We study entanglement percolation in qubit-based planar quantum network models of arbitrary topology, where neighboring nodes are initially connected by pure states with quenched disorder in their entanglement. To addres…
• DDNet: A Unified Physics-Informed Deep Learning Framework for Semiconductor Device Modeling
  2025 · 半导体与先进封装 · The accurate modeling of semiconductor devices plays a critical role in the development of new technology nodes and next-generation devices. Semiconductor device designers largely rely on advanced simulation software to …
• Generalized hetero-associative neural networks
  2024 · AI 安全与对齐 · Auto-associative neural networks (e.g., the Hopfield model implementing the standard Hebbian prescription) serve as a foundational framework for pattern recognition and associative memory in statistical mechanics. Howeve…
• Metric structural human connectomes: localization and multifractality of eigenmodes
  2024 · 脑科学 · In this study, we explore the fundamental principles behind the architecture of the human brain's structural connectome, from the perspective of spectral analysis of Laplacian and adjacency matrices. Building on the idea…
• Synergy between noisy quantum computers and scalable classical deep learning
  2024 · 量子材料 · We investigate the potential of combining the computational power of noisy quantum computers and of classical scalable convolutional neural networks (CNNs). The goal is to accurately predict exact expectation values of p…
• Subsystem Information Capacity in Random Circuits and Hamiltonian Dynamics
  2024 · 量子材料 · In this study, we explore the information capacity of open quantum systems, focusing on the effective channels formed by the subsystem of random quantum circuits and quantum Hamiltonian evolution. By analyzing the subsys…
• Inverse Design of Unitary Transmission Matrices in Silicon Photonic Coupled Waveguide Arrays using a Neural Adjoint Model
  2024 · 半导体与先进封装 · The development of low-loss reconfigurable integrated optical devices enables further research into technologies including photonic signal processing, analogue quantum computing, and optical neural networks. Here, we int…
• A Fully Quantum-Mechanical Treatment for Kaolinite
  2023 · 地外矿物 · Neural network potentials for kaolinite minerals have been fitted to data extracted from density functional theory calculation that were performed using the revPBE + D3 and revPBE + vdW functionals. These potentials have…
• What makes us humans: Differences in the critical dynamics underlying the human and fruit-fly connectome
  2022 · 脑科学 · Previous simulation studies on human connectomes suggested, that critical dynamics emerge subcrititcally in the so called Griffiths Phases. %This is the consequence of the strong heterogeneity of the graphs. Now we inves…
• Nonperturbative renormalization for the neural network-QFT correspondence
  2021 · AI 安全与对齐 · In a recent work arXiv:2008.08601, Halverson, Maiti and Stoner proposed a description of neural networks in terms of a Wilsonian effective field theory. The infinite-width limit is mapped to a free field theory, while fi…
• Simulation of quantum many-body dynamics with Tensor Processing Units: Floquet prethermalization
  2021 · 量子材料 · Tensor Processing Units (TPUs) are specialized hardware accelerators developed by Google to support large-scale machine-learning tasks, but they can also be leveraged to accelerate and scale other linear-algebra-intensiv…
• Brain functions emerge as thermal equilibrium states of the connectome
  2024 · 脑科学 · A fundamental idea in neuroscience is that cognitive functions -- such as perception, learning, memory, and locomotion -- are shaped and constrained by the brain's structural organization. Despite significant progress in…
• BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-inspired Materials
  2023 · 合成生物与生物制造 · The study of biological materials and bio-inspired materials science is well established; however, surprisingly little knowledge has been systematically translated to engineering solutions. To accelerate discovery and gu…
• Neural Networks and Schramm-Loewner Evolutions
  2026 · 仿生智能 · In this manuscript, we explore the application of neural networks to predict the natural parameter $κ\geq 0$ of Schramm-Loewner Evolution (SLE$_κ$) theory. SLE$_κ$ is a family of random fractal curves that has significan…
• Quantum Algorithm Software for Condensed Matter Physics
  2025 · 量子计算 · Realizing the promise of quantum computation for condensed matter many-body problems depends as much on software as on hardware, yet the area is reviewed far more often than it is quantified. We address this gap by pairi…
