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Earlier sources: Physics
This science thread follows physics through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗306 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
A hybrid encryption algorithm based on AES and Kyber for secure image protection in the post-quantum era ↗
The exponential rise in the sharing of multimedia information is accompanied by an increase in vulnerability during data exchange. As quantum computing is threatening the fundamentals of classical cryptography, it is important that multimedia data be protected by quantum-secured encryption techniques. Hybrid encryption that combines symmetric cyphers with post-quantum key encapsulation is an established architectural pattern, but its use for image data has not been explored in depth. This paper presents Quantum Good Privacy (QGP), a hybrid image-encryption scheme that combines AES-256 in Ciphe…
- OpenAlex · Published · First archived
A self-supervised physics-informed residual temporal convolutional network with progressive sparse reconstruction for moving load identification ↗
Existing model-driven moving load identification (MLI) methods are highly sensitive to the selection of regularization parameters, whereas purely data-driven approaches generally require extensive labeled datasets and often suffer from limited generalization under complex vehicle-bridge interaction conditions. To address these challenges, a self-supervised physics-informed residual temporal convolutional network (PI-ResTCN) framework is proposed for accurate and robust MLI. Firstly, an orthogonal matching pursuit (OMP)-based sparse inversion scheme is employed to obtain an initial load estimat…
- OpenAlex · Published · First archived
Physics-consistent Bayesian early warning of wind turbine blade stall using an auxiliary regularized particle filter ↗
Early warning of wind turbine blade stall is difficult because early aerodynamic degradation is weak and easily masked by operating-condition variability and non-Gaussian disturbances in SCADA data. This study proposes a physics-consistent Bayesian sequential early-warning framework based on an auxiliary regularized particle filter. A physically constrained nonlinear state-space model with a latent health factor represents aerodynamic degradation while preserving the coupling among wind speed, rotor speed, and power. For stable inference under turbulence and model mismatch, the likelihood-enha…
- OpenAlex · Published · First archived
Separating Artificial-Viscosity Annealing from the L-BFGS Viscosity in Physics-Informed Neural Networks for Two-Phase Flow ↗
Physics-informed neural networks (PINNs) remain difficult to train for hyperbolic conservation laws. Artificial viscosity is a common remedy, and several methods reduce its coefficient during training. We examine adaptive moment estimation (Adam) followed by limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) optimisation. The schedule followed during Adam, the viscosity used during L-BFGS, and the checkpoint supplied between them can change together. We separate these factors for the one-dimensional Buckley–Leverett equation using a fixed multilayer perceptron with hyperbolic-tangent act…
- OpenAlex · Published · First archived
Hybrid physics-data-driven diagnosis approach for transverse mechanical state of segmental tunnels considering discontinuous joint movements ↗
Forward prediction and inverse identification of the transverse mechanical state are essential for the structural health assessment of jointed segmental tunnels. Existing data-driven, physics-based, and hybrid approaches have limitations in addressing discontinuous joint movements and the inversion of external loads with unknown distributions. To this end, a hybrid physics-data-driven approach is proposed for intelligent diagnosis of the transverse mechanical state of jointed segmental tunnels, with discontinuous joint movements explicitly considered. In this method, characteristic functions r…
- OpenAlex · Published · First archived
Ising-Markov chains equivalence as an inverse problem of statistical physics ↗
We develop a consistent framework for introducing an effective temperature for symbolic stochastic systems with known statistical properties but unknown underlying interaction energies. Focusing on binary finite-memory Markov chains, we establish an exact correspondence with one-dimensional Ising models with finite-range interactions. Within this setting, we demonstrate that information temperature can be defined through three independent approaches: (i) matching joint probability distributions, (ii) matching conditional probabilities, and (iii) solving an entropy-based inverse problem of stat…
- OpenAlex · Published · First archived
CryoModel-4K: physics-based BSIM4 extension for 28 nm bulk CMOS compact modeling at 4 Kelvin ↗
Abstract Accurate compact transistor models for 28 nm bulk CMOS at cryogenic temperatures are essential for reliable quantum computing interface circuit design. Existing room-temperature BSIM4 models fail to capture carrier mobility freeze-out, subthreshold swing saturation, current kink effects, and threshold voltage shifts at 4 K. These failures produce post-fabrication performance deviations exceeding 300% in cryo-CMOS circuits designed using room-temperature models. This paper presents CryoModel-4K, a physics-based compact model that extends BSIM4 to accurately capture 28 nm bulk CMOS beha…
- OpenAlex · Published · First archived
A physics-informed dynamic graph and evidence fusion method for fault alarm detection in building HVAC systems ↗
To address the superposition of normal thermal disturbances and fault characteristics in building heating, ventilation, and air conditioning (HVAC) systems, as well as conflicts among different diagnostic evidence sources, a physics-constrained dynamic graph and multi-source evidence fusion method for fault alarm detection is developed. The method employs the Dynamic Coupling-Informed Graph Attention Network to characterize the time-varying directional coupling relationships among air-side temperature variables, equipment control variables, and operational states. The graph structure is subjec…
- OpenAlex · Published · First archived
Evaluating Gemma 3 27B for local undergraduate physics tutoring ↗
Abstract Physics education research has developed a range of student-centered approaches that emphasize conceptual understanding and problem solving, creating interest in whether large language models (LLMs) can provide complementary, on-demand tutoring support. Locally deployable models are particularly relevant for institutions seeking greater control over data handling and system operation, but their capability relative to commercial models and their reliability in authentic learning interactions remain insufficiently characterized. We introduce mlphys101, a multilingual multiple-choice ben…
- OpenAlex · Published · First archived
A physics-constrained surrogate for subcooled flow boiling in low-GWP immersion cooling microchannels: FiLM conditioning and gradient-balanced training ↗
In liquid immersion cooling with the low-GWP refrigerant R1233zd(E), the onset of nucleate boiling (ONB) governs both the wall temperature and the thermal margin. A real-time digital twin needs a fast differentiable surrogate of the boiling closure rather than repeated evaluation of it. We present one: a physics-constrained network for a micro-finned R1233zd(E) channel, trained on correlation-generated data over 81 operating scenarios. The network conditions its coordinate backbone by feature-wise linear modulation and balances the physics and data losses from their measured gradient norms, re…
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How to assess evidence about Physics
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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