31 research outputs found

    Emission of Spin-correlated Matter-wave Jets from Spinor Bose-Einstein Condensates

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    We report the observation of matter-wave jet emission in a strongly ferromagnetic spinor Bose-Einstein condensate of 7^7Li atoms. Directional atomic beams with F=1,mF=1|{F=1,m_F=1}\rangle and F=1,mF=1|{F=1,m_F=-1}\rangle spin states are generated from F=1,mF=0|{F=1,m_F=0}\rangle state condensates, or vice versa. This results from collective spin-mixing scattering events, where spontaneously produced pairs of atoms with opposite momentum facilitates additional spin-mixing collisions as they pass through the condensates. The matter-wave jets of different spin states (F=1,mF=±1|{F=1,m_F=\pm1}\rangle) can be a macroscopic Einstein-Podolsky-Rosen state with spacelike separation. Its spin-momentum correlations are studied by using the angular correlation function for each spin state. Rotating the spin axis, the inter-spin and intra-spin momentum correlation peaks display a high contrast oscillation, indicating collective coherence of the atomic ensembles. We provide numerical calculations that describe the experimental results at a quantitative level and can identify its entanglement after 100~ms of a long time-of-flight.Comment: 13 pages(6 main text, 7 supplemental material), 12 figure

    Failure Tolerant Training with Persistent Memory Disaggregation over CXL

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    This paper proposes TRAININGCXL that can efficiently process large-scale recommendation datasets in the pool of disaggregated memory while making training fault tolerant with low overhead. To this end, i) we integrate persistent memory (PMEM) and GPU into a cache-coherent domain as Type-2. Enabling CXL allows PMEM to be directly placed in GPU's memory hierarchy, such that GPU can access PMEM without software intervention. TRAININGCXL introduces computing and checkpointing logic near the CXL controller, thereby training data and managing persistency in an active manner. Considering PMEM's vulnerability, ii) we utilize the unique characteristics of recommendation models and take the checkpointing overhead off the critical path of their training. Lastly, iii) TRAININGCXL employs an advanced checkpointing technique that relaxes the updating sequence of model parameters and embeddings across training batches. The evaluation shows that TRAININGCXL achieves 5.2x training performance improvement and 76% energy savings, compared to the modern PMEM-based recommendation systems

    Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms

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    Commonsense norms are defeasible by context: reading books is usually great, but not when driving a car. While contexts can be explicitly described in language, in embodied scenarios, contexts are often provided visually. This type of visually grounded reasoning about defeasible commonsense norms is generally easy for humans, but (as we show) poses a challenge for machines, as it necessitates both visual understanding and reasoning about commonsense norms. We construct a new multimodal benchmark for studying visual-grounded commonsense norms: NORMLENS. NORMLENS consists of 10K human judgments accompanied by free-form explanations covering 2K multimodal situations, and serves as a probe to address two questions: (1) to what extent can models align with average human judgment? and (2) how well can models explain their predicted judgments? We find that state-of-the-art model judgments and explanations are not well-aligned with human annotation. Additionally, we present a new approach to better align models with humans by distilling social commonsense knowledge from large language models. The data and code are released at https://seungjuhan.me/normlens.Comment: Published as a conference paper at EMNLP 2023 (long

    A Deviation-Based Dynamic Vertex Reordering Technique for 2D Mesh Quality Improvement

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    We propose a novel deviation-based vertex reordering method for 2D mesh quality improvement. We reorder free vertices based on how likely this is to improve the quality of adjacent elements, based on the gradient of the element quality with respect to the vertex location. Specifically, we prioritize the free vertex with large differences between the best and the worst-quality element around the free vertex. Our method performs better than existing vertex reordering methods since it is based on the theory of non-smooth optimization. The downhill simplex method is employed to solve the mesh optimization problem for improving the worst element quality. Numerical results show that the proposed vertex reordering techniques improve both the worst and average element, compared to those with existing vertex reordering techniques

    Improved Stability and Controllability in ZrN-Based Resistive Memory Device by Inserting TiO2 Layer

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    In this work, the enhanced resistive switching of ZrN-based resistive switching memory is demonstrated by embedding TiO2 layer between Ag top electrode and ZrN switching layer. The Ag/ZrN/n-Si device exhibits unstable resistive switching as a result of the uncontrollable Ag migration. Both unipolar and bipolar resistive switching with high RESET current were observed. Negative-SET behavior in the Ag/ZrN/n-Si device makes set-stuck, causing permanent resistive switching failure. On the other hand, the analogue switching in the Ag/TiO2/ZrN/n-Si device, which could be adopted for the multi-bit data storage applications, is obtained. The gradual switching in Ag/TiO2/ZrN/n-Si device is achieved, possibly due to the suppressed Ag diffusion caused by TiO2 inserting layer. The current–voltage (I–V) switching characteristics of Ag/ZrN/n-Si and Ag/TiO2/ZrN/n-Si devices can be well verified by pulse transient. Finally, we established that the Ag/TiO2/ZrN/n-Si device is suitable for neuromorphic application through a comparison study of conductance update. This paper paves the way for neuromorphic application in nitride-based memristor devices

