Gravitational wave (GW) detection in space probes GW spectrum that is inaccessible from the Earth. In addition to LISA project led by European Space Agency, and the DECIGO detector proposed by the Japan Aerospace Exploration Agency, two Chinese space
-based GW observatories -- TianQin and Taiji -- are planned to be launched in the 2030s. TianQin has a unique concept in its design with a geocentric orbit. Taijis design is similar to LISA, but is more ambitious with longer arm distance. Both facilities are complementary to LISA, considering that TianQin is sensitive to higher frequencies and Taiji probes similar frequencies but with higher sensitivity. In this Perspective we explain the concepts for both facilities and introduce the development milestones of TianQin and Taiji projects in testing extraordinary technologies to pave the way for future space-based GW detections. Considering that LISA, TianQin and Taiji have similar scientific goals, all are scheduled to be launched around the 2030s and will operate concurrently, we discuss possible collaborations among them to improve GW source localization and characterization.
Quantum spin squeezing is an important resource for quantum information processing, but its squeezing degree is not easy to preserve in an open system with decoherence. Here, we propose a scheme to implement single-photon-triggered spin squeezing wit
h decoherence reduction in an open system. In our system, a Dicke model (DM) is introduced into the quadratic optomechanics, which can be equivalent to an effective DM manipulated by the photon number. Besides, the phonon mode of the optomechanical system is coupled to a squeezed vacuum reservoir with a phase matching, resulting in that the thermal noise caused by the environment can be suppressed completely. We show that squeezing of the phonon mode triggered by a single photon can be transferred to the spin ensemble totally, and pairwise entanglement of the spin ensemble can be realized if and only if there is spin squeezing. Importantly, when considering the impact of the environment, our system can obtain a better squeezing degree than the optimal squeezing that can be achieved in the traditional DM. Meanwhile, the spin squeezing generated in our system is immune to the thermal noise. This work offers an effective way to generate spin squeezing with a single photon and to reduce decoherence in an open system, which will have promising applications in quantum information processing.
Clustering has become a core technology in machine learning, largely due to its application in the field of unsupervised learning, clustering, classification, and density estimation. A frequentist approach exists to hand clustering based on mixture m
odel which is known as the EM algorithm where the parameters of the mixture model are usually estimated into a maximum likelihood estimation framework. Bayesian approach for finite and infinite Gaussian mixture model generates point estimates for all variables as well as associated uncertainty in the form of the whole estimates posterior distribution. The sole aim of this survey is to give a self-contained introduction to concepts and mathematical tools in Bayesian inference for finite and infinite Gaussian mixture model in order to seamlessly introduce their applications in subsequent sections. However, we clearly realize our inability to cover all the useful and interesting results concerning this field and given the paucity of scope to present this discussion, e.g., the separated analysis of the generation of Dirichlet samples by stick-breaking and Polyas Urn approaches. We refer the reader to literature in the field of the Dirichlet process mixture model for a much detailed introduction to the related fields. Some excellent examples include (Frigyik et al., 2010; Murphy, 2012; Gelman et al., 2014; Hoff, 2009). This survey is primarily a summary of purpose, significance of important background and techniques for Gaussian mixture model, e.g., Dirichlet prior, Chinese restaurant process, and most importantly the origin and complexity of the methods which shed light on their modern applications. The mathematical prerequisite is a first course in probability. Other than this modest background, the development is self-contained, with rigorous proofs provided throughout.
The stellar mass-to-light ratio gradient in SDSS $r-$band $ abla (M_*/L_r)$ of a galaxy depends on its mass assembly history, which is imprinted in its morphology and gradients of age, metallicity, and stellar initial mass function (IMF). Taking a Ma
NGA sample of 2051 galaxies with stellar masses ranging from $10^9$ to $10^{12}M_odot$ released in SDSS DR15, we focus on face-on galaxies, without merger and bar signatures, and investigate the dependence of the 2D $ abla (M_*/L_r)$ on other galaxy properties, including $M_*/L_r$-colour relationships by assuming a fixed Salpeter IMF as the mass normalization reference. The median gradient is $ abla M_*/L_rsim -0.1$ (i.e., the $M_*/L_r$ is larger at the centre) for massive galaxies, becomes flat around $M_*sim 10^{10} M_{odot}$ and change sign to $ abla M_*/L_rsim 0.1$ at the lowest masses. The $M_*/L_r$ inside a half light radius increases with increasing galaxy stellar mass; in each mass bin, early-type galaxies have the highest value, while pure-disk late-type galaxies have the smallest. Correlation analyses suggest that the mass-weighted stellar age is the dominant parameter influencing the $M_*/L_r$ profile, since a luminosity-weighted age is easily affected by star formation when the specific star formation rate (sSFR) inside the half light radius is higher than $10^{-3} {rm Gyr}^{-1}$. With increased sSFR gradient, one can obtain a steeper negative $ abla (M_*/L_r)$. The scatter in the slopes of $M_*/L$-colour relations increases with increasing sSFR, for example, the slope for post-starburst galaxies can be flattened to $0.45$ from the global value $0.87$ in the $M_*/L$ vs. $g-r$ diagram. Hence converting galaxy colours to $M_*/L$ should be done carefully, especially for those galaxies with young luminosity-weighted stellar ages, which can have quite different star formation histories.
