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Yuta Sato

Publications and source records attributed to Yuta Sato.

13 recordsLinked to original sources

Intuitionistic and Constructive Modal Logics for Classical Modal Logicians

This paper gives a survey of propositional modal logic in an intuitionistic setting. Mainly intended for readers already familiar with classical modal logic, we discuss why there are two prominent families of such logics, intuitionistic modal logics (IMLs) and constructive modal logics (CMLs), what motivates their study, and how they compare with each other. Moreover, we take a deeper look at the logics lying between the CML and IML traditions, including a new logic $\textbf{KI}$ for which we prove completeness, and survey various extensions and $\Diamond$/$\Box$-free fragments. We further record several observations which seem to be implicit or absent in the literature; we point out a small defect in the original semantics for $\textbf{CK}$ and prove Lyndon interpolation theorems for $\textbf{CK}$ and $\textbf{WK}$.

math.LO

Atomically Thin Amorphous Carbon with an Ultralow Dielectric Constant

Two-dimensional (2D) materials exhibit excellent properties at monolayer thickness and are viable replacements for various microelectronic components as scaling gradually approaches the atomic limit. Despite significant advancements in the ongoing 2D revolution of integrated circuits, one crucial building block, namely a 2D ultralow-k (ULK) dielectric, remains unreported. The challenge lies in achieving a dielectric constant less than 3, as traditional low-k dielectrics are inherently unstable at the 2D limit due to their amorphous or porous nature. The realisation of ultrathin dielectrics with low-k is also needed to address current bottlenecks in integrated circuits scaling. Specifically, low-k materials are necessary to minimise parasitic capacitances as the distance between conductive elements shrinks below 10 nm. Moreover, advanced architectures like gate-all-around field effect transistors (GAA FET) require even lower dielectric constants (k<2) at sub-3nm thickness. Here, we show that layer-by-layer grown multilayer amorphous carbon (ML-AC), as thin as 0.8 nm, is a mechanically robust 2D ULK dielectric with k of 1.35 and dielectric strength of 28-31 MV cm-1. The lack of any long-range order, its intrinsic 2D nature, sp2 carbon character and low density are all essential for minimising dielectric permittivity. Moreover, ML-AC overcomes the vulnerability of existing dielectrics to ion diffusion degradation with a record metal ion diffusion time to failure (TTF) of 10^10 s for even a single layer. Therefore, otherwise necessary additional layers occupying up to 3 nm can be eliminated, which is especially significant as metal line widths approach 10 nm. Combined with its low-temperature, direct and conformal growth even on a dielectric, these critical features enable substantial improvements in silicon-based semiconductor electronics and ensure compatibility with future 2D electronics.

cond-mat.mtrl-sci

Quantum Criticality in Monolayer Amorphous Carbon

Amorphous solids represent the extreme limit of broken translational symmetry, in which the absence of long-range order removes well-defined crystal momenta and invalidates the Bloch description of electronic states. Monolayer amorphous carbon (MAC) has emerged as a unique realization of a strictly two-dimensional (2D) amorphous lattice defined by a structurally contiguous but topologically disordered $sp^2$-bonded random network devoid of any defined long-range crystal symmetry. From atomic-resolution measurements of multifractal wavefunctions, we show that disorder in MAC effectively localizes the low-energy part of the electronic spectrum but retains an extended critical-like state near the band centre ($E\sim 0$). We conjecture that this state is protected from topological disorder by remnant chiral symmetry surviving within the continuous random network, described by a Wess-Zumino-Witten (WZW) topological term. Near criticality, we verify the multifractal scaling relation $\eta = -\Delta_2$, providing quantitative agreement between independently measured spatial correlation decay and multifractal scaling exponents. Our results are confirmed by atomistic tight-binding calculations that closely mirror the multifractal scaling near $E\sim 0$. Our results establish MAC as the first strictly 2D amorphous electronic system to exhibit Anderson criticality driven purely by topological disorder

cond-mat.dis-nn

Discovering Learning-Friendly Generation Orders for Sequential Computation

Sequential computation via autoregressive generation can make difficult tasks learnable, but the generation order of intermediate states strongly affects whether training succeeds. We address the problem of discovering a learning-friendly target order automatically, rather than relying on task-specific design. Our key observation is that learning-friendly orders cause a faster loss drop in the early stage of training. We exploit this by \emph{loss profiling}, which ranks candidate orders by the early-stage loss of a single short run. To handle the factorial candidate space, we wrap loss profiling in a hierarchical global -- local search over block- and within-block-level orderings. On six order-sensitive tasks, the method discovers effective orders up to $L=13$ from random initialization and up to $L=40$ from structured initialization, lifting success rates from about 10\% to near 100\%. On integer multiplication, it rediscovers the reverse-digit order that was reported to be efficient in prior studies. On delay dynamical systems, as a case study of multi-variate recurrences, learnability varies sharply even among valid topological sorts of the dependency graph: loss profiling identifies a learning-friendly one, and the global search even discovers orders surpassing hand-designed candidates.

