arXiv subjects

Sihao Cheng

Publications and source records attributed to Sihao Cheng.

At least 19 recordsLinked to original sources

arXiv2026

A weighted quantile filter based framework for interface optimal design problems

We present a robust and efficient numerical framework based on a median filter scheme for solving a broad class of interface optimal design problems, from image segmentation to topology optimization. A key innovation of our work is the extension of the binary scheme into a level-set scheme via a weighted quantile interpretation. Unlike traditional binary iterative convolution-thresholding method (ICTM), this continuous weighted quantile filter scheme effectively overcomes the pinning effect caused by spatial discretization, achieving interface evolution even with small time steps. We also provide a rigorous theoretical analysis, proving the unconditional energy stability of the iterative scheme. Furthermore, we prove that for a wide class of data fidelity terms, the convex relaxation inherently enforces a binary solution, justifying the effectiveness of the method without explicit penalization. Numerical experiments on the Chan--Vese model, the local intensity fitting (LIF) model, and topology optimization in Stokes flow demonstrate that the proposed efficient continuous framework effectively eliminates the pinning effect, guarantees unconditional energy stability, and accurately converges to binary solutions.

math.NA↗

arXiv2026

White Dwarf Merger Remnants with Cooling Delays on the Q Branch Lack Strong Magnetism

A population of anomalous ultra-massive white dwarfs discovered with Gaia, often referred to as the Q branch, show high (multi-Gyr) cooling delays produced by exotic physical mechanisms. They are believed to be the products of stellar mergers, but the exact origin and formation channel remain unclear. We obtained a spectroscopically complete, volume-limited sample of the Q branch region within 100 pc, and found significant differences in atmospheric composition and rotation rates as a function of tangential velocity. In particular, we discover that stellar remnants with the longest cooling delays do not show strong magnetism nor detectable short-period rotational variability, as opposed to what is generally believed for double-degenerate mergers. This indicates that either these white dwarfs arise from a formation channel with no strong magnetism induced, or that the magnetism produced from the merger dissipates over the cooling delay timescales. Our follow-up photometry has also discovered pulsations in the second and third hydrogen-dominated DAQ white dwarfs, one hotter than 15,500 K, possibly extending the boundaries of the DAV instability strip for white dwarfs with thin hydrogen layers.

astro-ph.SR↗

arXiv2026

Do Transformers Have the Ability for Periodicity Generalization?

Large language models (LLMs) based on the Transformer have demonstrated strong performance across diverse tasks. However, current models still exhibit substantial limitations in out-of-distribution (OOD) generalization compared with humans. We investigate this gap through periodicity, one of the basic OOD scenarios. Periodicity captures invariance amid variation. Periodicity generalization represents a model's ability to extract periodic patterns from training data and generalize to OOD scenarios. We introduce a unified interpretation of periodicity from the perspective of abstract algebra and reasoning, including both single and composite periodicity, to explain why Transformers struggle to generalize periodicity. Then we construct Coper about composite periodicity, a controllable generative benchmark with two OOD settings, Hollow and Extrapolation. Experiments reveal that periodicity generalization in Transformers is limited, where models can memorize periodic data during training, but cannot generalize to unseen composite periodicity. We release the source code to support future research.

cs.LG↗

arXiv2025

First Constraints from Marked Angular Power Spectra with Subaru Hyper Suprime-Cam Survey First-Year Data

We present the first application of marked angular power spectra to weak lensing data, using maps from the Subaru Hyper Suprime-Cam Year 1 (HSC-Y1) survey. Marked convergence fields, constructed by weighting the convergence field with non-linear functions of its smoothed version, are designed to encode higher-order information while remaining computationally tractable. Using simulations tailored to the HSC-Y1 data, we test three mark functions that up- or down-weight different density environments. Our results show that combining multiple types of marked auto- and cross-spectra improves constraints on the clustering amplitude parameter $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ by $\approx$43\% compared to standard two-point power spectra. When applied to the HSC-Y1 data, this translates into a constraint on $S_8 = 0.807\pm 0.024$. We assess the sensitivity of the marked power spectra to systematics, including baryonic effects, intrinsic alignment, photometric redshifts, and multiplicative shear bias. These results demonstrate the promise of marked statistics as a practical and powerful tool for extracting non-Gaussian information from weak lensing surveys.

astro-ph.CO↗

arXiv2025

A Fog Over the Cosmological SGWB: Unresolved Massive Black Hole Binaries in the LISA Band

