semvec/pypi-packages huggingface dataset:
QNPI-InRealisticWaveguides 0.1.4
Quantum nonlinear parametric interaction in realistic waveguides
License: MIT
Requires Python: >=3.9

# Quantum Nonlinear Parametric Interaction in Realistic Waveguides

The `QNPI_InRealisticWaveguides` is a module for modelling quantum nonlinear interaction in waveguides affected by imperfections and deviations-from-design typically associated with realistic fabrication processes. The modelling framework assumes an undepleted pump field, leading to an effectively Gaussian evolution.

This module contains a consolidated and streamlined version of the scripts that were used to generate the results in 

> Weiss, T. F., Youssry, A., & Peruzzo, A. (2025). Quantum nonlinear parametric interaction in realistic waveguides: a comprehensive study. [arXiv:2506.20184](https://doi.org/10.48550/arXiv.2506.20184)



## Installation

Install via pip:
```pip install QNPI-InRealisticWaveguides```
For using tailored poling structures install `custom-poling separately (there is a matplotlib restriction): 
```pip install custom-poling --no-deps```
```pip install matplotlib>=3.6.3```



## Examples and related material

An exemplary jupyter notebook introducing the capabilities and the workflow of the module can be found in the `example` directory.

A detailed description of the theory behind the modelling framework can be found in 

> Weiss, T. F., Youssry, A., & Peruzzo, A. (2025). Quantum nonlinear parametric interaction in realistic waveguides: a comprehensive study. [arXiv:2506.20184](https://doi.org/10.48550/arXiv.2506.20184)

> Quesada, N., et al. (2020). Theory of high-gain twin-beam generation in waveguides: From Maxwell's equations to efficient simulation. Phys. Rev. A 102, 033519 (https://doi.org/10.1103/PhysRevA.102.033519)


## Features & Comments

Quantitatively connecting the modelling framework with an explicit waveguide requires calculation of the respective dispersion and modal-field data. Exemplary data is provided in the files under `ModeSolverData` together with a COMSOL file capable of generating them for arbitrary waveguides. 
While the module can be used without the files containing the waveguide modes by directly supplying the nonlinear interaction coefficients calculated from them, a file containing dispersion data is strictly required.

In its current state, the module is (in all likelihood) far from computationally optimized, and requires implementation alongside significant parallelization when treating complex cases.
acforge 3.1.1
acforge cli for AI Code Forge configuration management
License: MIT
Requires Python: >=3.9
Keywords: ai, claude, cli, configuration, development, templates

# AI Code Forge CLI

A command-line tool for managing AI Code Forge templates and configurations.

## Installation

```bash
# Install via uvx (recommended for ephemeral usage)
uvx acforge --help

# Install persistently
uv tool install acforge
```

## Commands

### `acforge status`

Show comprehensive status of repository configuration and templates.

```bash
# Human-readable status
acforge status

# Verbose output with detailed information
acforge status --verbose

# JSON output for scripting
acforge status --format json
```

## Development

```bash
# Install in development mode
cd cli
uv pip install -e .

