{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ab-initio-calculation-of-real-solids-via","title":"Ab initio calculation of real solids via neural network ansatz","arxiv_id":"2203.15472","date":"2022-03-29","proceeding":null,"authors":["Xiang Li","Zhe Li","Ji Chen"],"abstract":"Neural networks have been applied to tackle many-body electron correlations for small molecules and physical models in recent years. Here we propose a new architecture that extends molecular neural networks with the inclusion of periodic boundary conditions to enable ab initio calculation of real solids. The accuracy of our approach is demonstrated in four different types of systems, namely the one-dimensional periodic hydrogen chain, the two-dimensional graphene, the three-dimensional lithium hydride crystal, and the homogeneous electron gas, where the obtained results, e.g. total energies, dissociation curves, and cohesive energies, outperform many traditional ab initio methods and reach the level of the most accurate approaches. Moreover, electron densities of typical systems are also calculated to provide physical intuition of various solids. Our method of extending a molecular neural network to periodic systems can be easily integrated into other neural network structures, highlighting a promising future of ab initio solution of more complex solid systems using neural network ansatz, and more generally endorsing the application of machine learning in materials simulation and condensed matter physics.","url_abs":"https://arxiv.org/abs/2203.15472v2","url_pdf":"https://arxiv.org/pdf/2203.15472v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"ab-initio-calculation-of-real-solids-via","repo_url":"https://github.com/bytedance/deepsolid","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"jax","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2203.15472","atlas_url":"https://app.syntology.ai/?focus=2203.15472","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.15472"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/bytedance/deepsolid","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":11,"unverified":5},"by_repo_kind":{"official":{"samples":16,"ran":11,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"aca630458a5d37c0","entry":"enforce_pbc","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/network.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/network.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"aca630458a5d37c0"}},{"code_sha256_prefix":"46014595574a2588","entry":"get_restore_path","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/checkpoint.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/checkpoint.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"46014595574a2588"}},{"code_sha256_prefix":"564925745b0dbab8","entry":"init_solid_fermi_net_params","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/network.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/network.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"564925745b0dbab8"}},{"code_sha256_prefix":"c8ab9823d4a04e02","entry":"local_kinetic_energy","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/hamiltonian.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/hamiltonian.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"c8ab9823d4a04e02"}},{"code_sha256_prefix":"9a2f5254b9004fff","entry":"local_kinetic_energy_real_imag","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/hamiltonian.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/hamiltonian.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"9a2f5254b9004fff"}},{"code_sha256_prefix":"85201fb3f5113d38","entry":"local_kinetic_energy_real_imag_dim_batch","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/hamiltonian.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/hamiltonian.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"85201fb3f5113d38"}},{"code_sha256_prefix":"044f4db035ee4c04","entry":"make_different_rng_key_on_all_devices","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/constants.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/constants.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"044f4db035ee4c04"}},{"code_sha256_prefix":"e5219d5df83dd3c4","entry":"np_enforce_pbc","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/distance.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/distance.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e5219d5df83dd3c4"}},{"code_sha256_prefix":"bf41787fb763d98d","entry":"resolve","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/base_config.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/base_config.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"bf41787fb763d98d"}},{"code_sha256_prefix":"bdb782a698bde89d","entry":"scaled_f","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/network.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/network.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"bdb782a698bde89d"}},{"code_sha256_prefix":"7cca7b1b82215a77","entry":"wrap_if_pmap","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/constants.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/constants.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7cca7b1b82215a77"}},{"code_sha256_prefix":"75ce92be27f93323","entry":"create_save_path","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/checkpoint.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/checkpoint.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"75ce92be27f93323"}},{"code_sha256_prefix":"ae13781efdf47223","entry":"enforce_pbc","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/distance.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/distance.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"ae13781efdf47223"}},{"code_sha256_prefix":"83cf365025dc973d","entry":"find_last_checkpoint","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/checkpoint.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/checkpoint.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"83cf365025dc973d"}},{"code_sha256_prefix":"d169a08cfcf72de2","entry":"replicate_all_local_devices","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/constants.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/constants.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"d169a08cfcf72de2"}},{"code_sha256_prefix":"b8423ac3becb0470","entry":"select_big","repo":"bytedance/deepsolid","repo_kind":"official","path":"DeepSolid/ewaldsum.py","file_url":"https://github.com/bytedance/deepsolid/blob/HEAD/DeepSolid/ewaldsum.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"b8423ac3becb0470"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}