Distance Learning LDRD: Using Latent Deep Learning Distances to Create Trusted Models
An overview of some results from our first year of analyses.
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An overview of some results from our first year of analyses.
We present the SpecDis value-added stellar distance catalog accompanying DESI Data Release 1. SpecDis trains a feed-forward neural network (NN) with Gaia parallaxes and gets the distance estimates. To build up an unbiased training sample, we do not apply selections on parallax error or signal-to-noise (S/N) of the stellar spectra, and instead, we incorporate parallax error into the loss function. Moreover, we employ principal component analysis to reduce the noise and dimensionality of stellar spectra. Validated by independent external samples of member stars with precise distances from globular clusters, dwarf galaxies, stellar streams, combined with blue horizontal branch stars, we demonstrate that our distance measurements show no significant bias up to 100 kpc, and are much more precise than Gaia parallax beyond 7 kpc. The median distance uncertainties are 23%, 19%, 11%, and 7% for S/N < 20, 20 ≤ S/N < 60, 60 ≤ S/N < 100, and S/N ≥ 100. Selecting stars with ${\mathrm{log}}\,g\lt 3.8$ and distance uncertainties smaller than 25%, we have more than 74,000 giant candidates within 50 kpc of the Galactic center and 1500 candidates beyond this distance. Additionally, we develop a Gaussian mixture model to identify unresolvable equal-mass binaries by modeling the discrepancy between the NN-predicted and the geometric absolute magnitudes from Gaia parallaxes and identify 120,000 equal-mass binary candidates. Our final catalog provides distances and distance uncertainties for >4 million stars, offering a valuable resource for Galactic astronomy.
AbstractIn addition to its fundamental interest, the long-distance spin transport is essential for spintronic devices. However, the spin relaxation caused by scattering of the particles carrying the spin limits spin transport. We explored spatially indirect excitons (IXs) in van der Waals heterostructures composed of atomically thin layers of transition-metal dichalcogenides as spin carries. We observed the long-distance spin transport: the spin polarized excitons travel over the entire sample, ~10 micron away from the excitation spot, with no spin density decay. This transport is characterized by the 1/e decay distances reaching ~100 micron. The 1/e decay distances are extracted from fits over the ~10 micron sample size. The emergence of long-distance spin transport is observed at the densities and temperatures where the IX transport decay distances and, in turn, scattering times are strongly enhanced. The suppression of IX scattering suppresses the spin relaxation and enables the long-distance spin transport.
Setback distances define a prescribed distance between a potentially hazardous system and different types of other systems, people, buildings, or materials that may be exposed to that hazard. Riskinformed separation distances are not meant to completely eliminate risk, but rather to limit the risk to an acceptable level. A sensitivity study of risk suggested that a leak size of 3% of the pipe cross-sectional area would be a conservative but reasonable basis. Calculation of the setback distances for gaseous hydrogen was done in a deterministic manner, using a selected leak size and harm criteria for each group of exposures. Harm criteria have been updated to better reflect the exposure types under consideration, and to be consistent with setback distances for liquid hydrogen. The resulting setback distance values are primarily driven by radiative heat flux values for all exposure groups. For the typical pipe sizes, the setback distances slightly increase compared to the previous version of NFPA 2.
Boasting a 6.5 m mirror in space, JWST can increase by several times the number of supernovae (SNe) to which a redshift-independent distance has been measured with a precision distance indicator (e.g., tip of the red giant branch (TRGB) or Cepheids); the limited number of such SN calibrators currently dominates the uncertainty budget in distance ladder Hubble constant (H 0 ) experiments. JWST/NIRCAM imaging of the Virgo Cluster galaxy NGC 4536 is used here to preview JWST program GO-1995, which aims to measure H 0 using three stellar distance indicators (Cepheids, TRGB, and J-branch asymptotic giant branch/carbon stars). Each population of distance indicator was here successfully detected—with sufficiently large number statistics, well-measured fluxes, and characteristic distributions consistent with ingoing expectations—so as to confirm that we can acquire distances from each method precise to about 0.05 mag (statistical uncertainty only). We leverage overlapping Hubble Space Telescope imaging to identify TRGB stars, crossmatch them with the JWST photometry, and present a preliminary constraint on the slope of the TRGB's F115W versus (F115W – F444W) relation equal to -0.99 ± 0.16 mag mag -1 . This slope is consistent with prior slope measurements in the similar Two Micron All-Sky Survey J band, as well as with predictions from the BaSTI isochrone suite. We use the new TRGB slope estimate to flatten the 2D TRGB feature and measure a (blinded) TRGB distance relative to a set of fiducial TRGB colors, intended to represent the absolute fiducial calibrations expected from geometric anchors such as NGC 4258 and the Magellanic Clouds. In doing so, we empirically demonstrate that the TRGB can be used as a standardizable candle at the IR wavelengths accessible with JWST.