cs.LG

Preferred Synthesis of Armchair Transition Metal Dichalcogenide Nanotubes

In this work, we present the synthesis of transition-metal dichalcogenide (TMDC) nanotubes with a preferred chiral angle. SnS2, MoS2, and WS2 are formed with high yield and structural purity inside the channels of boron nitride nanotubes. Atomic-resolution imaging, nano-area electron diffraction, and Circular Dichroism spectroscopy reveal that these synthesized TMDC nanotubes prefer to have an armchair configuration, with a probability up to 84%. Density functional theory reveals a negligible difference in the formation energy between armchair and zigzag nanotubes, suggesting that the chirality preference does not originate from the differences in structural stability. However, a detailed TEM investigation revealed that these TMDC nanotubes formed via a transition state of nanoribbons, and these nanoribbons are energetically more stable in a zigzag configuration. Subsequent machine learning potential molecular dynamics simulations verify that zigzag nanoribbons do roll up to form an armchair SnS2 nanotubes. Finally, this "zigzag nanoribbon to armchair nanotube" transition process is directly observed in real time by in-situ transmission electron microscopy. This work demonstrates the first, but likely general, experimental strategy for synthesizing chirality-preferred TMDC nanotubes.

cond-mat.mtrl-sci

CALT: A Library for Computer Algebra with Transformer

Recent advances in artificial intelligence have demonstrated the learnability of symbolic computation through end-to-end deep learning. Given a sufficient number of examples of symbolic expressions before and after the target computation, Transformer models - highly effective learners of sequence-to-sequence functions - can be trained to emulate the computation. This development opens up several intriguing challenges and new research directions, which require active contributions from the symbolic computation community. In this work, we introduce Computer Algebra with Transformer (CALT), a user-friendly Python library designed to help non-experts in deep learning train models for symbolic computation tasks.

cs.LG

Uniform Lyndon interpolation for the pure logic of necessitation with a modal reduction principle

We prove the uniform Lyndon interpolation property (ULIP) of some extensions of the pure logic of necessitation $\mathbf{N}$. For any $m, n \in \mathbb{N}$, $\mathbf{N}^+\mathbf{A}_{m,n}$ is the logic obtained from $\mathbf{N}$ by adding a single axiom $\Box^n \varphi \to \Box^m \varphi$, $\Diamond$-free modal reduction principle, together with a rule $\frac{\neg \Box \varphi}{\neg \Box \Box \varphi}$, required to make the logic complete with respect to its Kripke-like semantics. We first introduce a sequent calculus $\mathbf{GN}^+\mathbf{A}_{m,n}$ for $\mathbf{N}^+\mathbf{A}_{m,n}$ and show that it enjoys cut elimination, proving Craig and Lyndon interpolation properties as a consequence. We then introduce a general method, called propositionalization, that enables one to reduce ULIP of a logic to some weaker logic. Lastly, we construct a propositionalization of $\mathbf{N}^+\mathbf{A}_{m,n}$ into classical propositional logic $\mathbf{Cl}$, proving ULIP as a corollary. We also prove ULIP of $\mathbf{NA}_{m,n} = \mathbf{N} + \Box^n \varphi \to \Box^m \varphi$ and $\mathbf{NRA}_{m,n} = \mathbf{N} + \Box^n \varphi \to \Box^m \varphi + \frac{\neg \varphi}{\neg \Box \varphi}$ in the same manner.

math.LO

Janus MoSSe nanotubes on one-dimensional SWCNT-BNNT van der Waals heterostructures

2D Janus TMDC layers with broken mirror symmetry exhibit giant Rashba splitting and unique excitonic behavior. For their 1D counterparts, the Janus nanotubes possess curvature, which introduce an additional degree of freedom to break the structural symmetry. This could potentially enhance these effects or even give rise to novel properties. In addition, Janus MSSe nanotubes (M=W, Mo), with diameters surpassing 40 {\AA} and Se positioned externally, consistently demonstrate lower energy states than their Janus monolayer counterparts. However, there have been limited studies on the preparation of Janus nanotubes, due to the synthesis challenge and limited sample quality. Here we first synthesized MoS2 nanotubes based on SWCNT-BNNT heterostructure and then explored the growth of Janus MoSSe nanotubes from MoS2 nanotubes with the assistance of H2 plasma at room temperature. The successful formation of the Janus structure was confirmed via Raman spectroscopy, and microscopic morphology and elemental distribution of the grown samples were further characterized. The synthesis of Janus MoSSe nanotubes based on SWCNT-BNNT enables the further exploration of novel properties in Janus TMDC nanotubes.

cond-mat.mtrl-sci

Spatial Graph Coarsening: Weather and Weekday Prediction with London's Bike-Sharing Service using GNN

