Stellar halos of galaxies retain crucial clues to their mass assembly history. It is in these galactic components that the remains of cannibalised galactic building blocks are deposited. For the case of the Milky Way, the opportunity to analyse the stellar halo's structure on a star-by-star basis in a multi-faceted approach provides a basis from which to infer its past and assembly history in unrivalled detail. Moreover, the insights that can be gained about the formation of the Galaxy not only help constrain the evolution of our Milky Way, but may also help place constraints on the formation of other disc galaxies in the Universe. This paper includes a summary of work undertaken during a PhD thesis aiming to make progress toward answering the most fundamental question in the field of Galactic archaeology: "How did the Milky Way form?" Through the effort to answer this question, we summarise new insights into aspects of the history of assembly and evolution of our Galaxy and measurements of the structure of various of its Galactic components.
We develop and apply a new framework for reconstructing the ionization history during the epoch of recombination with combinations of cosmic microwave background (CMB), baryon acoustic oscillation (BAO) and supernova data. We find a wide range of ionization histories that are consistent with current CMB data, and also that cosmological parameter constraints are significantly weakened once freedom in recombination is introduced. BAO data partially break the degeneracy between cosmological parameters and the recombination model, and are therefore important in these reconstructions. The 95% confidence upper limits on H0 are 80.1 (70.7) km/s/Mpc given CMB (CMB+BAO) data, assuming no other changes are made to the standard cosmological model. Including Cepheid-calibrated supernova data in the analysis drives a preference for non-standard recombination histories with visibility functions that peak early and exhibit appreciable skewness. Forthcoming measurements from SPT-3G will reduce the uncertainties in our reconstructions by about a factor of two.
There are about 6000 stars, that can be seen with the naked eye and have been observed for centuries for various purposes. More modern investigations using advanced telescopes show that our Milky Way, a quite common galaxy, consists of about 100 -- 400 billion stars. And, it is estimated that there are between 200 billion to 2 trillion galaxies in the observable universe -- all of them consist mostly of stars, and sending observable signals which also represents nothing more than a superposition of the light of individual stars. So we can conclude that the most common observable objects in the Universe are $\textit{stars}$. In this chapter, we focus on the long history of the observation of stars (compared to studies in other fields of science) to find out more about the nature of these objects.
As the core technique of online recruitment platforms, person-job fit can improve hiring efficiency by accurately matching job positions with qualified candidates. However, existing studies mainly focus on the recommendation scenario, while neglecting another important channel for linking positions with job seekers, i.e. search. Intuitively, search history contains rich user behavior in job seeking, reflecting important evidence for job intention of users. In this paper, we present a novel Search History enhanced Person-Job Fit model, named as SHPJF. To utilize both text content from jobs/resumes and search histories from users, we propose two components with different purposes. For text matching component, we design a BERT-based text encoder for capturing the semantic interaction between resumes and job descriptions. For intention modeling component, we design two kinds of intention modeling approaches based on the Transformer architecture, either based on the click sequence or query text sequence. To capture underlying job intentions, we further propose an intention clustering technique to identify and summarize the major intentions from search logs. Extensive experiments on a large real-world recruitment dataset have demonstrated the effectiveness of our approach.
Environments in Reinforcement Learning are usually only partially observable. To address this problem, a possible solution is to provide the agent with information about the past. However, providing complete observations of numerous steps can be excessive. Inspired by human memory, we propose to represent history with only important changes in the environment and, in our approach, to obtain automatically this representation using self-supervision. Our method (TempAl) aligns temporally-close frames, revealing a general, slowly varying state of the environment. This procedure is based on contrastive loss, which pulls embeddings of nearby observations to each other while pushing away other samples from the batch. It can be interpreted as a metric that captures the temporal relations of observations. We propose to combine both common instantaneous and our history representation and we evaluate TempAl on all available Atari games from the Arcade Learning Environment. TempAl surpasses the instantaneous-only baseline in 35 environments out of 49. The source code of the method and of all the experiments is available at https://github.com/htdt/tempal.
Fabian Paischer, Thomas Adler, Vihang Patil
et al.
In a partially observable Markov decision process (POMDP), an agent typically uses a representation of the past to approximate the underlying MDP. We propose to utilize a frozen Pretrained Language Transformer (PLT) for history representation and compression to improve sample efficiency. To avoid training of the Transformer, we introduce FrozenHopfield, which automatically associates observations with pretrained token embeddings. To form these associations, a modern Hopfield network stores these token embeddings, which are retrieved by queries that are obtained by a random but fixed projection of observations. Our new method, HELM, enables actor-critic network architectures that contain a pretrained language Transformer for history representation as a memory module. Since a representation of the past need not be learned, HELM is much more sample efficient than competitors. On Minigrid and Procgen environments HELM achieves new state-of-the-art results. Our code is available at https://github.com/ml-jku/helm.
