arXiv subjects

El Mustapha Mansouri

Publications and source records attributed to El Mustapha Mansouri.

7 recordsLinked to original sources

arXiv2026

Universal scaling of electrochemical information transfer at solid-liquid interfaces

Electrochemical potentials at solid-liquid interfaces govern diverse chemical and energy conversion processes; however, the extent to which their electrochemical influence extends into the solid remains unclear. Here, we show that the maximum accessible electrochemical information is governed by a single dimensionless screening parameter $u$, defined as the ratio of the effective electrostatic separation between the interface and probe to the electrostatic propagation length in the solid. The maximum Fisher information follows a universal inverse-square scaling with this parameter. This relation identifies electrostatic screening as a fundamental constraint on information transfer across solid-liquid interfaces and provides quantitative design principles for interfacial electrochemical sensing.

physics.app-ph↗

arXiv2026

Current-dipole detection of microscale metal defects

An effective electric current dipole provides a compact description of localized current disturbances and has been employed across a broad range of physical systems and length scales. Despite its extensive use in macroscopic systems, its applicability to microscale material diagnostics remains unexplored. In this study, we demonstrate that the current-dipole representation provides an effective physical framework for the detection and characterization of microscopic defects in conductive materials. When an external current is applied to a metal, defects locally perturb the current distribution, thus generating an effective in-plane current dipole that yields a characteristic magnetic-field pattern. By measuring the magnetic-field distribution above the metal and fitting it with a dipole model, we reconstruct the position and effective strength of the dipole, thereby enabling the inference of the defect location and an effective defect-volume metric. Using wide-field magnetic imaging as a measurement platform, we observe a defect-associated magnetic signal from a 38-um-long defect on the front surface of copper samples and identify a defect on the back surface using a 0.5-mm-thick copper plate. We further examine the applicability of this approach to magnetic materials, where permeability contrasts modify the field distribution. Our results establish current-dipole imaging as a general physical framework for magnetic detection of defects and highlight its potential for nondestructive inspection across a wide range of length scales.

physics.app-ph↗

arXiv2026

Fisher Glasses: Tail-Certified Quantum Metrology in Quenched Environments

Quantum metrological advantage is certified by averaged Fisher responses: contrast, susceptibility, or quantum Fisher information (QFI). This fails in quenched sensors, where slow environmental variables freeze within a session but vary between repetitions: shallow nitrogen-vacancy (NV) centers, superconducting qubits with slow two-level fluctuators, and semiconductor spin qubits in drifting charge noise. They sample session-resolved Fisher geometries, not an averaged channel. Certification conditions on the latent session, projects nuisance directions, inverts to attainable loss, then tail-certifies; this inverse upper-tail loss defines quenched tail-certified information. A no-go theorem: no averaged Fisher data determine this certificate; ensembles sharing averaged Fisher matrix, QFI, and projected information have finite or zero certified precision. A Fisher-zero integrability transition governs collapse: the inverse-loss tail exponent $β$ sets the boundary, with nonintegrable certified loss for $β\le 1$, even when annealed information is large or scaling. The certified quantum resource is response transverse to latent disorder, not raw amplification sharing its generator; universal design laws: safe windows, nondegenerate portfolios, Fisher reserves, action separation, Fisher-cut criteria. A shallow-NV Ramsey tournament shows average-QFI optimization is tail-catastrophic, whereas tail-certified designs recover nearly three orders of magnitude in certified information at equal shot budget and latent ensemble. These non-self-averaging phases are Fisher glasses, governed by Fisher-zero rare-event statistics.

quant-ph↗

arXiv2026

Deployment-complete benchmarking

Benchmarks increasingly guide deployment, procurement and scientific screening, yet a score supports only the response it records, not necessarily the deployment action. We introduce deployment-complete benchmarking, which tests whether benchmark evidence determines a deployment action. A benchmark is complete for a claim exactly when the action is constant on each evidence fiber; mixed fibers expose missing deployment information, and completion curves quantify the evidence required to resolve ambiguity. In controlled response spaces, benchmark-channel conformal coverage of 94.98% transferred poorly to an unmeasured deployment channel (10.07%), whereas response-rank intervals achieved 94.91% coverage; even zero benchmark error certified only 45.4% of candidates at the largest residual size. Public audits revealed incompleteness, including 97.9% mixed Tox21 fibers and zero median certifiable fraction in main Matbench and JARVIS audits. In held-out replays, certify-then-acquire reduced false decisions from 1.19% to 0.027% in Tox21 and from 20.3% to 0.128% in JARVIS, while changing model choice and identifying deployment-relevant probes. Deployment-ready benchmarks should report evidence, supported actions, ambiguity and completion cost rather than scores alone.