• Spatial and temporal correlations in neural networks with structured connectivity
  2022 · AI 安全与对齐 · Correlated fluctuations in the activity of neural populations reflect the network's dynamics and connectivity. The temporal and spatial dimensions of neural correlations are interdependent. However, prior theoretical wor…
• Decomposing neural networks as mappings of correlation functions
  2022 · AI 安全与对齐 · Understanding the functional principles of information processing in deep neural networks continues to be a challenge, in particular for networks with trained and thus non-random weights. To address this issue, we study …
• Interaction of functional brain networks is formed by k-clique percolation in the human structural connectome
  2022 · 脑科学 · The human structural connectome has a complex internal community organization, characterized by a high degree of overlap and related to functional and cognitive phenomena. We explored connectivity properties in connectom…
• Network analysis of the human structural connectome including the brainstem
  2022 · 脑科学 · The underlying anatomical structure is fundamental to the study of brain networks, but the role of brainstem from a structural perspective is not very well understood. We conduct a computational and graph-theoretical stu…
• Monitoring Quantum Simulators via Quantum Non-Demolition Couplings to Atomic Clock Qubits
  2020 · 量子计算 · We discuss monitoring the time evolution of an analog quantum simulator via a quantum non-demolition (QND) coupling to an auxiliary `clock' qubit. The QND variable of interest is the `energy' of the quantum many-body sys…
• Investigating Network Parameters in Neural-Network Quantum States
  2022 · AI 安全与对齐 · Recently, quantum-state representation using artificial neural networks has started to be recognized as a powerful tool. However, due to the black-box nature of machine learning, it is difficult to analyze what machine l…
• Quantum annealing initialization of the quantum approximate optimization algorithm
  2021 · 量子材料 · The quantum approximate optimization algorithm (QAOA) is a prospective near-term quantum algorithm due to its modest circuit depth and promising benchmarks. However, an external parameter optimization required in QAOA co…
• Precise measurement of quantum observables with neural-network estimators
  2019 · 智慧农业 · The measurement precision of modern quantum simulators is intrinsically constrained by the limited set of measurements that can be efficiently implemented on hardware. This fundamental limitation is particularly severe f…
• Functional Geometry of Human Connectome and Robustness of Gender Differences
  2019 · 脑科学 · Mapping the brain imaging data to networks, where each node represents a specific area of the brain, has enabled an objective graph-theoretic analysis of human connectome. However, the latent structure on higher-order co…
• Dreaming neural networks: rigorous results
  2018 · AI 安全与对齐 · Recently a daily routine for associative neural networks has been proposed: the network Hebbian-learns during the awake state (thus behaving as a standard Hopfield model), then, during its sleep state, optimizing informa…
• Spectral peculiarity and criticality of the human connectome
  2018 · 脑科学 · We have performed the comparative spectral analysis of structural connectomes for various organisms using open-access data. Our analysis indicates several new peculiar features of the human connectome. We found that the …
• Quantum error correction for the toric code using deep reinforcement learning
  2018 · 量子计算 · We implement a quantum error correction algorithm for bit-flip errors on the topological toric code using deep reinforcement learning. An action-value Q-function encodes the discounted value of moving a defect to a neigh…
• Tailoring correlations of the local density of states in disordered photonic materials
  2016 · 量子材料 · We present experimental evidence for the different mechanisms driving the fluctuations of the local density of states (LDOS) in disordered photonic systems. We establish a clear link between the microscopic structure of …
• Cell reprogramming modelled as transitions in a hierarchy of cell cycles
  2016 · 合成生物与生物制造 · We construct a model of cell reprogramming (the conversion of fully differentiated cells to a state of pluripotency, known as induced pluripotent stem cells, or iPSCs) which builds on key elements of cell biology viz. ce…
• Direct Experimental Evidence for Differing Reactivity Alterations of Minerals following Irradiation: The Case of Calcite and Quartz
  2015 · 地外矿物 · Concrete, a mixture formed by mixing cement, water, and fine and coarse mineral aggregates is used in the construction of nuclear power plants (NPPs), e.g., to construct the reactor cavity concrete that encases the react…
