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statistical physics

GeneTech 知识引擎共收录 477 篇相关科研实体，横跨 30 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）

• Leveraging the Potential of Machine-Learning Interatomic Potentials for QM/MM Simulations.
  2026 · AI 驱动科学发现 · Machine-learning interatomic potentials (MLIPs) are increasingly used to replace computationally expensive quantum-mechanical (QM) calculations to obtain the energies and forces in ab initio or multiscale molecular dynam…
• Fast evaluation of unbiased atomic forces in ab initio variational Monte Carlo via the Lagrangian technique.
  2026 · AI 驱动科学发现 · Ab initio quantum Monte Carlo (QMC) methods are state-of-the-art electronic structure calculations based on highly parallelizable stochastic frameworks for accurate solutions of the many-body Schrödinger equation, s…
• Machine-learning interatomic potential for BaTiO<sub>3</sub>: phase transitions, domain walls, and grain boundaries.
  2025 · AI 驱动科学发现 · Abstract A machine learning interatomic potential for BaTiO 3 is presented based on the atomic cluster expansion formalism, enabling atomistic simulations of phase transitions, defect structures, and domain walls. Traine…
• Probing Lattice Anharmonicity and Thermal Transport in Ultralow-κ Materials Using Machine Learning Interatomic Potentials.
  2025 · AI 驱动科学发现 · Abstract Crystalline solids with ultralow lattice thermal conductivity (κ) are highly sought after for thermoelectric energy conversion and thermal barrier coating applications. However, a comprehensive theoretical under…
• Is the Future of Materials Amorphous? Challenges and Opportunities in Simulations of Amorphous Materials.
  2025 · AI 驱动科学发现 · Amorphous solids form an enormous and underutilized class of materials. In order to drive the discovery of new useful amorphous materials further we need to achieve a closer convergence between computational and experime…
• Polynomial-time quantum Gibbs sampling for the weak and strong coupling regime of the Fermi-Hubbard model at any temperature
  2025 · 量子材料 · Quantum computers hold the potential to revolutionise the simulation of quantum many-body systems, with profound implications for fundamental physics and applications like molecular and material design. However, demonstr…
• Zentropy Theory in Materials Science: Challenges and Opportunities
  2026 · AI 驱动科学发现 · Zentropy theory has emerged as a multiscale thermodynamic framework that bridges quantum mechanics, statistical mechanics, and macroscopic materials behavior by embedding internal degrees of freedom within configurationa…
• Foundational Machine‐Learning Interatomic Potential for Simulating Chemically Complex Ni‐Based Superalloys
  2026 · AI 驱动科学发现 · For decades, atomistic simulation of chemically complex Ni‐based superalloys has remained beyond practical reach. Here, we apply the GRACE foundational machine‐learning interatomic potential to predict chemical ordering …
• High-throughput determination of threshold displacement energies in AlGaN alloys
  2026 · AI 驱动科学发现 · Accompanying data and analysis from molecular dynamics simulations (machine learning interatomic potential and Stillinger–Weber potential) for AlGaN threshold displacement energies. Five compositions of AlGaN are conside…
• High-throughput determination of threshold displacement energies in AlGaN alloys
  2026 · AI 驱动科学发现 · Accompanying data and analysis from molecular dynamics simulations (machine learning interatomic potential and Stillinger–Weber potential) for AlGaN threshold displacement energies. Five compositions of AlGaN are conside…
• Machine learning nonequilibrium phase transitions in charge-density wave insulators
  2026 · 边缘智能 · Abstract Nonequilibrium electronic forces play a central role in voltage-driven phase transitions but are notoriously expensive to evaluate in dynamical simulations. Here we develop a machine-learning (ML) framework for …
• Revised entropy of the AQUA equation of state
  2026 · 地外科学 · Context . Water is a key constituent of the ice giants Uranus and Neptune, and potentially of Neptune-sized exoplanets. Understanding their present structure and evolution requires knowledge of the equation of state (EoS…
• Comparative blobs and holes dynamics in a tokamak plasma: deep learning analysis of fast imaging data
  2026 · 核能 · Abstract This work focuses on the dynamics of the turbulent structures revealed by tomographic inversion of fast passive imaging data acquired on the COMPASS tokamak. To highlight the fluctuations, a sliding median image…
