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Harnessing graphene devices for applications relies on a comprehensive understanding of how to interact with them. Specifically, scattering processes at the interface with metallic contacts can induce reproducible abnormalities in measurements. Here, we report on emergent transport signatures appearing when contacting sub-micrometer high-quality metallic top contacts to graphene. Using electrostatic simulations and first-principle calculations, we reveal their origin: the contact induces an n-doped radial cavity around it, which is cooperatively defined by the metal-induced electrostatic potential and Klein tunneling. This intricate mechanism leads to secondary resistance peaks as a function of graphene doping that decreases with increasing contact size. Interestingly, in the presence of a perpendicular magnetic field, the cavity spawns a distinct set of Landau levels that interferes with the Landau fan emanating from the graphene bulk. Essentially, an emergent 'second bulk' forms around the contact, as a result of the interplay between the magnetic field and the contact-induced electrostatic potential. The interplay between the intrinsic and emergent bulks leads to direct observation of bulk-boundary correspondence in our experiments. Our work unveils the microscopic mechanisms manifesting at metal-graphene interfaces, opening new avenues for understanding and devising graphene-based electronic devices.

Audio-Visual Source Localization (AVSL) aims to locate sounding objects within video frames given the paired audio clips. Existing methods predominantly rely on self-supervised contrastive learning of audio-visual correspondence. Without any bounding-box annotations, they struggle to achieve precise localization, especially for small objects, and suffer from blurry boundaries and false positives. Moreover, the naive semi-supervised method is poor in fully leveraging the information of abundant unlabeled data. In this paper, we propose a novel semi-supervised learning framework for AVSL, namely Dual Mean-Teacher (DMT), comprising two teacher-student structures to circumvent the confirmation bias issue. Specifically, two teachers, pre-trained on limited labeled data, are employed to filter out noisy samples via the consensus between their predictions, and then generate high-quality pseudo-labels by intersecting their confidence maps. The sufficient utilization of both labeled and unlabeled data and the proposed unbiased framework enable DMT to outperform current state-of-the-art methods by a large margin, with CIoU of 90.4% and 48.8% on Flickr-SoundNet and VGG-Sound Source, obtaining 8.9%, 9.6% and 4.6%, 6.4% improvements over self- and semi-supervised methods respectively, given only 3% positional-annotations. We also extend our framework to some existing AVSL methods and consistently boost their performance., Comment: Accepted to NeurIPS2023

Audio-Visual Source Localization (AVSL) is the task of identifying specific sounding objects in the scene given audio cues. In our work, we focus on semi-supervised AVSL with pseudo-labeling. To address the issues with vanilla hard pseudo-labels including bias accumulation, noise sensitivity, and instability, we propose a novel method named Cross Pseudo-Labeling (XPL), wherein two models learn from each other with the cross-refine mechanism to avoid bias accumulation. We equip XPL with two effective components. Firstly, the soft pseudo-labels with sharpening and pseudo-label exponential moving average mechanisms enable models to achieve gradual self-improvement and ensure stable training. Secondly, the curriculum data selection module adaptively selects pseudo-labels with high quality during training to mitigate potential bias. Experimental results demonstrate that XPL significantly outperforms existing methods, achieving state-of-the-art performance while effectively mitigating confirmation bias and ensuring training stability., Comment: Accepted To ICASSP2024

Frameproof codes have been extensively studied for many years due to their application in copyright protection and their connection to extremal set theory. In this paper, we investigate upper bounds on the cardinality of wide-sense $t$-frameproof codes. For $t=2$, we apply results from Sperner theory to give a better upper bound, which significantly improves a recent bound by Zhou and Zhou. For $t\geq 3$, we provide a general upper bound by establishing a relation between wide-sense frameproof codes and cover-free families. Finally, when the code length $n$ is at most $\frac{15+\sqrt{33}}{24}(t-1)^2$, we show that a wide-sense $t$-frameproof code has at most $n$ codewords, and the unique optimal code consists of all weight-one codewords. As byproducts, our results improve several best known results on binary $t$-frameproof codes.

Electron optics deals with condensed matter platforms for manipulating and guiding electron beams with high efficiency and robustness. Common devices rely on the spatial confinement of the electrons into one-dimensional channels. Recently, there is growing interest in electron optics applications in two dimensions, which heretofore are almost exclusively based on graphene devices. In this work, we study band-inverted systems resulting from particle-hole hybridization and demonstrate their potential for electron optics applications. We develop the theory of interface scattering in an inverted-band $pn$ junction using a scattering matrix formalism and observe negative refraction conditions as well as transmission filtering akin to graphene's Klein tunneling but at finite angles. Based on these findings, we provide a comprehensive protocol for constructing electron optic components, such as focusing and bifurcating lenses, polarizers, and mirrors. We numerically test the robustness of our designs to disorder and finite temperatures, and motivate the feasibility of experimental realization. Our work opens avenues for electron optics in two dimensions beyond graphene-based devices, where a plethora of inverted-band materials in contemporary experiments can be harnessed., Comment: 14 pages, 8 figures

We study the supersaturation problems of oddtown and eventown. Given a family $\mathcal A$ of subsets of an $n$ element set, let $op(\mathcal A)$ denote the number of distinct pairs $A,B\in \mathcal A$ for which $|A \cap B|$ is odd. We show that if $\mathcal A$ consists of $n+s$ odd-sized subsets, then $op(\mathcal A)\geq s+2$, which is tight when $s\le n-4$. This disproves a conjecture by O'Neill on the supersaturation problem of oddtown. For the supersaturation problem of eventown, we show that for large enough $n$, if $\mathcal A$ consists of $2^{\lfloor \frac n 2\rfloor}+s$ even-sized subsets, then $op(\mathcal A)\ge s\cdot2^{\lfloor \frac n 2\rfloor-1} $ for any positive integer $s\le \frac{2^{\lfloor\frac n 8\rfloor}} n$. This partially proves a conjecture by O'Neill on the supersaturation problem of eventown. Previously, the correctness of this conjecture was only verified for $s=1$ and $2$. We further provide a twice weaker lower bound in this conjecture for eventown, that is $op(\mathcal{A})\ge s\cdot 2^{\lfloor n/2\rfloor-2}$ for general $n$ and $s$ by using discrete Fourier analysis. Finally, some asymptotic results for the lower bounds of $op(\mathcal A)$ are given when $s$ is large for both problems., Comment: 16 pages, no figure