Miracle-dz/UniFAR-FTUs huggingface dataset:
Local Minimal Overrings

Let R be a (commutative integral) domain having quotient field K. A domain S satisfying , is called an overring of R. We say R has a minimal overring T, in case and there are no domains properly between R and T. The purpose of this paper is the study of certain classes of coherent domains having local minimal overrings; that is, having minimal overrings with unique maximal ideals.
Probing C-I bond fission in the UV photochemistry of 2-iodothiophene with core-to-valence transient absorption spectroscopy.

The UV photochemistry of small heteroaromatic molecules serves as a testbed for understanding fundamental photo-induced chemical transformations in moderately complex compounds, including isomerization, ring-opening, and molecular dissociation. Here, a combined experimental-theoretical study of 268 nm UV light-induced dynamics in 2-iodothiophene (C4H3IS) is performed. The dynamics are experimentally monitored with a femtosecond extreme ultraviolet (XUV) probe that measures iodine N-edge 4d core-to-valence transitions. Experiments are complemented by density functional theory calculations of both the pump-pulse induced valence excitations and the XUV probe-induced core-to-valence transitions. Possible intramolecular relaxation dynamics are investigated by ab initio molecular dynamics simulations. Gradual absorption changes up to ∼0.5 to 1 ps after excitation are observed for both the parent molecular species and emerging iodine fragments, with the latter appearing with a characteristic rise time of 160 ± 30 fs. Comparison of spectral intensities and energies with the calculations identifies an iodine dissociation pathway initiated by a predominant π → π* excitation. In contrast, initial excitation to a nearby n⟂ → σ* state appears unlikely based on a significantly smaller oscillator strength and the absence of any corresponding XUV absorption signatures. Excitation to the π → π* state is followed by contraction of the C-I bond, enabling a nonadiabatic transition to a dissociative π→σC-I* state. For the subsequent fragmentation, a relatively narrow bond-length region along the C-I stretch coordinate between 230 and 280 pm is identified, where the transition between the parent molecule and the thienyl radical + iodine atom products becomes prominent in the XUV spectrum due to rapid localization of two singly occupied molecular orbitals on the two fragments.
Partially Fault-Tolerant Quantum Computing Architecture with Error-Corrected Clifford Gates and Space-Time Efficient Analog Rotations

Quantum computers are expected to bring drastic acceleration to several computing tasks against classical computers. Noisy intermediate-scale quantum (NISQ) devices, which have tens to hundreds of noisy physical qubits, are gradually becoming available, but it is still challenging to achieve useful quantum advantages in meaningful tasks at this moment. On the other hand, the full fault-tolerant quantum computing (FTQC) based on the quantum error correction (QEC) code remains far beyond realization due to its extremely large requirement of high-precision physical qubits. In this study, we propose a quantum computing architecture to close the gap between NISQ and FTQC. Our architecture is based on erroneous arbitrary rotation gates and error-corrected Clifford gates implemented by lattice surgery. We omit the typical distillation protocol to achieve direct analog rotations and small qubit requirements, and minimize the remnant errors of the rotations by a carefully-designed state injection protocol. Our estimation based on numerical simulations shows that, for early-FTQC devices that consist of $10^4$ physical qubits with physical error probability $p = 10^{-4}$, we can perform roughly $1.72 \times 10^7$ Clifford operations and $3.75 \times 10^4$ arbitrary rotations on 64 logical qubits. Such computations cannot be realized by the existing NISQ and FTQC architectures on the same device, as well as classical computers. We hope that our proposal and the corresponding development of quantum algorithms based on it bring new insights on realization of practical quantum computers in future.
Classification and emergence of quantum spin liquids in chiral Rydberg models

