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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 ↗312 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.
- arXiv · Published · First archived
Digital Twin Modeling of Quantum Dynamical Systems: Dissipative Quantum Reservoir Computing ↗
Modeling the response of driven many-body quantum systems from input--output data is difficult: the dynamics are nonlinear, history dependent, and expensive to simulate as system size grows. A paradigmatic case is High-Harmonic Generation~(HHG), where a strong field drives a medium to emit radiation that is highly sensitive to the drive and encodes long-range temporal correlations. We introduce a dissipative quantum reservoir computing~(DQRC) framework that builds a digital twin of such a system, learning its input--output map directly from data while the reservoir---itself a small open quantu…
- OpenAlex · Published · First archived
Conventional and Quantum Feature Selection and Federated Learning Applications for Anomaly Detection in IoT Healthcare Networks ↗
Privacy is a major concern in the Internet Healthcare of Things (IoHT), where threat actors may intrude systems to access personally identifiable data. Federated Learning (FL) is a well suited Machine Learning (ML) approach to preserve confidentiality, availability, and integrity in such settings during data analysis. In this work, we introduce a Network of Quantum ML (N-QML) approach for IoHT intrusion detection, integrating quantum PCA (QPCA) with Quantum FL (QPCA+QFL), tested on a subset of the data set WUSTL-EHMS-2020 using classical and quantum computing experiments across three seeds, co…
- OpenAlex · Published · First archived
Enhanced physics-informed neural networks for Vlasov–Poisson simulations ↗
Kinetic theory is one of the fundamental descriptions in plasma physics. Large-scale numerical simulations for kinetic models such as the non-relativistic Vlasov–Poisson system and the Vlasov–Maxwell system are computationally demanding. To save computer resources, this work uses physics-informed neural network (PINN) and its variant separable PINN (SPINN) to approach the Vlasov–Poisson system. We constructed PINN and SPINN solvers for the multi-dimensional Vlasov–Poisson system and implemented the simulation of Landau damping and two-stream instabilities. The SPINN is proved to be effective f…
- OpenAlex · Published · First archived
Physics-informed explainable artificial intelligence framework for corrosion-fatigue life prediction, reliability assessment, and inspection planning of welded steel structures ↗
Atmospheric corrosion combined with cyclic loading is one of the most critical degradation mechanisms affecting the fatigue life of welded steel structures. Although numerous machine learning models have demonstrated the capability to accurately describe crack propagation processes, the direct application of these models to probabilistic analysis and life-cycle management often requires considerable computational effort. This study proposes a Physics-Informed Explainable Artificial Intelligence (XAI) Framework for corrosion-fatigue life prediction, reliability assessment, and inspection planni…
- OpenAlex · Published · First archived
Radiation-tolerant composites batteries in high energy physics facilities: paving the pathway for india-based neutrino observatory: a state-of-the-art perspective ↗
Abstract High-energy physics facilities, including underground neutrino observatories, demand highly reliable, long-lasting energy storage systems capable of operating for decades in constrained and specialised environments with minimal maintenance. Conventional batteries used in uninterruptible power supplies are not optimised for the required multi-year stability or compatibility with the ultra-clean conditions essential for precision experiments. This perspective explores the development of radiation-tolerant composite batteries as a promising solution for such demanding applications, with…
- OpenAlex · Published · First archived
Physics-Guided and Sustainability-Oriented Design of Carburized Steel Cases by Integrating Thermodynamic Kinetic Coupling with Alloy-Controlled Carbon Diffusion ↗
Gas carburization is widely used to improve the surface durability of load-bearing steels, yet alloy-dependent thermodynamic and kinetic effects often cause large variability in case development and component life. This study presents a physics-guided comparison of carburization behavior in EN3, 20MnCr5, and EN353 steels by integrating hardness profiles, mechanical and wear testing, and thermodynamic–diffusion analysis. Under an identical boost–diffuse–equalize cycle at 930 °C, distinct surface carbon levels of 0.764 wt.% (EN3), 0.792 wt.% (20MnCr5), and 0.822 wt.% (EN353) were obtained. These…
- OpenAlex · Published · First archived
Blade-tip vibration informed latent physics residual prognostics for fatigue crack growth and remaining useful life prediction ↗
Fatigue crack growth prognosis of blades remains challenging because crack length is difficult to measure continuously, while vibration responses are influenced by both damage evolution and loading conditions. A blade-tip vibration-informed latent physics residual prognostics (LPRP) framework is proposed for crack-growth modeling and remaining useful life (RUL) prediction. Blade-tip displacement and resonance-frequency degradation are used to characterize loading response and structural degradation, respectively, enabling crack-growth-rate prediction without direct crack-length input. Resonanc…
- OpenAlex · Published · First archived
Low-carbon core-shell cold-bonded lightweight aggregates using expanded polystyrene and limestone calcined clay cement: Particle-scale performance, sustainability, and physics-informed prediction ↗
Cold-bonded core-shell lightweight aggregates (CSLWAs) using an expanded polystyrene (EPS) core with a limestone calcined clay cement (LC3) shell offer a promising route to low-carbon lightweight aggregates; however, the coupled effects of core size, shell thickness, LC3 composition, and curing regime on particle-scale performance remain insufficiently understood. This study develops EPS-LC3-based CSLWAs by combining three discrete EPS core diameters (8, 10, and 12 mm) with three LC3 shell binders of 30%, 50%, and 70% cement content (denoted LC30, LC50, and LC70). The aggregates were cured und…
- OpenAlex · Published · First archived
Post-measurement readout and class-resolved hardware sensitivity of a variational quantum classifier on two IBM Heron r2 backends ↗
Variational quantum classifiers (VQCs) are increasingly evaluated on real quantum processors, yet their deployment behaviour can depend on post-measurement readout and variation across independently trained models. We study a four-qubit VQC for three-class traffic-state classification on two IBM Heron r2 backends. In a single-seed comparison, a four-channel linear-projection readout achieves higher clean balanced accuracy than a three-channel direct-argmax readout (94.4% versus 78.9%), whereas their hardware recoveries on ibm_kingston are 53.0% and 94.4%, respectively. A matched synthetic-nois…
- OpenAlex · Published · First archived
UAV-Induced Measurement Bias in Air Pollution Sensing: A Physics-Informed Framework for Characterization, Sensor Placement, and Correction ↗
Unmanned aerial vehicles (UAVs) offer flexible, three-dimensional access for air pollution monitoring, but rotor-induced aerodynamic disturbance can bias onboard sensor readings, an effect not yet well characterized for multi-rotor platforms. This paper presents a physics-informed framework unifying rotor wake characterization, turbulence zone classification, pollutant sensitivity analysis, sensor placement strategy, and bias correction into one design tool. Grounded in actuator disk momentum theory and literature-constrained relationships, it predicts or bounds measurement bias across nine po…
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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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