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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.
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Open in the map ↗317 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
An Optimal Quantum Linear Systems Algorithm ↗
In the quantum linear systems problem (QLSP), we are given query access to a $d$-sparse $N\times N$ matrix $A$ with condition number $κ$, and the ability to prepare a quantum state proportional to a vector $\vec b$. The goal is to output an $ε$-approximation to the quantum state proportional to the solution $\vec x$ of $A\vec{x}=\vec{b}$. Following a long line of work, the best previously known quantum algorithms for the QLSP had query complexities $O(κd\log(1/ε))$ and $κ\sqrt d(κd/ε)^{o(1)}$, while the best known lower bounds were $Ω(κ\log(1/ε))$ and $Ω(κ\sqrt d)$. We improve these bounds and…
- arXiv · Published · First archived
Optimal performance in a chaotic Floquet quantum battery ↗
We study a quantum battery consisting of $N$ qubits interacting uniformly with each other. Starting from its ground state, the battery is charged by introducing periodic kicks in the transverse direction along with adding disorder in the interaction direction. Although the battery Hamiltonian along with the initial state preserves the permutation symmetry, the dynamics in presence of disorder during the charging phase takes the system out of the permutation symmetric subspace, resulting to a larger amount of stored energy as compared to that without disorder. In the limit of large disorder, th…
- 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
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.
- arXiv · Published · First archived
Induced Coherence in Quantum and Classical Interferometry: Origin and Control ↗
The wave-particle duality that manifests in the Young's double-slit interferometry satisfying the well known Englert-Greenberger-Yasin inequality has recently been shown to obey a universal triality relation involving coherence, predictability and rather surprisingly entanglement. In the present work, we explicitly demonstrate the persistence of the triality relation in the quantum induced coherence interferometer and the classical configuration recovers the well known duality inequality. Furthermore, we explore the origin of coherence and entanglement, in the induced coherence interferometer,…
- arXiv · Published · First archived
How fast can a parent estimate the value of their children? A quantum algorithm for stochastic games ↗
We give a quantum algorithm for stochastic $2$-player games. Their game trees are the expectiminimax trees of classical game search: $m$ adversarial layers alternate with $m$ chance layers, every node has $deg$ children, and the leaf values lie in an interval of length $N$. The algorithm estimates the value of the game to root mean square error $ε$ with \[ O\!\left( K^{D}\, deg^{\frac{D}{4}} \, \frac{N}ε \, D^{4D} \log\left( \frac{deg N}ε \right)^{4D} \right), \qquad D = 2m \] queries to the leaf values, where $K$ is an absolute constant. If we treat the depth $D$ as a constant as is sometimes…
- arXiv · Published · First archived
Fourier-Geometric Circuit Design for Gate and Entanglement Placement in Quantum Neural Networks ↗
The output of a parameterized quantum circuit (PQC) can be expressed as a finite Fourier series whose accessible frequencies are fixed by the data-encoding gates. While the encoder determines which frequencies can appear, the corresponding Fourier coefficients depend on how the trainable and entangling gates are arranged. Although existing studies provide metrics for characterizing how gate structure affects Fourier coefficients, they do not translate these analyses into an explicit design criterion specifying how gates should be arranged to make a target coefficient reachable. In this paper,…
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