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DOE OSTI2023

Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations

ABSTRACT The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition to the previously known small-scale boost in projected correlation functions, we find that the projection effects also significantly boost three-dimensional correlation functions to scales of 100 $h^{-1} \, \rm Mpc$. We perform a likelihood analysis assuming survey conditions similar to the Dark Energy Survey and show that the selection bias can be self-consistently constrained at the 10 per cent level. We discuss strategies for applying this approach to real data. We expect that expanding the analysis to smaller scales and using deeper lensing data would further improve the constraints on cluster selection bias.

Astronomy & Astrophysics↗
DOE OSTI2023

Hidden deep in the halo: selection of a reduced proper motion halo catalogue and mining retrograde streams in the velocity space

ABSTRACT The Milky Way halo is one of the few galactic haloes that provides a unique insight into galaxy formation by resolved stellar populations. Here, we present a catalogue of ∼47 million halo stars selected independent of parallax and line-of-sight velocities, using a combination of Gaia DR3 proper motion and photometry by means of their reduced proper motion. We select high tangential velocity (halo) main sequence stars and fit distances to them using their simple colour-absolute-magnitude relation. This sample reaches out to ∼21 kpc with a median distance of 6.6 kpc thereby probing much further out than would be possible using reliable Gaia parallaxes. The typical uncertainty in their distances is $0.57_{-0.26}^{+0.56}$ kpc. Using the colour range 0.45 < (G0 − GRP, 0) < 0.715, where the main sequence is narrower, gives an even better accuracy down to $0.39_{-0.12}^{+0.18}$ kpc in distance. The median velocity uncertainty for stars within this colour range is 15.5 km s−1. The distribution of these sources in the sky, together with their tangential component velocities, are very well-suited to study retrograde substructures. We explore the selection of two complex retrograde streams: GD-1 and Jhelum. For these streams, we resolve the gaps, wiggles and density breaks reported in the literature more clearly. We also illustrate the effect of the kinematic selection bias towards high proper motion stars and incompleteness at larger distances due to Gaia’s scanning law. These examples showcase how the full RPM catalogue made available here can help us paint a more detailed picture of the build-up of the Milky Way halo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Correcting for Selection Biases in the Determination of the Hubble Constant from Time-Delay Cosmography

The time delay between multiple images of strongly lensed quasars has been used to infer the Hubble constant. The primary systematic uncertainty for time-delay cosmography is the mass-sheet transform (MST), which preserves the lensing observables while altering the inferred ⁠H 0 . The TDCOSMO collaboration used velocity dispersion measurements of lensed quasars and lensed galaxies to infer that mass sheets are present, which decrease the inferred H 0 by 8 per cent. Here, we test the assumption that the density profiles of galaxy–galaxy and galaxy–quasar lenses are the same. We use a composite star-plus-dark-matter mass profile for the parent deflector population and model the selection function for galaxy–galaxy and galaxy–quasar lenses. We find that a power-law density profile with an MST is a good approximation to a two-component mass profile around the Einstein radius, but we find that galaxy–galaxy lenses have systematically higher mass-sheet components than galaxy–quasar lenses. For individual systems, λ int correlates with the ratio of the half-light radius and Einstein radius of the lens. By propagating these results through the TDCOSMO hierarchical inference code, we find that H 0 is lowered by a further 3 per cent. Using a more recent measurement of velocity dispersions and our fiducial model for selection biases, we infer H 0 = 66 ± 4 (stat) ± 1 (model sys) ± 2 (measurement sys) km s -1 Mpc -1 for the TDCOSMO plus SLACS data set. The first residual systematic error is due to plausible alternative choices in modelling the selection function, and the second is an estimate of the remaining systematic error in the measurement of velocity dispersions for SLACS lenses. Accurate time-delay cosmography requires precise velocity dispersion measurements and accurate calibration of selection biases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The effect of dust bias on the census of neutral gas and metals in the high-redshift Universe due to SDSS-II quasar colour selection

