qmb - npm Package Compare versions

Comparing version 0.0.51 to 0.0.52

qmb/pert.py

+"""
+This file implements a perturbation estimator from haar.
+"""
+
+import logging
+import typing
+import dataclasses
+import tyro
+from .common import CommonConfig
+from .subcommand_dict import subcommand_dict
+
+
[e-mail]
+class PerturbationConfig:
+    """
+    The perturbation estimator from haar.
+    """
+
+    common: typing.Annotated[CommonConfig, tyro.conf.OmitArgPrefixes]
+
+    def main(self, *, model_param: typing.Any = None, network_param: typing.Any = None) -> None:
+        """
+        The main function of two-step optimization process based on imaginary time.
+        """
+        # pylint: disable=too-many-locals
+        # pylint: disable=too-many-statements
+        # pylint: disable=too-many-branches
+
+        model, _, data = self.common.main(model_param=model_param, network_param=network_param)
+
+        if "haar" not in data and "imag" in data:
+            data["haar"] = data.pop("imag")
+        configs, psi = data["haar"]["pool"]
+        configs = configs.to(self.common.device)
+        psi = psi.to(self.common.device)
+
+        energy0_num = psi.conj() @ model.apply_within(configs, psi, configs)
+        energy0_den = psi.conj() @ psi
+        energy0 = (energy0_num / energy0_den).real.item()
+        logging.info("Current energy is %.8f", energy0)
+        logging.info("Reference energy is %.8f", model.ref_energy)
+
+        number = configs.size(0)
+        last_result_number = 0
+        current_target_number = number
+        logging.info("Starting finding relative configurations with %d.", number)
+        while True:
+            other_configs = model.find_relative(configs, psi, current_target_number, configs)
+            current_result_number = other_configs.size(0)
+            logging.info("Found %d relative configurations.", current_result_number)
+            if current_result_number == last_result_number:
+                logging.info("No new configurations found, stopping at %d.", current_result_number)
+                break
+            current_target_number = current_target_number * 2
+            logging.info("Doubling target number to %d.", current_target_number)
+            break
+
+        hamiltonian_psi = model.apply_within(configs, psi, other_configs)
+        energy2_num = (hamiltonian_psi.conj() @ hamiltonian_psi).real / (psi.conj() @ psi).real
+        energy2_den = energy0 - model.diagonal_term(other_configs).real
+        energy2 = (energy2_num / energy2_den).sum().item()
+        logging.info("Correct energy is %.8f", energy2)
+        logging.info("Error is reduced from %.8f to %.8f", energy0 - model.ref_energy, energy2 - model.ref_energy)
+
+
+subcommand_dict["pert"] = PerturbationConfig

.github/workflows/docker.yml

@@ -20,3 +20,3 @@ name: Build docker images
 
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
         with:
@@ -23,0 +23,0 @@ fetch-depth: 0

.github/workflows/pre-commit.yml

@@ -12,3 +12,3 @@ name: Pre-commit Hooks
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
 
@@ -15,0 +15,0 @@ - uses: actions/setup-python@v5

.github/workflows/wheels.yml

@@ -13,3 +13,3 @@ name: Build wheels
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
         with:
@@ -31,3 +31,3 @@ fetch-depth: 0
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
         with:
@@ -53,6 +53,6 @@ fetch-depth: 0
       id-token: write
-    if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && github.event.repository.visibility == 'public'
+    if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v')
 
     steps:
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         with:
@@ -59,0 +59,0 @@ pattern: build-*

Dockerfile

 # Use the specified CUDA base image with Rocky Linux 9
-FROM nvidia/cuda:12.9.1-cudnn-devel-rockylinux9
+FROM nvidia/cuda:13.0.0-cudnn-devel-rockylinux9
 