Abstract Gromov–Hausdorff distances measure shape difference between the objects representable as compact metric spaces, e.g. point clouds, manifolds, or graphs. Computing any Gromov–Hausdorff distance is equivalent to solving an NP-hard optimization problem, deeming the notion impractical for applications. In this paper we propose a polynomial algorithm for estimating the so-called modified Gromov–Hausdorff (mGH) distance, a relaxation of the standard Gromov–Hausdorff (GH) distance with similar topological properties. We implement the algorithm for the case of compact metric spaces induced by unweighted graphs as part of Python library , and demonstrate its performance on real-world and synthetic networks. The algorithm finds the mGH distances exactly on most graphs with the scale-free property. We use the computed mGH distances to successfully detect outliers in real-world social and computer networks.
Although most mammalian transcriptional enhancers regulate their cognate promoters over distances of tens of kilobases, some enhancers act over distances in the megabase range1. The sequence features that enable such long-distance enhancer–promoter interactions remain unclear. Here we used in vivo enhancer-replacement experiments at the mouse Shh locus to show that short- and medium-range limb enhancers cannot initiate gene expression at long-distance range. We identify a cis-acting element, range extender (REX), that confers long-distance regulatory activity and is located next to a long-range limb enhancer of Sall1. The REX element has no endogenous enhancer activity. However, addition of the REX to other short- and mid-range limb enhancers substantially increases their genomic interaction range. In the most extreme example observed, addition of REX increased the range of an enhancer by an order of magnitude from its native 73 kb to 848 kb. The REX element contains highly conserved [C/T]AATTA homeodomain motifs that are critical for its activity. These motifs are enriched in long-range limb enhancers genome-wide, including the ZRS (zone of polarizing activity (ZPA) regulatory sequence), a benchmark long-range limb enhancer of Shh2. The ZRS enhancer with mutated [C/T]AATTA motifs maintains limb activity at short range, but loses its long-range activity, resulting in severe limb reduction in knock-in mice. In summary, we identify a sequence signature associated with long-range enhancer–promoter interactions and describe a prototypical REX element that is necessary and sufficient to confer long-distance activation by remote enhancers.
Effective monitoring of seismic explosions and hazard assessment relies heavily on the accurate discrimination of underground seismic sources. This study investigates the application of novel nonlinear alignment techniques, specifically Dynamic Time Warping (DTW), for event-type discrimination at regional and local distances. Building on prior research that used DTW and Elastic Shape Analysis (ESA) in discrimination at regional distances, we evaluate the performance of recently developed variants of DTW, including a method that employs Pearson cross-correlation as a measure of warping distance and a time distortion coefficient that quantifies the type and degree of time distortion between signals. By analyzing observational datasets that include different source types, we assess the performance of these approaches for realistic monitoring scenarios. Specifically, we consider a dataset recorded at regional distances in the Korean Peninsula and a local-distance subset from the Unconstrained Utah Event Bulletin catalog to evaluate DTW-based discrimination across multiple distance scales. Additionally, we introduce the maximum cross-correlations of warped waveforms as a similarity metric for event classification. Through hierarchical cluster analysis and dendrogram interpretation, we present our findings, highlighting the strengths and limitations of these techniques in seismic event classification.
This study compares the impacts of delay-, distance-, and cordon-based congestion pricing strategies for Austin, Texas, using the POLARIS agent-based activity-based travel demand simulation model. This approach enables agent-level heterogeneity and realistic choice options (including destination, mode, and activity scheduling) for dynamic traffic assignment and congestion feedbacks across a major metro region, which are features lacking in past work. To ensure comparability, distance-based tolls were set to generate the same revenue as delay-based tolling of $3.5 M/day, averaging $1.17/resident/day or $0.42/vehicle-trip. Delay-based pricing delivers 44% lower network delay and 13% lower VHT compared to the no-toll baseline, levels unmatched by other pricing strategies. At the height of the AM peak, drivers pay up to $0.13/mile on average, though most links in the network remain untolled. Distance-based pricing is the most effective at reducing VMT (by 4%), but VHT reductions (of 6%) primarily stem from drivers selecting closer destinations, achieving only one-fourth the delay reduction of delay-based pricing. Across various implementations of delay- and distance-based pricing, the results suggest that spatial variations of tolls are far more important than temporal variations. Cordon tolls produce minimal impacts at the network-wide level, but offer substantial delay reductions inside the cordon. Other major findings include: 1) delay-based pricing increases trip-making during the PM peak period due to backward shifts in discretionary-activity start times by higher-income residents; and 2) tolls’ spatial impacts, including changes in network flows and tolls paid by residents, vary substantially between delay- and distance-based pricing strategies.