We investigate the nature of quantum phases arising in chiral interacting Hamiltonians recently realized in Rydberg atom arrays. We classify all possible fermionic chiral spin liquids with $\mathrm{U}(1)$ global symmetry using parton construction on the honeycomb lattice. The resulting classification includes six distinct classes of gapped quantum spin liquids: the corresponding variational wave functions obtained from two of these classes accurately describe the Rydberg many-body ground state at $1/2$ and $1/4$ particle density. Complementing this analysis with tensor network simulations, we conclude that both particle filling sectors host a spin liquid with the same topological order of a $\nu=1/2$ fractional quantum Hall effect. At density $1/2$, our results clarify the phase diagram of the model, while at density $1/4$, they provide an explicit construction of the ground state wave function with almost unit overlap with the microscopic one. These findings pave the way to the use of parton wave functions to guide the discovery of quantum spin liquids in chiral Rydberg models.
Construction Methods Based Minimum Weight Distribution for Polar Codes with Successive Cancellation List Decoding

In this paper, we focus on the construction methods based MWD for polar codes to improve the performance with successive cancellation list (SCL) decoding. We first propose an ordered and nested reliability sequence, namely MWD sequence, to improve the ML performance of polar codes and apply fast construction without the original channel information. In the MWD sequence, the synthetic channels are sorted by the partial MWD which is used to evaluate the influence of information bit on MWD and we prove the MWD sequence is the optimum sequence under ML decoding. Then, since the list size of SCL decoding is limited, we introduce an entropy constraint to establish a relationship between the list size and the ML performance and propose a heuristic and greedy construction method named bit grouping reorder based MWD (BGR-MWD) algorithm. In the algorithm, we divide the synthetic channels into groups by the partial MWD and greedily reorder the synthetic channels in some groups until the entropy constraint is satisfied. The simulation results show the MWD sequence is suitable for constructing polar codes with short code length. Meanwhile, the BGR-MWD algorithm has superior performance over the traditional construction methods for long code length.
Upper limit on scalar field dark matter from LIGO-Virgo third observation run

If dark matter is a light scalar field weakly interacting with elementary particles, such a field induces oscillations of the physical constants, which results in time-varying force acting on macroscopic objects. In this paper, we report on a search for such a signal in the data of the two LIGO detectors during their third observing run (O3). We focus on the mass of the scalar field in the range of $10^{-13}-10^{-11}~{\rm eV}$ for which the signal falls within the detectors' sensitivity band. We first formulate the cross-correlation statistics that can be readily compared with publically available data. It is found that inclusion of the anisotropies of the velocity distribution of dark matter caused by the motion of the solar system in the Milky Way Galaxy enhances the signal by a factor of $\sim 2$ except for the narrow mass range around $\simeq 3\times 10^{-13}~{\rm eV}$ for which the correlation between the interferometer at Livingston and the one at Hanford is suppressed. From the non-detection of the signal, we derive the upper limits on the coupling constants between the elementary particles and the scalar field for five representative cases. For all the cases where the weak equivalence principle is not satisfied, tests of the violation of the weak equivalence principle provide the tightest upper limit on the coupling constants. Upper limits from the fifth-force experiment are always stronger than the ones from LIGO, but the difference is less than a factor of $\sim 5$ at large-mass range. Our study demonstrates that gravitational-wave experiments are starting to bring us meaningful information about the nature of dark matter. The formulation provided in this paper may be applied to the data of upcoming experiments as well and is expected to probe much wider parameter range of the model.
A Privacy-Preserving Energy Theft Detection Model for Effective Demand-Response Management in Smart Grids

