arXiv subjects

Teng Liu

Publications and source records attributed to Teng Liu.

At least 73 records · Page 4Linked to original sources

arXiv2023

A new discovery space opened by eROSITA: Ionised AGN outflows from X-ray selected samples

In the context of an evolutionary model, the outflow phase of an Active Galactic Nuclei (AGN) occurs at the peak of its activity, once the central SMBH is massive enough to generate sufficient power to counterbalance the potential well of the host galaxy. This phase plays a vital role in galaxy evolution. We aim to apply various selection methods to isolate powerful AGNs in the feedback phase, trace and characterise their outflows, and explore the link between AGN luminosity and outflow properties. We applied a combination of methods to the eROSITA Final Equatorial Depth survey (eFEDS) catalogue and isolated ~1400 candidates at z>0.5 out of ~11750 AGNs (~12\%). We tested the robustness of our selection on the small subsample of 50 sources with available good quality SDSS spectra at 0.5 1\%. We find that the majority of the outflows have momentum flux ratios lower than 20 which rules out an energy-conserving nature. Our present work points to the unequivocal existence of a rather short AGN outflow phase, paving the way towards a new avenue to dissect AGN outflows in large samples within eROSITA and beyond.

astro-ph.GA↗

arXiv2023

Human-like Energy Management Based on Deep Reinforcement Learning and Historical Driving Experiences

Development of hybrid electric vehicles depends on an advanced and efficient energy management strategy (EMS). With online and real-time requirements in mind, this article presents a human-like energy management framework for hybrid electric vehicles according to deep reinforcement learning methods and collected historical driving data. The hybrid powertrain studied has a series-parallel topology, and its control-oriented modeling is founded first. Then, the distinctive deep reinforcement learning (DRL) algorithm, named deep deterministic policy gradient (DDPG), is introduced. To enhance the derived power split controls in the DRL framework, the global optimal control trajectories obtained from dynamic programming (DP) are regarded as expert knowledge to train the DDPG model. This operation guarantees the optimality of the proposed control architecture. Moreover, the collected historical driving data based on experienced drivers are employed to replace the DP-based controls, and thus construct the human-like EMSs. Finally, different categories of experiments are executed to estimate the optimality and adaptability of the proposed human-like EMS. Improvements in fuel economy and convergence rate indicate the effectiveness of the constructed control structure.

eess.SY↗

arXiv2023

Decision-making for Autonomous Vehicles on Highway: Deep Reinforcement Learning with Continuous Action Horizon

Decision-making strategy for autonomous vehicles de-scribes a sequence of driving maneuvers to achieve a certain navigational mission. This paper utilizes the deep reinforcement learning (DRL) method to address the continuous-horizon decision-making problem on the highway. First, the vehicle kinematics and driving scenario on the freeway are introduced. The running objective of the ego automated vehicle is to execute an efficient and smooth policy without collision. Then, the particular algorithm named proximal policy optimization (PPO)-enhanced DRL is illustrated. To overcome the challenges in tardy training efficiency and sample inefficiency, this applied algorithm could realize high learning efficiency and excellent control performance. Finally, the PPO-DRL-based decision-making strategy is estimated from multiple perspectives, including the optimality, learning efficiency, and adaptability. Its potential for online application is discussed by applying it to similar driving scenarios.

cs.AI↗

arXiv2023

Experimental demonstration of enhanced violations of Leggett-Garg inequalities in a $\mathcal{PT}$-symmetric trapped-ion qubit

The Leggett-Garg inequality (LGI) places a bound for the distinction between quantum systems and classical systems. Despite that the tests of temporal quantum correlations on LGIs have been studied in Hermitian realm, there are still unknowns for LGIs in non-Hermitian conditions due to the interplay between dissipation and coherence. For example, a theoretical hypothesis to be experimentally validated, suggests that within non-Hermitian systems, the non-unitary evolution of the system dynamics allows the boundaries of the LGIs to surpass the constraints imposed by traditional quantum mechanics. Here, we demonstrate the experimental violation of LGIs in a parity-time ($\mathcal{PT}$)-symmetric trapped-ion qubit system by measuring the temporal correlation of the evolving states at different times. We find that the upper bounds of the three-time parameter $K_3$ and the four-time parameter $K_4$ show enhanced violations with the increasing dissipation, and can reach the upper limit by infinitely approaching exceptional point. We also observe the distinct behavior of the lower bounds for $K_3$ and $K_4$. While the lower bound for $K_3$ remains constant, the case for $K_4$ shows an upward trend with increasing dissipation. These results reveal a pronounced dependence of the system's temporal quantum correlations on its dissipation to the environment. This opens up a potential pathway for harnessing dissipation to modulate quantum correlations and entanglement.

