In this work, we address a related but different problem concerning the ordering of quantum states with respect to coherence. This result motivates the comparison among other total orders induced by different coherence measures (see e.g. For instance, the total order induced by the relative entropy of coherence and by \(\ell _1\)-norm of coherence do not coincide 14. In general, these total orders are different. Examples of coherence measures are the relative entropy of coherence 3, the \(\ell _1\)-norm of coherence 3 and the coherence of formation 6, among others 7, 8, 9, 10, 11, 12, 13.Ĭlearly, each coherence measure induces a total order on the quantum states.
More precisely, any bonafide coherence measure has to vanish only for incoherent states, to be strong monotone and convex 3 and to be maximal for maximal coherent sates as discussed in 5. There are several coherence quantifiers and most of them can be studied from an axiomatic point of view. Given any pair of quantum states, they can be classified as: (i) IO-comparable, when one state can be transformed into the other by means of IO, (ii) IO-equivalent, when both states can be transformed into the other, and (iii) IO-incomparable, when neither state can be transformed into the other.Īnother way to capture operational aspects of coherence is by means of coherence quantifiers. This preorder is useful for studying coherence transformations and classifying the set of quantum states according to its coherence resource power. The resource-theoretic formulation allows us to introduce a preorder between quantum states induced by the incoherent operations: one state is more or equally coherent than other if the former can be converted into the later by means of incoherent operations. In this work, we follow the definition of an incoherent operation (IO) introduced in 3, which has the property that coherence can not be created from an incoherent state, not even in a probabilistic way.
#Arbitrary coherence free#
Regarding the free operations of the theory, there is no single definition and each proposal leads to a different resource theory for coherence, see e.g. The rest of the states are resources and they are called coherent states. The free states of the theory, called incoherent states, are quantum states with diagonal density matrix in the incoherent basis. Since coherence is a basis-dependent notion, these three elements are defined in terms of a fixed basis, called incoherent basis. Furthermore, within the paradigm of quantum resource theories 2, quantum coherence is considered as a quantum resource that can be converted, consumed and quantified 3, 4.Īs any resource theory, the resource theory of coherence is built from three basic concepts: free states, resources and free operations. It has practical relevance in numerous fields of quantum physics, particularly in quantum information processing 1. Quantum coherence, which is a consequence of the superposition principle, is one of the fundamental aspects of the quantum theory. Qualitative and quantitative evaluations demonstrate that MCCNet performs well in arbitrary video and image style transfer tasks. To further improve the performance of MCCNet under complex light conditions, we also introduce illumination loss during training.
Moreover, MCCNet is also designed to explicitly align the features to input and thereby ensure that the outputs maintain the content structures and the temporal continuity. The outputs generated by MCC are features containing the desired style patterns that can further be decoded into images with vivid style textures. Specifically, MCCNet works directly on the feature space of style and content domain where it learns to rearrange and fuse style features on the basis of their similarity to content features. Towards this end, we propose a Multi-Channel Correlation network (MCCNet), which can be trained to fuse exemplar style features and input content features for efficient style transfer while naturally maintaining the coherence of input videos to output videos.
#Arbitrary coherence how to#
Relative to traditional image style transfer, video style transfer presents new challenges, including how to effectively generate satisfactory stylized results for any specified style while maintaining temporal coherence across frames. Video style transfer is attracting increasing attention from the artificial intelligence community because of its numerous applications, such as augmented reality and animation production. School of Artificial Intelligence, Jilin UniversityĬomputational Photography, Image & Video Synthesis Abstract NLPR, Institute of Automation, Chinese Academy of Sciences, School of Artificial Intelligence, University of Chinese Academy of Sciences,
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