Quantum simulation of exotic PT-invariant topological nodal loop bands with ultracold atoms in an optical lattice

Since the well-known PT symmetry has its fundamental significance and implication in physics, where PT denotes the combined operation of space-inversion P and time-reversal T, it is extremely important and intriguing to completely classify exotic PT-invariant topological metals and to physically realize them. Here we, for the first time, establish a rigorous classification of topological metals that are protected by the PT symmetry using KO-theory. As a physically realistic example, a PT-invariant nodal loop (NL) model in a 3D Brillouin zone is constructed, whose topological stability is revealed through its PT-symmetry-protected nontrivial Z2 topological charge. Based on these exact results, we propose an experimental scheme to realize and to detect tunable PT-invariant topological NL states with ultracold atoms in an optical lattice, in which atoms with two hyperfine spin states are loaded in a spin-dependent 3D OL and two pairs of Raman lasers are used to create out-of-plane spin-flip hopping with site-dependent phase. Such a realistic cold-atom setup can yield topological NL states, having a tunable ring-shaped band-touching line with the two-fold degeneracy in the bulk spectrum and non-trivial surface states. The states are actually protected by the combined PT symmetry even in the absence of both P and T symmetries, and are characterized by a Z2-type invariant (a quantized Berry phase). Remarkably, we demonstrate with numerical simulations that (i) the characteristic NL can be detected by measuring the atomic transfer fractions in a Bloch-Zener oscillation; (ii) the topological invariant may be measured based on the time-of-flight imaging; and (iii) the surface states may be probed through Bragg spectroscopy. The present proposal for realizing topological NL states in cold atom systems may provide a unique experimental platform for exploring exotic PT-invariant topological physics.Comment: 11 pages, 6 figures; accepted for publication in Phys. Rev.

An X-ray Spectroscopic Study of the Hot Interstellar Medium Toward the Galactic Bulge

We present a detailed spectroscopic study of the hot gas toward the Galactic bulge along the 4U 1820-303 sight line by a combination analysis of emission and absorption spectra. In addition to the absorption lines of OVII Kalpha, OVII Kbeta, OVIII Kalpha and NeIX Kalpha by Chandra LTGS as shown by previous works, Suzaku detected clearly the emission lines of OVII, OVIII, NeIX and NeX from the vicinity. We used simplified plasma models with constant temperature and density. Evaluation of the background and foreground emission was performed carefully, including stellar X-ray contribution based on the recent X-ray observational results and stellar distribution simulator. If we assume that one plasma component exists in front of 4U1820-303 and the other one at the back, the obtained temperatures are T= 1.7 +/- 0.2 MK for the front-side plasma and T=3.9(+0.4-0.3) MK for the backside. This scheme is consistent with a hot and thick ISM disk as suggested by the extragalactic source observations and an X-ray bulge around the Galactic center.Comment: 14 pages, 15 figures, accepted to be published in PASJ (Replace figure files to fix latex problem

Neoproterozoic S-type granites in the Alxa Block, westernmost North China and tectonic implications: in situ zircon U-Pb-Hf-O isotopic and geochemical constraints