• Complex synchronization patterns in the human connectome network
  2015 · 脑科学 · A major challenge in neuroscience is posed by the need for relating the emerging dynamical features of brain activity with the underlying modular structure of neural connections, hierarchically organized throughout sever…
• Anderson localization of entangled photons in an integrated quantum walk
  2013 · 半导体与先进封装 · Waves fail to propagate in random media. First predicted for quantum particles in the presence of a disordered potential, Anderson localization has been observed also in classical acoustics, electromagnetism and optics. …
• Disordered proteins and network disorder in network descriptions of protein structure, dynamics and function. Hypotheses and a comprehensive review
  2011 · AI 驱动科学发现 · During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequence…
• Development of input connections in neural cultures
  2010 · AI 安全与对齐 · We introduce a novel approach for the quantitative assessment of the connectivity in neuronal cultures, based on the statistical mechanics of percolation on a graph. This allows us to follow the development of the cultur…
• The Physics of Living Neural Networks
  2010 · AI 安全与对齐 · Improvements in technique in conjunction with an evolution of the theoretical and conceptual approach to neuronal networks provide a new perspective on living neurons in culture. Organization and connectivity are being m…
• Percolation Approach to Study Connectivity in Living Neural Networks
  2010 · 仿生智能 · We study neural connectivity in cultures of rat hippocampal neurons. We measure the neurons' response to an electric stimulation for gradual lower connectivity, and characterize the size of the giant cluster in the netwo…
• Many-particle confinement by constructed disorder and quantum computing
  2005 · 量子材料 · Many-particle confinement (localization) is studied for a 1D system of spinless fermions with nearest-neighbor hopping and interaction, or equivalently, for an anisotropic Heisenberg spin-1/2 chain. This system is freque…
• Neural Networks Processing Mean Values of Random Variables
  2004 · AI 安全与对齐 · We introduce a class of neural networks derived from probabilistic models in the form of Bayesian belief networks. By imposing additional assumptions about the nature of the probabilistic models represented in the belief…
• Modelling the atomic structure of very high-density amorphous ice
  2004 · 地外矿物 · The structure of very high-density amorphous (VHDA) ice has been modelled by positionally disordering three crystalline phases, namely ice IV, VI and XII. These phases were chosen because only they are stable or metastab…
• Recent Developments in Computer Modeling of Amorphous Materials
  2003 · 合成生物与生物制造 · In this paper, we review some recent work on amorphous materials using current "first principles" electronic structure/molecular dynamics techniques. The main theme of the paper is to emphasize new directions in the use …
• Thermal conductivity of amorphous carbon thin films
  2000 · 碳中和与 CCUS · Thermal conductivities $Λ$ of amorphous carbon thin films are measured in the temperatures range 80--400 K using the $3ω$ method. Sample films range from soft a-C:H prepared by remote-plasma deposition ($Λ= 0.20$ W m$^{-…
• Solution of a chaotic neural network at fixed connectivity
  2026 · AI 安全与对齐 · We calculate the moments and response functions of a nonlinear random recurrent neural network in the large-$N$ limit using a diagrammatic technique. Our approach does not require averaging over synaptic weights and give…
• Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation
  2019 · 仿生智能 · Several recent trends in machine learning theory and practice, from the design of state-of-the-art Gaussian Process to the convergence analysis of deep neural nets (DNNs) under stochastic gradient descent (SGD), have fou…
• Quantum Neural Machine Learning - Backpropagation and Dynamics
  2016 · AI 安全与对齐 · The current work addresses quantum machine learning in the context of Quantum Artificial Neural Networks such that the networks' processing is divided in two stages: the learning stage, where the network converges to a s…
• The effects of stochasticity at the single-cell level and cell size control on the population growth
  2016 · 合成生物与生物制造 · Establishing a quantitative connection between the population growth rate and the generation times of single cells is a prerequisite for understanding evolutionary dynamics of microbes. However, existing theories fail to…

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