@@ -4,0 +4,0 @@ # Install dependencies

PKG-INFO

 Metadata-Version: 2.4
 Name: qmb
-Version: 0.0.51
+Version: 0.0.52
 Summary: Quantum Manybody Problem
@@ -25,11 +25,11 @@ Author-email: Hao Zhang <[e-mail]>
 Requires-Dist: platformdirs~=4.3.7
-Requires-Dist: numpy~=1.26.4
-Requires-Dist: scipy~=1.15.2
-Requires-Dist: torch<2.8,>=2.6
-Requires-Dist: pybind11~=2.13.6
-Requires-Dist: ninja~=1.11.1.4
+Requires-Dist: numpy<2.4.0,>=1.26.4
+Requires-Dist: scipy<1.17.0,>=1.15.2
+Requires-Dist: torch<2.9,>=2.6
+Requires-Dist: pybind11<3.1.0,>=2.13.6
+Requires-Dist: ninja<1.13.1.0,>=1.11.1.4
 Requires-Dist: tyro~=0.9.18
 Requires-Dist: pyyaml~=6.0.2
 Requires-Dist: openfermion~=1.7.0
-Requires-Dist: tensorboard~=2.19.0
+Requires-Dist: tensorboard<2.21,>=2.19
 Requires-Dist: standard-imghdr~=3.13.0; python_version >= "3.13"
@@ -41,9 +41,9 @@ Provides-Extra: dev
 Requires-Dist: pytest<8.5.0,>=8.3.5; extra == "dev"
-Requires-Dist: pytest-cov~=6.0.0; extra == "dev"
+Requires-Dist: pytest-cov<6.3,>=6.0; extra == "dev"
 Requires-Dist: types-pyyaml~=6.0.12.20250326; extra == "dev"
 Dynamic: license-file
 
-# An efficient Neural-Network Quantum States Architecture for Strongly Correlated Systems
+# Hamiltonian-Guided Autoregressive Selected-Configuration Interaction(HAAR-SCI) Achieves Chemical Accuracy in Strongly Correlated Systems
 
-The Quantum-Many-Body (`qmb`) is a powerful tool designed to solve quantum-many-body problems.
+The current project temporarily named as Quantum-Many-Body (`qmb`) which is a powerful tool designed to solve quantum-many-body problems especially for strongly correlated systems.
 
@@ -50,0 +50,0 @@ ## About The Project

pyproject.toml

 [build-system]
-requires = ["setuptools>=78.0,<80.10", "setuptools_scm~=8.2.0"]
+requires = ["setuptools>=78.0,<80.10", "setuptools_scm>=8.2,<9.3"]
 build-backend = "setuptools.build_meta"
@@ -10,11 +10,11 @@
   "platformdirs~=4.3.7",
-  "numpy~=1.26.4",
-  "scipy~=1.15.2",
-  "torch>=2.6,<2.8",
-  "pybind11~=2.13.6",
-  "ninja~=1.11.1.4",
+  "numpy>=1.26.4,<2.4.0",
+  "scipy>=1.15.2,<1.17.0",
+  "torch>=2.6,<2.9",
+  "pybind11>=2.13.6,<3.1.0",
+  "ninja>=1.11.1.4,<1.13.1.0",
   "tyro~=0.9.18",
   "pyyaml~=6.0.2",
   "openfermion~=1.7.0",
-  "tensorboard~=2.19.0",
+  "tensorboard>=2.19,<2.21",
   "standard-imghdr~=3.13.0 ; python_version>='3.13'",
@@ -46,3 +46,3 @@ ]
   "pytest>=8.3.5,<8.5.0",
-  "pytest-cov~=6.0.0",
+  "pytest-cov>=6.0,<6.3",
   "types-pyyaml~=6.0.12.20250326",
@@ -49,0 +49,0 @@ ]

qmb.egg-info/PKG-INFO

 Metadata-Version: 2.4
 Name: qmb
-Version: 0.0.51
+Version: 0.0.52
 Summary: Quantum Manybody Problem
@@ -25,11 +25,11 @@ Author-email: Hao Zhang <[e-mail]>
 Requires-Dist: platformdirs~=4.3.7
-Requires-Dist: numpy~=1.26.4
-Requires-Dist: scipy~=1.15.2
-Requires-Dist: torch<2.8,>=2.6
-Requires-Dist: pybind11~=2.13.6
-Requires-Dist: ninja~=1.11.1.4
+Requires-Dist: numpy<2.4.0,>=1.26.4
+Requires-Dist: scipy<1.17.0,>=1.15.2
+Requires-Dist: torch<2.9,>=2.6
+Requires-Dist: pybind11<3.1.0,>=2.13.6
+Requires-Dist: ninja<1.13.1.0,>=1.11.1.4
 Requires-Dist: tyro~=0.9.18
 Requires-Dist: pyyaml~=6.0.2
 Requires-Dist: openfermion~=1.7.0
-Requires-Dist: tensorboard~=2.19.0
+Requires-Dist: tensorboard<2.21,>=2.19
 Requires-Dist: standard-imghdr~=3.13.0; python_version >= "3.13"
@@ -41,9 +41,9 @@ Provides-Extra: dev
 Requires-Dist: pytest<8.5.0,>=8.3.5; extra == "dev"
-Requires-Dist: pytest-cov~=6.0.0; extra == "dev"
+Requires-Dist: pytest-cov<6.3,>=6.0; extra == "dev"
 Requires-Dist: types-pyyaml~=6.0.12.20250326; extra == "dev"
 Dynamic: license-file
 
