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Unconventional superconductivity in bulk materials under ambient pressure is extremely rare among the 3d transition metal compounds outside the layered cuprates and iron-based family. It is predominantly linked to highly anisotropic electronic properties and quasi-two-dimensional (2D) Fermi surfaces. To date, the only known example of a Co-based exotic superconductor is the hydrated layered cobaltate, Na$_{x}$CoO$_{2}\cdot$ yH$_{2}$O, and its superconductivity is realized in the vicinity of a spin-1/2 Mott state. However, the nature of the superconductivity in these materials is still a subject of intense debate, and therefore, finding a new class of superconductors will help unravel the mysteries of their unconventional superconductivity. Here we report the discovery of superconductivity at $\sim$ 6.3 K in our newly synthesized layered compound Na$_{2}$CoSe$_{2}$O, in which the edge-shared CoSe$_{6}$ octahedra form [CoSe$_{2}$] layers with a perfect triangular lattice of Co ions. It is the first 3d transition metal oxychalcogenide superconductor with distinct structural and chemical characteristics. Despite its relatively low $T_{c}$, this material exhibits very high superconducting upper critical fields, $\mu_{0}H_{c2}(0)$, which far exceeds the Pauli paramagnetic limit by a factor of 3 - 4. First-principles calculations show that Na$_{2}$CoSe$_{2}$O is a rare example of a negative charge transfer superconductor. This cobalt oxychalcogenide with a geometrical frustration among Co spins shows great potential as a highly appealing candidate for the realization of unconventional and/or high-$T_{c}$ superconductivity beyond the well-established Cu- and Fe-based superconductor families and opens a new field in the physics and chemistry of low-dimensional superconductors.

A private decision tree evaluation (PDTE) protocol allows a feature vector owner (FO) to classify its data using a tree model from a model owner (MO) and only reveals an inference result to the FO. This paper proposes Mostree, a PDTE protocol secure in the presence of malicious parties with sublinear communication. We design Mostree in the three-party honest-majority setting, where an (untrusted) computing party (CP) assists the FO and MO in the secure computation. We propose two low-communication oblivious selection (OS) protocols by exploiting nice properties of three-party replicated secret sharing (RSS) and distributed point function. Mostree combines OS protocols with a tree encoding method and three-party secure computation to achieve sublinear communication. We observe that most of the protocol components already maintain privacy even in the presence of a malicious adversary, and what remains to achieve is correctness. To ensure correctness, we propose a set of lightweight consistency checks and seamlessly integrate them into Mostree. As a result, Mostree achieves sublinear communication and malicious security simultaneously. We implement Mostree and compare it with the state-of-the-art. Experimental results demonstrate that Mostree is efficient and comparable to semi-honest PDTE schemes with sublinear communication. For instance, when evaluated on the MNIST dataset in a LAN setting, Mostree achieves an evaluation using approximately 768 ms with communication of around 168 KB., Comment: This paper has been accepted by ACSAC2023

The Giant Radio Array for Neutrino Detection (GRAND) is an envisioned observatory of ultra-high-energy particles of cosmic origin, with energies in excess of 100 PeV. GRAND uses large surface arrays of autonomous radio-detection units to look for the radio emission from extensive air showers that are triggered by the interaction of ultra-high-energy cosmic rays, gamma rays, and neutrinos in the atmosphere or underground. In particular, for ultra-high-energy neutrinos, the future final phase of GRAND aims to be sensitive enough to discover them in spite of their plausibly tiny flux. Presently, three prototype GRAND radio arrays are in operation: GRANDProto300, in China, GRAND@Auger, in Argentina, and GRAND@Nancay, in France. Their goals are to field-test the design of the radio-detection units, understand the radio background to which they are exposed, and develop tools for diagnostic, data gathering, and data analysis. This list of contributions to the 38th International Cosmic Ray Conference (ICRC 2023) presents an overview of GRAND, in its present and future incarnations, and a look at the first data collected by GRANDProto13, the first phase of GRANDProto300., Comment: Note: To access the list of contributions, please follow the "HTML" link that can be found on the arXiv page (v2: fixed name spelling of one author)

Poisson's equation has been used in VLSI global placement for describing the potential field caused by a given charge density distribution. Unlike previous global placement methods that solve Poisson's equation numerically, in this paper, we provide an analytical solution of the equation to calculate the potential energy of an electrostatic system. The analytical solution is derived based on the separation of variables method and an exact density function to model the block distribution in the placement region, which is an infinite series and converges absolutely. Using the analytical solution, we give a fast computation scheme of Poisson's equation and develop an effective and efficient global placement algorithm called Pplace. Experimental results show that our Pplace achieves smaller placement wirelength than ePlace and NTUplace3. With the pervasive applications of Poisson's equation in scientific fields, in particular, our effective, efficient, and robust computation scheme for its analytical solution can provide substantial impacts on these fields.

Face recognition is a widely-used technique for identification or verification, where a verifier checks whether a face image matches anyone stored in a database. However, in scenarios where the database is held by a third party, such as a cloud server, both parties are concerned about data privacy. To address this concern, we propose CryptoMask, a privacy-preserving face recognition system that employs homomorphic encryption (HE) and secure multi-party computation (MPC). We design a new encoding strategy that leverages HE properties to reduce communication costs and enable efficient similarity checks between face images, without expensive homomorphic rotation. Additionally, CryptoMask leaks less information than existing state-of-the-art approaches. CryptoMask only reveals whether there is an image matching the query or not, whereas existing approaches additionally leak sensitive intermediate distance information. We conduct extensive experiments that demonstrate CryptoMask's superior performance in terms of computation and communication. For a database with 100 million 512-dimensional face vectors, CryptoMask offers ${\thicksim}5 \times$ and ${\thicksim}144 \times$ speed-ups in terms of computation and communication, respectively., Comment: 18 pages,3 figures, accepted by ICICS2023

We propose a generalization of the stochastic resetting mechanism for a Brownian particle diffusing in a one-dimensional periodic potential: randomly in time, the particle gets reset at the bottom of the potential well it was in. Numerical simulations show that in mirror asymmetric potentials, stochastic resetting rectifies the particle's dynamics, with maximum drift speed for an optimal average resetting time. Accordingly, an unbiased Brownian tracer diffusing on an asymmetric substrate can rectify its motion by adopting an adaptive stop-and-go strategy. Our proposed ratchet mechanism can model directed autonomous motion of molecular motors and micro-organisms, Comment: Journal of Chemical Physics 2023 (in press)