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1. Designing workflows for materials characterization

   https://doi.org/10.1063/5.0169961  

   Kalinin, Sergei V.; Ziatdinov, Maxim; Ahmadi, Mahshid; Ghosh, Ayana; Roccapriore, Kevin; Liu, Yongtao; Vasudevan, Rama K. (March 2024, Applied Physics Reviews)

   Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. We discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research. 

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2. A characterization of nested canalyzing functions with maximum average sensitivity

   Stearns, R; Rosenkrantz, D; Ravi, S; Marathe, M (January 2018, Discrete applied mathematics)

   Nested canalyzing functions (NCFs) are a class of Boolean functions which are used to model certain biological phenomena. We derive a complete characterization of NCFs with the largest average sensitivity, expressed in terms of a simple structural property of the NCF. This characterization provides an alternate, but elementary, proof of the tight upper bound on the average sensitivity of any NCF established by Klotz et al. (2013). We also utilize the characterization to derive a closed form expression for the number of NCFs that have the largest average sensitivity. 

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3. Microlensing Discovery and Characterization Efficiency in the Vera C. Rubin Legacy Survey of Space and Time

   https://doi.org/10.3847/1538-4365/ad91b0  

   Abrams, Natasha_S; Hundertmark, Markus_P_G; Khakpash, Somayeh; Street, Rachel_A; Jones, R_Lynne; Lu, Jessica_R; Bachelet, Etienne; Tsapras, Yiannis; Moniez, Marc; Blaineau, Tristan; et al (December 2024, The Astrophysical Journal Supplement Series)

   Abstract The Vera C. Rubin Legacy Survey of Space and Time will discover thousands of microlensing events across the Milky Way, allowing for the study of populations of exoplanets, stars, and compact objects. We evaluate numerous survey strategies simulated in the Rubin Operation Simulations to assess the discovery and characterization efficiencies of microlensing events. We have implemented three metrics in the Rubin Metric Analysis Framework: a discovery metric and two characterization metrics, where one estimates how well the light curve is covered and the other quantifies how precisely event parameters can be determined. We also assess the characterizability of microlensing parallax, critical for detection of free-floating black hole lenses. We find that, given Rubin’s baseline cadence, the discovery and characterization efficiency will be higher for longer-duration and larger-parallax events. Microlensing discovery efficiency is dominated by the observing footprint, where more time spent looking at regions of high stellar density, including the Galactic bulge, Galactic plane, and Magellanic Clouds, leads to higher discovery and characterization rates. However, if the observations are stretched over too wide an area, including low-priority areas of the Galactic plane with fewer stars and higher extinction, event characterization suffers by >10%. This could impact exoplanet, binary star, and compact object events alike. We find that some rolling strategies (where Rubin focuses on a fraction of the sky in alternating years) in the Galactic bulge can lead to a 15%–20% decrease in microlensing parallax characterization, so rolling strategies should be chosen carefully to minimize losses. 

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4. A FUNCTION SPACE VIEW OF BOUNDED NORM INFINITE WIDTH RELU NETS: THE MULTIVARIATE CASE

   Ongie, Greg; Willett, Rebecca; Soudry, Daniel; Srebro, Nathan (April 2020, International Conference on Learning Representations)

   We give a tight characterization of the (vectorized Euclidean) norm of weights required to realize a function f : R^d -> R as a single hidden-layer ReLU network with an unbounded number of units (infinite width), extending the univariate characterization of Savarese et al. (2019) to the multivariate case. 

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5. Large-scale optical characterization of solid-state quantum emitters

   https://doi.org/10.1038/s41563-023-01644-8  

   Sutula, Madison; Christen, Ian; Bersin, Eric; Walsh, Michael P.; Chen, Kevin C.; Mallek, Justin; Melville, Alexander; Titze, Michael; Bielejec, Edward S.; Hamilton, Scott; et al (November 2023, Nature Materials)

   Solid-state quantum emitters have emerged as a leading quantum memory for quantum networking applications. However, standard optical characterization techniques are neither efficient nor repeatable at scale. Here we introduce and demonstrate spectroscopic techniques that enable large-scale, automated characterization of colour centres. We first demonstrate the ability to track colour centres by registering them to a fabricated machine-readable global coordinate system, enabling a systematic comparison of the same colour centre sites over many experiments. We then implement resonant photoluminescence excitation in a widefield cryogenic microscope to parallelize resonant spectroscopy, achieving two orders of magnitude speed-up over confocal microscopy. Finally, we demonstrate automated chip-scale characterization of colour centres and devices at room temperature, imaging thousands of microscope fields of view. These tools will enable the accelerated identification of useful quantum emitters at chip scale, enabling advances in scaling up colour centre platforms for quantum information applications, materials science and device design and characterization. 

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