-# An efficient Neural-Network Quantum States Architecture for Strongly Correlated Systems
+# Hamiltonian-Guided Autoregressive Selected-Configuration Interaction(HAAR-SCI) Achieves Chemical Accuracy in Strongly Correlated Systems
 
-The Quantum-Many-Body (`qmb`) is a powerful tool designed to solve quantum-many-body problems.
+The current project temporarily named as Quantum-Many-Body (`qmb`) which is a powerful tool designed to solve quantum-many-body problems especially for strongly correlated systems.
 
@@ -50,0 +50,0 @@ ## About The Project

qmb.egg-info/requires.txt

 platformdirs~=4.3.7
-numpy~=1.26.4
-scipy~=1.15.2
-torch<2.8,>=2.6
-pybind11~=2.13.6
-ninja~=1.11.1.4
+numpy<2.4.0,>=1.26.4
+scipy<1.17.0,>=1.15.2
+torch<2.9,>=2.6
+pybind11<3.1.0,>=2.13.6
+ninja<1.13.1.0,>=1.11.1.4
 tyro~=0.9.18
 pyyaml~=6.0.2
 openfermion~=1.7.0
-tensorboard~=2.19.0
+tensorboard<2.21,>=2.19
 
@@ -20,3 +20,3 @@ [:python_version >= "3.13"]
 pytest<8.5.0,>=8.3.5
-pytest-cov~=6.0.0
+pytest-cov<6.3,>=6.0
 types-pyyaml~=6.0.12.20250326

qmb.egg-info/SOURCES.txt

@@ -43,2 +43,3 @@ .clang-format
 qmb/optimizer.py
+qmb/pert.py
 qmb/precompile.py
@@ -45,0 +46,0 @@ qmb/random_engine.py

qmb/__main__.py

@@ -18,2 +18,3 @@ """
 from . import chop_imag as _  # type: ignore[no-redef]
+from . import pert as _  # type: ignore[no-redef]
 from . import run as _  # type: ignore[no-redef]
@@ -20,0 +21,0 @@ from .subcommand_dict import subcommand_dict

qmb/_hamiltonian.cpp

@@ -87,2 +87,3 @@ #include <pybind11/complex.h>
     );
+    m.def("diagonal_term(Tensor configs, Tensor site, Tensor kind, Tensor coef) -> Tensor");
     m.def("single_relative(Tensor configs, Tensor site, Tensor kind, Tensor coef) -> Tensor");
@@ -89,0 +90,0 @@ }

qmb/_version.py

 # file generated by setuptools-scm
 # don't change, don't track in version control
 
-__all__ = ["__version__", "__version_tuple__", "version", "version_tuple"]
+__all__ = [
+    "__version__",
+    "__version_tuple__",
+    "version",
+    "version_tuple",
+    "__commit_id__",
+    "commit_id",
+]
 
@@ -12,4 +19,6 @@ TYPE_CHECKING = False
     VERSION_TUPLE = Tuple[Union[int, str], ...]
+    COMMIT_ID = Union[str, None]
 else:
     VERSION_TUPLE = object
+    COMMIT_ID = object
 
@@ -20,4 +29,8 @@ version: str
 version_tuple: VERSION_TUPLE
+commit_id: COMMIT_ID
+__commit_id__: COMMIT_ID
 
-__version__ = version = '0.0.51'
-__version_tuple__ = version_tuple = (0, 0, 51)
+__version__ = version = '0.0.52'
+__version_tuple__ = version_tuple = (0, 0, 52)
+
+__commit_id__ = commit_id = 'g9ec0312c4'

qmb/fcidump.py

@@ -195,2 +195,5 @@ """
 