This survey is meant to provide an introduction to the fundamental theorem of linear algebra and the theories behind them. Our goal is to give a rigorous introduction to the readers with prior exposure to linear algebra. Specifically, we provide some
details and proofs of some results from (Strang, 1993). We then describe the fundamental theorem of linear algebra from different views and find the properties and relationships behind the views. The fundamental theorem of linear algebra is essential in many fields, such as electrical engineering, computer science, machine learning, and deep learning. This survey is primarily a summary of purpose, significance of important theories behind it. The sole aim of this survey is to give a self-contained introduction to concepts and mathematical tools in theory behind the fundamental theorem of linear algebra and rigorous analysis in order to seamlessly introduce its properties in four subspaces in subsequent sections. However, we clearly realize our inability to cover all the useful and interesting results and given the paucity of scope to present this discussion, e.g., the separated analysis of the (orthogonal) projection matrices. We refer the reader to literature in the field of linear algebra for a more detailed introduction to the related fields. Some excellent examples include (Rose, 1982; Strang, 2009; Trefethen and Bau III, 1997; Strang, 2019, 2021).
Observationally, there are a small fraction GRBs prompt emission observed by Fermi/GBM that are composed of two pulses. Occasionally, the cosmological distance of GRB may be lensed when a high mass astrophysical object reside in path between GRB sour
ce and observer. In this paper, we are lucky to find out GRB 200716C with two-pulse emission which duration is a few seconds. We present a Bayesian analysis identifying gravitational lensing in both temporal and spectral properties, and calculate the time decay ($Delta tsim 1.92$ s) and magnification ($gammasim 1.5$) between those two pulses based on the temporal fits. One can roughly estimate the lens mass is about $2.38times 10^{5}~M_{odot}$ in the rest frame. If the first pulse of this GRB near triggered time is indeed gravitationally echoed by a second pulse, GRB 200716C may be a short GRB candidate with extended emission.
In this paper, we investigate the effect of different optical field initial states on the performance of Tavis-Cummings(T-C) quantum battery. In solving the dynamical evolution of the system, we found a fast way to solve the Bethe ansatz equation. We
find that the stored energy and the average charging power of the T-C quantum battery are closely related to the probability distribution of the optical field initial state in the number states. We define a quantity called the number state stored energy. With this prescribed quantity, we only need to know the probability distribution of the optical field initial state in the number states to obtain the stored energy and the average charging power of the T-C quantum battery at any moment. We propose an equal probability and equal expected value allocation method by which we can obtain two inequalities, and the two inequalities can be reduced to Jensens inequalities. By this method, we found the optimal initial state of the optical field. We found that the maximum stored energy and the maximum average charging power of the T-C quantum battery are proportional to the initial average photon number. The quantum battery can be fully charged when the initial average photon number is large enough. We found two novel phenomena, which can be described by two empirical inequalities. These two novel phenomena reflect the hypersensitivity of the stored energy of the T-C quantum battery to the number-state cavity field.
We consider moderately interacting particle systems with singular interaction kernel and environmental noise. It is shown that the mollified empirical measures converge in strong norms to the unique (local) solutions of nonlinear Fokker-Planck equati
ons. The approach works for the Biot-Savart and Poisson kernels.
We consider the problem of regularization by noise for the three dimensional magnetohydrodynamical (3D MHD) equations. It is shown that, in a suitable scaling limit, multiplicative noise of transport type gives rise to bounds on the vorticity fields
of the fluid velocity and magnetic fields. As a result, if the noise intensity is big enough, then the stochastic 3D MHD equations admit a pathwise unique global solution for large initial data, with high probability.
Homotopy model is an excellent tool exploited by diverse research works in the field of machine learning. However, its flexibility is limited due to lack of adaptiveness, i.e., manual fixing or tuning the appropriate homotopy coefficients. To address
the problem above, we propose a novel adaptive homotopy framework (AH) in which the Maclaurin duality is employed, such that the homotopy parameters can be adaptively obtained. Accordingly, the proposed AH can be widely utilized to enhance the homotopy-based algorithm. In particular, in this paper, we apply AH to contrastive learning (AHCL) such that it can be effectively transferred from weak-supervised learning (given label priori) to unsupervised learning, where soft labels of contrastive learning are directly and adaptively learned. Accordingly, AHCL has the adaptive ability to extract deep features without any sort of prior information. Consequently, the affinity matrix formulated by the related adaptive labels can be constructed as the deep Laplacian graph that incorporates the topology of deep representations for the inputs. Eventually, extensive experiments on benchmark datasets validate the superiority of our method.