• A variational formulation of the free energy of mixed quantum-classical systems: Coupling classical and electronic density functional theories
  2026 · 量子材料 · Combining classical density functional theory (cDFT) with quantum mechanics (QM) methods offers a computationally efficient alternative to traditional QM/molecular mechanics (MM) approaches for modeling mixed quantum-cla…
• Time-Dependent Neural Galerkin Method for Quantum Dynamics
  2026 · 量子材料 · We introduce a classical computational method for quantum dynamics that relies on a global-in-time variational principle. Unlike conventional time-stepping approaches, our scheme computes the entire state trajectory over…
• Quantum-classical study of charge transport in organic semiconductors with multiple low-frequency vibrational modes
  2026 · 量子材料 · Building on the recent success of a quantum-classical method for computing transport properties in the Holstein model with a single phonon mode [P. Mitrić et al., Phys. Rev. B ${\bf 111}$, L161105 (2025)], we now assess …
• Transferable Machine Learning Interatomic Potential for Pd-Catalyzed Cross-Coupling Reactions
  2025 · AI 驱动科学发现 · Finding efficient substrate-catalyst combinations for palladium-catalyzed cross-coupling reactions remains a critical challenge in synthetic chemistry, with broad implications for pharmaceutical and materials manufacturi…
• Exploring the energy landscape of aluminas through machine learning interatomic potential
  2025 · AI 驱动科学发现 · Despite the widespread applications of alumina due to its rich polymorphism, the structures of many transitional aluminas remain unresolved. This work employs the neuroevolution potential (NEP) approach to accurately des…
• High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo
  2025 · AI 驱动科学发现 · We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the im…
• Using Physics-Informed Neural Networks for Modeling Biological and Epidemiological Dynamical Systems
  2025 · 生物计算 · Physics-Informed Neural Networks (PINNs) have emerged as a powerful approach for integrating physical laws into a deep learning framework, offering enhanced capabilities for solving complex problems. Despite their potent…
• Extending quantum-mechanical benchmark accuracy to biological ligand-pocket interactions
  2025 · 生物计算 · Predicting the binding affinity of ligands to protein pockets is key in the drug design pipeline. The flexibility of ligand-pocket motifs arises from a range of attractive and repulsive electronic interactions during bin…
• Between repulsion and attraction in serial biases: Replication of Chen and Bae (2024)
  2025 · 脑科学 · What you see depends on what you have seen before, and commonly your perception is drawn toward the past. Such attractive biases, known as serial dependence, are well established for many visual features. Interestingly, …
• Architecture independent absolute solvation free energy calculations with neural network potentials
  2025 · 类脑计算 · Allowing atoms or molecules to disappear is a critical step in alchemical free energy simulations (FES). The necessary tricks are well understood when using force fields. Over the past few years, neural network potential…
• Selected advances in nuclear mass predictions based on covariant density functional theory with continuum effects
  2025 · 核能 · Abstract Precision measurements and reliable predictions of nuclear masses are pivotal in advancing nuclear physics and astrophysics. In this paper, we review recent progress in constructing a microscopic nuclear mass ta…
• Thermalization and criticality on an analogue–digital quantum simulator
  2025 · 量子计算 · Abstract Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators 1,2 . Unlocking the full potential of such systems towards this goal requires flexible initial stat…
• Non-Markovian Quantum Mpemba Effect
  2025 · 量子计算 · Since its rediscovery in the twentieth century, the Mpemba effect, where a far-from-equilibrium state may relax faster than a state closer to equilibrium, has been extensively studied in classical systems and has recentl…
• Entanglement asymmetry dynamics in random quantum circuits
  2025 · 量子计算 · We study the dynamics of entanglement asymmetry in random unitary circuits (RUCs). Focusing on a local U ( 1 ) charge, we consider symmetric initial states evolved by both local one-dimensional circuits and geometrically…
• Proposal for many-body quantum chaos detection
