Measure WWjj polarization fraction

Overview

WlWl Polarization

Measure WWjj polarization fraction

sm sm_lltt sm_lttl

Paper: arXiv:2109.09924
Notice: This code can only be used for the inference process, if you want to train your own model, please contact [email protected].

Requirements

  • Both Linux and Windows are supported.
  • 64-bit Python3.6(or higher, recommend 3.8) installation.
  • Tensorflow2.x(recommend 2.6), Numpy(recommend 1.19.5), Matplotlib(recommend 3.4.2)
  • One or more high-end NVIDIA GPUs(at least 4 GB of DRAM), NVIDIA drivers, CUDA(recommend 11.4) toolkit and cuDNN(recommend 8.2.x).

Preparing dataset

The raw dataset needs to be transformed before it can be imported into the model.

  • You need to create a raw dataset(we provide a test dataset, stored in ./raw/), the data structure is as follows:
The file has N events:
   Event 1
   Event 2
   ...
   Event N
One event for every 6 lines:
   1. first lepton 
   2. second lepton 
   3. first FB jet 
   4. second FB jet 
   5. MET 
   6. remaining jet 
Each line has the following five columns of elements:
   1.ParticleID  2.Px  3.Py  4.Pz  5.E
The format of an event in the dataset is as follows:
   ...
   -1.0  166.023   5.35817   10.784    166.459
   1.0   -36.1648  -64.1513  -28.9064  79.113
   7.0   -11.3233  -39.6316  -318.178  320.85
   7.0   -34.2795  22.0472   622.79    624.128
   0.0   -22.6711  52.8976   -422.567  426.468
   6.0   -49.9758  29.3283   274.517   294.098
   ...

ParticleID: 1 for electron, 2 for muon, 3 for tau, 4 for b-jet, 5 for normal jet, 0 for met, 6 for remaining jets, 7 for forward backward jet, signs represent electric charge.

  • Use the command python create_dataset.py YOUR_RAWDATA_PATH, it will create a file with the same name as YOUR_RAWDATA_PATH in the ./dataset/.

Using pre-trained models

After completing the preparation of the dataset, you can use the model to predict the polarization fraction.

  • Pre-trained weights are placed in ./weights/.
  • Use the command python inference.py --dataset YOUR_TRADATA_NAME --model_name <MODEL_NAME> --energy_level <ENERGY_LEVEL>, it will give the polarization fractions.

Notice: <ENERGY_LEVEL> should correspond to the collision energy of events.

Example

Run the following command to get the polarization fractions for the standard model:

python create_dataset.py ./raw/sm.dat
python inference.py --dataset sm --model_name TRANS --energy_level 13

Citation

@misc{li2021polarization,
    title={Polarization measurement for the dileptonic channel of $W^+ W^-$ scattering using generative adversarial network},
    author={Jinmian Li and Cong Zhang and Rao Zhang},
    year={2021},
    eprint={2109.09924},
    archivePrefix={arXiv},
    primaryClass={hep-ph}
}
The source codes for ACL 2021 paper 'BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data'

BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data This repository provides the implementation details for

124 Dec 27, 2022
Minimisation of a negative log likelihood fit to extract the lifetime of the D^0 meson (MNLL2ELDM)

Minimisation of a negative log likelihood fit to extract the lifetime of the D^0 meson (MNLL2ELDM) Introduction The average lifetime of the $D^{0}$ me

Son Gyo Jung 1 Dec 17, 2021
Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning" (AAAI 2021)

Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic

NAVER/LINE Vision 30 Dec 06, 2022
ESTDepth: Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks (CVPR 2021)

ESTDepth: Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks (CVPR 2021) Project Page | Video | Paper | Data We present a novel metho

65 Nov 28, 2022
a curated list of docker-compose files prepared for testing data engineering tools, databases and open source libraries.

data-services A repository for storing various Data Engineering docker-compose files in one place. How to use it ? Set the required settings in .env f

BigData.IR 525 Dec 03, 2022
YouRefIt: Embodied Reference Understanding with Language and Gesture

YouRefIt: Embodied Reference Understanding with Language and Gesture YouRefIt: Embodied Reference Understanding with Language and Gesture by Yixin Che

16 Jul 11, 2022
An original implementation of "Noisy Channel Language Model Prompting for Few-Shot Text Classification"

Channel LM Prompting (and beyond) This includes an original implementation of Sewon Min, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer. "Noisy Cha

Sewon Min 92 Jan 07, 2023
Minimal implementation and experiments of "No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging".

No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N

19 Jan 03, 2023
LBK 35 Dec 26, 2022
Load What You Need: Smaller Multilingual Transformers for Pytorch and TensorFlow 2.0.

Smaller Multilingual Transformers This repository shares smaller versions of multilingual transformers that keep the same representations offered by t

Geotrend 79 Dec 28, 2022
✨风纪委员会自动投票脚本,利用Github Action帮你进行裁决操作(为了让其他风纪委员有案件可判,本程序从中午12点才开始运行,有需要请自己修改运行时间)

风纪委员会自动投票 本脚本通过使用Github Action来实现B站风纪委员的自动投票功能,喜欢请给我点个STAR吧! 如果你不是风纪委员,在符合风纪委员申请条件的情况下,本脚本会自动帮你申请 投票时间是早上八点,如果有需要请自行修改.github/workflows/Judge.yml中的时间,

Pesy Wu 25 Feb 17, 2021
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"

BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq

Taehoon Kim 922 Dec 21, 2022
Implementation of Heterogeneous Graph Attention Network

HetGAN Implementation of Heterogeneous Graph Attention Network This is the code repository of paper "Prediction of Metro Ridership During the COVID-19

5 Dec 28, 2021
Open source code for the paper of Neural Sparse Voxel Fields.

Neural Sparse Voxel Fields (NSVF) Project Page | Video | Paper | Data Photo-realistic free-viewpoint rendering of real-world scenes using classical co

Meta Research 647 Dec 27, 2022
Paper list of log-based anomaly detection

Paper list of log-based anomaly detection

Weibin Meng 411 Dec 05, 2022
Improving adversarial robustness by a coupling rejection strategy

Adversarial Training with Rectified Rejection The code for the paper Adversarial Training with Rectified Rejection. Environment settings and libraries

Tianyu Pang 29 Jan 06, 2023
Deploy optimized transformer based models on Nvidia Triton server

Deploy optimized transformer based models on Nvidia Triton server

Lefebvre Sarrut Services 1.2k Jan 05, 2023
Cookiecutter PyTorch Lightning

Cookiecutter PyTorch Lightning Instructions # install cookiecutter pip install cookiecutter

Mazen 8 Nov 06, 2022
Implements the training, testing and editing tools for "Pluralistic Image Completion"

Pluralistic Image Completion ArXiv | Project Page | Online Demo | Video(demo) This repository implements the training, testing and editing tools for "

Chuanxia Zheng 615 Dec 08, 2022
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Kai Zhang 1.2k Dec 29, 2022