ABSTRACT We present a systematic study of the impact of a dust bias on samples of damped Ly α absorbers (DLAs). This bias arises as an effect of the magnitude and colour criteria utilized in the Sloan Digital Sky Survey (SDSS) quasar target selection up until data release 7 (DR7). The bias has previously been quantified assuming only a contribution from the dust obscuration. In this work, we apply the full set of magnitude and colour criteria used up until SDSS-DR7 in order to quantify the full impact of dust biasing against dusty and metal-rich DLAs. We apply the quasar target selection algorithm on a modelled population of intrinsic colours, and by exploring the parameter space consisting of redshift, ($z_{\rm{\small QSO}}$and zabs), optical extinction, and H i column density, we demonstrate how the selection probability depends on these variables. We quantify the dust bias on the following properties derived for DLAs at z ≈ 3: the incidence rate, the mass density of neutral hydrogen and metals, and the average metallicity. We find that all quantities are significantly affected. When considering all uncertainties, the mass density of neutral hydrogen is underestimated by 10–50 per cent, and the mass density in metals is underestimated by 30–200 per cent. Lastly, we find that the bias depends on redshift. At redshift z = 2.2, the mass density of neutral hydrogen and metals might be underestimated by up to a factor of 2 and 5, respectively. Characterizing such a bias is crucial in order to accurately interpret and model the properties and metallicity evolution of absorption-selected galaxies.

Krogager, Jens-Kristian↗
DOE OSTI2022

The effect of selection – a tale of cluster mass measurement bias induced by correlation and projection

ABSTRACT Cosmology analyses using galaxy clusters by the Dark Energy Survey have recently uncovered an issue of a previously unknown selection effect affecting weak-lensing mass estimates. In this letter, we use the Illustris-TNG simulation to demonstrate that selecting on galaxy counts induces a selection effect because of projection and correlation between different observables. We compute the weak-lensing-like projected mass estimations of dark matter haloes and examine their projected subhalo counts. In the two-dimensional (2D) projected space, haloes that are measured as more massive than truth have higher subhalo counts. Thus, projection along the line of sight creates cluster observables that are correlated with cluster mass measurement deviations, which in turn creates a mass measurement bias when the clusters are selected by this correlated observable. We demonstrate that the bias is predicted in a forward model using the observable-mass measurement correlation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Mechanistic studies of small molecule ligands selective to RNA single G bulges

Abstract Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated molecular dynamics simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity relationship studies and transverse relaxation measurements by nuclear magnetic resonance spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Our work deepened the understanding of RNA-small molecule interactions and integrated a new framework for the rational design of selective small-molecule RNA binders.

Biochemistry & Molecular Biology↗
DOE OSTI2023

Selective Detection in Impulsive Low-Frequency Raman Imaging Using Shaped Probe Pulses

Impulsive stimulated Raman scattering (ISRS) using a single short femtosecond pump pulse to excite molecular vibrations offers an elegant pump-probe approach to perform vibrational imaging below 200 cm –1 . One shortcoming of ISRS is its inability to offer vibrational selectivity as all the vibrational bonds whose frequencies lie within the short pump-pulse bandwidth are excited. To date, several coherent control techniques have been explored to address this issue and selectively excite a specific molecular vibration by shaping the pump pulse. There has not been any systematic work that reports an analogous shaping of the probe pulse to implement preferential detection. In this work, we focus on vibrational imaging and report vibrational selective detection by shaping the probe pulse in time. Here, we demonstrate numerically and experimentally two pulse-shaping strategies with one functioning as a vibrational notch filter and the other functioning as a vibrational low-pass filter. This enables fast (25 μs/pixel) and selective hyperspectral imaging in the low-frequency regime (< 200 cm –1 ).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Orbital selective pairing and gap structures of iron-based superconductors

We discuss the in uence on spin-fluctuation pairing theory of orbital selective strong correlation effects in Fe-based superconductors, particularly Fe chalcogenide systems. We propose that a key ingredient for an improved itinerant pairing theory is orbital selectivity, i.e., incorporating the reduced coherence of quasiparticles occupying specific orbital states. This modifies the usual spin-fluctuation via suppression of pair scattering processes involving those less coherent states and results in orbital selective Cooper pairing of electrons in the remaining states. We show that this paradigm yields remarkably good agreement with the experimentally observed anisotropic gap structures in both bulk and monolayer FeSe, as well as LiFeAs, indicating that orbital selective Cooper pairing plays a key role in the more strongly correlated iron-based superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Understanding the selectivity of nonsteroidal anti-inflammatory drugs for cyclooxygenases using quantum crystallography and electrostatic interaction energy