  2025 · 量子计算 · In this work, the term “quantum chaos” refers to spectral correlations similar to those found in the random matrix theory. Quantum chaos can be diagnosed through the analysis of level statistics using, e.g., the spectral…
• Evolution of entanglement entropy at SU( N ) deconfined quantum critical points
  2025 · 量子计算 · Over past two decades, the enigma of the deconfined quantum critical point (DQCP) has attracted broad attention across physics communities, as it offers a new paradigm beyond the Landau-Ginzburg-Wilson framework. However…
• Lindblad-like quantum tomography for non-Markovian quantum dynamical maps
  2025 · 量子材料 · Abstract We introduce Lindblad-like quantum tomography (LℓQT) as a quantum characterization technique of time-correlated noise in quantum information processors. This approach enables the estimation of time-local master …
• De Sitter quantum gravity within the covariant Lorentzian approach to asymptotic safety
  2025 · 量子材料 · Abstract Recent technical and conceptual advancements in the asymptotic safety approach to quantum gravity have enabled studies of the UV completion of Lorentzian Einstein gravity, emphasizing the role of the state depen…
• Combining kinetic and thermodynamic uncertainty relations in quantum transport
  2025 · 量子材料 · Abstract We study the fluctuations of generic currents in multi-terminal, multi-channel coherent quantum transport settings. In the quantum regime, these fluctuations and the resulting precision differ strongly depending…
• Quantum critical scaling of specific heat in a quasicrystal
  2025 · 量子材料 · In strongly correlated systems, interactions give rise to critical fluctuations surrounding the quantum critical point (QCP) of a quantum phase transition. Quasicrystals allow the study of quantum critical phenomena in a…
• Dynamical mean field theory for real materials on a quantum computer
  2025 · 量子材料 · Quantum computers (QC) could harbor the potential to significantly advance materials simulations, particularly at the atomistic scale involving strongly correlated fermionic systems, where an accurate description of quan…
• Monitored long-range interacting systems: spin-wave theory for quantum trajectories
  2025 · 量子材料 · Measurement-induced phases exhibit unconventional dynamics as emergent collective phenomena, yet their behavior in tailored interacting systems - crucial for quantum technologies - remains less understood. We develop a s…
• Accurate quantum-centric simulations of intermolecular interactions
  2025 · 量子材料 · Modelling and simulating non-covalent interactions is challenging, as they are inherently weak, dynamic, and system-specific. Common predictive methods often require trading the accuracy for reducing the otherwise cumber…
• Deep Learning Quantum Monte Carlo for Solids
  2025 · 量子材料 · ABSTRACT Deep learning has deeply changed the paradigms of many research fields. At the heart of chemical and physical sciences is the accurate ab initio calculation of many‐body wavefunctions, which has become one of th…
• Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in germanium.
  2024 · AI 驱动科学发现 · We introduce a data-driven potential aimed at the investigation of pressure-dependent phase transitions in bulk germanium, including the estimate of kinetic barriers. This is achieved by suitably building a database incl…
• Machine learning interatomic potential: Bridge the gap between small-scale models and realistic device-scale simulations.
  2024 · AI 驱动科学发现 · Machine learning interatomic potential (MLIP) overcomes the challenges of high computational costs in density-functional theory and the relatively low accuracy in classical large-scale molecular dynamics, facilitating mo…
• Predictions of Boron Phase Stability Using an Efficient Bayesian Machine Learning Interatomic Potential.
  2024 · AI 驱动科学发现 · Thermodynamic phase stability of three elemental boron allotropes, i.e., α-B, β-B, and γ-B, was investigated using a Bayesian interatomic potential trained via a sparse Gaussian process (SGP). SGP poten…
• Transferable Machine Learning Interatomic Potential for Bond Dissociation Energy Prediction of Drug-like Molecules.
  2024 · AI 驱动科学发现 · We present a transferable MACE interatomic potential that is applicable to open- and closed-shell drug-like molecules containing hydrogen, carbon, and oxygen atoms. Including an accurate description of radical species ex…
• Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in <i>RMCProfile</i>.
  2024 · AI 驱动科学发现 · Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach…
• A Molecular View of Methane Activation on Ni(111) through Enhanced Sampling and Machine Learning.
