The supertranslation ambiguity issue of angular momentum is a long-standing problem in general relativity.Recently,there appeared the first definition of angular momentum at null infinity that is supertranslation inva...The supertranslation ambiguity issue of angular momentum is a long-standing problem in general relativity.Recently,there appeared the first definition of angular momentum at null infinity that is supertranslation invariant.However,in the compact binary coalescence community,supertranslation ambiguity is often ignored.This paper demonstrates that we have the happy circumstance that the newly defined angular momentum coincides with the classical definition at the quadrupole level.展开更多
Among the rich spectrum of GW sources,galactic compact binaries(GCBs) and extreme mass-ratio inspirals(EMRIs) stand out as crucial targets for space-based detectors.GCBs pose challenges in signal extraction due to the...Among the rich spectrum of GW sources,galactic compact binaries(GCBs) and extreme mass-ratio inspirals(EMRIs) stand out as crucial targets for space-based detectors.GCBs pose challenges in signal extraction due to their overlapping nature.This paper introduces a deep learning framework designed to separate overlapping GCB and EMRI GW signals.The framework employs a two-stage approach:initially,we consider the mixed GCB waveforms as an ensemble,and an ensemble separation method is utilized to separate the mixed GCBs and EMRI signals;subsequently,a recursive reasoning process is applied to further isolate individual GCB signals from the mixed GCB ensemble.We demonstrate the model's robust performance across varying signal-to-noise ratios(SNRs) and overlapping signal counts.The framework exhibits high separation fidelity,particularly for the ensemble separation stage,with overlap metrics exceeding 0.998 under the same parameter ranges of the training set,thereby ensuring accurate signal extraction for subsequent recursive reasoning.For the recursive reasoning process,we have empirically demonstrated that the deep learning framework is capable of effectively separating mixed GCB GW signals even when the frequency differences between them are near or marginally below the frequency resolution limit.We have also observed that the proposed framework exhibits generalization capabilities when applied to GW strain data characterized by lower SNR ranges and larger numbers of mixed GCB signals.展开更多
Most efficient indeces and query techniques over XML （extensible markup language） data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between tw...Most efficient indeces and query techniques over XML （extensible markup language） data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between two nodes. The current basic labeling schemes such as containment scheme and prefix scheme cannot avoid re- labeling when XML documents are updated. After analyzing the essence of existing dynamic XML labels such as compact dynamic binary string （CDBS） and vector encoding, this paper gives a common unifying framework for the numeric-based generalized dynamic label, which can be implemented into a variety of dynamic labels according to the different user-defined value comparison methods. This paper also proposes a novel dynamic labeling scheme called radical sign label. Extensive experiments show that the radical sign label performs well for the initialization, insertion and query operations, and especially for skewed insertion where the storage cost of the radical sign label is better than that of former methods.展开更多
The effective one-body theories, introduced by Buonanno and Damour, are novel approaches to constructing a gravitational waveform template. By taking a gauge in which ψ_(1)^(B) and ψ_(3)^(B) vanish, we find a decoup...The effective one-body theories, introduced by Buonanno and Damour, are novel approaches to constructing a gravitational waveform template. By taking a gauge in which ψ_(1)^(B) and ψ_(3)^(B) vanish, we find a decoupled equation with separable variables for ψ_(4)^(B) in the effective metric obtained in the post-Minkowskian approximation. Furthermore, we set up a new self-consistent effective one-body theory for spinless binaries, which can be applicable to any post-Minkowskian orders. This theory not only releases the assumption that v/c should be a small quantity but also resolves the contradiction that the Hamiltonian, radiation-reaction force, and waveform are constructed from different physical models in the effective one-body theory with the post-Newtonian approximation. Compared with our previous theory [Sci. China-Phys. Mech. Astron. 65, 260411(2022)], the computational effort for the radiation-reaction force and waveform in this new theory will be tremendously reduced.展开更多
基金partially supported by the Key Project of the Education Department of Hunan Province (21A0576)partially supported by the National Natural Science Foundation of China (11731001)partially supported by the National Natural Science Foundation of China (11671089)。
文摘The supertranslation ambiguity issue of angular momentum is a long-standing problem in general relativity.Recently,there appeared the first definition of angular momentum at null infinity that is supertranslation invariant.However,in the compact binary coalescence community,supertranslation ambiguity is often ignored.This paper demonstrates that we have the happy circumstance that the newly defined angular momentum coincides with the classical definition at the quadrupole level.
