arXiv subjects

Wen Zhao

Publications and source records attributed to Wen Zhao.

At least 91 records · Page 5Linked to original sources

arXiv2024

Forecast of CMB TB and EB correlations for AliCPT-1

The correlations between T, E modes and B modes in cosmic microwave background (CMB) radiation, which are expected to vanish under parity symmetry, have become a sensitive probe of the new physics beyond the standard model. In this paper, we forecast the estimation of TB and EB cross power spectra using NILC and cILC on AliCPT-1 simulations together with Planck HFI and WMAP K maps as ancillary data. We find that, NILC performs better than cILC on measuring TB and EB correlations in light of its lower uncertainties. In terms of the birefringence angle estimation without assuming systematic errors, the combination of CMB TB and EB spectra from NILC cleaned simulations could reach a sensitivity of $|β|<0.058^\circ$ with 2$σ$ significance for the first observing season of AliCPT. Tripling the survey duration will improve this sensitivity to $|β|<0.041^\circ$.

astro-ph.CO↗

arXiv2024

Full characterization of an all fiber source of heralded single photons

We demonstrate a heralded single photon source which is based on the photon pairs generated from pulse pumped spontaneous four wave mixing in a piece of commercially available dispersion shifted fiber. The single photon source at 1550 nm telecom band is characterized with both photon counting technique and homodyne detection method. The heralding efficiency and mode purity can be measured by photon counting while the vacuum contribution part can be found by homodyne detection.

quant-ph↗

arXiv2024

Constraints on parity and Lorentz violations in gravity from GWTC-3 through a parametrization of modified gravitational wave propagations

Gravitational wave (GW) observations provide sensitive tests of parity and Lorentz symmetries of gravity. Any violation of these fundamental symmetries induces possible deviations in the GW propagations. Through a systematic parametrization for characterizing possible derivations from GW propagations in general relativity, we construct the modified GW waveforms generated by the coalescence of compact binaries with the effects of the parity and Lorentz violations as predicted by many parity- and Lorentz-violating gravities and then analyze them with the open data of compact binary merging events detected by LIGO-Virgo-KAGRA Collaboration. No signature of gravitational parity and Lorentz violations are found for most GW events, thereby allowing us to place several of the most stringent constraints on parity and Lorentz violations in gravity and a first constraint on the Lorentz-violating damping effect in GW.

gr-qc↗

arXiv2024

Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning

Sequential modeling has demonstrated remarkable capabilities in offline reinforcement learning (RL), with Decision Transformer (DT) being one of the most notable representatives, achieving significant success. However, RL trajectories possess unique properties to be distinguished from the conventional sequence (e.g., text or audio): (1) local correlation, where the next states in RL are theoretically determined solely by current states and actions based on the Markov Decision Process (MDP), and (2) global correlation, where each step's features are related to long-term historical information due to the time-continuous nature of trajectories. In this paper, we propose a novel action sequence predictor, named Mamba Decision Maker (MambaDM), where Mamba is expected to be a promising alternative for sequence modeling paradigms, owing to its efficient modeling of multi-scale dependencies. In particular, we introduce a novel mixer module that proficiently extracts and integrates both global and local features of the input sequence, effectively capturing interrelationships in RL datasets. Extensive experiments demonstrate that MambaDM achieves state-of-the-art performance in Atari and OpenAI Gym datasets. Furthermore, we empirically investigate the scaling laws of MambaDM, finding that increasing model size does not bring performance improvement, but scaling the dataset amount by 2x for MambaDM can obtain up to 33.7% score improvement on Atari dataset. This paper delves into the sequence modeling capabilities of MambaDM in the RL domain, paving the way for future advancements in robust and efficient decision-making systems.

cs.LG↗

arXiv2024

Wave effect of gravitational waves intersected with a microlens field II: an adaptive hierarchical tree algorithm and population study