quant-ph↗

arXiv2023

MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals

Brain signals are important quantitative data for understanding physiological activities and diseases of human brain. Most existing studies pay attention to supervised learning methods, which, however, require high-cost clinical labels. In addition, the huge difference in the clinical patterns of brain signals measured by invasive (e.g., SEEG) and non-invasive (e.g., EEG) methods leads to the lack of a unified method. To handle the above issues, we propose to study the self-supervised learning (SSL) framework for brain signals that can be applied to pre-train either SEEG or EEG data. Intuitively, brain signals, generated by the firing of neurons, are transmitted among different connecting structures in human brain. Inspired by this, we propose MBrain to learn implicit spatial and temporal correlations between different channels (i.e., contacts of the electrode, corresponding to different brain areas) as the cornerstone for uniformly modeling different types of brain signals. Specifically, we represent the spatial correlation by a graph structure, which is built with proposed multi-channel CPC. We theoretically prove that optimizing the goal of multi-channel CPC can lead to a better predictive representation and apply the instantaneou-time-shift prediction task based on it. Then we capture the temporal correlation by designing the delayed-time-shift prediction task. Finally, replace-discriminative-learning task is proposed to preserve the characteristics of each channel. Extensive experiments of seizure detection on both EEG and SEEG large-scale real-world datasets demonstrate that our model outperforms several state-of-the-art time series SSL and unsupervised models, and has the ability to be deployed to clinical practice.

eess.SP↗

arXiv2023

The eROSITA Final Equatorial Depth Survey (eFEDS): Complex absorption and soft excesses in hard X-ray--selected active galactic nuclei

Context. The soft excess, a surplus of X-ray photons above 2 keV with respect to a power law, is a feature of debated physical origin found in the X-ray spectra of many type-1 active galactic nuclei (AGN). The eROSITA instrument aboard the Spectrum-Roentgen-Gamma (SRG) mission will provide an all-sky census of AGN suitable for spectral analysis. Aims. The primary goal of this work is to test a variety of models for the soft X-ray emission of AGN (thermal emission, non-thermal emission, ionised absorption, or neutral partial covering absorption) to help identify the physical origin of the soft X-ray spectral complexity. Differences between these models are examined in the context of this sample to understand the physical properties. Methods. We used Bayesian X-ray analysis to fit a sample of 200 AGN from the eFEDS hard X-ray--selected sample with a variety of phenomenological and physically motivated models. Model selection was performed using the Bayes factor to compare the applicability of each model. Results. We find that 29 sources have evidence for a soft excess at a confidence level >97.5%, all of which are better modelled by an additional soft power law than by thermal blackbody emission. We find 23 of these sources prefer a warm corona model, while six sources prefer relativistic blurred reflection. Additionally many sources show evidence for complex absorption, with 29 preferring a warm absorber and 25 a partial covering absorber. Sources with a soft excess show a significantly higher Eddington ratio than those with warm absorbers. We discuss the implication of these results for the physical processes in the central regions of AGN. Conclusions. Spectral fitting with Bayesian statistics is ideal for the identification of complex absorption and soft excesses in the X-ray spectra of AGN and can allow one to distinguish between different physical interpretations. (Abridged)

astro-ph.HE↗

arXiv2023

Implementation of electromagnetic analogy to gravity mediated entanglement

Recently, experiments aimed at measuring gravity mediated entanglement (GME) using quantum information techniques have been proposed, based on the assumption that if two systems get entangled through local interactions with gravitational field, then this field must be quantum. While there is a debate about what could be drawn from GME, quantum simulation might provide some clarification. Here, we present electromagnetic analogy of GME using magnetic-field mediated interaction between the electron and nucleus in a single atom. Our work successfully implements the general procedures of GME experiments and confirms that the mediating field does not support the mean-field description. It also clarifies that, without considering the light-crossing time, the GME experiment would not distinguish a quantum-field-theory description from a quantum-controlled classical field one. Furthermore, this work provides a novel method to construct two-qubit systems in a single atom, and providing the first quantum simulation of GME using material qubits. It helps to conceive the future GME experiments on the scale of light-crossing time.

