دورية أكاديمية
A Nonstochastic Optimization Algorithm for Neural-Network Quantum States
| العنوان: | A Nonstochastic Optimization Algorithm for Neural-Network Quantum States |
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| المؤلفون: | Xiang Li, Jia-Cheng Huang, Guang-Ze Zhang, Hao-En Li, Chang-Su Cao, Dingshun Lv, Han-Shi Hu |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Biophysics, Medicine, Space Science, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Physical Sciences not elsewhere classified, Information Systems not elsewhere classified, variational monte carlo, nonstochastic optimization algorithm, network quantum states, important configurations simultaneously, entire optimization process, body wave functions, superior accuracy compared, nqs offers comparable, efficiency compared, vmc framework, vmc ), thereby accelerating, stochastic counterpart, stable convergence, selected set, second quantization, opens avenues, method bypasses, future enhancements, energy evaluation, encode many, deterministically generates, chemical systems |
| الوصف: | Neural-network quantum states (NQS) employ artificial neural networks to encode many-body wave functions in a second quantization through variational Monte Carlo (VMC). They have recently been applied to accurately describe electronic wave functions of molecules and have shown the challenges in efficiency compared with traditional quantum chemistry methods. Here, we introduce a general nonstochastic optimization algorithm for NQS in chemical systems, which deterministically generates a selected set of important configurations simultaneously with energy evaluation of NQS. This method bypasses the need for Markov-chain Monte Carlo within the VMC framework, thereby accelerating the entire optimization process. Furthermore, this newly developed nonstochastic optimization algorithm for NQS offers comparable or superior accuracy compared to its stochastic counterpart and ensures more stable convergence. The application of this model to test molecules exhibiting strong electron correlations provides further insight into the performance of NQS in chemical systems and opens avenues for future enhancements. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| العلاقة: | https://figshare.com/articles/journal_contribution/A_Nonstochastic_Optimization_Algorithm_for_Neural-Network_Quantum_States/24648034Test |
| DOI: | 10.1021/acs.jctc.3c00831.s001 |
| الإتاحة: | https://doi.org/10.1021/acs.jctc.3c00831.s001Test https://figshare.com/articles/journal_contribution/A_Nonstochastic_Optimization_Algorithm_for_Neural-Network_Quantum_States/24648034Test |
| حقوق: | CC BY-NC 4.0 |
| رقم الانضمام: | edsbas.B6A77F1C |
| قاعدة البيانات: | BASE |
| DOI: | 10.1021/acs.jctc.3c00831.s001 |
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