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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 ↗318 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
Implicit-Explicit time integration scheme with Physics-based preconditioning for two-fluid tokamak boundary simulations ↗
In this work, a globally stiffly accurate Implicit-Explicit (IMEX) Runge-Kutta scheme is developed and implemented in the GBS code [Ricci et al., Plasma Phys. Control. Fusion, 2012], for two-fluid plasma turbulence simulations. The stiffest phenomena, governed by shear Alfvén waves and parallel diffusion, are treated implicitly, while the remaining non-stiff terms are advanced explicitly. This splitting enables time steps well beyond the Courant-Friedrichs-Lewy limit, without incurring the full computational cost of a globally implicit formulation. To efficiently solve the implicit subsystem a…
- Hacker News · Posted on Hacker News · First archived
DOE releases national quantum computing roadmap ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Quantum computing's "dark horse" just proved it can go universal ↗
Hacker News discussion.
- arXiv · Published · First archived
Terminal-Register Certification for Finite-Measurement Learning of Multiscale Quantum States ↗
Structured quantum-state learning not only depends on an expressive ansatz but also on an operational certificate that stays meaningful with finite measurements and imperfect implementation. We study pure one dimensional states learning by an inverse binary multiscale entanglement renormalization ansatz (MERA). In the learning procedure, the qubits removed during coarse graining are controlled coherently and measured together at the terminal register. We confirm that an ideal sequential and terminal measurement schedule delivers the same complete bit string distribution under matched causal op…
- Hacker News · Posted on Hacker News · First archived
Interesting observation and test. Quantum entanglement ↗
Hacker News discussion.
- arXiv · Published · First archived
Temperature--Hamiltonian Ambiguity in Strong-Coupling Quantum Equilibrium ↗
Strong coupling generally drives a subsystem away from the Gibbs state of its bare Hamiltonian at the bath temperature. We formulate a temperature--Hamiltonian ambiguity: the reduced equilibrium state fixes the dimensionless Gibbs generator, but does not by itself uniquely determine the local Hamiltonian and temperature entering a Gibbs representation. We propose an operational resolution in which the local Hamiltonian is identified from physical information independent of the stationary Gibbs parametrization. Whenever the exact reduced state is compatible with the Gibbs family generated by th…
- arXiv · Published · First archived
NxM-Version Programming for Quantum Software: High-Level Components across Frameworks and Engines ↗
Quantum computing has in recent years evolved from a purely theoretical field to an active area in both academia and industry. As a result, Quantum Software Engineering has emerged as an area that aims to organize the process of building, testing, and running quantum software. However, writing quantum software still requires programming with quantum gates and qubits, as well as knowledge specific to quantum software frameworks such as Qiskit, Cirq, Qrisp, pyQuil and PennyLane, each of which reaches quantum hardware through its own toolchain. We present Quanifi, which packages the high-level ro…
- arXiv · Published · First archived
High-fidelity geometric quantum gates exceeding 99.9% in germanium quantum dots ↗
Achieving high-fidelity and robust qubit manipulations is a crucial requirement for realizing faulttolerant quantum computation. Here, we demonstrate a single-hole spin qubit in a germanium quantum dot and characterize its control fidelity using gate set tomography. The maximum control fidelities reach 97.48%, 99.81%, 99.88% for the I, X/2 and Y /2 gate, respectively. These results reveal that off-resonance noise during consecutive I gates in gate set tomography sequences severely limits qubit performance. Therefore, we introduce geometric quantum computation to realize noiseresilient qubit ma…
- OpenAlex · Published · First archived
Energy consumption prediction of range-extended electric vehicles using dependency-guided physics-regularised neural networks ↗
The reliable prediction of energy consumption for range-extended electric vehicles under unseen driving scenarios remains challenging due to variations in driving conditions and vehicle operating characteristics. This paper proposes a two-stage framework integrating a difference-gated long short-term memory (dLSTM) model with a dependency-guided physics-regularised neural network (DG-PRNN) model. The dLSTM captures short-horizon temporal variations in vehicle operating signals, while DG-PRNN introduces dependency-guided sparse connectivity and physics regularisation to improve prediction robus…
- OpenAlex · Published · First archived
Monotonicity-constrained physics-informed neural networks for concrete compressive strength prediction ↗
Abstract Accurate prediction of concrete compressive strength is critical for mix design optimization, quality control, and reliable decision-making in modern construction. While data-driven machine learning models have demonstrated strong predictive capability, most existing approaches treat concrete behavior as a purely statistical problem, often neglecting well-established physical relationships among mix constituents and curing conditions. This limitation can lead to physically inconsistent predictions and reduced interpretability, hindering adoption in engineering practice. To address the…
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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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