Disentangling the rich astrophysical structure of the stochastic gravitational-wave background (SGWB) from its cosmological component is essential for the Laser Interferometer Space Antenna (LISA) to access the physics of the early Universe beyond the reach of any other probe. In this work, we develop an analytical framework to compute the astrophysical contribution to the SGWB arising from an unresolved ensemble of inspiraling and merging black hole binaries. Accounting for various resolvability thresholds, we leverage this framework to predict the amplitude, spectral shape, and detection signal-to-noise ratio of the unresolved background from massive black hole binaries (MBHBs), capturing the possible diversity of its SGWB imprint across a range of astrophysically motivated populations. Through a joint analysis of astrophysical and primordial contributions to the SGWB, we determine the minimum detectable amplitude of the cosmological background across a range of spectral shapes. We demonstrate that, even under optimistic subtraction thresholds, unresolved MBHBs can degrade the detectability of a cosmological signal by multiple orders of magnitude, depending on the spectral shape of the primordial component. Ultimately, the MBHB-induced astrophysical SGWB acts both as a veil and a lens: it imposes a fundamental limit on cosmological sensitivity, yet simultaneously reveals the hidden population of massive black holes beyond the reach of individual detections. Accurate modeling of this late-Universe background is therefore a prerequisite for robust component separation and for realizing LISA's full scientific potential.

astro-ph.CO↗

arXiv2025

Discovery of a dwarf planet candidate in an extremely wide orbit: 2017 OF201

We report the discovery of a dwarf planet candidate, 2017 OF201, currently located at a distance of 90 au. Its orbit is extremely wide and extends to the inner Oort cloud, with a semi-major axis of 830 au and a perihelion of 45 au, precisely determined from 24 observations over 20 years. Assuming a typical albedo of 0.13, we estimate a diameter about 700 km, making it the second-largest known object in this dynamical population and a dwarf planet candidate with the widest orbit. Its high eccentricity suggests that an unseen population of similar objects would total about 1% of Earth's mass. Notably, the longitude of perihelion of 2017 OF201 lies outside the clustering observed in extreme trans-Neptunian objects, posing a challenge to the proposed dynamical evidence for the hypothetical Planet Nine.

astro-ph.EP↗

arXiv2024

Buoyant crystals halt the cooling of white dwarf stars

White dwarfs are stellar remnants devoid of a nuclear energy source, gradually cooling over billions of years and eventually freezing into a solid state from the inside out. Recently, it was discovered that a population of freezing white dwarfs maintains a constant luminosity for a duration comparable to the age of the universe, signaling the presence of a powerful yet unknown energy source that inhibits the cooling. For certain core compositions, the freezing process is predicted to trigger a solid-liquid distillation mechanism, due to the solid phase being depleted in heavy impurities. The crystals thus formed are buoyant and float up, thereby displacing heavier liquid downward and releasing gravitational energy. Here we show that distillation interrupts the cooling for billions of years and explains all the observational properties of the unusual delayed population. With a steady luminosity surpassing that of some main-sequence stars, these white dwarfs defy their conventional portrayal as dead stars. Our results highlight the existence of peculiar merger remnants and have profound implications for the use of white dwarfs in dating stellar populations.

astro-ph.SR↗

arXiv2024

Cosmology from HSC Y1 Weak Lensing with Combined Higher-Order Statistics and Simulation-based Inference

We present cosmological constraints from weak lensing with the Subaru Hyper Suprime-Cam (HSC) first-year (Y1) data, using a simulation-based inference (SBI) method. % We explore the performance of a set of higher-order statistics (HOS) including the Minkowski functionals, counts of peaks and minima, and the probability distribution function and compare them to the traditional two-point statistics. The HOS, also known as non-Gaussian statistics, can extract additional non-Gaussian information that is inaccessible to the two-point statistics. We use a neural network to compress the summary statistics, followed by an SBI approach to infer the posterior distribution of the cosmological parameters. We apply cuts on angular scales and redshift bins to mitigate the impact of systematic effects. Combining two-point and non-Gaussian statistics, we obtain $S_8 \equiv \sigma_8 \sqrt{\Omega_m/0.3} = 0.804_{-0.040}^{+0.041}$ and $\Omega_m = 0.344_{-0.090}^{+0.083}$, similar to that from non-Gaussian statistics alone. These results are consistent with previous HSC analyses and Planck 2018 cosmology. Our constraints from non-Gaussian statistics are $\sim 25\%$ tighter in $S_8$ than two-point statistics, where the main improvement lies in $\Omega_m$, with $\sim 40$\% tighter error bar compared to using the angular power spectrum alone ($S_8 = 0.766_{-0.056}^{+0.054}$ and $\Omega_m = 0.365_{-0.141}^{+0.148}$). We find that, among the non-Gaussian statistics we studied, the Minkowski functionals are the primary driver for this improvement. Our analyses confirm the SBI as a powerful approach for cosmological constraints, avoiding any assumptions about the functional form of the data's likelihood.

