Using a quantum computer to simulate fermionic systems requires fermion-to-qubit transformations.Usually,lower Pauli weight of transformations means shallower quantum circuits.Therefore,most existing transformations a...Using a quantum computer to simulate fermionic systems requires fermion-to-qubit transformations.Usually,lower Pauli weight of transformations means shallower quantum circuits.Therefore,most existing transformations aim for lower Pauli weight.However,in some cases,the circuit depth depends not only on the Pauli weight but also on the coefficients of the Hamiltonian terms.In order to characterize the circuit depth of these algorithms,we propose a new metric called weighted Pauli weight,which depends on Pauli weight and coefficients of Hamiltonian terms.To achieve smaller weighted Pauli weight,we introduce a novel transformation,Huffman-code-based ternary tree(HTT)transformation,which is built upon the classical Huffman code and tailored to different Hamiltonians.We tested various molecular Hamiltonians and the results show that the weighted Pauli weight of the HTT transformation is smaller than that of commonly used mappings.At the same time,the HTT transformation also maintains a relatively small Pauli weight.The mapping we designed reduces the circuit depth of certain Hamiltonian simulation algorithms,facilitating faster simulation of fermionic systems.展开更多
As video compression is one of the core technologies required to enable seamless medical data streaming in mobile healthcare applications,there is a need to develop powerful media codecs that can achieve minimum bitra...As video compression is one of the core technologies required to enable seamless medical data streaming in mobile healthcare applications,there is a need to develop powerful media codecs that can achieve minimum bitrates while maintaining high perceptual quality.Versatile Video Coding(VVC)is the latest video coding standard that can provide powerful coding performance with a similar visual quality compared to the previously developed method that is High Efficiency Video Coding(HEVC).In order to achieve this improved coding performance,VVC adopted various advanced coding tools,such as flexible Multi-type Tree(MTT)block structure which uses Binary Tree(BT)split and Ternary Tree(TT)split.However,VVC encoder requires heavy computational complexity due to the excessive Ratedistortion Optimization(RDO)processes used to determine the optimalMTT block mode.In this paper,we propose a fast MTT decision method with two Lightweight Neural Networks(LNNs)using Multi-layer Perceptron(MLP),which are applied to determine the early termination of the TT split within the encoding process.Experimental results show that the proposed method significantly reduced the encoding complexity up to 26%with unnoticeable coding loss compared to the VVC TestModel(VTM).展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2024YFB4504101)the National Nat-ural Science Foundation of China(Grant No.22303022)the Anhui Province Innovation Plan for Science and Technology(Grant No.202423r06050002).
文摘Using a quantum computer to simulate fermionic systems requires fermion-to-qubit transformations.Usually,lower Pauli weight of transformations means shallower quantum circuits.Therefore,most existing transformations aim for lower Pauli weight.However,in some cases,the circuit depth depends not only on the Pauli weight but also on the coefficients of the Hamiltonian terms.In order to characterize the circuit depth of these algorithms,we propose a new metric called weighted Pauli weight,which depends on Pauli weight and coefficients of Hamiltonian terms.To achieve smaller weighted Pauli weight,we introduce a novel transformation,Huffman-code-based ternary tree(HTT)transformation,which is built upon the classical Huffman code and tailored to different Hamiltonians.We tested various molecular Hamiltonians and the results show that the weighted Pauli weight of the HTT transformation is smaller than that of commonly used mappings.At the same time,the HTT transformation also maintains a relatively small Pauli weight.The mapping we designed reduces the circuit depth of certain Hamiltonian simulation algorithms,facilitating faster simulation of fermionic systems.
基金This work was supported by Institute for Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2017-0-00072,Development of Audio/Video Coding and Light Field Media Fundamental Technologies for Ultra Realistic Tera-media)。
文摘As video compression is one of the core technologies required to enable seamless medical data streaming in mobile healthcare applications,there is a need to develop powerful media codecs that can achieve minimum bitrates while maintaining high perceptual quality.Versatile Video Coding(VVC)is the latest video coding standard that can provide powerful coding performance with a similar visual quality compared to the previously developed method that is High Efficiency Video Coding(HEVC).In order to achieve this improved coding performance,VVC adopted various advanced coding tools,such as flexible Multi-type Tree(MTT)block structure which uses Binary Tree(BT)split and Ternary Tree(TT)split.However,VVC encoder requires heavy computational complexity due to the excessive Ratedistortion Optimization(RDO)processes used to determine the optimalMTT block mode.In this paper,we propose a fast MTT decision method with two Lightweight Neural Networks(LNNs)using Multi-layer Perceptron(MLP),which are applied to determine the early termination of the TT split within the encoding process.Experimental results show that the proposed method significantly reduced the encoding complexity up to 26%with unnoticeable coding loss compared to the VVC TestModel(VTM).
