Incremental Updates

docs/index.md

@@ -1,17 +1,46 @@
-# Welcome to Mklorum
+# 欢迎使用 Quantum Algorithm (qalgo)
 
-For full documentation visit [mkdocs.org](https://www.mkdocs.org).
+这是 Quantum Algorithm 项目的文档。本项目基于量子虚拟机实现了一些量子算法。
 
-## Commands
+并且本项目还提供了大量用于组成量子算法的组件，例如量子逻辑门，量子算术运算，QRAM，量子态制备，量子傅里叶变换，量子测量等。
 
-* `mkdocs new [dir-name]` - Create a new project.
-* `mkdocs serve` - Start the live-reloading docs server.
-* `mkdocs build` - Build the documentation site.
-* `mkdocs -h` - Print help message and exit.
+## 安装
 
-## Project layout
+### 系统需求
 
-    mkdocs.yml    # The configuration file.
-    docs/
-        index.md  # The documentation homepage.
-        ...       # Other markdown pages, images and other files.
+- 操作系统：Windows、Linux 或 macOS
+- Python 版本：3.9 或以上，推荐3.10+
+
+### 安装方式
+
+```python
+pip install qalgo
+```
+
+## 快速开始
+
+```python
+import qalgo
+
+## TODO:
+
+# 打印结果
+print(result)
+```
+
+## 算法列表
+
+### 已实现
+- 线性求解器 (Quantum Linear System Solver)，基于离散绝热定理
+
+### 待实现
+- Shor算法
+- 线性求解器 (Quantum Linear System Solver)，基于Quantum Walk
+- 线性求解器 (Quantum Linear System Solver)，基于HHL算法
+- 量子态制备
+
+
+## 关于
+本项目由 USTC-IAI 量子人工智能团队开发，主要成员为：
+
+TODO.

qalgo/qda/fundamental.py

@@ -108,23 +108,42 @@ def get_mid_eigenstate(self) -> NDArray[np.float64]:
         print(f"fs = {self.fs}")
         n = self.row_size
 
-        match self.fs:
-            case 0:
-                vec = self.get_vector_0b()
-            case 1:
-                sol = np.linalg.solve(self.matrix_A, self.vector_b)
-                sol /= np.linalg.norm(sol)
-                vec = np.concatenate([np.zeros(n), sol])
-            case _ if 0 < self.fs < 1:
-                Af = self.get_matrix_Af()
-                b = self.get_vector_0b()
-                sol = np.linalg.solve(Af, b)
-                sol /= np.linalg.norm(sol)
-                vec = sol
-            case _:
-                raise RuntimeError(
-                    f"Invalid fs value: {self.fs}. Expected 0 <= fs <= 1."
-                )
+        # match self.fs:
+        #     case 0:
+        #         vec = self.get_vector_0b()
+        #     case 1:
+        #         sol = np.linalg.solve(self.matrix_A, self.vector_b)
+        #         sol /= np.linalg.norm(sol)
+        #         vec = np.concatenate([np.zeros(n), sol])
+        #     case _ if 0 < self.fs < 1:
+        #         Af = self.get_matrix_Af()
+        #         b = self.get_vector_0b()
+        #         sol = np.linalg.solve(Af, b)
+        #         sol /= np.linalg.norm(sol)
+        #         vec = sol
+        #     case _:
+        #         raise RuntimeError(
+        #             f"Invalid fs value: {self.fs}. Expected 0 <= fs <= 1."
+        #         )
+
+        # match statement only works for python 3.10+
+        # Fix this by using if-else statements
+        if self.fs == 0:
+            vec = self.get_vector_0b()
+        elif self.fs == 1:
+            sol = np.linalg.solve(self.matrix_A, self.vector_b)
+            sol /= np.linalg.norm(sol)
+            vec = np.concatenate([np.zeros(n), sol])
+        elif 0 < self.fs < 1:
+            Af = self.get_matrix_Af()
+            b = self.get_vector_0b()
+            sol = np.linalg.solve(Af, b)
+            sol /= np.linalg.norm(sol)
+            vec = sol
+        else:
+            raise RuntimeError(
+                f"Invalid fs value: {self.fs}. Expected 0 <= fs <= 1."
+            )
 
         return np.concatenate([vec, np.zeros(2 * n)], dtype=np.float64)