Enhanced Corner Turning (ECOT) experiments provide an important metric of performance of high explosive (HE) formulations. The breakout distance is a single scalar value that characterizes the corner turning efficiency of an HE. Extracting the breakout distance from the raw ECOT results, whether experimental or simulated, is a conceptually straightforward procedure which, however, is non-unique, especially in the presence of noise. More specifically, this procedure involves numerical smoothing and selecting particular values for parameters of this smoothing introduces human bias. In this work, we propose to use the Gaussian process regression to analyze ECOT results. This analysis involves the effective smoothing of the data, thus allowing for accurate extraction of the breakout distance. Most importantly, the parameters of this smoothing can be inferred from the ECOT data itself, rendering the approach effectively parameter-free and thus diminishing the human bias. An additional benefit of the Gaussian process regression, being a statistical inference method, is that not just the value of the breakout distance, but also its confidence interval can be extracted from the data. This report introduces the Gaussian process regression, as applied to ECOT, and demonstrates its usefulness by extracting the breakout distances for a selection of experimental and simulated data.
Estimating the distance from the hydraulic fracture tip to the monitor well can be useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. A heart-shaped signal is referred to as the extensional precursor of a fracture hit recorded by crosswell strain measurements and can serve as a vital tool for such estimation. This study incorporates the 3D displacement discontinuity method (DDM) to understand the impact of fracture geometry and monitor well offset on the heart-shaped signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of the heart-shaped signal and the fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2 (HFTS2). A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and enhanced geothermal system reservoir development, as well as caprock integrity monitoring for carbon sequestration projects.
Electrical grids increased the integration of power electronics sources onto transmission lines. In addition, recent reports show a significant rise in geomagnetic storms occurring in 2024. These geomagnetic storms can affect transmission lines by inducing electrical currents within them, potentially causing power outages due to overloaded power transformers. Geomagnetic induced current neutral blocking devices (GIC-NBDs) are capacitors on the ground of wye power transformers, to avoid damage caused by geomagnetic storms. The integration of distance relays and transmission lines with power electronics sources and GIC-NBDs needs to be studied to observe if GIC-NBDs and power electronics sources could adversely affect operation of the electrical grid. In this analysis, the effect of 2 MW power electronics sources and GIC-NBDs on distance relays is assessed for different 230 kV transmission line lengths in radial and nonradial power systems. The simulations measured the apparent impedances, with different electrical faults. Results for a typical 2,650 μF GIC-NBD application were presented on impedance plots, and the distance relay model operations were assessed. In conclusion, the tests for radial and nonradial power systems showed the behavior of the distance elements and source impedance ratios, assessing the effect of power electronics sources and GIC-NBDs on 230 kV transmission lines.
Efficiently removing/converting methane via methane combustion imposes challenges on catalyst design: how to design local structures of a catalytic site so that it has both high intrinsic activity and atomic efficiency? By manipulating the atomic distance of isolated Pd atoms, herein we show that the intrinsic activity of Pd catalysts can be significantly improved for methane combustion via a stable Pd 2 structure on a ceria nanorod support. Guided by theory and confirmed by experiment, we find that the turnover frequency (TOF) of the Pd 2 structure with the Pd–Pd distance of 2.99 Å is higher than that of the Pd 2 structure with the Pd–Pd distance of 2.75 Å; at least 26 times that of ceria supported Pd single atoms and 4 times that of ceria supported PdO nanoparticles. The high intrinsic activity of the 2.99 Å Pd–Pd structure is attributed to the conductive local redox environment from the two O atoms bridging the two Pd 2+ ions, which facilitates both methane adsorption and activation as well as the production of water and carbon dioxide during the methane oxidation process. In conclusion, this work highlights the sensitivity of catalytic behavior on the local structure of active sites and the fine-tuning of the metal–metal distance enabled by a support local environment for guiding the design of efficient catalysts for reactions that highly rely on Pt-group metals.