The detection of energy thefts is vital for the safety of the whole smart grid system. However, the detection alone is not enough since energy thefts can crucially affect the electricity supply leading to some blackouts. Moreover, privacy is one of the major challenges that must be preserved when dealing with clients' energy data. This is often overlooked in energy theft detection research as most current detection techniques rely on raw, unencrypted data, which may potentially expose sensitive and personal data. To solve this issue, we present a privacy-preserving energy theft detection technique with effective demand management that employs two layers of privacy protection. We explore a split learning mechanism that trains a detection model in a decentralised fashion without the need to exchange raw data. We also employ a second layer of privacy by the use of a masking scheme to mask clients' outputs in order to prevent inference attacks. A privacy-enhanced version of this mechanism also employs an additional layer of privacy protection by training a randomisation layer at the end of the client-side model. This is done to make the output as random as possible without compromising the detection performance. For the energy theft detection part, we design a multi-output machine learning model to identify energy thefts, estimate their volume, and effectively predict future demand. Finally, we use a comprehensive set of experiments to test our proposed scheme. The experimental results show that our scheme achieves high detection accuracy and greatly improves the privacy preservation degree.
Light double-gluon hybrid states with the exotic quantum numbers 
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We apply the QCD sum rule method to study the double-gluon hybrid states with the quark-gluon contents $\bar q q gg$ ($q=u/d$) and $\bar s s gg$. We construct twenty-eight double-gluon hybrid currents, eleven of which are found to be zero due to some internal symmetries between the two gluons fields. We concentrate on the non-vanishing currents with the exotic quantum numbers $J^{PC} = 1^{-+}$ and $3^{-+}$. Their masses are calculated to be $M_{|\bar q q gg;1^{-+}\rangle} = 4.35^{+0.26}_{-0.30}$ GeV, $M_{|\bar s s gg;1^{-+}\rangle} = 4.49^{+0.25}_{-0.30}$ GeV, $M_{|\bar q q gg;3^{-+}\rangle} = 3.02^{+0.24}_{-0.31}$ GeV, and $M_{|\bar s s gg;3^{-+}\rangle} = 3.16^{+0.22}_{-0.28}$ GeV. The decay behaviors of the $J^{PC} = 3^{-+}$ states are studied, and we propose to search for them in the $\pi a_1(1260)/\rho \omega/\phi \phi$ channels in future particle experiments.
Confidence-Aware and Self-Supervised Image Anomaly Localisation

Universal anomaly detection still remains a challenging problem in machine learning and medical image analysis. It is possible to learn an expected distribution from a single class of normative samples, e.g., through epistemic uncertainty estimates, auto-encoding models, or from synthetic anomalies in a self-supervised way. The performance of self-supervised anomaly detection approaches is still inferior compared to methods that use examples from known unknown classes to shape the decision boundary. However, outlier exposure methods often do not identify unknown unknowns. Here we discuss an improved self-supervised single-class training strategy that supports the approximation of probabilistic inference with loosen feature locality constraints. We show that up-scaling of gradients with histogram-equalised images is beneficial for recently proposed self-supervision tasks. Our method is integrated into several out-of-distribution (OOD) detection models and we show evidence that our method outperforms the state-of-the-art on various benchmark datasets.
Towards Global Optimality in Cooperative MARL with the Transformation And Distillation Framework

Decentralized execution is one core demand in cooperative multi-agent reinforcement learning (MARL). Recently, most popular MARL algorithms have adopted decentralized policies to enable decentralized execution and use gradient descent as their optimizer. However, there is hardly any theoretical analysis of these algorithms taking the optimization method into consideration, and we find that various popular MARL algorithms with decentralized policies are suboptimal in toy tasks when gradient descent is chosen as their optimization method. In this paper, we theoretically analyze two common classes of algorithms with decentralized policies -- multi-agent policy gradient methods and value-decomposition methods to prove their suboptimality when gradient descent is used. In addition, we propose the Transformation And Distillation (TAD) framework, which reformulates a multi-agent MDP as a special single-agent MDP with a sequential structure and enables decentralized execution by distilling the learned policy on the derived ``single-agent"MDP. This approach uses a two-stage learning paradigm to address the optimization problem in cooperative MARL, maintaining its performance guarantee. Empirically, we implement TAD-PPO based on PPO, which can theoretically perform optimal policy learning in the finite multi-agent MDPs and shows significant outperformance on a large set of cooperative multi-agent tasks.
Finding a Maximum Clique.