Quantum crystallography methods have been employed to investigate complex formation between nonsteroidal anti-inflammatory drugs (NSAIDs) and cyclooxygenase (COX) enzymes, with particular focus on the COX-1 and COX-2 isoforms. This study analyzed the electrostatic interaction energies of selected NSAIDs (flurbiprofen, ibuprofen, meloxicam and celecoxib) with the active sites of COX-1 and COX-2, revealing significant differences in binding profiles. Flurbiprofen exhibited the strongest interactions with both COX-1 and COX-2, indicating its potent binding affinity. Celecoxib and meloxicam showed a preference for COX-2, consistent with their known selectivity for this isoform, while ibuprofen showed comparable interaction energies with both isoforms, reflecting its nonselective inhibition pattern. Key amino-acid residues, including Arg120, Arg/His513 and Tyr355, were identified as critical determinants of NSAID selectivity and binding affinity. The findings highlight the complex interplay between interaction energy and selectivity, suggesting that while electrostatic interactions play a fundamental role, additional factors such as enzyme dynamics and the hydrophobic effect also contribute to the therapeutic efficacy and safety profiles of NSAIDs. These insights provide valuable guidance for the rational design of NSAIDs with enhanced therapeutic benefits and minimized adverse effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗
DOE OSTI2019

Damping Selection Strategy for Maximum Energy on Wave Energy Power Converters

An optimal damping selection strategy on the power electronics in wave energy application is introduced to increase the total energy produced from the power converter in a wave energy converter (WEC) system. A damping map for maximum energy is built for the selection. The map is based on an irregular wave-towire simulation and reliability analysis on the IGBT module. From the yearly wave mission profile, the damping selection strategy is proved to provide 40% more energy than the conventional optimal power with passive damping selection in the WEC power converter.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case

Federated Learning (FL) has become a ubiquitous approach for training machine learning models on decentralized data, addressing the myriad privacy concerns inherent in traditional centralized methods. However, the efficiency of FL depends on effective client selection and robust privacy preservation mechanisms. Inadequate client selection may lead to suboptimal model performance, while insufficient privacy measures risk exposing sensitive data. This paper proposes a client selection framework for FL that integrates differential privacy and fault tolerance. Our adaptive approach dynamically adjusts the number of selected clients based on model performance and system constraints, ensuring privacy through calibrated noise addition. We evaluate our method on a network anomaly detection use case using the UNSW-NB15 and ROAD datasets. Results show up to a 7% increase in accuracy and a 25% reduction in training time compared to FedL2P. Moreover, we highlight the trade-offs between privacy budgets and model performance, with higher privacy budgets reducing noise and improving accuracy. Our fault tolerance mechanism, while causing a slight performance drop, enhances robustness to client failures. Statistical validation using Mann-Whitney U tests confirms the significance of these improvements (p < 0.05).

Marfo, William [University of Texas at El Paso,Dep↗
DOE OSTI2018

Understanding Selection And Diversity For Evolution Of Spiking Recurrent Neural Networks

Evolutionary optimization or genetic algorithms have been used to optimize a variety of neural network types, including spiking recurrent neural networks, and are attractive for many reasons. However, a key impediment to their widespread use is the potential for slow training times and failure to converge to a good fitness value in a reasonable amount of time. In this work, we evaluate the effect of different selection algorithms on the performance of an evolutionary optimization method for designing spiking recurrent neural networks, including those that are meant to be deployed in a neuromorphic system. We propose a selection approach that utilizes a richer understanding of the fitness of an individual network to inform the selection process and to promote diversity in the population. We show that including this feature can provide a significant increase in performance over utilizing a standard selection approach.

Schuman, Catherine↗
DOE OSTI2018

NO-LESS: Near optimal curtailment strategy selection for net load balancing in micro grids

The integration of renewable energy sources such as solar PVs into micro grids has increased in recent years. However, the intermittent and unpredictable nature of renewable energy generation makes supply uncertain, in turn requiring continuous net load balancing to ensure grid stability. One technique to achieve net load balancing is curtailment, however, selection of the optimal set of curtailment strategies to achieve a targeted curtailment is NP-hard. State-of-the-art curtailment selection techniques approach this problem by either developing computationally expensive optimal curtailment strategies or reduce accuracy to generate sub-optimal solutions quickly. In this work, we develop NO-LESS: a Near OptimaL CurtailmEnt Strategy Selection algorithm. NO-LESS is a novel Fully Polynomial Time Approximation Scheme (FPTAS) which determines bounded (near optimal) curtailment strategies in a small amount of time while simultaneously satisfying practical constraints on strategy switching overhead and curtailment fairness. We perform both theoretical analysis and practical evaluation to show that NO-LESS is a scalable solution for performing net load balancing through curtailment strategy selection in Micro Grids.

