5,027 research outputs found
Efficient scheme for three-photon Greenberger-Horne-Zeilinger state generation
We propose an efficient scheme for the generation of three-photon
Greenberger-Horne-Zeilinger (GHZ) state with linear optics and postselection.
Several devices are designed and a two-mode quantum nondemolition (QND)
detection is introduced to obtain the desired state. It is worth noting that
the states which have entanglement in both polarization and spatial degrees of
freedom are created in one of the designed setups. The method described in the
present scheme can create a large number of three-photon GHZ states in
principle. We also discuss an approach to generate the desired GHZ state in the
presence of channel noise.Comment: 7pages, 3 figure
Uplift, Climate and Biotic Changes at the Eocene-Oligocene Transition in Southeast Tibet
The uplift history of southeastern Tibet is crucial to understanding processes driving the tectonic evolution of the Tibetan Plateau and surrounding areas. Underpinning existing palaeoaltimetric studies has been regional mapping based in large part on biostratigraphy that assumes a Neogene modernisation of the highly diverse, but threatened, Asian biota. Here, with new radiometric dating and newly-collected plant fossil archives, we quantify the surface height of part of Tibet’s southeastern margin of Tibet in the latest Eocene (~34 Ma) to be ~3 km and rising, possibly attaining its present elevation (3.9 km) in the early Oligocene. We also find that the Eocene-Oligocene transition in southeastern Tibet witnessed leaf size diminution and a floral composition change from sub-tropical/warm temperate to cool temperate, likely reflective of both uplift and secular climate change, and that by the latest Eocene floral modernization on Tibet had already taken place implying modernization was deeply-rooted in the Paleogene
TripleRE: Knowledge Graph Embeddings via Tripled Relation Vectors
Translation-based knowledge graph embedding has been one of the most
important branches for knowledge representation learning since TransE came out.
Although many translation-based approaches have achieved some progress in
recent years, the performance was still unsatisfactory. This paper proposes a
novel knowledge graph embedding method named TripleRE with two versions. The
first version of TripleRE creatively divide the relationship vector into three
parts. The second version takes advantage of the concept of residual and
achieves better performance. In addition, attempts on using NodePiece to encode
entities achieved promising results in reducing the parametric size, and solved
the problems of scalability. Experiments show that our approach achieved
state-of-the-art performance on the large-scale knowledge graph dataset, and
competitive performance on other datasets
Phylogeny of Prokaryotes and Chloroplasts Revealed by a Simple Composition Approach on All Protein Sequences from Complete Genomes Without Sequence Alignment
The complete genomes of living organisms have provided much information on their phylogenetic relationships. Similarly, the complete genomes of chloroplasts have helped to resolve the evolution of this organelle in photosynthetic eukaryotes. In this paper we propose an alternative method of phylogenetic analysis using compositional statistics for all protein sequences from complete genomes. This new method is conceptually simpler than and computationally as fast as the one proposed by Qi et al. (2004b) and Chu et al. (2004). The same data sets used in Qi et al. (2004b) and Chu et al. (2004) are analyzed using the new method. Our distance-based phylogenic tree of the 109 prokaryotes and eukaryotes agrees with the biologists tree of life based on 16S rRNA comparison in a predominant majority of basic branching and most lower taxa. Our phylogenetic analysis also shows that the chloroplast genomes are separated to two major clades corresponding to chlorophytes s.l. and rhodophytes s.l. The interrelationships among the chloroplasts are largely in agreement with the current understanding on chloroplast evolution
Model Compression and Efficient Inference for Large Language Models: A Survey
Transformer based large language models have achieved tremendous success.
However, the significant memory and computational costs incurred during the
inference process make it challenging to deploy large models on
resource-constrained devices. In this paper, we investigate compression and
efficient inference methods for large language models from an algorithmic
perspective. Regarding taxonomy, similar to smaller models, compression and
acceleration algorithms for large language models can still be categorized into
quantization, pruning, distillation, compact architecture design, dynamic
networks. However, Large language models have two prominent characteristics
compared to smaller models: (1) Most of compression algorithms require
finetuning or even retraining the model after compression. The most notable
aspect of large models is the very high cost associated with model finetuning
or training. Therefore, many algorithms for large models, such as quantization
and pruning, start to explore tuning-free algorithms. (2) Large models
emphasize versatility and generalization rather than performance on a single
task. Hence, many algorithms, such as knowledge distillation, focus on how to
preserving their versatility and generalization after compression. Since these
two characteristics were not very pronounced in early large models, we further
distinguish large language models into medium models and ``real'' large models.
Additionally, we also provide an introduction to some mature frameworks for
efficient inference of large models, which can support basic compression or
acceleration algorithms, greatly facilitating model deployment for users.Comment: 47 pages, review 380 papers. The work is ongoin
Colossal dielectric constants in transition-metal oxides
Many transition-metal oxides show very large ("colossal") magnitudes of the
dielectric constant and thus have immense potential for applications in modern
microelectronics and for the development of new capacitance-based
energy-storage devices. In the present work, we thoroughly discuss the
mechanisms that can lead to colossal values of the dielectric constant,
especially emphasising effects generated by external and internal interfaces,
including electronic phase separation. In addition, we provide a detailed
overview and discussion of the dielectric properties of CaCu3Ti4O12 and related
systems, which is today's most investigated material with colossal dielectric
constant. Also a variety of further transition-metal oxides with large
dielectric constants are treated in detail, among them the system La2-xSrxNiO4
where electronic phase separation may play a role in the generation of a
colossal dielectric constant.Comment: 31 pages, 18 figures, submitted to Eur. Phys. J. for publication in
the Special Topics volume "Cooperative Phenomena in Solids: Metal-Insulator
Transitions and Ordering of Microscopic Degrees of Freedom
Asymptotic Analytical Solutions of First-Passage Rate to Quasi- Nonintegrable Hamiltonian Systems
The first-passage problem of quasi-nonintegrable Hamiltonian systems subject to light linear/nonlinear dampings and weak external/parametric random excitations is investigated here. The motivation is to acquire asymptotic analytical solution of the firstpassage rate or the mean first-passage time based on the averaged Itô stochastic differential equation for quasi-nonintegrable Hamiltonian systems. By using the probability current equation and the Laplace integral method, a new method is proposed to obtain the asymptotic analytical expressions for the first-passage rate in the case of high passage threshold. The associated functions such as the reliability function and the probability density function of first-passage time can then be obtained from the first-passage rate. High passage threshold is the crucial condition for the validity of the proposed method. The random bistable oscillator is studied as an illustrative example using the method. The analytical result obtained from the asymptotic analysis shows its consistency with the Kramers formula. A coupled two-degree-of-freedom (2DOF) nonlinear oscillator subjected to stochastic excitations is studied to illustrate the procedure of acquiring the asymptotic analytical solution. The results obtained from the analytical solution agree well with those from numerical simulation, which verifies the accuracy of the proposed method
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