The gravitational lensing wave effect generated by a microlensing field embedded in a lens galaxy is an inevitable phenomenon in strong lensed gravitational waves (SLGWs). This effect presents both challenges and opportunities for the detection and application of SLGWs. However, investigating this wave effect requires computing a complete diffraction integral over each microlens in the field. This is extremely time-consuming due to the large number of microlenses. Therefore, simply adding all the microlenses is impractical. Additionally, the complexity of the time delay surface makes the lens plane resolution a crucial factor in controlling numerical errors. In this paper, we propose a trapezoid approximation-based adaptive hierarchical tree algorithm to meet the challenges of calculation speed and precision. We find that this algorithm accelerates the calculation by four orders of magnitude compared to the simple adding method and is one order of magnitude faster than the fixed hierarchical tree algorithm proposed for electromagnetic microlensing. More importantly, our algorithm ensures controllable numerical errors, increasing confidence in the results. Together with our previous work, this paper addresses all numerical issues, including integral convergence, precision, and computational time. Finally, we conducted a population study on the microlensing wave effect of SLGWs using this algorithm and found that the microlensing wave effect cannot be ignored, especially for Type II SLGWs due to their intrinsic geometric structures and their typical intersection with a denser microlensing field. Statistically, more than 33% (11%) of SLGWs have a mismatch larger than 1% (3%) compared to the unlensed waveform. Additionally, we found that the mismatch between signal pairs in a doubly imaged GW is generally larger than 10^{-3}, and 61% (25%) of signal pairs have a mismatch larger than 1% (3%).

astro-ph.IM↗

arXiv2024

Whole-body Humanoid Robot Locomotion with Human Reference

Recently, humanoid robots have made significant advances in their ability to perform challenging tasks due to the deployment of Reinforcement Learning (RL), however, the inherent complexity of humanoid robots, including the difficulty of designing complicated reward functions and training entire sophisticated systems, still poses a notable challenge. To conquer these challenges, after many iterations and in-depth investigations, we have meticulously developed a full-size humanoid robot, "Adam", whose innovative structural design greatly improves the efficiency and effectiveness of the imitation learning process. In addition, we have developed a novel imitation learning framework based on an adversarial motion prior, which applies not only to Adam but also to humanoid robots in general. Using the framework, Adam can exhibit unprecedented human-like characteristics in locomotion tasks. Our experimental results demonstrate that the proposed framework enables Adam to achieve human-comparable performance in complex locomotion tasks, marking the first time that human locomotion data has been used for imitation learning in a full-size humanoid robot.

cs.RO↗

arXiv2024

Single-photon phase spectrum recovery from the Hong-Ou-Mandel dip

Characterizing the temporal-spectral profile of single photons is essential for quantum information protocol utilizing temporal mode for encoding. Based on the phase retrieval algorithm, we present a method to reconstruct the phase spectrum difference between two wave packets from their Hong-Ou-Mandel dip, and intensity spectra. Our confirmatory experiment with weak coherent wave packets demonstrated the accuracy of the reconstructed phase spectrum difference to within plus or minus 0.1 rad. This method is generalizable to the measurement of unknown single-photon wave packets with the aid of a reference wave packet, requiring only the collection of one-dimensional data, which simplifies and expedites the process.

quant-ph↗

arXiv2024

Power spectra and circular polarization of primordial gravitational waves with parity and Lorentz violations

The violations of parity and Lorentz symmetries in gravity can change the propagating properties of gravitational waves (GWs) in the cosmological background, which can arise from a large number of parity- and Lorentz-violating theories. In this paper, through a systematic parametrization for characterizing possible derivations from the standard GW propagation in general relativity, we study both the parity- and Lorentz-violating effects on the power spectra and the polarization of the primordial gravitational waves (PGWs) during the slow-roll inflation. To this end, we calculate explicitly the power spectrum and the corresponding circular polarization of the PGWs analytically by using the uniform asymptotic approximation. It is shown that the new contributions to power spectra contain two parts, one from the parity-violating terms and the other from the Lorentz-violating terms. While the Lorentz-violating terms can only affect the overall amplitudes of PGWs, the parity-violating terms induce nonzero circular polarization of PGWs, i.e., the left-hand and right-hand polarization modes of GWs have different amplitudes.