    Mutation in the Spatial Rock-Paper-Scissors Game

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    Voltage Amplitude-Controlled Synaptic Plasticity from Complementary Resistive Switching in Alloying HfOx with AlOx-Based RRAM

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    In this work, the synaptic plasticity from complementary resistive switching in a HfAlOx-based resistive memory device was emulated by a direct current (DC) voltage sweep, current sweep, and pulse transient. The alloyed HfAlOx dielectric was confirmed by X-ray photoelectron spectroscopy analysis. The negative differential resistance observed before the forming and set processes can be used for interface resistive switching with a low current level. Complementary resistive switching is obtained after the forming process at a negative bias. This unique resistive switching is also suitable for synaptic device applications in which the reset process occurs after an additional set process. The current sweep mode provides more clear information on the complementary resistive switching. Multiple current states are achieved by controlling the amplitude of the set and reset voltages under DC sweep mode. The potentiation and depression characteristics are mimicked by varying the pulse voltage amplitude for synaptic device application in a neuromorphic system. Finally, we demonstrate spike-timing-dependent plasticity by tuning the timing differences between pre-spikes and post-spikes

    Phase-field analysis of the effects of particle size, diffusivities, and mechanical properties on the cracking of silicon nanoparticle

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    In this study, a multiphysics model that reproduces the cracking of Si nanoparticle for a battery application was demonstrated. Two types of cracks appear on Si nanoparticle during lithiation. An essential condition for surface crack (SC) nucleation and propagation is a fast charging rate to form a high concentration gradient of lithium ions near the surface. A slower charging rate induces internal cracks (ICs) radiating from the center of the particle. The critical charging rates, at which SC or IC occurs, decrease rapidly with increasing particle radius. This indicates the difficulty of cracking of small nanoparticles, which is in a good agreement with the previous experimental results. Multiple cracks can appear in the particle, especially when the diffusivity is high. These cracks can be combined during the charging process, leading to the fracture or isolation of the particles. Additionally, two different peak stresses and Young's moduli from the literature were used considering their effects on the cracking of Si nanoparticle films. We believe our results provide a guideline for the fabrication and operation of Si nanoparticle-based anodes for lithium ion batteries. © 2023 Author(s).FALS

    Study on the Applicability of Dynamic Stability Evaluation Criteria by Comparison of Trackside Measurement Results of Different Track Structures

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    Countries such as Korea adopt design codes, evaluation criteria and specifications from standards originating abroad; this leads to a lack of distinction of the separate applications of dynamic stability evaluation parameters between various track structures of different track moduli. This paper discusses the applicability of the dynamic stability evaluation method of railway track structures by assessing 10 different types of railway track sections of a newly constructed railway operation line (5 ballasted and 5 concrete type track structures) by field instrumentation testing. Parameters of track support stiffness (TSS), wheel load fluctuation, derailment coefficient, and rail displacement are measured. The respective results are first compared to the standard criteria (design specification) and comparisons between the different track types are presented as ratios. Findings show that while all of the tracks satisfy the design specification requirements, each track type measurement result varies by a noticeable degree, particularly when comparing between concrete and ballast type track structures. Results of the study demonstrate that using the same dynamic stability evaluation criteria can lead to an incorrect assessment of the track performance evaluation of track structure, and a separate evaluation parameter for ballasted and concrete track structures is required

    Study on the Applicability of Dynamic Factor Standards by Comparison of Spring Constant Based Dynamic Factor of Ballasted and Concrete Track Structures

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    Dynamic factor evaluation method calculation methods outlined by Eisenmann (DAFEisenmann) and the American Railway Engineering Association (DAFArea) are used to calculate the dynamic factor during design and for trackside measurement, respectively, in nations where the construction of concrete track structures is relatively new. In this situation, dynamic factor calculation methods may be incorrect, and this is demonstrated by comparison of the respective track types’ total spring constant. A finite element analysis of a standard design railway track is conducted, and the design total spring constant (TSC, or K) obtained from the time history function analysis is compared to the TSC of existing tracks through trackside measurement results. The comparison result shows that TSC obtained by finite element analysis result is 22% higher than that of the trackside measurement value, indicating that the TSC is conservative in the current track design. Considering the proportional relationship between TSC and dynamic factor, it is estimated that the dynamic factor currently being applied in track design is also conservative. Based on these findings, an assessment of the applicability of different dynamic factors (DAFEisenmann and DAFArea), theoretical calculation and field measurement (DAFField) using the probabilistic analysis of wheel loads from the field measurement data is conducted. A correlative analysis between DAFEisenmann and DAFArea shows that DAFEisenmann and DAFArea were estimated to be higher by 33% and 27% in ballasted track and by 39% and 30% in concrete track than the dynamic factor derived from field measurement, respectively, which indicates that the dynamic factor currently in use can potentially lead to over-estimation in track design and maintenance
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