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We give an unconditional construction of information theoretically secure one time private key unclonable encryption scheme for one bit messages, with efficient encryption and decryption and exponentially small unclonable indistinguishability advantage.
The interplay between charge order and superconductivity offers a fertile ground for emergent quantum phases. Here we theoretically investigate a square lattice superconductor coexisting with a composite charge density wave (CDW) consisting of a real bond modulation (charge bond order, CBO) and an imaginary hopping modulation (chiral flux phase, CFP) that breaks time reversal symmetry. We uncover that, while CFP a...
Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi turn reasoning, tool use, and access to external systems. While powerful, these complex harnesses also make agents hard to train end to end with open infrastructure, whose SFT/RL stacks cannot natively express stateful, multi process harness inference. To address this, we present OpenForgeRL, an open sour...
Faithful explanations of time series classifiers should identify subsequences that are not only sufficient to preserve a black box model's prediction, but also necessary for maintaining it. However, existing sufficiency oriented methods can assign high importance to spurious subsequences that support the prediction without being essential to the model's decision. We introduce \textbf{TimePNS}, a necessity aware fr...
Flow based generative models have enabled remarkable progress in fast and controllable generation across continuous and discrete state spaces, yet existing parameterizations are constrained to fixed dimensions or fixed sequence lengths. Here, we introduce Expanding Generative Flows (EFlows), which define flows between distributions of increasing dimensionality along an expanding interpolant that grows the state by...
Learning effective robot manipulation policies requires diverse, high quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites. We present AXIS, a growable community driven data engine and benchmark for scalable robot learning, which enables browser based teleoperation for large scale demonstration collec...
Continuous variable quantum state tomography is limited by the cost of resolving non Gaussian structure in high dimensional phase space. We introduce QST Flow, a quantum state tomography framework via flow based generative modeling that represents experimentally accessible phase space quasiprobability distributions with normalized, samplable neural densities rather than a truncated density matrix. The framework ha...
Tuning the coupling strength $g$ of an interacting quantum system may drive a sudden change in its ground state or thermal properties. To identify and grasp non analytical, or even discontinuous, transitions in far from equilibrium dynamics proves more challenging. Recently Krylov complexity $C K$ has offered fresh insights about operator growth, thermalization, and chaos in quantum dynamics. Yet it remains unclea...
Compositional generalization is essential for robot to follow diverse instructions. However, pretrained policies are known to take shortcuts, deferring to salient cues rather than grounding language. We introduce a diagnostic framework that localizes this failure to individual \textit{instruction factors}, \textit{e.g.,} reusable semantic components such as color, verb, object, size, and spatial attribute. Our fra...
Controllable video generation remains challenging due to the difficulty of specifying precise multi object interactions using text prompts or motion control inputs that primarily constrain pixel movement. In practice, trajectory based control often requires users to draw accurate tracks for multiple objects, which scales poorly with scene complexity and becomes ambiguous under occlusion or overlap. To enable flexi...
Quality control in printing, particularly in rotogravure printing, still depends on slow, costly, and subjective manual inspection. Automated surface defect detection is critical for maintaining high quality standards in rotogravure printing. Deep learning models give prospects for automation. However, training robust deep learning models, such as YOLO or Vision Transformers, is heavily hindered by the extreme sca...
Embodied question answering (EQA) is traditionally evaluated under an episodic formulation, where agents solve each task independently and reset internal state between episodes. However, real world robots operate continuously and must accumulate, retain, and selectively reuse information acquired from prior interactions. Despite this practical requirement, the architectural mechanisms needed to support sequential ...
Spin relaxation is conventionally described by two independent phenomenological rates longitudinal ($R 1$) and transverse ($R 2$) whose separation obscures a deeper structural unity. Here we develop a geometric framework in which dissipation is represented by a single covariant relaxation tensor acting in Liouville space, from which $R 1$ and $R 2$ emerge as complementary projections. This tensor structure is not ...
The coupled ghost and gluon Dyson Schwinger equations (DSEs) of four dimensional Landau gauge Yang Mills (YM) theory are solved with a neural representation trained only from renormalized equation residuals. The neural and fixed point solutions agree at the percent level and remain stable under changes of initialization, network size, integration grid, and infrared boundary condition. Variations of the three gluon...
We propose a new approach to two sample testing for deciding whether two sets of samples are drawn from the same distribution. The test is built on a statistical discrepancy based on the zero flow criterion, termed zero flow discrepancy (ZFD). We prove the validity of ZFD and propose a practical testing procedure, termed the zero flow two sample test (ZF2ST). The key idea is to learn how samples from the two distr...
Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings. Large language models can synthesize executable Rust tests, but their outputs often violate API preconditions, remain shallow, or reduce concurrency to accidental sequential traces. Conversely, model based and systematic testing techniques provide semantic control but commonly requir...
Test Time Tuning (TTT) on pretrained diffusion models has emerged as a powerful paradigm for video editing. However, there exists a foundational mismatch between the distribution mapping nature of generative models and the single point optimization of standard TTT. In this paper, we demonstrate that this mismatch triggers \textit{Prior Collapse}, a degenerate state where the model discards the text conditions and ...
In a two dimensional electron gas, a strong perpendicular magnetic field confines electrons to quantized cyclotron orbits, giving rise to Landau levels with discrete orbit radii. Even the smallest Landau orbit, set by the magnetic length, spans tens of nanometers for fields of a few Tesla, imposing an intrinsic nonlocal response to electromagnetic excitations. From a microscopic theory of the nonlocal susceptibili...
We deform the Carlen Maas Wirth framework for noncommutative dynamical optimal transport by an Arnold Nielsen type complexity operator. A positive state independent operator $G$ compatible with the Hilbert bimodule structure of a noncommutative differential calculus $\partial\colon\M\to\Hcal$ can be absorbed into the calculus itself, \[ \partial G:=G^{1/2}\partial. \] The corresponding complexity weighted transpor...
BCI FIT is a customization protocol dataset for non implantable communication brain computer interface (cBCI) systems, comprising EEG recordings from five participants with speech and/or physical impairments due to amyotrophic lateral sclerosis (ALS). Participants completed calibration and copy spelling tasks using both customized and non customized versions of a cBCI system across multiple visits, with iterative ...