gr-qc↗

arXiv2024

Reinforcement Learning with Generalizable Gaussian Splatting

An excellent representation is crucial for reinforcement learning (RL) performance, especially in vision-based reinforcement learning tasks. The quality of the environment representation directly influences the achievement of the learning task. Previous vision-based RL typically uses explicit or implicit ways to represent environments, such as images, points, voxels, and neural radiance fields. However, these representations contain several drawbacks. They cannot either describe complex local geometries or generalize well to unseen scenes, or require precise foreground masks. Moreover, these implicit neural representations are akin to a ``black box", significantly hindering interpretability. 3D Gaussian Splatting (3DGS), with its explicit scene representation and differentiable rendering nature, is considered a revolutionary change for reconstruction and representation methods. In this paper, we propose a novel Generalizable Gaussian Splatting framework to be the representation of RL tasks, called GSRL. Through validation in the RoboMimic environment, our method achieves better results than other baselines in multiple tasks, improving the performance by 10%, 44%, and 15% compared with baselines on the hardest task. This work is the first attempt to leverage generalizable 3DGS as a representation for RL.

cs.CV↗

arXiv2024

Impact of LRG1 and LRG2 in DESI 2024 BAO data on dark energy evolution

Recent measurements of baryon acoustic oscillations (BAO) by the Dark Energy Spectroscopic Instrument (DESI) suggest a preference for a dynamic dark energy model over a cosmological constant. This conclusion emerges from the combination of DESI's BAO data with observations of the Cosmic Microwave Background (CMB) and various type Ia supernova (SN Ia) catalogues. The deviation observed in the cosmological constant ($Λ$) reflects a departure from the standard cosmological model. Testing this deviation involves examining the consistency between cosmological parameters derived from early and late-time observations. Specifically, we focus on the matter density parameter $ω_m = Ω_mh^2$ and introduce ${\rm ratio}(ω_m)$ to assess consistency, which is defined as the ratio of $ω_m$ values constrained by high and low-redshift measurements. This ratio serves as a metric for quantifying deviations from the $Λ$CDM model. In this paper, we find that the DESI BAO+CMB yields ${\rm ratio}(ω_m)=1.0171\pm0.0066$. Upon excluding the LRG1 and LRG2 data in DESI BAO, this ratio adjusts to ${\rm ratio}(ω_m)=1.0100\pm0.0082$. This shift, corresponding to a change from $2.6σ$ to $1.2σ$, indicates that the deviation from the $Λ$CDM model is predominantly driven by these two samples from the DESI BAO measurements. To substantiate this conclusion, we utilized two cosmological model-independent methods to reconstruct the cosmic expansion history. Both reconstructions of the Hubble parameter $H(z)$ indicate that the evolving features of dark energy are determined by the combined LRG1 and LRG2 data. Therefore, different methods have reached the same conclusion, namely the importance of accurately measuring the BAO feature in LRG1 and LRG2 data.

astro-ph.CO↗

arXiv2024

Forecast of foreground cleaning strategies for AliCPT-1

We report the test results of several independent foreground-cleaning pipelines used in the Ali CMB Polarization Telescope experiment (AliCPT-1), a high-altitude CMB imager in the Northern hemisphere with thousands of detectors dedicated to the search for a primordial CMB polarization $B$-mode signature. Based on simulated data from 4 detector modules and a single season of observation, which we refer to as Data Challenge 1 (DC1), we employ different and independent pipelines to examine the robustness and effectiveness of the estimates on foreground parameters and the primordial $B$-mode detection. The foreground-cleaning strategies used in the pipelines include the parametric method of template fitting (TF) and the non-parametric methods of the constrained internal linear combination (cILC), the analytical blind separation (ABS), and the generalized least squares (GLS). We examine the impact of possible foreground residuals on the estimate of the CMB tensor-to-scalar ratio ($r$) for each pipeline by changing the contamination components in the simulated maps and varying the foreground models and sky patches for various tests. According to the DC1 data with the simulation input value $r_{\rm true}=0.023$, the foreground residual contamination levels in the TF/ABS/cILC/GLS pipelines are well within the corresponding statistical errors at the $2σ$ level. Furthermore, by utilizing the tension estimator, which helps identify significant residual foreground contamination in the detection of the primordial $B$-mode signal by quantifying the discrepancy between various $r$ measurements, we conclude that the presence of small foreground residuals does not lead to any significant inconsistency in the estimation of $r$.