14 SOLAR ENERGY↗
DOE OSTI2021

Modeling and Understanding of Rear Junction Double-Side Passivated Contact Solar Cells with Selective Area TOPCon on Front

Device modeling is performed to propose > 25% efficient industry-compatible rear junction double-side passivated contacts solar cell structure with full area p-TOPCon on the rear and selective area n-TOPCon under the front grid pattern (selective TOPCon). Here, this design enables the use of thicker TOPCon (>100nm) on the front for traditional screen-printed contacts without incurring metal-induced damage, high parasitic absorption loss, and compromise in lateral transport or carrier collection on the front. Rear junction design with appropriate bulk lifetime and resistivity combination eliminate the need for heavy doping in the front field region because carriers can flow through the bulk Si without appreciable FF loss. High VOC is maintained because high-quality Si surface passivation in the field region by Al 2 O 3 /SiN gives J 0 comparable to the TOPCon. Our device modeling specifies the practically achievable properties and parameters for each region, including full area rear p-TOPCon, selective area front n-TOPCon, bulk and contacts, to achieve 25.4% efficiency screen-printed bifacial rear junction selective TOPCon cells.

14 SOLAR ENERGY↗
DOE OSTI2020

Surface Photovoltage Measurement of Perovskite Solar Cells to Screen Carrier Selective Contacts

SPV measurement through the Kelvin probe method is described. Silicon heterojunction structures show the maximum SPV of 700 V. Measurement on perovskite structures, and the results suggest adding BCP with C60 enhances the selectivity of C60 electron contact. Furthermore, PTAA and PTAA/PFN have similar selectivity but NiO x is poorly selective. SPV is an easy way to provide a relative comparison between various cell structures and contact layers to determine the relative extractable Voc and properties of the contact layer (selectivity, passivation) limiting the efficiency.

Kavadiya, Shalinee↗
DOE OSTI2015

Functional metagenomic selection of ribulose 1, 5-bisphosphate carboxylase/oxygenase from uncultivated bacteria

Ribulose 1,5-bisphosphate carboxylase/oxygenase (RubisCO) is a critical yet severely inefficient enzyme that catalyses the fixation of virtually all of the carbon found on Earth. Here, we report a functional metagenomic selection that recovers physiologically active RubisCO molecules directly from uncultivated and largely unknown members of natural microbial communities. Selection is based on CO 2 -dependent growth in a host strain capable of expressing environmental deoxyribonucleic acid (DNA), precluding the need for pure cultures or screening of recombinant clones for enzymatic activity. Seventeen functional RubisCO-encoded sequences were selected using DNA extracted from soil and river autotrophic enrichments, a photosynthetic biofilm and a subsurface groundwater aquifer. Notably, three related form II RubisCOs were recovered which share high sequence similarity with metagenomic scaffolds from uncultivated members of the Gallionellaceae family. One of the Gallionellaceae Rubis COs was purified and shown to possess CO 2 /O 2 specificity typical of form II enzymes. X-ray crystallography determined that this enzyme is a hexamer, only the second form II multimer ever solved and the first RubisCO structure obtained from an uncultivated bacterium. Functional metagenomic selection leverages natural biological diversity and billions of years of evolution inherent in environmental communities, providing a new window into the discovery of CO 2 -fixing enzymes not previously characterized.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structural bases for stoichiometry‐selective calcium potentiation of a neuronal nicotinic receptor

Background and Purpose α4β2 nicotinic acetylcholine (nACh) receptors assemble in two stoichiometric forms, one of which is potentiated by calcium. The sites of calcium binding that underpin potentiation are not known. Experimental Approach To identify calcium binding sites, we applied cryo‐electron microscopy (cryo‐EM) and molecular dynamics (MD) simulations to each stoichiometric form of the α4β2 nACh receptor in the presence of calcium ions. To test whether the identified calcium sites are linked to potentiation, we generated mutants of anionic residues at the sites, expressed wild type and mutant receptors in clonal mammalian fibroblasts, and recorded ACh‐elicited single‐channel currents with or without calcium. Key Results Both cryo‐EM and MD simulations show calcium bound to a site between the extracellular and transmembrane domains of each α4 subunit (ECD‐TMD site). Substituting alanine for anionic residues at the ECD‐TMD site abolishes stoichiometry‐selective calcium potentiation, as monitored by single‐channel patch clamp electrophysiology. Additionally, MD simulation reveals calcium association at subunit interfaces within the extracellular domain. Substituting alanine for anionic residues at the ECD sites reduces or abolishes stoichiometry‐selective calcium potentiation. Conclusions and Implications Stoichiometry‐selective calcium potentiation of the α4β2 nACh receptor is achieved by calcium association with topographically distinct sites framed by anionic residues within the α4 subunit and between the α4 and β2 subunits. Stoichiometry‐selective calcium potentiation could result from the greater number of calcium sites in the stoichiometric form with three rather than two α4 subunits. The results are relevant to modulation of signalling via α4β2 nACh receptors in physiological and pathophysiological conditions.

Pharmacology & Pharmacy↗