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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.
- arXiv · Published · First archived
Benchmarking Modular Optimization Strategies for Parameterized Quantum Circuits ↗
Training parameterized quantum circuits requires balancing optimization progress with limited evaluation budgets and the statistical uncertainty of near-term quantum hardware. We present a modular benchmarking framework that separates quantum search-direction estimation from classical parameter-update rules, allowing their interactions and sensitivities to be examined independently. We evaluate a suite of gradient-based, stochastic, and derivative-free optimizers across combinatorial optimization using the Quantum Approximate Optimization Algorithm (QAOA), supervised quantum machine learning u…
- arXiv · Published · First archived
Engineering of Chirped Apodized Sources for Quantum Spectroscopy ↗
Quantum sources of light are of paramount importance for the development of photonic quantum technologies. The growing demand for bright, efficient, and spectrally engineered photonic sources for applications in quantum sensing, spectroscopy, and imaging has motivated the development of tailored nonlinear crystals. Here, we report on the development and characterization of chirped, apodized KTP crystals specifically engineered for quantum spectroscopy. Our source exhibits an unprecedented bandwidth in a highly non-degenerate configuration, demonstrating its potential to support quantum spectro…
- arXiv · Published · First archived
Collusion-Secure Semi-Quantum Secret Sharing Scheme using a Quantum Third Party ↗
The security of a secret sharing protocol is compromised if one or more dishonest participants can reconstruct the secret by deviating from the prescribed protocol, particularly when such malicious behavior remains undetected. Semi-Quantum Secret Sharing (SQSS) is a variant of secret sharing in which the participants possess only classical capabilities, such as preparing and measuring qubits in the computational ($Z$) basis, while a quantum-capable third party assists the dealer in generating and distributing quantum shares of a classical secret. The limited quantum capabilities of the partici…
- arXiv · Published · First archived
Inequivalent Quantum Resources from Multipartite State Discrimination ↗
Any two orthogonal quantum states can be perfectly distinguished via local operations and classical communication (LOCC), yet whether all orthogonal multipartite pairs incur an identical operational cost remains an open question. Here, we address the resource consumption required for local state discrimination across multipartite pair of states. We demonstrate that distinct pairs of orthogonal multipartite maximally entangled states require unequal amounts of quantum resources to achieve local distinguishability. Extending our framework beyond individual pairs, we analyze larger sets of both l…
- Hacker News · Posted on Hacker News · First archived
IBM Anderon Quantum Foundry Automates Qubit Fabs ↗
Hacker News discussion.
- arXiv · Published · First archived
Learning Traffic Flow Dynamics with Stochastic Physics-Informed Neural Cellular Automata ↗
Traffic flow modeling is essential for understanding and predicting the collective dynamics of vehicles on road networks. Cellular automata provide a simple, interpretable yet powerful framework for representing these dynamics via local interaction rules, while retaining the ability to reproduce complex macroscopic traffic phenomena. However, learning local transition rules from data while preserving physically meaningful constraints remains challenging, particularly for stochastic models. In this work, we propose a physics-informed neural cellular automaton (PI-NCA) for data-driven traffic fl…
- GitHub · Repository created · First archived
kwoktung/sapling2d ↗
Code-first, agent-friendly 2D game engine: PixiJS + planck.js physics + Godot-style node tree. Runs in the browser and as a WeChat Mini Game. 代码优先、对 Agent 友好的 2D 游戏引擎，支持微信小游戏。
- arXiv · Published · First archived
Real-time Tokamak Equilibrium Reconstruction Under Limited Experimental Data via Physics-Grounded Synthetic Pre-training ↗
Real-time equilibrium reconstruction is essential for tokamak plasma control. Data-driven surrogates are usually trained on high-quality labeled experimental data, but producing a large amount of labeled data sufficient for surrogate learning requires many expensive discharge shots, and few exist at the start of a new campaign or the operation of a new device. To reduce this cost, we propose to pre-train on simulated equilibria, generated at low cost by physics-based simulation, then fine-tune on limited real data. We evaluate under three settings with increasing difficulties, i.e., in-distrib…
- Hacker News · Posted on Hacker News · First archived
2D Vehicles (Driving Physics in GTA1) ↗
Hacker News discussion.
- OpenAlex · Published · First archived
Physics-aware and uncertainty-guided deep learning-based surrogate optimization for low-power OTA design ↗
This paper presents a physics-aware and uncertainty-guided surrogate optimization framework for the design of ultra-low-power and low-noise cross-coupled feed-forward (CCFF) operational transconductance amplifiers (OTAs) for biosignal acquisition systems. Designing such OTAs involves complex trade-offs among gain, bandwidth, noise, and power, which are difficult to address using conventional methods. To overcome these challenges, a deep learning-based surrogate modeling framework implemented in PyTorch neural networks is proposed, explicitly incorporating device-level constraints such as $$g_m…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
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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