astro-ph.CO↗

arXiv2024

Gravitational Radiation from Eccentric Binary Black Hole System in Dynamical Chern-Simons Gravity

Dynamical Chern-Simons (DCS) gravity, a typical parity-violating gravitational theory, modifies both the generation and propagation of gravitational waves from general relativity (GR). In this work, we derive the gravitational waveform radiated from a binary black hole system with eccentric orbits under the spin-aligned assumption in the DCS theory. Compared with GR, DCS modification enters the second-order post-Newtonian (2PN) approximation, affecting the spin-spin coupling and monopole-quadrupole coupling of binary motion. This modification produces an extra precession rate of periastron. This effect modulates the scalar and gravitational waveform through a quite low frequency. Additionally, the dissipation of conserved quantities results in the secular evolution of the semimajor axis and the eccentricity of binary orbits. Finally, the frequency-domain waveform is given in the post-circular scheme, requiring the initial eccentricity to be $\lesssim0.3$. This ready-to-use template will benefit the signal searches and improve the future constraint on DCS theory.

gr-qc↗

arXiv2024

Testing the consistency of early and late cosmological parameters with BAO and CMB data

The recent local measurements of the Hubble constant $H_0$, indicate a significant discrepancy of over 5$σ$ compared to the value inferred from \textit{Planck} observations of the cosmic microwave background (CMB). In this paper, we try to understand the origin of this tension by testing the consistency of early and late cosmological parameters in the same observed data. In practice, we simultaneously derive the early and late parameters using baryon acoustic oscillation (BAO) measurements, which provide both low and high-redshift information. To resolve parameter degeneracy, the complementary data from CMB observations are included in the analysis. By using the parameter $ω_m = Ω_mh^2$, we introduce ${\rm ratio}(ω_m)$, defined as the ratio of $ω_m$ which are constrained from high and low-redshift measurements respectively, to quantify the consistency between early and late parameters. We obtained a value of ${\rm ratio}(ω_m) = 1.0069\pm0.0070$, indicating there is no tension between early parameters and late parameters in the framework of $Λ$CDM model. As a result, the Hubble tension may arise from the differences of datasets or unknown systematic errors in the current data. In addition, we forecast the future BAO measurements of ${\rm ratio}(ω_m)$, using several galaxy redshift surveys and 21 cm intensity mapping surveys, and find that these measurements can significantly improve the precision of cosmological parameters.

astro-ph.CO↗

arXiv2024

AT2023lli: A Tidal Disruption Event with Prominent Optical Early Bump and Delayed Episodic X-ray Emission

High-cadence, multiwavelength observations have continuously revealed the diversity of tidal disruption events (TDEs), thus greatly advancing our knowledge and understanding of TDEs. In this work, we conducted an intensive optical-UV and X-ray follow-up campaign of TDE AT2023lli, and found a remarkable month-long bump in its UV/optical light curve nearly two months prior to maximum brightness. The bump represents the longest separation time from the main peak among known TDEs to date. The main UV/optical outburst declines as $t^{-4.10}$, making it one of the fastest decaying optically selected TDEs. Furthermore, we detected sporadic X-ray emission 30 days after the UV/optical peak, accompanied by a reduction in the period of inactivity. It is proposed that the UV/optical bump could be caused by the self-intersection of the stream debris, whereas the primary peak is generated by the reprocessed emission of the accretion process. In addition, our results suggest that episodic X-ray radiation during the initial phase of decline may be due to the patched obscurer surrounding the accretion disk, a phenomenon associated with the inhomogeneous reprocessing process. The double TDE scenario, in which two stars are disrupted in sequence, is also a possible explanation for producing the observed early bump and main peak. We anticipate that the multicolor light curves of TDEs, especially in the very early stages, and the underlying physics can be better understood in the near future with the assistance of dedicated surveys such as the deep high-cadence survey of the 2.5-meter Wide Field Survey Telescope (WFST).