astro-ph.CO↗

arXiv2024

A candidate giant planet companion to the massive, young white dwarf GALEX J071816.4+373139 informs the occurrence of giant planets orbiting B stars

It has been suggested that giant planet occurrence peaks for stars with $M_{\ast}~\approx~3~M_{\odot}$ at a value a factor of 4 higher than observed for solar-mass stars. This population of giant planets predicted to frequently orbit main-sequence B stars at $a$ ~ 10au is difficult to characterize during the few hundred million years while fusion persists in their host stars. By the time those stars become massive, young white dwarfs, any giant planets present would still be luminous as a consequence of their recent formation. From an initial sample of 2195 Gaia-identified massive, young white dwarfs, we use homogeneous Spitzer Infrared Array Camera (IRAC) photometry to search for evidence of unresolved giant planets. For 30 systems, these IRAC data provide sensitivity to objects with $M~\lesssim$ 10 $M_{\text{Jup}}$, and we identify one candidate with ~ 4 $M_{\text{Jup}}$ orbiting the white dwarf GALEX J071816.4+373139. Correcting for the possibility that some of the white dwarfs in our sample result from mergers, we find a giant planet occurrence $\eta_{\text{GP}}~=~0.11_{-0.07}^{+0.13}$ for stars with initial masses $M_{\ast}~\gtrsim~3~M_{\odot}$. Our occurrence inference is consistent with both the Doppler-inferred occurrence of giant planets orbiting 2 $M_{\odot}$ giant stars and the theoretically predicted factor of 4 enhancement in the occurrence of giant planets orbiting 3 $M_{\odot}$ stars relative to solar-mass stars. Future James Webb Space Telescope NIRCam observations of our sample would provide sensitivity to Saturn-mass planets and thereby a definitive estimate of the occurrence of giant planets orbiting stars with $M_{\ast}~\gtrsim~3~M_{\odot}$.

astro-ph.EP↗

arXiv2024

A new code for low-resolution spectral identification of white dwarf binary candidates

Close white dwarf binaries (CWDBs) are considered to be progenitors of several exotic astronomical phenomena (e.g., type Ia supernovae, cataclysmic variables). These violent events are broadly used in studies of general relativity and cosmology. However, obtaining precise stellar parameter measurements for both components of CWDBs is a challenging task given their low luminosities, swift time variation, and complex orbits. High-resolution spectra (R$> 20 000$) are preferred but expensive, resulting in a sample size that is insufficient for robust population study. To release the full potential of the less expensive low-resolution spectroscopic surveys, and thus greatly expand the CWDB sample size, it is necessary to develop a robust pipeline for spectra decomposition and analysis. We used an artificial neural network (ANN) to build spectrum generators for DA/DB white dwarfs and main-sequence stars. The best-fit stellar parameters were obtained by finding the least $\chi^2$ solution to these feature lines and the continuum simultaneously. We demonstrate the reliability of our code with two well-studied CWDBs, WD 1534+503 and PG 1224+309. We also estimate the stellar parameters of 14 newly identified CWDB candidates, most of which are fitted with double component models for the first time. Our estimates agree with previous results for the common stars and follow the statistical distribution in the literature. The application of our code to a large volume of white dwarf binary candidates will offer important statistic samples to stellar evolution studies and future gravitational wave monitoring.

astro-ph.IM↗

arXiv2024

Cosmological constraints from weak lensing scattering transform using HSC Y1 data

As weak lensing surveys go deeper, there is an increasing need for reliable characterization of non-Gaussian structures at small angular scales. Here we present the first cosmological constraints with weak lensing scattering transform, a statistical estimator that combines efficiency, robustness, and interpretability. With the Hyper Suprime-Cam survey (HSC) year 1 data, we obtain $\Omega_\text{m}=0.29_{-0.03}^{+0.04}$, $S_8\equiv \sigma_8(\Omega_\text{m}/0.3)^{0.5}=0.83\pm0.02$, and intrinsic alignment strength $A_\text{IA}=1.0\pm0.4$ through simulation-based forward modeling. Our constraints are consistent with those derived from Planck. The error bar of $\Omega_\text{m}$ is 2 times tighter than that obtained from the power spectrum when the same scale range is used. This constraining power is on par with that of convolutional neural networks, suggesting that further investment in spatial information extraction may not yield substantial benefits. We also point out an internal tension of $S_8$ estimates linked to a redshift bin around z ~ 1 in the HSC data. We found that discarding that bin leads to a consistent decrease of $S_8$ from 0.83 to 0.79, for all statistical estimators. We argue that photometric redshift estimation is now the main limitation in the estimation of $S_8$ using HSC. This limitation is likely to affect other ground-based weak lensing surveys reaching redshifts greater than one. Alternative redshift estimation techniques, like clustering redshifts, may help alleviate this limitation.

