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The complex structures and electronic properties of alkali metals and their alloys provide a natural laboratory for studying the interelectronic interactions of metals under compression. A recent theoretical study (J. Phys. Chem. Lett. 2019, 10, 3006) predicted an interesting pressure-induced decomposition-recombination behavior of the Na2K compound over a pressure range of 10 - 500 GPa. However, a subsequent experiment (Phys. Rev. B 2020, 101, 224108) reported the formation of NaK rather than Na2K at pressures above 5.9 GPa. To address this discordance, we study the chemical stability of different stoichiometries of NaxK (x = 1/4, 1/3, 1/2, 2/3, 3/4, 4/3, 3/2 and 1 - 4) by effective structure searching method combined with first-principles calculations. Na2K is calculated to be unstable at 5 - 35 GPa due to the decomposition reaction Na2K-> NaK + Na, coinciding well with the experiment. NaK undergoes a combination-decomposition-recombination process accompanied by an opposite charge-transfer behavior between Na and K with pressure. Besides NaK, two hitherto unknown compounds NaK3 and Na3K2 are uncovered. NaK3 is a typical metallic alloy, while Na3K2 is an electride with strong interstitial electron localization., Comment: 19 pages, 4 figures, with supporting information

The estimation of spectroscopic and photometric redshifts (spec-z and photo-z) is crucial for future cosmological surveys. It can directly affect several powerful measurements of the Universe, e.g. weak lensing and galaxy clustering. In this work, we explore the accuracies of spec-z and photo-z that can be obtained in the China Space Station Optical Surveys (CSS-OS), which is a next-generation space survey, using neural networks. The 1-dimensional Convolutional Neural Networks (1-d CNN) and Multi-Layer Perceptron (MLP, one of the simplest forms of Artificial Neural Network) are employed to derive the spec-z and photo-z, respectively. The mock spectral and photometric data used for training and testing the networks are generated based on the COSMOS catalog. The networks have been trained with noisy data by creating Gaussian random realizations to reduce the statistical effects, resulting in similar redshift accuracy for both high-SNR (signal to noise ratio) and low-SNR data. The probability distribution functions (PDFs) of the predicted redshifts are also derived via Gaussian random realizations of the testing data, and then the best-fit redshifts and 1-sigma errors also can be obtained. We find that our networks can provide excellent redshift estimates with accuracies ~0.001 and 0.01 on spec-z and photo-z, respectively. Compared to existing photo-z codes, our MLP has similar accuracy but is more efficient in the training process. The fractions of catastrophic redshifts or outliers can be dramatically suppressed comparing to the ordinary template-fitting method. This indicates that the neural network method is feasible and powerful for spec-z and photo-z estimations in future cosmological surveys., Comment: 14 pages, 13 figures, 2 tables. Accepted for publication in ApJ

We study a simplified version of the Sachdev-Ye-Kitaev (SYK) model with real interactions by exact diagonalization. Instead of satisfying a continuous Gaussian distribution, the interaction strengths are assumed to be chosen from discrete values with a finite separation. A quantum phase transition from a chaotic state to an integrable state is observed by increasing the discrete separation. Below the critical value, the discrete model can well reproduce various physical quantities of the original SYK model, including the volume law of the ground-state entanglement, level distribution, thermodynamic entropy, and out-of-time-order correlation (OTOC) functions. For systems of size up to $N=20$, we find that the transition point increases with system size, indicating that a relatively weak randomness of interaction can stabilize the chaotic phase. Our findings significantly relax the stringent conditions for the realization of SYK model, and can reduce the complexity of various experimental proposals down to realistic ranges., Comment: 7 pages, 5 figures

Bulk superconductivity (SC) has recently been observed in the Al-Zn-Mg quasicrystal (QC). To settle several fundamental issues of the SC on the QC, we use an attractive Hubbard model to perform a systematic study on the Penrose lattice. The first issue is the Cooper instability of the QC, i.e., no Fermi surface under an infinitesimal attractive interaction. Starting from the two-electron problem outside the filled Fermi-sea, we analytically prove that an infinitesimal Hubbard attraction can lead to the Cooper instability as long as the density of state is nonzero at the Fermi level, which provides the basis of the SC on the QC. Our numerical results yield that the Cooper pairing always takes place between the two time-reversal states, satisfying the Anderson's theorem. On this theorem, we perform a mean-field (MF) study at both zero and finite temperatures. The MF study also shows that an arbitrarily weak attraction can lead to the pairing order, with the resulted pairing state being well described by the BCS theory and the thermal dynamic behaviors being well consistent with experimental results. The second issue is about the superfluid density on the QC without translational symmetry. It's clarified that although the normal state of the system locates at the critical point of the metal-insulator transition, the pairing state exhibits real SC, carrying finite superfluid density that can be verified by the Meissner effect, consistent with experiment also. These revealed properties of the SC on the Penrose lattice are universal for all QCs., Comment: 11 pages, 6 figures