astro-ph.HE↗

arXiv2024

Foreground removal with ILC methods for AliCPT-1

One of the main goals of most future CMB experiments is the precise measurement of CMB B-mode polarization, whose major obstacle is the Galactic foregrounds. In this paper, we evaluate the foreground cleaning performance of the variants of the ILC method on partial sky B-modes and analyze the main sources of biases on the BB power spectrum. Specially, we compare the NILC, the cILC (in three domains) and the cMILC methods for AliCPT-1 simulations. We find that the cILC methods implemented in harmonic space and needlet space are both competent to clean different models of foregrounds, which bias the tensor-to-scalar ratio about 0.008 at maximum, and constrain the tensor-to-scalar ratio to r<0.043 (95%CL) for the AliCPT-1 configuration. We also note that the deviation of the estimated noise bias from the actual one for ILC, dubbed the noise bias error (NBE) in this paper, might make significant effects on the power spectrum for a small footprint and low signal-to-noise ratio CMB experiment. We finally obtain its relation with respect to the noise residual which fits well with the simulated results.

astro-ph.CO↗

arXiv2024

Multi-parameter Tests of General Relativity Using Bayesian Parameter Estimation with Principal Component Analysis for LISA

In the near future, space-borne gravitational wave (GW) detector LISA can open the window of low-frequency band of GW and provide new tools to test gravity theories. In this work, we consider multi-parameter tests of GW generation and propagation where the deformation coefficients are varied simultaneously in parameter estimation and the principal component analysis (PCA) method are used to transform posterior samples into new bases for extracting the most informative components. The dominant components can be more sensitive to potential departures from general relativity (GR). We extend previous works by employing Bayesian parameter estimation and performing both tests with injections of GR and injections of subtle GR-violated signals. We also apply multi-parameter tests with PCA in the phenomenological test of GW propagation. This work complements previous works and further demonstrates the enhancement provided by the PCA method. Considering a supermassive black hole binary system as the GW source, we show that subtle departures will be more obvious in posteriors of PCA parameters. The departures less than $1σ$ in original parameters can yield significant departures in first 5 dominant PCA parameters.

gr-qc↗

arXiv2024

The Multi-parameter Test of Gravitational Wave Dispersion with Principal Component Analysis

In this work, we consider a conventional test of gravitational wave (GW) propagation which is based on the phenomenological parameterized dispersion relation to describe potential departures from General Relativity (GR) along the propagation of GWs. But different from tests conventionally performed previously, we vary multiple deformation coefficients simultaneously and employ the principal component analysis (PCA) method to remedy the strong degeneracy among deformation coefficients and obtain informative posteriors. The dominant PCA components can be better measured and constrained, thus are expected to be more sensitive to potential departures from the waveform model. Using this method we analyze 10 selected events and get the result that the combined posteriors of the dominant PCA parameters are consistent with GR within 3-$σ$ uncertainty. The standard deviation of the first dominant PCA parameter is 3 times smaller than that of the original dispersion parameter of the leading order. However, the multi-parameter test with PCA is more sensitive to not only potential deviations from GR but also systematic errors of waveform models. the difference in results obtained by using different waveform templates indicates that the demands of waveform accuracy are higher to perform the multi-parameter test with PCA.

gr-qc↗

arXiv2023

Kilonova-Targeting Lightcurve Classification for Wide Field Survey Telescope

With the enhancement of sensitivity of Gravitational Wave (GW) detectors and capabilities of large survey facilities, such as Vera Rubin Observatory Legacy Survey of Space and Time (LSST) and 2.5-m Wide Field Survey Telescope (WFST), we now have the potential to detect an increasing number of distant kilonova (KN). However, distinguishing KN from the plethora of detected transients in ongoing and future follow-up surveys presents a significant challenge. In this study, our objective is to establish an efficient classification mechanism tailored for the follow-up survey conducted by WFST, with a specific focus on identifying KN associated with GW. We employ a novel temporal convolutional neural network architecture, trained using simulated multi-band photometry lasting for 3 days by WFST, accompanied by contextual information, i.e. luminosity distance information by GW. By comparison of the choices of contextual information, we can reach 95\% precision, and 94\% recall for our best model. It also performs good validation on photometry data on AT2017gfo and AT2019npv. Furthermore, we investigate the ability of the model to distinguish KN in a GW follow-up survey. We conclude that there is over 80\% probability that we can capture true KN in selected 20 candidates among $\sim 250$ detected astrophysical transients that have passed real-bogus filter and cross-matching.

astro-ph.IM↗