cs.LG↗

arXiv2026

The Privacy Price of Tail-Risk Learning: Effective Tail Sample Size in Differentially Private CVaR Optimization

Differential privacy changes the effective sample size governing CVaR learning. For tail mass $τ$, the privacy-relevant sample size is not $n$, but $nτ$; equivalently, the effective private tail sample size is $εnτ$. Private CVaR excess risk decomposes into ordinary tail-risk statistical error and a privacy price. This decomposition is complete for scalar estimation and finite classes: scalar estimation has rate $Θ(B \min\{1,(nτ)^{-1/2}+(εnτ)^{-1}\})$, and finite classes of size $M$ have rate $Θ(B \min\{1,\sqrt{\log(2M)/(nτ)}+\log(2M)/(εnτ)\})$. These complete rates hold under pure DP, and their lower bounds extend to approximate DP in the stated small-$δ$ regimes. For convex Lipschitz learning, modular upper and lower reductions show that the CVaR-specific privacy term necessarily scales as $1/(εnτ)$, with dimension dependence inherited from private stochastic convex optimization. Together, these results identify ordinary private learning on $Θ(nτ)$ informative tail records as the canonical hard subproblem inside private CVaR learning.

cs.LG↗

arXiv2026

Crystallographic Symmetry Generates Phononic Holonomic Gates with Biased-Erasure Channels

Solid-state processors require control layers whose errors are legible to quantum-error-correction decoders. We show that crystallographic symmetry can provide such a layer in strain-active Lambda manifolds. When the projected strain tensor and Lambda-transition operators share a multiplicity-one two-dimensional irreducible representation, symmetry fixes the linear strain interaction to a scalar dot product. Two phase-locked mechanical modes synthesize a circular strain field, enabling complex phononic Lambda-leg control without local microwave near fields. On this manifold we construct a superadiabatic echo-lune holonomic gate using Lambda-leg control and a resonant double-quantum counterdiabatic tone. Rotating-frame simulations of a nitrogen-vacancy center give 99.88% conditional average fidelity in 1.833 microseconds, or 99.40% when leakage is counted as error. A resonant gigahertz high-overtone bulk acoustic resonator analysis translates the Hamiltonian into Rabi-rate, linewidth, and envelope-tracking requirements. The bright-state structure organizes noise: A2-sector perturbations are parity-filtered into an optically distinguishable auxiliary state, whereas transverse E-sector faults are echo suppressed and retained as a decoder stress axis. The extracted channel has 0.47% erasure probability and 0.168% residual Z error. In XZZX code-capacity simulations, this biased-erasure model yields a nominal 64% fit-extrapolated data-qubit reduction relative to an unstructured Rabi baseline. Repeated-round detector-model diagnostics preserve the nominal distance-9 proxy and identify missed erasures, transverse floors, leakage/flag timing, and strong crosstalk as validation limits. Extensions to orbital Lambda systems and bright-projector phonon-bus diagnostics identify crystallographic symmetry as a principle for co-designing phononic actuation, leakage, noise bias, and quantum decoding.

quant-ph↗

arXiv2025

Autonomous AI Bird Feeder for Backyard Biodiversity Monitoring

This paper presents a low cost, on premise system for autonomous backyard bird monitoring in Belgian urban gardens. A motion triggered IP camera uploads short clips via FTP to a local server, where frames are sampled and birds are localized with Detectron2; cropped regions are then classified by an EfficientNet-B3 model fine tuned on a 40-species Belgian subset derived from a larger Kaggle corpus. All processing runs on commodity hardware without a discrete GPU, preserving privacy and avoiding cloud fees. The physical feeder uses small entry ports (30 mm) to exclude pigeons and reduce nuisance triggers. Detector-guided cropping improves classification accuracy over raw-frame classification. The classifier attains high validation performance on the curated subset (about 99.5 percent) and delivers practical field accuracy (top-1 about 88 percent) on held-out species, demonstrating feasibility for citizen-science-grade biodiversity logging at home.

cs.CV↗