quant-ph↗

arXiv2023

The cosmic web of X-ray active galactic nuclei seen through the eROSITA Final Equatorial Depth Survey (eFEDS)

Which galaxies in the general population turn into active galactic nuclei (AGNs) is a keystone of galaxy formation and evolution. Thanks to SRG/eROSITA's contiguous 140 square degree pilot survey field, we constructed a large, complete, and unbiased soft X-ray flux-limited ($F_X>6.5\times 10^{-15}$ erg s$^{-1}$ cm$^{-2}$) AGN sample at low redshift, $0.05<z<0.55$. Two summary statistics, the clustering using spectra from SDSS-V and galaxy-galaxy lensing with imaging from HSC, are measured and interpreted with halo occupation distribution and abundance matching models. Both models successfully account for the observations. We obtain an exceptionally complete view of the AGN halo occupation distribution. The population of AGNs is broadly distributed among halos with a mean mass of $3.9 _{- 2.4 }^{+ 2.0 }\times10^{12}M_\odot$. This corresponds to a large-scale halo bias of $b(z=0.34)= 0.99 ^{+0.08}_{-0.10}$. The central occupation has a large transition parameter, $σ_{\log_{10}(M)}=1.28\pm0.2$. The satellite occupation distribution is characterized by a shallow slope, $α_{\rm sat}=0.73\pm0.38$. We find that AGNs in satellites are rare, with $f_{\rm sat}<20\%$. Most soft X-ray-selected AGNs are hosted by central galaxies in their dark matter halo. A weak correlation between soft X-ray luminosity and large-scale halo bias is confirmed (3.3$σ$). We discuss the implications of environmental-dependent AGN triggering. This study paves the way toward fully charting, in the coming decade, the coevolution of X-ray AGNs, their host galaxies, and dark matter halos by combining eROSITA with SDSS-V, 4MOST, DESI, LSST, and \textit{Euclid} data.

astro-ph.GA↗

arXiv2023

The eROSITA Final Equatorial-Depth Survey (eFEDS): Host-galaxy Demographics of X-ray AGNs with Subaru Hyper Suprime-Cam

We investigate the physical properties, such as star-forming activity, disk vs. bulge nature, galaxy size, and obscuration of 3796 X-ray selected AGNs at $0.2<z<0.8$ in the eFEDS field. Using Subaru Hyper Suprime-Cam imaging data in the $grizy$ bands for SRG/eROSITA-detected AGNs, we measure the structural parameters for AGN host galaxies by performing a 2D AGN-host image decomposition. We then conduct spectral energy distribution fitting to derive stellar mass and rest-frame colors for AGN hosts. We find that (1) AGNs can contribute significantly to the total optical light down to ${\rm log}\,L_{\rm X}\sim 42.5\ \rm erg\,s^{-1}$, thus ignoring the AGN component can significantly bias the structural measurements; (2) AGN hosts are predominately star-forming galaxies at ${\rm log}\,\mathcal{M}_\star \lesssim 11.3\ M_\odot$; (3) the bulk of AGNs (64%) reside in galaxies with significant stellar disks, while their host galaxies become increasingly bulge dominated and quiescent at ${\rm log}\,\mathcal{M}_\star \gtrsim 11.0\ M_\odot$; (4) the size-stellar mass relation of AGN hosts tends to lie between that of inactive star-forming and quiescent galaxies, suggesting that the physical mechanism responsible for building the central stellar density also efficiently fuel the black hole growth; (5) the hosts of X-ray unobscured AGNs are biased towards face-on systems and the average $E(B-V)/N_{\rm H}$ is similar to the galactic dust-to-gas ratio, suggesting that some of the obscuration of the nuclei could come from galaxy-scale gas and dust, which may partly account for (up to 30%) the deficiency of star-forming disks as host galaxies for the most massive AGNs. These results are consistent with a scenario in which the black hole and galaxy grow in mass while transform in structure and star-forming activity, as desired to establish the local scaling relations.