# Run tests
uv run pytest

# Type checking
uv run mypy src/

# Formatting
uv run ruff format
uv run ruff check
```

## Architecture

This CLI manages AI development workflows through:

- **Configuration Management**: Bundled templates for agents, commands, and configurations
- **State Management**: Atomic state tracking in `.acforge/state.json`  
- **Configuration Analysis**: Detection and analysis of existing configurations
- **Customization Preservation**: Support for `.local` files and user modifications

## Phase 1 Implementation

Currently implements:
- ✅ `acforge status` - Complete status reporting and analysis

Coming next:
- 🚧 `acforge init` - Repository initialization with templates
- 🚧 `acforge update` - Template synchronization with customization preservation
AnChinSegmenter 1.1
一个古汉语分词工具
License: MIT
Requires Python: >=3.8

# （AnChinSeg）古汉语分词及词性标注工具 Word Segmentation and Part-of-speech for Ancient Chinese
基于2022年的分词文章，做了古汉语的分词和词性标注
这是一个非常粗糙朴素的分词和标注词性的工具
词性效果评估如下：
P:	92.82
R:	92.85
F:	92.84
分词效果评估如下：
P:	97.19
R:	97.22
F:	97.20

## Citation
词性标注并没有发表论文，但是如果您使用了我们的工具进行了学术研究，可以引用以下论文，我们是在该论文的基础上实现的
```
@inproceedings{tang-su-2022-slepen,
    title = "That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory",
    author = "Tang, Xuemei  and
      Su, Qi",
    booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.acl-long.540",
    doi = "10.18653/v1/2022.acl-long.540",
    pages = "7830--7840",
}
```

## Requirements
环境配置请查看 requriments.txt

## How to use it
1)请从百度网盘或者google drive下载模型model.dt放到model文件夹中
baidu链接: https://pan.baidu.com/s/1jIbqk5b4GYBEMAdBPVJwYg 提取码: dac4
google drive: https://drive.google.com/drive/folders/1zFK30h6PQYRDDZ2uEScLy0l5VoC7jXHU?usp=sharing


在文件夹下执行：
#python segmenter.py --predict_data ./data/sample_data.txt --output_path ./data/output.txt
（./data/sample_data.txt替换为你的需要分词的文件的路径，一行为一个句子，./data/output.txt替换为分词结果的存储位置）
 
最后分好词的格式如下：
端明殿_NA 学士_NA 兼_VT 翰林侍读_NA 学士_NA 朝散大夫_NA 右谏议大夫_NA 充_VT 集贤院_NA

4）词性标记参考台湾中央研究院
https://lingcorpus.iis.sinica.edu.tw/kiwi/dkiwi/middle_chinese_c_wordtype.html
https://lingcorpus.iis.sinica.edu.tw/kiwi/akiwi/ancient_mandarin_chinese_c_wordtype.html

## Contact

Please contact us at tangxuemei@polyu.edu.hk if you have any questions.
Welcome to Research Center for Digital Humanities of Peking University! https://pkudh.org
physdes-py 0.5
Physical Design Python Code
License: MIT

[![codecov](https://codecov.io/gh/luk036/physdes-py/branch/main/graph/badge.svg?token=EIv4D8NlYj)](https://codecov.io/gh/luk036/physdes-py)
[![Documentation Status](https://readthedocs.org/projects/physdes-py/badge/?version=latest)](https://physdes-py.readthedocs.io/en/latest/?badge=latest)

<p align="center">
  <img src="./rectilinear-shapes-for-vlsi-physical-desgin.svg"/>
</p>

# 🧱 physdes-py

> Physical Design Python Code

## ✨ Features

- Rectilinear Polygon support

## Dependencies

- [luk036/mywheel](https://github.com/luk036/mywheel)
- [luk036/lds-gen](https://github.com/luk036/lds-gen) (for testing only)

## 👀 See also

- [physdes-cpp](https://github.com/luk036/physdes-cpp)
- [physdes-rs](https://github.com/luk036/physdes-rs)

## 👉 Note

This project has been set up using PyScaffold 3.2.1. For details and usage
information on PyScaffold see <https://pyscaffold.org/>.
kitten-mcp-server 0.1.0
MCP Server for Kitten
License: MIT
Requires Python: >=3.11

# Kitten MCP Server

一个轻量级的 MCP（消息控制协议）服务器，专为 Kitten 应用设计。

## 功能
- 快速高效的消息处理
- 基于 Python 3.11+ 构建
- MIT 许可证

## 安装

1. 确保已安装 Python 3.11 或更高版本。
2. 使用 pip 安装包：
   ```bash
   pip install kitten_mcp_server
   ```

## 使用方法

运行以下命令启动服务器：
```bash
  kitten_mcp_server
```

## 依赖

- `fastmcp>=2.0.0`

## 许可证

本项目采用 MIT 许可证。详情请参阅 [LICENSE](LICENSE) 文件。