The Kohn-Luttinger mechanism for unconventional superconductivity (SC) driven by weak repulsive electron-electron interactions on a periodic lattice is generalized to the quasicrystal (QC) via a real-space perturbative approach. The repulsive Hubbard model on the Penrose lattice is studied as an example, on which a classification of the pairing symmetries is performed and a pairing phase diagram is obtained. Two remarkable properties of these pairing states are revealed, due to the combination of the presence of the point-group symmetry and the lack of translation symmetry on this lattice. Firstly, the spin and spacial angular momenta of a Cooper pair is de-correlated: for each pairing symmetry, both spin-singlet and spin-triplet pairings are possible even in the weak-pairing limit. Secondly, the pairing states belonging to the 2D irreducible representations of the $D_5$ point group can be time-reversal-symmetry-breaking topological SCs carrying spontaneous bulk super current and spontaneous vortices. These two remarkable properties are general for the SCs on all QCs, and are rare on periodic lattices. Our work starts the new area of unconventional SCs driven by repulsive interactions on the QC., Comment: 4.5 pages, 4 figures, with Supplementary Material shown in the Appendix

Domains walls and topological defects in ferroelectric materials have emerged as a powerful new paradigm for functional electronic devices including memory and logic. Similarly, wall interactions and dynamics underpin a broad range of mesoscale phenomena ranging from giant electromechanical responses to memory effects. Exploring the functionalities of individual domain walls, their interactions, and controlled modifications of the domain structures is crucial for applications and fundamental physical studies. However, the dynamic nature of these features severely limits studies of their local physics since application of local biases or pressures in piezoresponse force microscopy induce wall displacement as a primary response. Here, we introduce a fundamentally new approach for the control and modification of domain structures based on automated experimentation whereby real space image-based feedback is used to control the tip bias during ferroelectric switching, allowing for modification routes conditioned on domain states under the tip. This automated experiment approach is demonstrated for the exploration of domain wall dynamics and creation of metastable phases with large electromechanical response.

The cosmic infrared background (CIB) anisotropies and cosmic microwave background (CMB) lensing are powerful measurements for exploring the cosmological and astrophysical problems. In this work, we measure the auto-correlation power spectrum of the CIB anisotropies in the Herschel-SPIRE HerMES Large Mode Survey (HeLMS) field, and the cross power spectrum with the CMB lensing measurements from the Planck satellite. The HeLMS field covers more than 270 deg^2, which is much larger than the previous analysis. We use the Herschel Level 1 time stream data to merge the CIB maps at 250, 350, and 500 um bands, and mask the areas where the flux is greater than 3-sigma (~50 mJy/beam) or no measured data. We obtain the final CIB power spectra at 100

The Chinese Space Station Optical Survey (CSS-OS) is a planned full sky survey operated by the Chinese Space Station Telescope (CSST). It can simultaneously perform the photometric imaging and spectroscopic slitless surveys, and will probe weak and strong gravitational lensing, galaxy clustering, individual galaxies and galaxy clusters, active galactic nucleus (AGNs), and so on. It aims to explore the properties of dark matter and dark energy and other important cosmological problems. In this work, we focus on two main CSS-OS scientific goals, i.e. the weak gravitational lensing (WL) and galaxy clustering surveys. We generate the mock CSS-OS data based on the observational COSMOS and zCOSMOS catalogs. We investigate the constraints on the cosmological parameters from the CSS-OS using the Markov Chain Monte Carlo (MCMC) method. The intrinsic alignments, galaxy bias, velocity dispersion, and systematics from instrumental effects in the CSST WL and galaxy clustering surveys are also included, and their impacts on the constraint results are discussed. We find that the CSS-OS can improve the constraints on the cosmological parameters by a factor of a few (even one order of magnitude in the optimistic case), compared to the current WL and galaxy clustering surveys. The constraints can be further enhanced when performing joint analysis with the WL, galaxy clustering, and galaxy-galaxy lensing data. Therefore, the CSS-OS is expected to be a powerful survey for exploring the Universe. Since some assumptions may be still optimistic and simple, it is possible that the results from the real survey could be worse. We will study these issues in details with the help of simulations in the future., Comment: 19 pages, 19 figures, 2 tables, accepted for publication in ApJ

The pursuit of more advanced electronics, finding solutions to energy needs, and tackling a wealth of social issues often hinges upon the discovery and optimization of new functional materials that enable disruptive technologies or applications. However, the discovery rate of these materials is alarmingly low. Much of the information that could drive this rate higher is scattered across tens of thousands of papers in the extant literature published over several decades, and almost all of it is not collated and thus cannot be used in its entirety. Many of these limitations can be circumvented if the experimentalist has access to systematized collections of prior experimental procedures and results that can be analyzed and built upon. Here, we investigate the property-processing relationship during growth of oxide films by pulsed laser deposition. To do so, we develop an enabling software tool to (1) mine the literature of relevant papers for synthesis parameters and functional properties of previously studied materials, (2) enhance the accuracy of this mining through crowd sourcing approaches, (3) create a searchable repository that will be a community-wide resource enabling material scientists to leverage this information, and (4) provide through the Jupyter notebook platform, simple machine-learning-based analysis to learn the complex interactions between growth parameters and functional properties (all data and codes available on https://github.com/ORNL-DataMatls). The results allow visualization of growth windows, trends and outliers, and which can serve as a template for analyzing the distribution of growth conditions, provide starting points for related compounds and act as feedback for first-principles calculations. Such tools will comprise an integral part of the materials design schema in the coming decade., Comment: 30 pages; 8 figures