astro-ph.CO↗

arXiv2024

Impact of baryonic feedback on HSC Y1 weak lensing non-Gaussian statistics

Baryonic feedback is a major systematic in weak lensing cosmology. Its most studied effect is the suppression of the lensing power spectrum, a second-order statistic, on small scales. Motivated by the growing interest in statistics beyond the second order, we investigate the effect of baryons on lensing non-Gaussian statistics and the resulting biases in the matter clustering amplitude $S_8 = \sigma_8\sqrt{\Omega_m/0.3}$. We focus on the Subaru Hyper Suprime-Cam Year 1 (HSC-Y1) data which, with its high source number density, closely resembles those expected from the upcoming Euclid and Rubin LSST. We study four non-Gaussian statistics -- peak counts, minimum counts, the probability distribution function, and the scattering transform -- in addition to the usual power spectrum. We first estimate the biases in $S_8$ using mock observations built from the IllustrisTNG and BAHAMAS hydrodynamical simulations and theoretical models built from dark matter-only simulations. We find up to $1\sigma$ bias in $S_8$ when the smallest scales (2 arcmin) and the highest feedback level are considered. We then analyze the HSC-Y1 data and compare the $S_8$ obtained for each statistic with different smoothing scales or scale cuts. As we expect that baryons mostly affect the small scales, comparing the results obtained from including and excluding small scales can indicate the level of impact from baryons. With HSC data, we find only minor ($\leq0.5\sigma$) differences in $S_8$ for all statistics, even when considering very small scales (2 arcmin). Our results suggest that the effect of baryons is insignificant at the level of HSC-Y1 down to 2~arcmin for all statistics examined here, or it is canceled by other scale-dependent systematics.

astro-ph.CO↗

arXiv2023

Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam survey first-year data

We present cosmological constraints derived from peak counts, minimum counts, and the angular power spectrum of the Subaru Hyper Suprime-Cam first-year (HSC Y1) weak lensing shear catalog. Weak lensing peak and minimum counts contain non-Gaussian information and hence are complementary to the conventional two-point statistics in constraining cosmology. In this work, we forward-model the three summary statistics and their dependence on cosmology, using a suite of $N$-body simulations tailored to the HSC Y1 data. We investigate systematic and astrophysical effects including intrinsic alignments, baryon feedback, multiplicative bias, and photometric redshift uncertainties. We mitigate the impact of these systematics by applying cuts on angular scales, smoothing scales, statistic bins, and tomographic redshift bins. By combining peaks, minima, and the power spectrum, assuming a flat-$\Lambda$CDM model, we obtain $S_{8} \equiv \sigma_8\sqrt{\Omega_m/0.3}= 0.810^{+0.022}_{-0.026}$, a 35\% tighter constraint than that obtained from the angular power spectrum alone. Our results are in agreement with other studies using HSC weak lensing shear data, as well as with Planck 2018 cosmology and recent CMB lensing constraints from the Atacama Cosmology Telescope and the South Pole Telescope.

astro-ph.CO↗

arXiv2023

Dynamical masses across the Hertzsprung-Russell diagram

We infer the dynamical masses of stars across the Hertzsprung-Russell (H-R) diagram using wide binaries from the Gaia survey. Gaia's high-precision astrometry measures the wide binaries' orbital motion, which contains the mass information. Using wide binaries as the training sample, we measure the mass of stars across the two-dimensional H-R diagram using the combination of statistical inference and neural networks. Our results provide the dynamical mass measurements for main-sequence stars from 0.1 to 2 M$_\odot$, unresolved binaries and unresolved triples on the main sequence, and the mean masses of giants and white dwarfs. Two regions in the H-R diagram show interesting behaviors in mass, where one of them is pre-main-sequence stars, and the other one may be related to close compact object companions like M dwarf-white dwarf binaries. These mass measurements depend solely on Newtonian dynamics, providing independent constraints on stellar evolutionary models and the occurrence rate of compact objects.