+    def diagonal_term(self, configs: torch.Tensor) -> torch.Tensor:
+        return self.hamiltonian.diagonal_term(configs)
+
     def single_relative(self, configs: torch.Tensor) -> torch.Tensor:
@@ -197,0 +200,0 @@ return self.hamiltonian.single_relative(configs)

qmb/haar.py

@@ -526,16 +526,2 @@ """
 subcommand_dict["haar"] = HaarConfig
-
-
-class ImagConfig(HaarConfig):
-    """
-    Deprecated, use "haar" instead.
-    """
-
-    # pylint: disable=too-few-public-methods
-
-    def __post_init__(self) -> None:
-        logging.warning("The 'imag' subcommand is deprecated, please use 'haar' instead.")
-        super().__post_init__()
-
-
-subcommand_dict["imag"] = ImagConfig
+subcommand_dict["imag"] = HaarConfig

qmb/hamiltonian.py

@@ -168,2 +168,22 @@ """
 
+    def diagonal_term(self, configs: torch.Tensor) -> torch.Tensor:
+        """
+        Get the diagonal term of the Hamiltonian for the given configurations.
+
+        Parameters
+        ----------
+        configs : torch.Tensor
+            A uint8 tensor of shape [batch_size, n_qubytes] representing the input configurations.
+
+        Returns
+        -------
+        torch.Tensor
+            A complex64 tensor of shape [batch_size] representing the diagonal term of the Hamiltonian for the given configurations.
+        """
+        self._prepare_data(configs.device)
+        _diagonal_term: typing.Callable[[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor], torch.Tensor]
+        _diagonal_term = getattr(self._load_module(configs.device.type, configs.size(1), self.particle_cut), "diagonal_term")
+        psi_result = torch.view_as_complex(_diagonal_term(configs, self.site, self.kind, self.coef))
+        return psi_result
+
     def single_relative(self, configs: torch.Tensor) -> torch.Tensor:
@@ -170,0 +190,0 @@ """

qmb/hubbard.py

@@ -115,2 +115,5 @@ """
 
+    def diagonal_term(self, configs: torch.Tensor) -> torch.Tensor:
+        return self.hamiltonian.diagonal_term(configs)
+
     def single_relative(self, configs: torch.Tensor) -> torch.Tensor:
@@ -117,0 +120,0 @@ return self.hamiltonian.single_relative(configs)

qmb/ising.py

@@ -224,2 +224,5 @@ """
 
+    def diagonal_term(self, configs: torch.Tensor) -> torch.Tensor:
+        return self.hamiltonian.diagonal_term(configs)
+
     def single_relative(self, configs: torch.Tensor) -> torch.Tensor:
@@ -226,0 +229,0 @@ return self.hamiltonian.single_relative(configs)

qmb/model_dict.py

@@ -176,2 +176,17 @@ """
 
+    def diagonal_term(self, configs: torch.Tensor) -> torch.Tensor:
+        """
+        Calculate the diagonal term for the given configurations.
+
+        Parameters
+        ----------
+        configs : torch.Tensor
+            The configurations to calculate the diagonal term for.
+
+        Returns
+        -------
+        torch.Tensor
+            The diagonal term of the configurations.
+        """
+
     def single_relative(self, configs: torch.Tensor) -> torch.Tensor:
@@ -178,0 +193,0 @@ """

qmb/openfermion.py

@@ -89,2 +89,5 @@ """
 
+    def diagonal_term(self, configs: torch.Tensor) -> torch.Tensor:
+        return self.hamiltonian.diagonal_term(configs)
+
     def single_relative(self, configs: torch.Tensor) -> torch.Tensor:
@@ -91,0 +94,0 @@ return self.hamiltonian.single_relative(configs)

README.md

@@ -1,4 +0,4 @@
-# An efficient Neural-Network Quantum States Architecture for Strongly Correlated Systems
+# Hamiltonian-Guided Autoregressive Selected-Configuration Interaction(HAAR-SCI) Achieves Chemical Accuracy in Strongly Correlated Systems
 
-The Quantum-Many-Body (`qmb`) is a powerful tool designed to solve quantum-many-body problems.
+The current project temporarily named as Quantum-Many-Body (`qmb`) which is a powerful tool designed to solve quantum-many-body problems especially for strongly correlated systems.
 
@@ -5,0 +5,0 @@ ## About The Project

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Improved metrics

Total package byte prevSize

384583

3.18%

Number of package files

60

1.69%

Lines of code

4425

2.22%