Abstract : An algorithm for finding a maximum clique in an arbitrary graph is described. The algorithm has a worst-case time bound of k(1.286) sup N for some constant k, where n is the number of vertices in the graph. Within a fixed time, the algorithm can analyze a graph with 2 3/4 as many vertices as the largest graph which the obvious algorithm (examining all subsets of vertices) can analyze. (Author)
Interferometric survey of Be stars with the CHARA array

Abstract We present the first spatially resolved observations of circumstellar envelopes of 25 bright northern Be stars. The survey was performed with the CHARA Array interferometer in the K-band at intermediate and long baselines. The interferometric visibilities are well fitted by a viscous disk model where the gas density steeply decreases with the radius. Physical and geometrical parameters such as the density profile, the inclination, and the position angles of the circumstellar disks are determined. We find that the density radial exponent ranges between n ≈ 2.4 − 3.2, which is consistent with previous IRAS measurements. We have also obtained simultaneous optical and near-IR spectrophotometric measurements, and found that the model reproduces well the observed disk IR-continuum excess emission. By combining the projected rotational velocity of the Be star with the disk inclination derived from interferometry, we give estimates of the equatorial rotational velocities of these Be stars.
Integrating biopolymer design with physical unclonable functions for anticounterfeiting and product traceability in agriculture

Smallholder farmers and manufacturers in the Agri-Food sector face substantial challenges because of increasing circulation of counterfeit products (e.g., seeds), for which current countermeasures are implemented mainly at the secondary packaging level, and are generally vulnerable because of limited security guarantees. Here, by integrating biopolymer design with physical unclonable functions (PUFs), we propose a cryptographic protocol for seed authentication using biodegradable and miniaturized PUF tags made of silk microparticles. By simply drop casting a mixture of variant silk microparticles on a seed surface, tamper-evident PUF tags can be seamlessly fabricated on a variety of seeds, where the unclonability comes from the stochastic assembly of spectrally and visually distinct silk microparticles in the tag. Unique, reproducible, and unpredictable PUF codes are generated from both Raman mapping and microscopy imaging of the silk tags. Together, the proposed technology offers a highly secure solution for anticounterfeiting and product traceability in agriculture.
Phase Transitions and Magnetic Correlations in Two‐Dimensional Antiferromagnets

Recent neutron scattering work on the planar antiferromagnet K2NiF4 has indicated that this system undergoes a true two‐dimensional antiferromagnetic phase transition. In this paper we review these studies together with measurements of the magnons at low temperatures and in the vicinity of TN. New high precision measurements of the sublattice magnetization around TN are presented. It is shown that the power law M(T)/M(4.2)=0.973(1−T/92.23)0.138±0.004 holds for 2×10−1 > 1‐T/TN > 3×10−4. Preliminary measurements of the wavevector‐dependent staggered susceptibility χαβ (q) in K2NiF4 show that only χzz, the component parallel to the anisotropy axis, has pronounced diffusive character, diverging at TN. This provides definitive proof that the phase transition is anisotropy‐induced.
Functional neurological restoration of amputated peripheral nerve using biohybrid regenerative bioelectronics

The development of neural interfaces with superior biocompatibility and improved tissue integration is vital for treating and restoring neurological functions in the nervous system. A critical factor is to increase the resolution for mapping neuronal inputs onto implants. For this purpose, we have developed a new category of neural interface comprising induced pluripotent stem cell (iPSC)–derived myocytes as biological targets for peripheral nerve inputs that are grafted onto a flexible electrode arrays. We show long-term survival and functional integration of a biohybrid device carrying human iPSC-derived cells with the forearm nerve bundle of freely moving rats, following 4 weeks of implantation. By improving the tissue-electronics interface with an intermediate cell layer, we have demonstrated enhanced resolution and electrical recording in vivo as a first step toward restorative therapies using regenerative bioelectronics.
Design of underwater superoleophobic TiO2 coatings with additional photo-induced self-cleaning properties by one-step route bio-inspired from fish scales

Self-cleaning properties inspired by the structures and functions of some creatures are of great interest since the late 20th century. In this paper, TiO2 coatings with hierarchical rutile TiO2 flowers on fluorine-doped tin oxide substrate are fabricated through a simple one-step hydrothermal method. The flower-like coatings exhibit superhydrophilicity in air and superoleophobicity underwater with a contact angle as high as 157°, presenting good underwater self-cleaning performance. In addition, when contaminated by oleic acid, the as-prepared TiO2 coatings also exhibit excellent photocatalytic capability under ultraviolet irradiation, which demonstrated self-cleaning properties in a different way. This self-cleaning film provides a good strategy for some industrial and ocean applications.
The Heat Balance of a Riming Graupel Pellet and the Charge Separation during Ice–Ice Collisions