Here, this work demonstrates new attempts to determine the intermolecular distances between charged macroionic solutes in their dilute solutions, which regulate the solute’s microphase (self-assembly) and macrophase transitions. Small-angle X-ray scattering (SAXS) and analytical ultracentrifuge (AUC) techniques were applied to determine the intermolecular distances for the 2.42 nm-sized, spherical uranyl peroxide molecular cluster {U 60 } in their self-assembled states in dilute aqueous solution and concentrated phases, respectively. The counterion-mediated attraction among {U 60 } leads to characteristic, inter-{U 60 } distances in solutions, which increase gradually with decreasing the strength of introduced counterions (e.g., lower valency). The gradual increment of inter-{U 60 } distance demonstrates a nice correlation with the macroscopic phase transitions of {U 60 }, from single crystals to concentrated fluids containing rigid 2-D sheets, then to dilute solutions containing a small amount of standalone, floating 2-D sheets of {U 60 }, and finally to dilute solutions containing a limited amount of self-assembled single-layered, spherical blackberry structures of different sizes from the bending of more flexible 2-D sheets.
This paper investigates the potential of intensity interferometry, based on the Hanbury Brown-Twiss effect, for measuring supernova sizes and distances. With optimized telescope positioning, observing strategy, and advancements in single-photon detection technology, this method can provide precise angular size measurements of supernovae with apparent magnitudes as bright as 12 mag. For type Ia supernovae, this limiting brightness corresponds to a local volume extending to redshift z∼0.004 and an anticipated discovery rate of approximately 1 event per year. The combination of angular size data with known physical dimensions enables accurate distance determination. Multiple telescope pairs at different relative positions allow tomographic mapping of the ejecta structure while reducing distance uncertainties. As type Ia supernovae serve as standardizable candles for measuring the Universe’s expansion history, combining intensity interferometry distances with the supernova Hubble diagram facilitates measurements of the Hubble constant H0.
High-resolution phase-contrast 3D imaging using nano-holotomography typically requires collecting multiple tomograms at varying sample-to-detector distances, usually 3 to 4. This multi-distance approach limits temporal resolution, making it impractical for operando studies. Moreover, shifting the sample complicates reconstruction, requiring precise alignment, registration, and interpolation to correct for shift-dependent magnification on the detector. In response, we propose and validate through simulations a novel, to the best of our knowledge, single-distance approach that leverages coded apertures to structure beam illumination while the sample rotates. Finally, this approach relies on a joint reconstruction scheme, which integrates phase retrieval with 3D tomography, ensuring data consistency and achieving artifact-free reconstructions from a single distance, unlocking dynamic experiments.
We measure the current expansion rate of the Universe, Hubble’s constant $H_0$, by calibrating the absolute magnitudes of supernovae to distances measured by baryon acoustic oscillations (BAO). This ‘inverse distance ladder’ technique provides an alternative to calibrating supernovae using nearby absolute distance measurements, replacing the calibration with a high-redshift anchor. We use the recent release of 1829 supernovae from the Dark Energy Survey spanning $0.01\lt z\lt 1.13$ anchored to the recent baryon acoustic oscillation measurements from Dark Energy Spectroscopic Instrument (DESI) spanning $0.30 \lt z_{\mathrm{eff}}\lt 2.33$. To trace cosmology to $z=0$, we use the third-, fourth-, and fifth-order cosmographic models, which, by design, are agnostic about the energy content and expansion history of the universe. With the inclusion of the higher redshift DESI-BAO data, the third-order model is a poor fit to both data sets, with the fourth-order model being preferred by the Akaike Information Criterion. Using the fourth-order cosmographic model, we find $H_0=67.19^{+0.66}_{-0.64}\mathrm{~km} \mathrm{~s}^{-1} \mathrm{~Mpc}^{-1}$, in agreement with the value found by Planck without the need to assume Flat-$\Lambda$CDM. However, the best-fitting expansion history differs from that of Planck, providing continued motivation to investigate these tensions.
For any unitary conformal field theory in two dimensions with the central charge c, we prove that, if there is a nontrivial primary operator whose conformal dimension ∆ vanishes in some limit on the conformal manifold, the Zamolodchikov distance t to the limit is infinite, the approach to this limit is exponential ∆ = exp(−αt + O(1)), and the decay rate obeys the universal bounds c−1/2 ≤ α ≤ 1. In the limit, we also find that an infinite tower of primary operators emerges without a gap above the vacuum and that the conformal field theory becomes locally a tensor product of a sigma-model in the large radius limit and a compact theory. As a corollary, we establish a part of the Distance Conjecture about gravitational theories in three-dimensional anti-de Sitter space. In particular, our bounds on α indicate that the emergence of exponentially light states is inevitable as the moduli field corresponding to t rolls beyond the Planck scale along the steepest path and that this phenomenon can begin already at the curvature scale of the bulk geometry. We also comment on implications of our bounds for gravity in asymptotically flat spacetime by taking the flat space limit and compare with the Sharpened Distance Conjecture.