astro-ph.GA↗

arXiv2023

eROSITA Final Equatorial-Depth Survey (eFEDS): eFEDS X-ray view of WERGS Radio Galaxies selected by the Subaru/HSC and VLA/FIRST survey

We construct the eROSITA X-ray catalog of radio galaxies discovered by the WERGS survey that is made by the cross-matching of the wide-area Subaru/HSC optical survey and VLA/FIRST 1.4 GHz radio survey. We find 393 eROSITA detected radio galaxies in the 0.5--2 keV band in the eFEDS field covering 140~deg$^2$. Thanks to the wide and medium depth eFEDS X-ray survey, the sample contains the rare and most X-ray luminous radio galaxies above the knee of the X-ray luminosity function, spanning 44 22$. Those obscured and radio AGN reside in $0.4<z<3.2$, indicating that they are obscured counterparts of the radio-loud quasar, which are missed in the previous optical quasar surveys. By combining radio and X-ray luminosities, the jet production efficiency $η_\mathrm{jet}$ is investigated, and we find 14 sources with extremely high jet production efficiency at $η_\mathrm{jet}\approx1$. This high $η_\mathrm{jet}$ value might be a result of 1) the decreased radiation efficiency of $η_\mathrm{rad}<0.1$ due to the low accretion rate for those sources and/or 2) the boosting due to the decline of $L_\mathrm{bol}$ by a factor of 10--100 by keeping $P_\mathrm{jet}$ constant in the previous Myr, indicating the experience of the AGN feedback. Finally, inferring the BH masses from the stellar-mass, we find that X-ray luminous sources show the excess of the radio emission with respect to the value estimated from the fundamental plane. Such radio emission excess cannot be explained by the Doppler booming alone, and therefore disk-jet connection of X-ray luminous eFEDS-WERGS is fundamentally different from the conventional fundamental plane which mainly covers low accretion regime.

astro-ph.HE↗

arXiv2022

Decision-making at Unsignalized Intersection for Autonomous Vehicles: Left-turn Maneuver with Deep Reinforcement Learning

Decision-making module enables autonomous vehicles to reach appropriate maneuvers in the complex urban environments, especially the intersection situations. This work proposes a deep reinforcement learning (DRL) based left-turn decision-making framework at unsignalized intersection for autonomous vehicles. The objective of the studied automated vehicle is to make an efficient and safe left-turn maneuver at a four-way unsignalized intersection. The exploited DRL methods include deep Q-learning (DQL) and double DQL. Simulation results indicate that the presented decision-making strategy could efficaciously reduce the collision rate and improve transport efficiency. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time.

cs.AI↗

arXiv2022

Data-Driven Transferred Energy Management Strategy for Hybrid Electric Vehicles via Deep Reinforcement Learning

Real-time applications of energy management strategies (EMSs) in hybrid electric vehicles (HEVs) are the harshest requirements for researchers and engineers. Inspired by the excellent problem-solving capabilities of deep reinforcement learning (DRL), this paper proposes a real-time EMS via incorporating the DRL method and transfer learning (TL). The related EMSs are derived from and evaluated on the real-world collected driving cycle dataset from Transportation Secure Data Center (TSDC). The concrete DRL algorithm is proximal policy optimization (PPO) belonging to the policy gradient (PG) techniques. For specification, many source driving cycles are utilized for training the parameters of deep network based on PPO. The learned parameters are transformed into the target driving cycles under the TL framework. The EMSs related to the target driving cycles are estimated and compared in different training conditions. Simulation results indicate that the presented transfer DRL-based EMS could effectively reduce time consumption and guarantee control performance.

