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Earlier sources: Science
Science investigates the natural world through observation, experiments, and mathematical models. Explore papers and developments in biology, medicine, materials, neuroscience, physics, climate, and mathematics; a reported finding is not necessarily established consensus.
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 ↗1623 classified signals in the fourteen-day window. Recent momentum: steady. 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
Learning sparse quantum states from single-qubit measurements ↗
We study the problem of learning a sparse quantum state, an $n$-qubit quantum state whose density matrix has at most $s$ nonzero matrix entries in an unknown product basis. While such states admit compact classical descriptions, they can carry long-range entanglement that prevents reconstruction from local reduced density matrices alone. Therefore, previous learning approaches addressed such long-range-entangled states using many entangling gates to extract the necessary information. In this work, we show that sparse states can nevertheless be efficiently learned using only single-qubit measur…
- arXiv · Published · First archived
A neural network-based Universal Thermal Climate Index for reliable global thermal-stress classification across extreme weather ↗
Extreme temperatures are the leading cause of climate-related mortality world-wide. Climate-health research and operational weather forecasting require accurate estimates of human thermal stress. The Universal Thermal Climate Index (UTCI) is among the most sophisticated and widely used feels-like temperature metrics. However, its ubiquitous polynomial approximation does not generalize well to extreme weather conditions. Here, we introduce Neural-UTCI, a neural network that calculates UTCI with substantially higher accuracy across global conditions at a lower computational cost for operational…
- arXiv · Published · First archived
Bounding Retraining Equivalence and the Deletion Floor in Materials Machine Unlearning ↗
In materials machine learning, closely related retained structures can sustain accurate property predictions even after removing a specific record, rendering post-deletion prediction error an ambiguous metric for machine unlearning. To resolve this ambiguity, we define the deletion floor as the expected target loss under a specified retraining procedure at the deleted request. Standard indistinguishability constraints yield a sharp interval bounding an update's target loss around this baseline reference. Theoretically, a conditional neighbor bound links a low deletion floor directly to retaine…
- arXiv · Published · First archived
Succinct Arguments for QMA from Collapsing Hash Functions ↗
We prove the existence of succinct arguments for QMA, assuming only the existence of collapsing hash functions. This is the first scheme that relies only on unstructured ``Minicrypt'' assumptions, which are not known to imply public-key encryption. Our main technical contribution is a quantum-succinct \emph{claw-state generation} protocol that allows us to bootstrap a small number of quantum correlations into an arbitrarily large number of claw-state correlations, using classical communication only. This improves upon the work of [Zhang, STOC 2021], having better round complexity, a proof in t…
- arXiv · Published · First archived
Electrothermal behavior of superconducting nanowires buried in a commercial CMOS process ↗
Superconducting films native to a commercial CMOS process enable co-integration of superconducting devices (high-kinetic-inductance elements and nanowire detectors) with cryogenic CMOS on one monolithic die. Such films are buried in the front-end-of-line, beneath the back-end-of-line metal stack, an environment that might quench a self-heated hot spot. Current-voltage characteristics are reported for titanium nitride (TiN) nanowires in the polycrystalline-silicon resistor layer of a 22 nm FD-SOI process, and measured retrapping currents are compared with thermal models for longitudinal conduct…
- arXiv · Published · First archived
Low-Weight Canonical Logical Bases from Pair-Partition Codes ↗
We construct complete canonical logical bases for qubit CSS codes by assigning quaternary coefficients to binary circulant permutation matrix pair-partition (CPM-PP) checks, constructing and normalizing logical representatives, and expanding the result into binary matrices. When the two check systems have invertible submatrices on disjoint column sets, cofactor representatives are canonically paired by the inverse of a single pairing polynomial. The resulting pairs span the entire logical space. When the pairing polynomial is a cyclic-shift monomial with coefficient one, normalization preserve…
- arXiv · Published · First archived
Exponential lower bounds for low-degree strategies in position-based quantum cryptography ↗
Non-local quantum computation (NLQC) consists on the implementation of a bipartite unitary $U_{AB}$ by two cooperating distant players by means of a two-round protocol with a single intermediate round of simultaneous communication. It is a major open question to know whether there exists a unitary $U_{AB}$ whose implementation in NLQC requires extra quantum systems with dimensions ${\rm exp}(n^{Ω(1)})$, where $n$ is the dimension of systems $A$ and $B$. This type of exponential lower bound is essential for security of position-based quantum cryptography, since the capabilities of the adversari…
- arXiv · Published · First archived
QC-Stark: A Multi-Task Benchmark Revealing Capability Dissociations in LLMs Evaluated on Quantum Computing Tasks ↗
We introduce QC-Stark, a benchmark for evaluating large language models (LLMs) on 11 quantum computing (QC) tasks, spanning circuit construction, debugging, compilation, error correction, and simulation. Across 2,750 evaluations (10 models $\times$ 11 tasks x 5 difficulty levels x 5 seeds), we find that overall rankings mask substantial per-task variation. The Spearman correlation between overall and per-task rankings is statistically insignificant for 4 out of the 11 tasks included in this benchmark. A 2-parameter Item Response Theory (IRT) model validates measurement quality, and prompt sens…
- arXiv · Published · First archived
Quantum Query Complexity Beyond the Worst Case ↗
Smoothed analysis is a central framework in classical algorithms for explaining the performance of algorithms beyond the worst case, often explaining why algorithms perform well in practice. We initiate a systematic study of its quantum counterpart and show the following results. $(1)$ We show that there is a total function whose smoothed quantum query complexity is exponentially smaller than its classical query complexity. $(2)$ We give near-tight characterizations of smoothed randomized and quantum query complexities for symmetric Boolean functions, unifying the worst-case complexity results…
- Hacker News · Posted on Hacker News · First archived
Building a physics model with fitted parameters is machine learning, but slower ↗
Hacker News discussion.
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