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๐Ÿ” parham bateni ๐Ÿ“‚ Physics
Showing 2686 results for "parham bateni" in Physics
Physics Preprint PDF DOI

Learning quantum disentanglement scheduling from reduced states via modular hybrid policies

Y.-X. Xiao, J.-Z. Han, Z. Zheng, Z.-H. Zhang, M. Xue, J. Li, X. Lv ยท 2026

Quantum control with restricted state access is central to near-term quantum devices, where full wave-function information is unavailable. We study this problem through multiqubit disentanglement scheโ€ฆ

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Data-Efficient Indentation Size Effect Correction in Steels Using Machine Learning and Physics-Guided Augmentation

Radmir Karamov, Tagir Karamov ยท 2026

Shallow nanoindentation enables mechanical characterization of thin films, individual phases and other volume-constrained materials, but measured hardness is often inflated by the indentation size effโ€ฆ

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Quantum Coordination without Conditioning under Restricted Information

Faisal Shah Khan ยท 2026

We study coordination under restricted information, where classical local models fail to implement certain correlated distributions because agents cannot condition on past history. We show that quantuโ€ฆ

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Physics Preprint PDF DOI

Domain-induced control of latent heat in freestanding BaTiO$_3$ membranes

Tapas Bar, David Pesquera, Arnau Villalobos-Martin, Cristian Rodriguez-Tinoco, Umair Saeed, Kumara Cordero-Edwards, Jessica Padilla, Jose Manuel Caicedo Roque, Jose Santiso, Pol Lloveras, Leo Boron, Igor Lukyanchuk, Gustau Catalan, Javier Rodriguez-Viejo ยท 2026

Thin ferroelectric BaTiO$_3$ films often exhibit continuous transitions instead of the first-order behavior of bulk crystals, a discrepancy usually attributed to epitaxial strain or dimensionality. Usโ€ฆ

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Physics Preprint PDF DOI

Formalizing Galaxy Population Evolution: Drift and Mergers as Transport Processes on Manifolds

Tsutomu T. Takeuchi (Nagoya University, Institute of Statistical Mathematics) ยท 2026

Galaxy evolution is commonly described through the time evolution of observational statistics such as luminosity functions and stellar mass functions. However, these quantities are projections of an uโ€ฆ

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Physics Preprint PDF DOI

Autonomous Emergence of Hamiltonian in Deep Generative Models

Wenjie Xi, Wei-Qiang Chen ยท 2026

The unprecedented predictive success of deep generative models in complex many-body systems, such as AlphaFold3, raises an epistemological question: do these networks merely memorize data distributionโ€ฆ

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Thermodynamics and phase transitions of nonlinearly scalarized black holes in Einstein-scalar-Gauss-Bonnet theory

De-Cheng Zou, Xu Yang, Meng-Yun Lai, Hyat Huang, Yun Soo Myung ยท 2026

We investigate the thermodynamic properties of static nonlinearly scalarized black holes in Einstein-scalar-Gauss-Bonnet theory with polynomial coupling functions. Based on the scalarized solutions coโ€ฆ

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Information decomposition for disentangled and interpretable manifold learning of fluid flows via variational autoencoders

Zhiyuan Wang, Iacopo Tirelli, Stefano Discetti, Andrea Ianiro ยท 2026

We introduce an information-theoretic framework that uses variational autoencoders (VAEs) to extract compact, physically interpretable manifolds from high-dimensional flow-field data. To this end, theโ€ฆ

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Physics-Informed Latent Space Dynamics Identification for Time-Dependent NLTE Atomic Kinetics

Jeongwoo Nam, William Anderson, Youngsoo Choi, Hai P. Le, Mark E. Foord, Byoung Ick Cho, Haewon Jeong, Min Sang Cho ยท 2026

Non-local thermodynamic equilibrium (NLTE) calculations remain a major computational bottleneck in radiation--hydrodynamics, while most existing machine-learning surrogates treat NLTE as a static inpuโ€ฆ

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Heuristic Search for Minimum-Distance Upper-Bound Witnesses in Quantum APM-LDPC Codes

Kenta Kasai ยท 2026

This paper investigates certified upper bounds on the minimum distance of an explicit family of Calderbank-Shor-Steane quantum LDPC codes constructed from affine permutation matrices. All codes considโ€ฆ

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AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction

Sushrut Kumar ยท 2026

Surrogate modeling of body-driven fluid flows where immersed moving boundaries couple structural dynamics to chaotic, unsteady fluid phenomena remains a fundamental challenge for both computational phโ€ฆ

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Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel

Abhinaba Basu ยท 2026

Band gap engineering of oxide semiconductors through doping is critical for photocatalysis and optoelectronics, yet the combinatorial space of dopant elements, substitution sites, and co-doping combinโ€ฆ

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A Minimal Model of Representation Collapse: Frustration, Stop-Gradient, and Dynamics

Louie Hong Yao, Yuhao Li, Shengchao Liu ยท 2026

Self-supervised representation learning is central to modern machine learning because it extracts structured latent features from unlabeled data and enables robust transfer across tasks and domains. Hโ€ฆ

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Differentiable free energy surface: a variational approach to directly observing rare events using generative deep-learning models

Shuo-Hui Li, Chen Chen, Yao-Wen Zhang, Ding Pan ยท 2026

Rare events are central to the evolution of complex many-body systems, characterized as key transitional configurations on the free energy surface (FES). Conventional methods require adequate samplingโ€ฆ

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Unseen Astronomy

Dr James W. Trayford ยท 2026

The 2025 UK National Astronomy Meeting (NAM) in Durham played host to a session titled "Unseen Astronomy", involving a variety of astronomy researchers in diverse fields. This unique meeting focussed โ€ฆ

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Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training

Saul Alonso-Monsalve, Fabio Cufino, Umut Kose, Anna Mascellani, Andre Rubbia ยท 2026

Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally dense, overlapping detector signatures. In this regime, eveโ€ฆ

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A deep learning framework for jointly solving transient Fokker-Planck equations with arbitrary parameters and initial distributions

Xiaolong Wang, Jing Feng, Qi Liu, Chengli Tan, Yuanyuan Liu, Yong Xu ยท 2026

Efficiently solving the Fokker-Planck equation (FPE) is central to analyzing complex parameterized stochastic systems. However, current numerical methods lack parallel computation capabilities across โ€ฆ

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PATHFINDER: Multi-objective discovery in structural and spectral spaces

Kamyar Barakati, Boris N. Slautin, Utkarsh Pratiush, Hiroshi Funakubo, Sergei V. Kalinin ยท 2026

Automated decision-making is becoming key for automated characterization including electron and scanning probe microscopies and nano indentation. Most machine learning driven workflows optimize a singโ€ฆ

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PhaseFlow4D: Physically Constrained 4D Beam Reconstruction via Feedback-Guided Latent Diffusion

Alexander Scheinker, Alexander Plastun, Peter Ostroumov ยท 2026

We address the problem of recovering a time-varying 4D distribution from a sparse sequence of 2D projections - analogous to novel-view synthesis from sparse cameras, but applied to the 4D transverse pโ€ฆ

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Localization of coherent light into photons in a single-crystalline material

Daniel Kazenwadel, Jacob Holder, Livio Ciorciaro, Noel Neathery, Raphael Schwenzer, Leon Oleschko, Jannik Hertkorn, Margaretha Sandor, Peter Baum ยท 2026

The absorption of light by materials is one of the most fundamental processes in optics and condensed-matter physics. Here we investigate whether laser light is absorbed by a crystalline material as aโ€ฆ

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