eess.SP↗

arXiv2022

X-ray emission from a rapidly accreting narrow-line Seyfert 1 galaxy at z=6.56

This study aims at identifying luminous quasars at $z>5.7$ among X-ray-selected sources in the eROSITA Final Equatorial-Depth Survey (eFEDS) in order to place a lower limit on black hole accretion well into the epoch of re-ionisation. We confirm the low significance detection with eROSITA of a previously known, optically faint $z=6.56$ quasar from the Subaru High-z Exploration of Low-luminosity Quasars (SHELLQs) survey. We obtained a pointed follow-up observation of the source with the Chandra X-ray telescope in order to confirm the eROSITA detection. Using new near-infrared spectroscopy, we derived the physical properties of the super-massive black hole. Finally, we used this detection to infer a lower limit on the black hole accretion density rate at $z>6$. The Chandra observation confirms the eFEDS source as the most distant blind X-ray detection to date. The derived X-ray luminosity is high with respect to the rest-frame optical emission of the quasar. With a narrow MgII line, low derived black hole mass, and high Eddington ratio, as well as its steep photon index, the source shows properties that are similar to local narrow-line Seyfert 1 galaxies, which are thought to be powered by young super-massive black holes. In combination with a previous high-redshift quasar detection in the field, we show that quasars with $L_{2-10 \, \mathrm{keV}} >10^{45} \, \mathrm{erg \, s^{-1}}$ dominate accretion onto super-massive black holes at $z\sim 6$.

astro-ph.HE↗

arXiv2022

Teleconnections among Tipping Elements in the Earth System

Tipping elements of the Earth system may shift abruptly and irreversibly from one state to another at tipping points, resulting in a growing threat to our society. Yet, it is not fully clear how to assess and quantify the influence of a tipping element and how to explore the teleconnections between different tipping elements. To fill this knowledge gap, we propose a climate network approach to quantitatively analyze the global impacts of a prominent tipping element, the Amazon Rainforest Area (ARA). We find that regions, such as, the Tibetan Plateau (TP) and West Antarctic ice sheet, are characterized by higher network weighted links and exhibit strong correlations with the ARA. We then identify a teleconnection propagation path between the ARA and the TP. This path is robust under climate change as simulated by various climate models of CMIP5 and CMIP6. In addition, we detect early warning signals for critical transition in the snow cover extent on the Tibetan Plateau by applying critical slowing down indicators, lag-1 autocorrelation and detrended fluctuation analysis. We find that the snow cover of the TP has been losing stability since 2008, revealing that the TP is operating like a tipping element and approaching a potential tipping point. We further uncover that various climate extremes between the ARA and the TP are significantly synchronized under climate change. Our framework provides new insights into how tipping elements are linked to each other and into the potential predictability of cascading tipping dynamics.

physics.soc-ph↗

arXiv2022

The eROSITA Final Equatorial Depth Survey (eFEDS): X-ray emission around star-forming and quiescent galaxies at $0.05<z<0.3$

We aim at characterizing the hot phase of the Circum-Galactic Medium in a large sample of galaxies. We stack X-ray events from the SRG/eROSITA eFEDS survey around central galaxies in the GAMA 9hr field to construct radially projected soft X-ray luminosity profiles as a function of their stellar mass and specific star formation rate. We consider samples of quiescent (star-forming) galaxies in the stellar mass range $2\times 10^{10}$ -- $10^{12}$ M$_\odot$ ($3\times 10^9$ -- $6\times10^{11}$ M$_\odot$). For quiescent galaxies, the X-ray profiles are clearly extended throughout the available mass range; however, the measured profile is likely biased high due to projection effects, as these galaxies tend to live in dense and hot environments. For the most massive star forming samples ($\geq10^{11}$ M$_\odot$), there is a hint of detection of extended emission. For star-forming galaxies with $< 10^{11}$ M$_\odot$ the X-ray stacked profiles are compatible with unresolved sources and consistent with the expected emission from faint Active Galactic Nuclei and X-ray binaries. We measure for the first time the mean relation between average X-ray luminosity and stellar mass separately for quiescent and star-forming galaxies. High-mass ($\geq 10^{11}$ M$_\odot$) star-forming or quiescent galaxies follow the expected scaling of virialized hot haloes, while lower mass star-forming galaxies show a less prominent luminosity and a weaker dependence on stellar mass, consistent with empirical models of the weak AGN population. When comparing our results with state-of-the art numerical simulations, we find an overall consistency on large ($>80$ kpc) scales at masses $\geq 10^{11}$ M$_\odot$, but disagreement on the small scales, where brighter than observed compact cores are predicted. Simulations also do not predict the clear differentiation that we observe between quiescent and star-forming galaxies.