The Alxa Block in northern China has been traditionally considered as the westernmost part of the Archean North China Craton (NCC). However, recent studies revealed that there are few Archean rocks exposed in the Alxa Block, and the Paleoproterozoic geology of this block is different from that of the western part of the NCC. Thus, the tectonic affinity of the Alxa Block to the NCC and/or other Precambrian blocks needs further investigations. In this study, we carry out integrated analyses of in situ zircon U–Pb age and Hf–O isotopes as well as whole-rock geochemistry and Nd isotopes for the Neoproterozoic Dabusushan and Naimumaodao granites from central Alxa Block. Secondary ion mass spectrometry (SIMS) U–Pb zircon dating results indicate that the Naimumaodao and Dabusushan granite plutons were formed at ca. 930 Ma and ca. 910 Ma, respectively. These granites are peraluminous (A/CNK value >1.0), and contain peraluminous minerals such as muscovite and tourmaline, similar to those of S-type granites. They are characterized by high zircon δ18O values of ca. 8.2 to 12.1 permil, corresponding to a calculated magmatic δ18O value of ca. 10.5 to 14.3 permil, variable zircon εHf(t) values of −6.2 to +3.8 (corresponding to Hf model ages of 2.2 to 1.6 Ga) and whole-rock εNd(t) values of −10.1 to −4.5 (corresponding to Nd model ages of 2.4-1.9 Ga). The petrological and Nd–Hf–O isotopic study indicated that these granites were most probably generated by remelting of dominant (meta)sedimentary rocks in an orogenesis-related compressional environment. There is a clear contrast in the Precambrian geological evolution, including basement rock age data, Precambrian magmatism and detrital zircon age patterns, between the Alxa Block and the NCC. Furthermore, the new in-situ detrital zircon ages on Neoproterozoic (meta)sedimentary rock suggest that Alxa Block is likely related to the Cathaysia Block of South China during the Neoproterozoic, and amalgamated with the NCC since the Early Paleozoic. Thus, our new data suggest that the Alxa Block is most likely a separated Precambrian terrane from the Western Block of the NCC

Tune-In: Training Under Negative Environments with Interference for Attention Networks Simulating Cocktail Party Effect

We study the cocktail party problem and propose a novel attention network called Tune-In, abbreviated for training under negative environments with interference. It firstly learns two separate spaces of speaker-knowledge and speech-stimuli based on a shared feature space, where a new block structure is designed as the building block for all spaces, and then cooperatively solves different tasks. Between the two spaces, information is cast towards each other via a novel cross- and dual-attention mechanism, mimicking the bottom-up and top-down processes of a human's cocktail party effect. It turns out that substantially discriminative and generalizable speaker representations can be learnt in severely interfered conditions via our self-supervised training. The experimental results verify this seeming paradox. The learnt speaker embedding has superior discriminative power than a standard speaker verification method; meanwhile, Tune-In achieves remarkably better speech separation performances in terms of SI-SNRi and SDRi consistently in all test modes, and especially at lower memory and computational consumption, than state-of-the-art benchmark systems.Comment: Accepted in AAAI 202

Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation

One of the leading single-channel speech separation (SS) models is based on a TasNet with a dual-path segmentation technique, where the size of each segment remains unchanged throughout all layers. In contrast, our key finding is that multi-granularity features are essential for enhancing contextual modeling and computational efficiency. We introduce a self-attentive network with a novel sandglass-shape, namely Sandglasset, which advances the state-of-the-art (SOTA) SS performance at significantly smaller model size and computational cost. Forward along each block inside Sandglasset, the temporal granularity of the features gradually becomes coarser until reaching half of the network blocks, and then successively turns finer towards the raw signal level. We also unfold that residual connections between features with the same granularity are critical for preserving information after passing through the bottleneck layer. Experiments show our Sandglasset with only 2.3M parameters has achieved the best results on two benchmark SS datasets -- WSJ0-2mix and WSJ0-3mix, where the SI-SNRi scores have been improved by absolute 0.8 dB and 2.4 dB, respectively, comparing to the prior SOTA results.Comment: Accepted in ICASSP 202

Contrastive Separative Coding for Self-supervised Representation Learning

To extract robust deep representations from long sequential modeling of speech data, we propose a self-supervised learning approach, namely Contrastive Separative Coding (CSC). Our key finding is to learn such representations by separating the target signal from contrastive interfering signals. First, a multi-task separative encoder is built to extract shared separable and discriminative embedding; secondly, we propose a powerful cross-attention mechanism performed over speaker representations across various interfering conditions, allowing the model to focus on and globally aggregate the most critical information to answer the "query" (current bottom-up embedding) while paying less attention to interfering, noisy, or irrelevant parts; lastly, we form a new probabilistic contrastive loss which estimates and maximizes the mutual information between the representations and the global speaker vector. While most prior unsupervised methods have focused on predicting the future, neighboring, or missing samples, we take a different perspective of predicting the interfered samples. Moreover, our contrastive separative loss is free from negative sampling. The experiment demonstrates that our approach can learn useful representations achieving a strong speaker verification performance in adverse conditions.Comment: Accepted in ICASSP 202