This study introduced the use of Graph Neural Network (GNN) for predicting the weather and weekday of a day in London, from the dataset of Santander Cycles bike-sharing system as a graph classification task. The proposed GNN models newly introduced (i) a concatenation operator of graph features with trained node embeddings and (ii) a graph coarsening operator based on geographical contiguity, namely "Spatial Graph Coarsening". With the node features of land-use characteristics and number of households around the bike stations and graph features of temperatures in the city, our proposed models outperformed the baseline model in cross-entropy loss and accuracy of the validation dataset.

cs.LG

Mesh-Wise Prediction of Demographic Composition from Satellite Images Using Multi-Head Convolutional Neural Network

Population aging is one of the most serious problems in certain countries. In order to implement its countermeasures, understanding its rapid progress is of urgency with a granular resolution. However, a detailed and rigorous survey with high frequency is not feasible due to the constraints of financial and human resources. Nowadays, Deep Learning is prevalent for pattern recognition with significant accuracy, with its application to remote sensing. This paper proposes a multi-head Convolutional Neural Network model with transfer learning from pre-trained ResNet50 for estimating mesh-wise demographics of Japan as one of the most aged countries in the world, with satellite images from Landsat-8/OLI and Suomi NPP/VIIRS-DNS as inputs and census demographics as labels. The trained model was performed on a testing dataset with a test score of at least 0.8914 in $\text{R}^2$ for all the demographic composition groups, and the estimated demographic composition was generated and visualised for 2022 as a non-census year.

cs.CV

The finite frame property of some extensions of the pure logic of necessitation

We study the finite frame property of some extensions of Fitting, Marek, and Truszczy\'nski's pure logic of necessitation $\mathbf{N}$. For any natural numbers $m, n$, we introduce the logic $\mathbf{N}^+\mathbf{A}_{m, n}$ by adding the single axiom scheme $\Box^n \varphi \to \Box^m \varphi$ and the rule $\dfrac{\neg \Box \varphi}{\neg \Box \Box \varphi}$ (Ros$^\Box$) into $\mathbf{N}$. We prove the finite frame property of $\mathbf{N}^+\mathbf{A}_{m, n}$ with respect to Fitting, Marek, and Truszczy\'nski's relational semantics. We also prove that for $n \ge 2$, the logic obtained by removing the rule Ros$^\Box$ from $\mathbf{N}^+\mathbf{A}_{0, n}$ is incomplete with respect to that semantics.

math.LO

One-dimensional van der Waals Heterostructures: Growth Mechanism and Handedness Correlation Revealed by Non-destructive TEM

In this work, we perform a follow-up and comprehensive study on the structural details and formation mechanism of chemical vapor deposition (CVD) synthesized one-dimensional (1D) van der Waals heterostructures. Edge structures, nucleation sites, crystal epitaxial relationships are clearly revealed using transmission electron microscopy (TEM). This is achieved by the direct synthesis of heteronanotubes on a CVD-compatible Si/SiO2 TEM grid, which enabled a transfer-free and non-destructive access to many intrinsic structural details. In particular, we have distinguished different shaped boron nitride nanotube (BNNT) edges, which are confirmed, by electron diffraction at the same location, to be strictly associated with its own chiral angle and polarity. We also demonstrate the importance of surface cleanness and isolation for the formation of perfect 1D heterostructures. Furthermore, we elucidate the handedness correlation between SWCNT template and BNNT crystals. This work not only provides an in-depth understanding of this new 1D heterostructure material group, but also, in a more general perspective, serves as an interesting investigation on crystal growth on highly curved (radius of a couple of nm) atomic substrates.

cond-mat.mtrl-sci

One-dimensional van der Waals heterostructures

Property by design is one appealing idea in material synthesis but hard to achieve in practice. A recent successful example is the demonstration of van der Waals (vdW) heterostructures,1-3 in which atomic layers are stacked on each other and different ingredients can be combined beyond symmetry and lattice matching. This concept, usually described as a nanoscale Lego blocks, allows to build sophisticated structures layer by layer. However, this concept has been so far limited in two dimensional (2D) materials. Here we show a class of new material where different layers are coaxially (instead of planarly) stacked. As the structure is in one dimensional (1D) form, we name it "1D vdW heterostructures". We demonstrate a 5 nm diameter nanotube consisting of three different materials: an inner conductive carbon nanotube (CNT), a middle insulating hexagonal boron nitride nanotube (BNNT) and an outside semiconducting MoS2 nanotube. As the technique is highly applicable to other materials in the current 2D libraries,4-6 we anticipate our strategy to be a starting point for discovering a class of new semiconducting nanotube materials. A plethora of function-designable 1D heterostructures will appear after the combination of CNTs, BNNTs and semiconducting nanotubes.

cond-mat.mtrl-sci