astro-ph.SR↗

arXiv2023

Scattering Spectra Models for Physics

Physicists routinely need probabilistic models for a number of tasks such as parameter inference or the generation of new realizations of a field. Establishing such models for highly non-Gaussian fields is a challenge, especially when the number of samples is limited. In this paper, we introduce scattering spectra models for stationary fields and we show that they provide accurate and robust statistical descriptions of a wide range of fields encountered in physics. These models are based on covariances of scattering coefficients, i.e. wavelet decomposition of a field coupled with a point-wise modulus. After introducing useful dimension reductions taking advantage of the regularity of a field under rotation and scaling, we validate these models on various multi-scale physical fields and demonstrate that they reproduce standard statistics, including spatial moments up to 4th order. These scattering spectra provide us with a low-dimensional structured representation that captures key properties encountered in a wide range of physical fields. These generic models can be used for data exploration, classification, parameter inference, symmetry detection, and component separation.

physics.data-an↗

arXiv2023

A Systematic Search for Short-period Close White Dwarf Binary Candidates Based on Gaia EDR3 Catalog and Zwicky Transient Facility Data

Galactic short-period close white dwarf binaries (CWDBs) are important objects for space-borne gravitational-wave (GW) detectors in the millihertz frequency bands. Due to the intrinsically low luminosity, only about 25 identified CWDBs are detectable by the Laser Interferometer Space Antenna (LISA), which are also known as verification binaries (VBs). The Gaia Early Data Release 3 (EDR3) provids a catalog containing a large number of CWDB candidates, which also includes parallax and photometry measurements. We crossmatch the Gaia EDR3 and Zwicky Transient Facility public data release 8, and apply period-finding algorithms to obtain a sample of periodic variables. The phase-folded light curves are inspected, and finally we obtain a binary sample containing 429 CWDB candidates. We further classify the samples into eclipsing binaries (including 58 HW Vir-type binaries, 65 EA-type binaries, 56 EB-type binaries, and 41 EW-type binaries) and ellipsoidal variations (209 ELL-type binaries). We discovered four ultrashort period binary candidates with unique light-curve shapes. We estimate the GW amplitude of all of our binary candidates, and calculate the corresponding signal-to-noise ratio (S/N) for TianQin and LISA. We find two (six) potential GW candidates with S/Ns greater than 5 in the nominal mission time of TianQin (LISA), which increases the total number of candidate VBs for TianQin (LISA) to 18 (31).

astro-ph.SR↗

arXiv2021

How to quantify fields or textures? A guide to the scattering transform

Extracting information from stochastic fields or textures is a ubiquitous task in science, from exploratory data analysis to classification and parameter estimation. From physics to biology, it tends to be done either through a power spectrum analysis, which is often too limited, or the use of convolutional neural networks (CNNs), which require large training sets and lack interpretability. In this paper, we advocate for the use of the scattering transform (Mallat 2012), a powerful statistic which borrows mathematical ideas from CNNs but does not require any training, and is interpretable. We show that it provides a relatively compact set of summary statistics with visual interpretation and which carries most of the relevant information in a wide range of scientific applications. We present a non-technical introduction to this estimator and we argue that it can benefit data analysis, comparison to models and parameter inference in many fields of science. Interestingly, understanding the core operations of the scattering transform allows one to decipher many key aspects of the inner workings of CNNs.

astro-ph.IM↗

arXiv2021

Weak lensing scattering transform: dark energy and neutrino mass sensitivity

As weak lensing surveys become deeper, they reveal more non-Gaussian aspects of the convergence field which can only be extracted using statistics beyond the power spectrum. In Cheng et al. (2020) we showed that the scattering transform, a novel statistic borrowing mathematical concepts from convolutional neural networks, is a powerful tool for cosmological parameter estimation in the non-Gaussian regime. Here, we extend that analysis to explore its sensitivity to dark energy and neutrino mass parameters with weak lensing surveys. We first use image synthesis to show visually that, compared to the power spectrum and bispectrum, the scattering transform provides a better statistical vocabulary to characterize the perceptual properties of lensing mass maps. We then show that it is also better suited for parameter inference: (i) it provides higher sensitivity in the noiseless regime, and (ii) at the noise level of Rubin-like surveys, though the constraints are not significantly tighter than those of the bispectrum, the scattering coefficients have a more Gaussian sampling distribution, which is an important property for likelihood parametrization and accurate cosmological inference. We argue that the scattering coefficients are preferred statistics considering both constraining power and likelihood properties.

astro-ph.CO↗