Entanglement and Tensor Network (TN)
Tensor Network Methods for Quantum Phases
... via tensor networks) or obtain expectations with respect to ground states ...sampling). Tensor network (TN) methods have proven very useful for this pur- pose, [ ...
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A simple tensor network algorithm for two-dimensional steady states
... There seems to be, however, one problem with this idea: unlike in imaginary time evolution, we are now dealing with real-time. In the master equation, part of the evolution is generated by a Hamiltonian H, and part by ...
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Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
... tree tensor network states (TTNS), and give a step-by- step demonstration of how we can manipulate ab initio data with machine-learning techniques to formulate the problem in a form suitable for TTNS ...the ...
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Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
... allows tensor network methods to effectively compute the non-perturbative, real-time dynamics of exponentially large vibronic wave functions of real ...and entanglement analysis can enable ...
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Tensor Network Wavefunctions for Topological Phases
... where tensor network represen- tations lead to novel insights into strongly correlated physics beyond what is accessi- ble to more traditional methods, such as the quantum-to-classical mappings pursued in ...
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Isometric Tensor Network States in Two Dimensions.
... entire network using, ...This entanglement is different from the vertical entanglement of the full many-body wave function: it differs by the action of the isometries, which contain the 2D area law ...
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T3NS : three-legged tree tensor network states
... E-mail: [email protected] Abstract We present a new variational tree tensor net- work state (TTNS) ansatz, the three-legged tree tensor network state (T3NS). Physical ten- sors are interspersed ...
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Entanglement rates and the stability of the area law for the entanglement entropy
... entanglement entropy of the reduced density matrix of such a ground state of a certain subregion scales with the size of the boundary of this region, instead of the volume law scaling of a typical quantum many ...
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Symmetries in topological tensor network states: classification, construction and detection
... is entanglement : the correlations between the parties of a system that cannot be described ...the entanglement properties of strongly-correlated systems plays a fundamental role for condensed-matter ...the ...
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Tensor network methods for Radiotherapy Dose Optimization
... the entanglement in a pure system we always need to consider a bipartion of the system into two subsystems A and B, compute the reduced density matrix of one them and evaluate its entanglement entropy in ...
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Tensor Network study of the (1+1)-dimensional Thirring Model
... bipartite entanglement entropy, we divide the system into two equal-size subsystems, A and B, and then determine the entanglement entropy S A | B using ...
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Tensor on tensor regression with tensor normal errors and tensor network states on the regression parameter
... Note that based on equation 7.2 the first two elements in the second differential corre- spond to the second differential of the complete log likelihood of n iid samples from the tensor normal distribution with ...
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Emergence of Network Bifurcation Triggered by Entanglement
... In many non-linear systems, such as plasma oscillation, boson condensation, chemical reaction, and even predatory- prey oscillation, the coarse-grained dy- namics are governed by an equation con- taining anti-symmetric ...
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Parameterization of Tensor Network Contraction
... allow tensor networks (G, M) in which G is a ...“copy” tensor with k legs of the same bond dimension b [5]. The copy tensor is one when all indices have the same value and is zero ...a tensor ...
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Entanglement Classification via Neural Network Quantum States
... state entanglement. 3.5. Efficiency of entanglement classification via NNS The effectiveness and efficiency of our entanglement classification method stems from the reduction of the problem from ...
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Quantum Competition Network Model Based On Quantum Entanglement
... In the past ten years, the academic papers and reports about quantum computing have been widely published; the theory of quantum computing has made great progress, however, to the successful development of a practical ...
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Tensor Fusion Network for Multimodal Sentiment Analysis
... Carnegie Mellon University [email protected] Abstract Multimodal sentiment analysis is an in- creasingly popular research area, which extends the conventional language-based definition of sentiment analysis to a mul- ...
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Symmetric topological phases and tensor network states:
... Topological orders in 2+1D are well studied. They are classified by tensor categories[82]. Ground states of a topological ordered state are degenerate if one put the system on a closed manifold. Low-energy ...
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Multimodal Relational Tensor Network for Sentiment and Emotion Classification
... Relational Tensor Network archi- tecture where we use the inter-modal in- teractions within a segment and also con- sider the sequence of segments in a video to model the inter-segment inter-modal in- ...
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Entanglement properties of a measurement-based entanglement distillation experiment
... of entanglement can be employed for the analysis of numerous quantum information ...measurement-based entanglement distillation experiment using a collection of entanglement ...negativity, ...
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