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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 ↗311 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
Toward Quantum Software Automation: A Quantum-Aware Harness for LLM-Guided Evolution ↗
Quantum software is critical for improving the efficiency and reliability of scarce quantum hardware. However, its design still relies heavily on ad-hoc, handcrafted heuristics that are often suboptimal and quickly become obsolete as quantum hardware evolves. LLM-guided evolutionary search offers a promising way to automatically explore complex software designs, but existing search frameworks lack the quantum-specific support needed for efficient evolution: verification is expensive, feedback is sparse, and heterogeneous quantum programs require different optimization objectives. In this paper…
- OpenAlex · Published · First archived
DuBCG: Unlocking In-Home, Clinically Comparable mmWave Cardiac Monitoring for Co-Sleepers via Physics-Informed Spatial Sensing ↗
Continuous, fine-grained cardiac monitoring during sleep is vital for cardiovascular health. Emerging as a promising alternative to cumbersome wearables, mmWave radar offers a contactless, privacy-preserving modality capable of capturing minute skin vibrations. However, transitioning mmWave radar from labs to real-world bedrooms remains challenging. Our rigorous empirical evaluation of state-of-the-art systems reveals a severe reliability gap: valid Inter-Beat Intervals (IBI) are captured for only 24%-42% of the night within an error threshold of 50 ms. Since clinical HRV analysis requires mil…
- OpenAlex · Published · First archived
The Marb(e)lous BB84: Exploring Tangible Interfaces to Explain Quantum Key Distribution to Adults ↗
We explored the use of tangible interfaces to explain Quantum Key Distribution (QKD) - an inherently complex but increasingly important cybersecurity topic - to adults. Tangible interfaces can support the understanding of complex topics. Yet their role in cybersecurity remains underexplored, despite persistent demands for security awareness and Quantum Computing education. To address this, we applied a participatory approach: (1) exploring current explanations through a survey of QKD professionals ( N = 8) and analysis of popular YouTube videos, (2) conducting ideation workshops ( N = 9) to de…
- OpenAlex · Published · First archived
Multiport quantum interferometry with universal nonunitary transformations ↗
Quantum interferometry provides a pivotal method for investigating complex photon-photon interaction, enabling various quantum information technologies that beyond the possibilities of classical physics. While such an effective interaction is mostly studied in N × N unitary transformation, m × n nonunitary transformation that relates to lossy multiport quantum interferometry requires a different approach. Here, we experimentally demonstrate a concise yet powerful tool to unravel fundamental features of multiport quantum interferometry with universal nonunitary transformations. To confirm their…
- OpenAlex · Published · First archived
A Hybrid Physics‐Informed Computational Framework for Adaptive Microrobotic Navigation and Causal Structure Discovery in Simulated Non‐Newtonian Environments ↗
ABSTRACT Target optimization and autonomous navigation of untethered magnetic microrobots inside complex environments remain open challenges for computational biomedical engineering. The tumor microenvironment imposes complex physical variations, including cross‐linked extracellular matrices, anomalous subdiffusive particle transport, and shear‐thinning non‐Newtonian fluid behaviors. Classic closed‐loop control schemes utilizing explicit online estimators frequently struggle to balance structural parameter convergence with precise track retention due to conflicting excitation requirements. To…
- OpenAlex · Published · First archived
A Reality Gap Taxonomy for Physics-Informed Anomaly Detection in Industrial Control Systems: Cross-Regime Evaluation, Operating-Point and Temporal Distribution Shifts ↗
Physics-informed anomaly detectors for industrial control systems are usually validated on a single synthetic or testbed dataset, which can yield optimistic estimates that do not transfer to deployment-like conditions. This validation-to-deployment discrepancy, the reality gap, is normally treated as one phenomenon and attributed to generic domain shift. We argue that it comprises at least three mechanistically distinct failure modes and propose a taxonomy that separates them by what a practitioner can observe and act on: Type 1, cross-regime evaluation; Type 2, operating-point shift; and Type…
- OpenAlex · Published · First archived
Physics-Informed Machine Learning for Fatigue and Fracture Analysis and Prediction: A Scoping Review ↗
Physics-Informed Machine Learning has emerged as a powerful paradigm for fatigue and fracture analysis, combining the data-driven flexibility of neural networks with the consistency of physical laws. This scoping review maps the extent, range, and nature of research on PIML applied to fatigue life prediction, crack growth and propagation, multiaxial fatigue, damage mechanics, prognostics and health management, and structural health monitoring, covering the literature published from 2018 up to August 2026. A comprehensive search strategy integrated the core terminology of the field with broader…
- OpenAlex · Published · First archived
Agentic AI—Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data ↗
We present an agentic measurement of the thrust distribution in \(e^+e^-\) collisions at \(\sqrt{s}=91.2\) GeV using ALEPH archived data. This work was carried out through an AI agent–physicist collaboration, using interactive natural-language prompting of Anthropic Claude and OpenAI Codex. Under physicist guidance, the agents wrote and executed all analysis code and drafted the majority of the text included in this paper. A fully-corrected thrust spectrum is obtained via Iterative Bayesian Unfolding and Monte Carlo based corrections. The principal contribution of this work is the demonstratio…
- OpenAlex · Published · First archived
Passive polarization stabilization for robust entanglement distribution via cross-aligned polarization maintaining fiber pairs ↗
Maintaining stable entanglement distribution through perturbed fiber links is essential for practical quantum-optics experiments, yet it remains challenging because of polarization fluctuations and phase or temporal-delay variations. We demonstrate stable entangled-photon transmission using a cross-aligned polarization-maintaining fiber (CAPMF) structure composed of two polarization-maintaining fiber sections with mutually orthogonal principal axes. The CAPMF configuration passively compensates polarization fluctuations without real-time active polarization control. We theoretically analyze th…
- OpenAlex · Published · First archived
Physics-Informed Nonlinear Vector Autoregressive Models for the Prediction of Dynamical Systems ↗
Abstract. Machine learning techniques have recently been of great interest for solving differential equations. Training these models is classically a data-fitting task, but knowledge of the expression of the differential equation can be used to supplement the training objective, leading to the development of physics-informed scientific machine learning. In this article, we focus on one class of models called nonlinear vector autoregression (NVAR) to solve ordinary differential equations (ODEs). Motivated by connections to numerical integration and physics-informed neural networks, we explicitl…
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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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