arXiv preprints from January 1, 2026 through September 5, 2026 — 00:31:53 EST
Photonic chips with silicon nitride ($\mathrm{Si_3N_4}$) microring resonators are well established as heralded single-photon sources, but their operation as frequency-degenerate twin-photon sources has not previously been demonstrated. Here, we realise a twin-photon source at telecommunication wavelengths in a $\mathrm{Si_3N_4}$ ring...
Tunable mechanical networks are being developed as materials that learn in place. Capacity is estimated by counting tunable parameters against target constraints, ignoring Maxwell-Betti reciprocity, the symmetry every passive, linear elastic network obeys by construction. When p degrees of freedom are both driven and read out, every...
Parameterised graph theory studies how the complexity of graph-theoretic problems depends on structural parameters of the input graph. This perspective has proved useful in analysing tensor-network simulation (Markov and Shi, 2008). Its implications for tensor-network representations and tomography are less well understood. In...
The Peierls instability is a foundational mechanism in condensed matter physics, showing how the electron--phonon interaction can transform a simple metal into an insulating state with a new lattice periodicity. In a one-dimensional (1D) metal the Peierls instability follows from the enhanced electronic response at wavevector $Q=2k_F$...
The high-recoil event reported by LUX--ZEPLIN motivates a TeV Higgsino with a sub-MeV neutral-state splitting. Away from cancellations, such a small gap in the MSSM points to electroweak-gaugino masses of order $10^7\,\mathrm{GeV}$, far above the Higgsino mass. We show that the non-universal boundary condition $M_1^G/M_2^G=-3/5$ at...
We derive nonasymptotic upper bounds on the probability that a generalized current of a geometrically ergodic diffusion observed for any amount of time, or its sample mean over any arbitrary sample size, deviates from the stationary mean by more than any given amount. The concentration-of-measure behavior of generalized currents is...
Exact CNOT synthesis asks for a minimum-size CNOT circuit implementing an invertible linear transformation. Although several related synthesis models have been shown to be computationally hard, their hardness proofs rely on additional structure such as restricted qubit connectivity, encoded inputs, or unrestricted intermediate...
In his seminal paper, Bell [Physics Physique Fizika 1, 195 (1964)] considers the correlations that result from space-like separated measurements on a pair of entangled particles. He uses relativity theory to motivate the Bell causal structure, then shows the existence of quantum correlations that cannot be explained classically within...
Electric quadrupole transition probabilities $B(E2)$ serve as key probe of nuclear shell evolution, yet anomalous $B(E2)$ values in exotic nuclei complicate the identification of new magic numbers. In this letter, employing the configuration-interaction relativistic Hartree-Fock model, we demonstrate that effective charges are...
We study the spectral and eigenvector properties of random mixed graphs, combining undirected and directed interactions, using random matrix theory (RMT). The network is represented by a Hermitian adjacency matrix, with undirected links as real entries and directed links as purely imaginary conjugate pairs, ensuring a real spectrum....
Coherent interfaces between optical photons and mechanical excitations provide a promising route towards phonon-state engineering and hybrid quantum information processing. Cavity optomechanical systems enable such interfaces via optomechanically induced transparency (OMIT), allowing coherent mapping between traveling optical fields...
Moiré materials host fractional Chern insulators and electron crystals in close proximity, but the mechanism selecting between them remains an open question. We address this competition in Chern bands with ideal but momentum-dependent quantum geometry -- Aharonov-Casher bands. We present an ansatz wave function for generalized Wigner...
Describing competing phases of strongly correlated systems often requires trial wave functions built from phase-specific assumptions. We propose the \emph{hyperdeterminant (HyperDet) wavefunction} as a phase-agnostic ansatz for both bosonic and fermionic quantum many-body systems exhibiting spontaneous symmetry-breaking order,...
X-ray flares from Sgr~A* span broad ranges in duration, fluence, and luminosity, but their origin remains unsettled. We test whether standing shocks in low-angular-momentum magnetized accretion flows can provide a viable energy reservoir to account for these events. Using semi-analytic trans-magnetosonic shock solutions, we estimate...
Minimal electroweak dark matter (DM) extended by a Majorana (M) and a Dirac (D) multiplet coupled through Higgs interactions provides a predictive framework for high-energy inelastic nuclear recoils. We show that this setup can account for the type of event recently reported by the LUX-ZEPLIN (LZ) Collaboration. At the custodial...
We present the first QCD determination of an energy-dependent form factor for a two-hadron scattering state. In particular, we calculate the QCD contribution to the forward electromagnetic $π^+π^+ + γ\toπ^+π^+$ amplitude at $m_π\approx 400$~MeV using lattice QCD. Because lattice calculations are performed in a finite Euclidean...
We introduce S$^3$T (Self-Supervised Self-Distillation over Time), which, to the best of our knowledge, is the first fully self-contained framework for continuous video state tracking. Our method treats temporal sampling density as privileged information, based on the hypothesis that a denser view of the same clip recovers the running...
While data-driven 3D shape correspondence estimation has recently seen substantial progress, robust matching under partial observations and strong non-isometric deformations remains challenging. Existing learning-based approaches often rely on hand-crafted descriptors or template-based representations, whereas recent generative models...
Online 3D reconstruction models perform poorly on long videos. This happens because regressing poses relative to a fixed first-frame anchor forces extrapolation far beyond the training distribution. Small drifts accumulate and amplify into significant geometric collapse. However, we observe that per-frame depth remains stable...
Evaluating physical reasoning in video models is difficult because absolute motion measurements depend on frame rate, object scale, and camera calibration, all of which are often ambiguous or unavailable in generated video. We propose a different approach. When two objects in the same scene obey the same physical law, their motions...
Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduces repeated cost, latency, and dependency on a provider. We present compile by training, which turns a natural-language specification into a reusable neural function. At compile time,...
Language-model judges now gate training data, score generations, and drive leaderboards. The judge is then a measurement instrument, resting on one rarely stated assumption: the same request, sent to the same model name, reads the same tomorrow. We audited that assumption in two preregistered campaigns with every threshold fixed in...
Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, producing prompts up to 3$\times$ longer yet no more accurate. We trace this to three deficiencies - incomplete error observation, limited search diversity, and unreliable selection - and propose ESPO (Error-Structured...
We propose Puffin-World, a unified multimodal architecture that integrates physical understanding, spatial simulation, and 3D world generation and reconstruction without relying on external offline modules. To reliably construct and interact with 3D worlds, our framework jointly models three native world states: physics (gravity field...
Reasoning traces from chain-of-thought models appear to offer a legible window into how a model arrives at its answer. A growing body of work treats them as such, using LLM judges to diagnose errors, evaluate faithfulness, and provide step-level supervision via process reward models and generative critics. These practices rely on the...