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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 ↗304 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
Interpretable physics-guided neural networks for state of health estimation of lithium-ion battery ↗
Accurate prediction of lithium-ion battery state of health (SOH) is essential for safe and reliable operation. Although model-based and data-driven methods have achieved significant progress, their lack of decision transparency leads to limited reliability and poor interpretability in industrial applications. To address this key challenge, we propose a novel SOH estimation method based on a Physics-Guided Kolmogorov-Arnold Network (PGKAN). This dual-module coevolutionary architecture integrates an SOH Estimator (SOHE) and a Degradation Mechanism Surrogate (DMS) to co-evolve SOH estimation and…
- OpenAlex · Published · First archived
Predicting Angle Beam Ultrasonic Inspection Signals with a Physics-Informed Neural Network ↗
Simulation of angle beam ultrasonic inspection supports procedure qualification, probe design, and defect detectability studies, but conventional solvers require a conforming mesh for each configuration and return the solution only at mesh nodes and discrete time steps. Physics-Informed Neural Networks (PINNs) have been applied to ultrasonic wave propagation, but existing formulations solve the wave equation within the propagation medium alone and impose the excitation as a prescribed surface source. The quantity an inspector actually measures; the voltage returned at the transducer terminal;…
- OpenAlex · Published · First archived
Qubit-parity interference despite unknown interaction phases ↗
Abstract Quantum interference between interacting systems is fundamental to basic science and quantum technology, but it typically requires precise control of the interaction phases of lasers or microwave generators. Can interference be observed if those interaction phases are stable but unknown, usually prohibitive for complex state without active control? Here, we answer this question by experimentally preparing a Schrödinger-cat-like state of an internal qubit and a motional oscillator of a trapped 40 Ca + ion, and its robustness to such uncontrolled phases. By applying alternating red and…
- OpenAlex · Published · First archived
Multimode and Random-Access Optical Quantum Memory via Adiabatic Phase Imprinting ↗
A photonic quantum memory that can store multiple qubits and later recall any randomly chosen subset is essential for large-scale quantum networking and computing. This capability, similar to random-access memory in classical computers, has been difficult to achieve due to the lack of a versatile random-access mechanism and the limited multi-mode storage capacity of existing quantum memory protocols. One promising route uses photon-echo protocols, which apply optical rephasing pulses to selectively read out frequency-multiplexed photonic qubits within a broadened optical transition. Here we ad…
- arXiv · Published · First archived
Quantum Channel Stein Theorem beyond Definite Causal Order ↗
Distinguishability is a central concept in information theory and extends naturally to quantum systems. This work shows that, for any two finite-dimensional memoryless quantum channels, parallel, adaptive and general testing strategies achieve the same Stein exponent at every fixed type-I error tolerance $ε\in(0,1)$, namely the regularized channel relative entropy. When this rate is finite, any larger type-II exponent forces the probability of correctly accepting the null hypothesis to decay exponentially. Thus, adaptivity provides no asymptotic advantage. The key step is proving the continuit…
- arXiv · Published · First archived
Quantum Feature Selection for Biomedical Data Analysis ↗
Feature selection is an essential step for reducing complexity of high dimensional data, usually in preparation for developing machine learning models such as computational biomarkers. However, there are limitations associated with feature selection such as for metabolomic data where there are hundreds or even thousands of features per study participant, while the available number of participants in a clinical trials is limited. Classical methods such as exhaustive search require evaluation of all possible feature combinations, making them costly in terms of computation and runtime, or even in…
- arXiv · Published · First archived
The Moreau-Yosida approximation of the Entanglement of Formation: basic properties and accuracy estimates ↗
We describe a family of convex uniformly continuous functions $E^λ_F$, $λ>0$, on the set of states of a bipartite quantum system (consisting of finite-dimensional or infinite-dimensional subsystems), which monotonically increase and converge pointwise to the Entanglement of Formation (EoF) as $λ\to0$. These functions are "nonselective" entanglement monotones defined by the way close to the construction of the Moreau-Yosida regularization (the Moreau envelope) of a convex function on a convex set used in the modern convex analysis. So, we call the functions $E^λ_F$ the Moreau-Yosida approximati…
- arXiv · Published · First archived
Variational Multi-Gaussian Quantum Trajectories ↗
We propose a variational framework for the efficient simulation of stochastic quantum dynamics in interacting bosonic systems. Our method generalizes the time-dependent variational principle to accommodate quantum state diffusion processes and is tailored for describing quantum trajectories unraveled from a master equation. We adopt a wavefunction ansatz composed of a coherent superposition of Gaussian wavepackets, which allows the fully analytical assembly of the variational equations of motion while capturing both the quantum trajectory dynamics and the Lindblad evolution beyond semiclassica…
- arXiv · Published · First archived
Loan Portfolio Optimization with Variational Quantum Algorithms ↗
Loan portfolio optimization (LPO) seeks portfolios that minimize credit risk while satisfying practical selection constraints. Accounting for portfolio-level risk requires modeling not only expected losses but also loss variability and borrower-default correlations, leading to a large-scale combinatorial optimization problem whose complexity grows rapidly with portfolio size. In this work, we formulate LPO as a Quadratic Constrained Binary Optimization (QCBO) problem that jointly captures expected and unexpected losses and transform the resulting formulation into a Quadratic Unconstrained Bina…
- arXiv · Published · First archived
Non-Abelian sheaf quantum LDPC codes: good and magical ↗
Non-Abelian quantum codes connect quantum error correction, phases of matter, and computational resources. In this work, we develop a general framework for constructing non-Abelian quantum low-density parity-check (qLDPC) codes by gauging sheaf codes via cup products and use it to obtain families with constant encoding rate and linear distance. We resolve the coupled logical constraints using explicit representatives to characterize the full gauged code space. We provide a fundamental treatment of code distance based on the general Knill--Laflamme condition and combine expansion with cleaning…
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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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