Triangle centrality is introduced for finding important vertices in a graph based on the concentration of triangles surrounding each vertex. It has the distinct feature of allowing a vertex to be central if it is in many triangles or none at all. We show experimentally that triangle centrality is broadly applicable to many different types of networks. Our empirical results demonstrate that 30% of the time triangle centrality identified central vertices that differed with those found by five well-known centrality measures, which suggests novelty without being overly specialized. It is also asymptotically faster to compute on sparse graphs than all but the most trivial of these other measures. We introduce optimal algorithms that compute triangle centrality in $O(m\barδ)$ time and $O(m+n)$ space, where $\barδ\le O(\sqrt{m})$ is the $\textit{average degeneracy}$ introduced by Burkhardt, Faber, and Harris (2020). In practical applications, $\barδ$ is much smaller than $\sqrt{m}$ so triangle centrality can be computed in nearly linear time. On a Concurrent Read Exclusive Write (CREW) Parallel Random Access Machine (PRAM), we give a near work-optimal parallel algorithm that takes $O(\log n)$ time using $O(m\sqrt{m})$ CREW PRAM processors. In MapReduce, we show it takes four rounds using $O(m\sqrt{m})$ communication bits and is therefore optimal. We also derive a linear algebraic formulation of triangle centrality which can be computed in $O(m\barδ)$ time on sparse graphs.
This paper proposes two algorithms, namely "back-tracking" and "history following", to reach consensus in case of communication loss for a network of distributed agents with switching topologies. To reach consensus in distributed control, considered communication topology forms a strongly connected graph. The graph is no more strongly connected whenever an agent loses communication.Whenever an agent loses communication, the topology is no more strongly connected. The proposed back-tracking algorithm makes sure that the agent backtracks its position unless the communication is reestablished, and path is changed to reach consensus. In history following, the agents use their memory and move towards previous consensus point until the communication is regained. Upon regaining communication, a new consensus point is calculated depending on the current positions of the agents and they change their trajectories accordingly. Simulation results, for a network of six agents, show that when the agents follow the previous history, the average consensus time is less than that of back-tracking. However, situation may arise in history following where a false notion of reaching consensus makes one of the agents stop at a point near to the actual consensus point. An obstacle avoidance algorithm is integrated with the proposed algorithms to avoid collisions. Hardware implementation for a three robots system shows the effectiveness of the algorithms.
This is a study of the history of the asteroids in the main asteroid belt. Collisions have been the dominant process. Every asteroid has been impacted by others a multitude of times, with consequences of cratering, erosion, spin increments, fragmentation, and occasional catastrophic disruption and dispersion. Extensive information for asteroid orbits, sizes, shapes, composition, and rotation rates of those asteroids is now available. Those are a result of their history, but to interpret them requires understanding the processes. That understanding can be improved by simulations of the history. A simulation needs robust models of the dynamical and collisional events. Such models have evolved substantially in the last few decades. Here I present current models, a method, and a code "SSAH" for stochastic simulations of the history of the main belt. That code gives a framework upon which existing and future models can be based. The results lead to new paradigms for asteroid histories including the distribution of spins; the irrelevance of strength spin limits; the "unusual" spins of 2001 OE84; and of large slow-spinning tumbling objects (Mathilde); the "V-shape" in the spin versus diameter plot; the non-Maxwellian distribution of spins of a given diameter range; the numbers of expected tumblers, and more. At the same time, the simulations expose gaps in our knowledge that require further research. The SSAH code is freely available for the use of others.
The paper briefly presents history, status, and plans of the search for the critical structures - the onset of fireball, the onset of deconfinement, and the deconfinement critical point - in high energy nucleus-nucleus collisions. First, the basic ideas are introduced, the history of the observation of strongly interacting matter in heavy ion collisions is reviewed, and the path towards the quark-gluon plasma discovery is sketched. Then the status of the search for critical structures is discussed - the discovery of the onset of deconfinement, indications for the onset of fireball, and still inconclusive results concerning the deconfinement critical point. Finally, an attempt to formulate priorities for future measurements - charm quarks vs the onset of deconfinement and detailed study of the onset of fireball - closes the paper.
