Updates SWH
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@ -237,13 +237,14 @@ i@article{watson_2016,
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issn = {1549-9618},
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publisher = {American Chemical Society},
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doi = {10.1021/acs.jctc.9b00176},
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note = {\url{https://archive.softwareheritage.org/swh:1:dir:6d82ae7ac757c78d7720dd89dfa52d7a453d2f68;origin=https://github.com/QuantumPackage/qp2;visit=swh:1:snp:1f9d307c45a14259eea8991c328065400029b975;anchor=swh:1:rev:c63b69e8dac8017d6415df602c5f7f5c02e35a2a;path=/src/ccsd/}}
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note = {\url{
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swh:1:dir:6d82ae7ac757c78d7720dd89dfa52d7a453d2f68;origin=https://github.com/QuantumPackage/qp2;visit=swh:1:snp:402c2c2b30ef63cfd75b7a985700bc794ff07859;anchor=swh:1:rev:0c8845f5f208e1c405a6aa5aba1ceb276ddbdcdf;path=/src/ccsd/}}
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}
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@misc{form_w_abc,
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title = {Formation of the {$W$} tensor in Quantum Package},
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year = {2024},
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note = {\url{https://archive.softwareheritage.org/swh:1:cnt:12a71045f2333584fe7b499f1c70b5ff2dc4989c;origin=https://github.com/QuantumPackage/qp2;visit=swh:1:snp:1f9d307c45a14259eea8991c328065400029b975;anchor=swh:1:rev:c63b69e8dac8017d6415df602c5f7f5c02e35a2a;path=/src/ccsd/ccsd_t_space_orb_abc.irp.f;lines=233-395}}
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note = {\url{https://archive.softwareheritage.org/swh:1:cnt:12a71045f2333584fe7b499f1c70b5ff2dc4989c;origin=https://github.com/QuantumPackage/qp2;visit=swh:1:snp:402c2c2b30ef63cfd75b7a985700bc794ff07859;anchor=swh:1:rev:0c8845f5f208e1c405a6aa5aba1ceb276ddbdcdf;path=/src/ccsd/ccsd_t_space_orb_abc.irp.f;lines=233-395}}
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}
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@ -376,7 +376,7 @@ less precise data points. These findings are supported by an analysis of
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machine learning models, where noise not only helped improve model accuracy but
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also enabled error estimation in model predictions.
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Similarly to QMC, our semi-stochastic formulation could take advantage of many
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low-accuracy points.
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points computed with a low accuracy.
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In this section, we discuss the application of our novel algorithm within the context of computing vibrational frequencies, specifically through the example of copper chloride (\ce{CuCl}).
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