  2024 · AI 驱动科学发现 · A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation of methane on a Ni(111) surface. The work entails the development and iterative refi…
• The Dynamical State of the Didymos System before and after the DART Impact
  2024 · AI 安全与对齐 · Abstract NASA’s Double Asteroid Redirection Test (DART) spacecraft impacted Dimorphos, the natural satellite of (65803) Didymos, on 2022 September 26, as a first successful test of kinetic impactor technology for deflect…
• Diffusion coefficients calculations of 110mAg in ZrC at very high temperature using machine-learning interatomic potential
  2024 · AI 驱动科学发现 · • Machine-learning potential for the Zr-C-Ag ternary system was developed. • Ag diffusion in ZrC 0.94 and ZrC 0.97 was computed using molecular dynamics simulations. • Ag diffusion accelerates with higher temperature and…
• Many-body localization in the age of classical computing *
  2024 · 生物计算 · Abstract Statistical mechanics provides a framework for describing the physics of large, complex many-body systems using only a few macroscopic parameters to determine the state of the system. For isolated quantum many-b…
• Saddle avoidance of noise-induced transitions in multiscale systems
  2024 · 脑科学 · In multistable dynamical systems driven by weak Gaussian noise, transitions between competing states are often assumed to pass via a saddle on the separating basin boundary. By contrast, we show that timescale separation…
• Machine learning-inferred and energy landscape-guided analyses reveal kinetic determinants of CRISPR/Cas9 gene editing
  2024 · 基因技术工具 · Abstract The CRISPR/Cas nucleases system is widely considered the most important tool in genome engineering. However, current methods for predicting on/off-target effects and designing guide RNA (gRNA) rely on purely dat…
• KAN 2.0: Kolmogorov-Arnold Networks Meet Science
  2024 · 生命科学 · A major challenge of AI + Science lies in their inherent incompatibility: today's AI is primarily based on connectionism, while science depends on symbolism. To bridge the two worlds, we propose a framework to seamlessly…
• Causality Detection and Quantification by Ensembles of Time Delay Neural Networks for Application to Nuclear Fusion Reactors
  2024 · 核能 · Abstract The understanding and control of complex systems in general, and thermonuclear plasmas in particular, require analysis tools, which can detect not the simple correlations but can also provide information about t…
• An Introduction to Relativistic Theory as Implemented in GRASP
  2024 · 核能 · Computational atomic physics continues to play a crucial role in both increasing the understanding of fundamental physics (e.g., quantum electrodynamics and correlation) and producing atomic data for interpreting observa…
• Enhancement of fusion reactivities using non-Maxwellian energy distributions
  2024 · 核能 · We discuss conditions for the enhancement of fusion reactivities arising from different choices of energy distribution functions for the reactants. The key element for potential gains in fusion reactivity is identified i…
• Barren Plateaus in Variational Quantum Computing
  2024 · 量子计算 · Variational quantum computing offers a flexible computational paradigm with applications in diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) phenomenon. When a model exhibits…
• Current Fluctuations in Open Quantum Systems: Bridging the Gap Between Quantum Continuous Measurements and Full Counting Statistics
  2024 · 量子计算 · Continuously measured quantum systems are characterized by an output current, in the form of a stochastic and correlated time series, which conveys crucial information about the underlying quantum system. The many tools …
• Fast and converged classical simulations of evidence for the utility of quantum computing before fault tolerance
  2024 · 量子计算 · A recent quantum simulation of observables of the kicked Ising model on 127 qubits implemented circuits that exceed the capabilities of exact classical simulation. We show that several approximate classical methods, base…
• Variational quantum time evolution without the quantum geometric tensor
  2024 · 量子计算 · Real- and imaginary-time quantum state evolutions are crucial in physics and chemistry for exploring quantum dynamics, preparing ground states, and computing thermodynamic observables. On near-term devices, variational q…
• Many-body localization in the age of classical computing *
  2024 · 量子计算 · Abstract Statistical mechanics provides a framework for describing the physics of large, complex many-body systems using only a few macroscopic parameters to determine the state of the system. For isolated quantum many-b…
• Testing the Quantumness of Gravity without Entanglement
  2024 · 量子计算 · Given a unitary evolution U on a multipartite quantum system and an ensemble of initial states, how well can U be simulated by local operations and classical communication (LOCC) on that ensemble? We answer this question…
• Exponentially tighter bounds on limitations of quantum error mitigation
  2024 · 量子计算 · Quantum error mitigation has been proposed as a means to combat unwanted and unavoidable errors in near-term quantum computing without the heavy resource overheads required by fault-tolerant schemes. Recently, error miti…
• Characterizing barren plateaus in quantum ansätze with the adjoint representation
  2024 · 量子计算 · Variational quantum algorithms, a popular heuristic for near-term quantum computers, utilize parameterized quantum circuits which naturally express Lie groups. It has been postulated that many properties of variational q…

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