We investigate the utility of the 3-dimensional Two-Point Correlation Function (3D 2PCF) in quantifying substructure in the stellar halo of the Milky Way, particularly as a means of constraining the accretion history of our Galaxy. We use RR Lyrae variable stars from two different surveys as tracers of the structure in the Galactic stellar halo. We compare our measurements of the 3D 2PCF in these datasets to a suite of simulations of the formation of the stellar halo from Bullock and Johnston (2005). While there is some room for interpretation, we find that the amounts of structure to be broadly consistent with the simulations, while appearing smoother than average within the inner halo and at small scales. This suggests a preferred accretion history scenario in which the Milky Way's stellar halo acquired most of its mass about ~8 Gigayears ago, and has been largely quiescent since. Finally, we discuss the prospects of statistical tools such as the 2PCF in the Gaia era of galactic archaeology.
In this paper we study spiderweb central configurations for the $N$-body problem, i.e configurations given by $N=n \times \ell+1$ masses located at the intersection points of $\ell$ concurrent equidistributed half-lines with $n$ circles and a central mass $m_0$, under the hypothesis that the $\ell$ masses on the $i$-th circle are equal to a positive constant $m_i$; we allow the particular case $m_0=0$. We focus on constructive proofs of the existence of spiderweb central configurations, which allow numerical implementation. Additionally, we prove the uniqueness of such central configurations when $\ell \in \{2,\dots,9\}$ and arbitrary $n$ and $m_i$; under the constraint $m_1\geq m_2\geq \ldots \geq m_n$ we also prove uniqueness for $\ell \in \{10,\dots,18\}$ and $n$ not too large. We also give an algorithm providing a rigorous proof of the existence and local unicity of such central configurations when given as input a choice of $n$, $\ell$ and $m_0, . . . ,m_n$. Finally, our numerical simulations highlight some interesting properties of the mass distribution.
Feynman's sum-over-histories formulation of quantum mechanics has been considered a useful calculational tool in which virtual Feynman histories entering into a coherent quantum superposition cannot be individually measured. Here we show that sequential weak values, inferred by consecutive weak measurements of projectors, allow direct experimental probing of individual virtual Feynman histories thereby revealing the exact nature of quantum interference of coherently superposed histories. Because the total sum of sequential weak values of multi-time projection operators for a complete set of orthogonal quantum histories is unity, complete sets of weak values could be interpreted in agreement with the standard quantum mechanical picture. We also elucidate the relationship between sequential weak values of quantum histories with different coarse-graining in time and establish the incompatibility of weak values for non-orthogonal quantum histories in history Hilbert space. Bridging theory and experiment, the presented results may enhance our understanding of both weak values and quantum histories.
ChangHoon Hahn, Jeremy L. Tinker, Andrew R. Wetzel
Central galaxies make up the majority of the galaxy population, including the majority of the quiescent population at $\mathcal{M}_* > 10^{10}\mathrm{M}_\odot$. Thus, the mechanism(s) responsible for quenching central galaxies plays a crucial role in galaxy evolution as whole. We combine a high resolution cosmological $N$-body simulation with observed evolutionary trends of the "star formation main sequence," quiescent fraction, and stellar mass function at $z < 1$ to construct a model that statistically tracks the star formation histories and quenching of central galaxies. Comparing this model to the distribution of central galaxy star formation rates in a group catalog of the SDSS Data Release 7, we constrain the timescales over which physical processes cease star formation in central galaxies. Over the stellar mass range $10^{9.5}$ to $10^{11} \mathrm{M}_\odot$ we infer quenching e-folding times that span $1.5$ to $0.5\; \mathrm{Gyr}$ with more massive central galaxies quenching faster. For $\mathcal{M}_* = 10^{10.5}\mathrm{M}_\odot$, this implies a total migration time of $\sim 4~\mathrm{Gyrs}$ from the star formation main sequence to quiescence. Compared to satellites, central galaxies take $\sim 2~\mathrm{Gyrs}$ longer to quench their star formation, suggesting that different mechanisms are responsible for quenching centrals versus satellites. Finally, the central galaxy quenching timescale we infer provides key constraints for proposed star formation quenching mechanisms. Our timescale is generally consistent with gas depletion timescales predicted by quenching through strangulation. However, the exact physical mechanism(s) responsible for this still remain unclear.
A brief review of the problem of neutrino masses and oscillations is given. In the beginning we present an early history of neutrino masses, mixing and oscillations. Then we discuss all possibilities of neutrino masses and mixing (neutrino mass terms). The phenomenology of neutrino oscillations in vacuum is considered in some details. We present also the neutrino oscillation data and the seesaw mechanism of the neutrino mass generation.