基金supported by the National Key Research and Development Program of China (Grant No.2021YFC2203001)the National Natural Science Foundation of China (Grant Nos.12463012,11920101003+2 种基金12021003)the Natural Science Foundation of Jiangxi (Grant Nos.20224BAB211012,and 20252BAC220003)the Jiangxi Province Key Laboratory of Multidimensional Intelligent Perception and Control of China(Grant No.2024SSY03161)。
文摘Among the rich spectrum of GW sources,galactic compact binaries(GCBs) and extreme mass-ratio inspirals(EMRIs) stand out as crucial targets for space-based detectors.GCBs pose challenges in signal extraction due to their overlapping nature.This paper introduces a deep learning framework designed to separate overlapping GCB and EMRI GW signals.The framework employs a two-stage approach:initially,we consider the mixed GCB waveforms as an ensemble,and an ensemble separation method is utilized to separate the mixed GCBs and EMRI signals;subsequently,a recursive reasoning process is applied to further isolate individual GCB signals from the mixed GCB ensemble.We demonstrate the model's robust performance across varying signal-to-noise ratios(SNRs) and overlapping signal counts.The framework exhibits high separation fidelity,particularly for the ensemble separation stage,with overlap metrics exceeding 0.998 under the same parameter ranges of the training set,thereby ensuring accurate signal extraction for subsequent recursive reasoning.For the recursive reasoning process,we have empirically demonstrated that the deep learning framework is capable of effectively separating mixed GCB GW signals even when the frequency differences between them are near or marginally below the frequency resolution limit.We have also observed that the proposed framework exhibits generalization capabilities when applied to GW strain data characterized by lower SNR ranges and larger numbers of mixed GCB signals.
基金the National Major Projects on Science and Technology(No.2010ZX01042-002-003-004)the National Basic Research Program (973) of China(No.2010CB328106)+2 种基金the National Natural Science Foundation of China(No. 61170085)the Program for New Century Excellent Talents in China(No.NCET-10-0388)the Shanghai Leading Academic Discipline Project(No.B412)
文摘Most efficient indeces and query techniques over XML （extensible markup language） data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between two nodes. The current basic labeling schemes such as containment scheme and prefix scheme cannot avoid re- labeling when XML documents are updated. After analyzing the essence of existing dynamic XML labels such as compact dynamic binary string （CDBS） and vector encoding, this paper gives a common unifying framework for the numeric-based generalized dynamic label, which can be implemented into a variety of dynamic labels according to the different user-defined value comparison methods. This paper also proposes a novel dynamic labeling scheme called radical sign label. Extensive experiments show that the radical sign label performs well for the initialization, insertion and query operations, and especially for skewed insertion where the storage cost of the radical sign label is better than that of former methods.
基金supported by the National Natural Science Foundation of China (Grant Nos. 12035005, 12122504, and 11875025)National Key Research and Development Program of China (Grant No.2020YFC2201400)。
文摘The effective one-body theories, introduced by Buonanno and Damour, are novel approaches to constructing a gravitational waveform template. By taking a gauge in which ψ_(1)^(B) and ψ_(3)^(B) vanish, we find a decoupled equation with separable variables for ψ_(4)^(B) in the effective metric obtained in the post-Minkowskian approximation. Furthermore, we set up a new self-consistent effective one-body theory for spinless binaries, which can be applicable to any post-Minkowskian orders. This theory not only releases the assumption that v/c should be a small quantity but also resolves the contradiction that the Hamiltonian, radiation-reaction force, and waveform are constructed from different physical models in the effective one-body theory with the post-Newtonian approximation. Compared with our previous theory [Sci. China-Phys. Mech. Astron. 65, 260411(2022)], the computational effort for the radiation-reaction force and waveform in this new theory will be tremendously reduced.