Abstract It has been suggested that the sign of charge acquired by a riming graupel pellet during ice crystal interactions depends on its surface state being negative when it is evaporating and positive when growing by vapor diffusion. Experiments were conducted to determine the surface states of riming cylinders in two previous laboratory studies of thunderstorm electrification. Calculations of the heat balance of the simulated graupel pellets are considered in terms of experimental measurements of the charge transferred under similar conditions. The results show that the contribution from in-cloud supercooled droplets is not always adequate to enable the graupel surface to grow by vapor diffusion in all laboratory cloud conditions where it acquires a net positive charge. It is suggested that factors such as the vapor fields around droplets freezing on its surface and the shape and surface roughness of the graupel may play important roles in determining the surface state and hence the overall sign of the.
Strong orbital polarization in orthorhombic DyMnO3: A combined x-ray linear dichroism and ab initio electronic structure study

We present a combined experimental and theoretical study on the $\text{Mn}\text{ }3d$ orbital occupation in orthorhombic ${\text{DyMnO}}_{3}$ single crystals. We have observed a very strong polarization dependence in the $\text{Mn}\text{ }{L}_{2,3}$ x-ray absorption spectra, indicative for a distinct anisotropic orbital occupation. Ab initio electronic-structure calculations clearly infer the existence of a strong orbital polarization in the ${e}_{g}$ band with a staggered ${d}_{3{x}^{2}\ensuremath{-}{r}^{2}}/{d}_{3{y}^{2}\ensuremath{-}{r}^{2}}$-type ordering pattern in the $ab$ plane. This finding is in excellent agreement with a quantitative analyis of the spectra using the atomic multiplet cluster approach.
Implementation of Monte Carlo Method on Electromagnetic Launcher Simulator

Electromagnetic launcher (EML) is a prominent candidate for transporting payloads to the earth orbits or deep into space. Major space powers have been developing EMLs for a long time either nationally or internationally. Although a lot of progress has been made, some technological barriers still exist. Further studies are required to overcome these challenges. These research and manufacturing activities include, not only experimental and theoretical studies, but also simulations. In this paper, a small-scale EML is simulated. During simulation, magnetic flux density and self-induction are calculated using the Monte Carlo methods. These findings are validated with the analytical solutions taken from the literature and found to be identical. These values are used to solve coupled equations of motion and electric circuits. Finally, this paper ends with the presentation of current and velocity profiles in the time domain.
5D Tensor completion via nuclear norm minimization: application to a heavy oil survey from the WCSB

SUMMARY We explore the tensor completion problem in a dataset obtained over a heavy oil field in the Western Canadian Sedimentary Basin. The fully sampled prestack volume in the frequencyspace domain is a low-rank fourth order tensor. In this context, the reconstruction problem becomes a tensor completion problem that we choose to solve via a nuclear norm minimization approach. The nuclear norm of a tensor is the closest convex approximation to the rank of a tensor. The reconstruction problem entails minimizing the nuclear norm of the tensor subject to data constraints and is implemented with the alternating direction method of multipliers. Our land data example clearly exhibits the performance of this reconstruction method.
Regression for time series with errors of measurement

where the xj, t are not directly observable but instead we record gj,t = Xj,t+6j,t. It is well known that if et and the 6j,t are sequences of uncorrelated random variables then the /% cannot be identified by means of estimates based only on variances and covariances. Reiersol (1941) and Geary (1949) have, amongst others, considered the use of 'instrumental variables' to enable the relation (1) to be estimated. The main instrumental variables considered by them were lagged values of the 6,t themselves, it being assumed that the 6, t are not serially correlated while the xj, t are. We will discuss the asymptotic properties, including the asymptotic efficiency, of Geary's and Reiersol's procedures using spectral methods. The additional information introduced by these authors can best be viewed as information on the relative shapes of the spectra of