astro-ph.GA↗

arXiv2022

The eROSITA extragalactic CalPV serendipitous catalog

The eROSITA X-ray telescope on board the Spectrum-Roentgen-Gamma (SRG) observatory performed calibration and performance verification (CalPV) observations between September 2019 and December 2019, ahead of the planned four-year all-sky surveys. Most of them were deep, pointing-mode observations. We present here the X-ray catalog detected from the set of extra-galactic CalPV observations released to the public by the German eROSITA consortium, and the multiband counterparts of these X-ray sources. We developed a source detection method optimized for point-like X-ray sources by including extended X-ray emission in the background measurement. The multiband counterparts were identified using a Bayesian method from the CatWISE catalog. Combining 11 CalPV fields, we present a catalog containing 9515 X-ray sources, whose X-ray fluxes were measured through spectral fitting. CatWISE counterparts are presented for 77% of the sources. Significant variabilities are found in 99 of the sources, which are also presented with this paper. Most of these fields show similar number counts of point sources as typical extragalactic fields, and a few harbor particular stellar populations.

astro-ph.HE↗

arXiv2022

The eROSITA Final Equatorial-Depth Survey (eFEDS): X-ray Properties and Scaling Relations of Galaxy Clusters and Groups

We investigate the scaling relations between X-ray observables of the clusters detected in the eFEDS field using Spectrum-Roentgen-Gamma/eROSITA observations taking into account the selection effects and the distributions of observables with cosmic time. We extract X-ray observables (Lx, Lbol, T, Mgas, Yx) within R500 for the sample of 542 clusters in the eFEDS field. By applying detection and extent likelihoods, we construct a subsample of 265 clusters with a contamination level of <10% (including AGNs and spurious fluctuations) to be utilized in the scaling relation analysis. The selection function based on the state-of-the-art simulations of the eROSITA sky is fully accounted for in our work. We provide the X-ray observables in the core-included 3sigma confidence level however, our results are in good agreement with the simulations including non-gravitational physics and the recent results that take into account selection effects. Strong deviations we find from the self-similar scenario indicate that the non-gravitational effects play an important role in shaping the observed physical state of clusters. This work extends the scaling relations to low mass, low luminosity galaxy cluster and group regime using eFEDS observations, demonstrating eROSITA's ability to measure ICM emission out to R500 with survey-depth exposures and constrain the scaling relations in a wide mass-luminosity-redshift range.

astro-ph.CO↗

arXiv2022

Protection of quantum evolutions under parity-time symmetric non-Hermitian Hamiltonians by dynamical decoupling

Parity-time (PT) symmetric non-Hermitian Hamiltonians bring about many novel features and interesting applications such as quantum gates faster than those in Hermitian systems, and topological state transfer. The performance of evolutions under $\mathcal{PT}$-symmetric Hamiltonians is degraded by the inevitable noise and errors due to system-environment interaction and experimental imperfections. In contrast to Hermitian Hamiltonians, the fluctuations in dissipative beams that are utilized to generate non-Hermitian contributions in the PT-symmetric Hamiltonians cause additional errors. Here we achieve the protection of PT-symmetric Hamiltonians against noise acting along the qubit's quantization axis by combining quantum evolutions with dynamical decoupling sequences. We demonstrate the performance of our method by numerical simulations. Realistic noise sources and parameters are chosen including: constant detuning error, time-varying detuning noise and dissipative-beam noise. The fidelities of the protected evolutions are well above the unprotected ones under all the above situations. Our work paves the way for further studies and applications of non-Hermitian $\mathcal{PT}$-symmetric physics in noisy quantum systems.

quant-ph↗