arXiv subjects

G. Landry

Publications and source records attributed to G. Landry.

3 recordsLinked to original sources

arXiv2025

Machine Learning Based Optical Thermometry Using Photoluminescence and Raman Spectra of Diamonds Containing SiV Centers

Micro- and nanothermometry enable precise temperature monitoring and control at the micro- and nanoscale, and have become essential diagnostic tools in applications ranging from high-power microelectronics to biosensing and nanomedicine. Most existing techniques rely on secondary micro- and nanothermometers that require individual calibration of each sensor, ideally both off- and in-situ, before use. We present an alternative approach that overcomes this limitation by employing fluorescent diamonds containing silicon-vacancy centers, where the thermo-sensitive physical quantities are the centers' photoluminescence and the diamond host's Raman signals. The photoluminescence and Raman data are analyzed using two multi-feature regression algorithms that leverage a minimal number of calibration diamonds and temperature set points to predict the temperature of previously unseen diamonds. Using this approach, the models achieve accuracies as low as 0.7 K, resolutions down to 0.6 K Hz$^{-1/2}$, and sensitivity as high as 0.04 K$^{-1}$. These correspond to improvements of roughly 70 percent (over threefold) in accuracy, 50 percent (twofold) in resolution, and 567 percent (sevenfold) in sensitivity compared with traditional single-feature models. Our approach is particularly suited to applications where pre-deployment calibration of every thermosensor is impractical, and it is generalizable to any thermometry platform with two or more simultaneously measurable temperature-dependent observables.

cond-mat.mtrl-sci↗

arXiv2023

Efficient characterization of blinking quantum emitters from scarce data sets via machine learning

Single photon emitters are core building blocks of quantum technologies, with established and emerging applications ranging from quantum computing and communication to metrology and sensing. Regardless of their nature, quantum emitters universally display fluorescence intermittency or photoblinking: interaction with the environment can cause the emitters to undergo quantum jumps between on and off states that correlate with higher and lower photoemission events, respectively. Understanding and quantifying the mechanism and dynamics of photoblinking is important for both fundamental and practical reasons. However, the analysis of blinking time traces is often afflicted by data scarcity. Blinking emitters can photo-bleach and cease to fluoresce over time scales that are too short for their photodynamics to be captured by traditional statistical methods. Here, we demonstrate two approaches based on machine learning that directly address this problem. We present a multi-feature regression algorithm and a genetic algorithm that allow for the extraction of blinking on/off switching rates with >85% accuracy, and with >10x less data and >20x higher precision than traditional methods based on statistical inference. Our algorithms effectively extend the range of surveyable blinking systems and trapping dynamics to those that would otherwise be considered too short-lived to be investigated. They are therefore a powerful tool to help gain a better understanding of the physical mechanism of photoblinking, with practical benefits for applications based on quantum emitters that rely on either mitigating or harnessing the phenomenon.

quant-ph↗

arXiv2014

Generalized isospin, generalized mass groups, and generalized Gell-Mann--Okubo formalism

The current concepts of isospin and baryon mass groups are only well-adapted to deal with baryon multiplets involving both the u and d quarks, and some other quark k. In this paper, we generalize isospin and mass groups to accommodate baryon multiplets involving quarks of any flavor, and the Gell-Mann--Okubo (GMO) formalism is generalized accordingly. Generalized isospin proves to be a simple and valuable framework when working in non-udk baryon multiplets, and provides new quantum numbers that allows us to distinguish $Λ$-like baryons from $Σ$-like baryons in the non-udk multiplets. The generalized GMO formalism allows us to quantify the quality of flavor symmetries seen in baryon multiplets, and also allows us to predict the masses of all observable $J^P = \frac{1}{2}^+$ and $\frac{3}{2}^+$ baryons with an estimated accuracy on the order of 50 MeV in the worst cases, on mass scales that span anywhere from 1000 MeV to 15000 MeV.

hep-ph↗