A quantum game modeling of pandemic (QHack 2022)

Overview

Abstract

In the regime of a global pandemic, leaders around the world need to consider various possibilities and take conscious actions to protect their citizens from the infectious virus. In the quantum world that we model in this game, every possible situation exists as a superposed state. Nothing is decisive at all. You, as the leader of this quantum city, need to suppress the possibility, or amplitude of states representing bad situations. Lastly, the mandatory PCR test for every citizen is waiting you---it 'measures' the city and will show whether your policies rescued the city or not. Predict, act, and measure!

The Game

Objectives

  • Obtain negative result for everyone at the last PCR test.

Contents

  • Mode
    In this game, there are two modes: Pure Quandemic and Mixed Quandemic. From the former one, the state of the citizens is always pure state. All the actions are unitary. On the other hand, when using the latter one, the state of the citizens can be mixed state. Considering a density matrix will be a good strategy. Most of actions are unitary, however, swapping two citiznes lead to non-unitary evolution. More details are described at 'Regular Action: Move Citizens (Swap)'. Input : write 1(0) if you want to play 'Mixed Quandemic'('Pure Quandemic'). ex) 1

  • Level
    The level indicates the initial number of infected people. However, indices of infected people are selected randomly. Input : write the number of level. ex) 3

  • Citizens
    A quantum circuit with N by M qubits represents a city that N*M citizens live with a deadly virus. 0's and 1's appearing on the computational basis of this system corresponds to healthy and infected states, respectively. Since the people live in a quantum world, the city stays in a superposition of possible infection states!

  • Regular Action: PCR Testing (Single Person)
    A PCR test corresponds to measurement on a specific qubit, or a citizen of this city. Not only obtains a decisive result about the citizen's infection status, the test destroys possibility of the city to be in states which counter the test result. In quantum-like words, the measurement projects previous state into a subspace contains the measured result. Input : write the index of person you want to inspect. ex) 4

  • Special Action: PCR Testing (Total Inspection)
    For sake of the player, one can measure states of all qubits at once for only one time during the game. It will remove superposition of the city's state, but the state will quickly branch and involve possibilities as time goes on. Input : write 1(0) if you want(do not want) to do the action. ex) 1

  • Regular Action: Move Citizens (Swap)
    In each turn, player should choose pairs of citizens to swap position. However, when a player use 'Mixed Quandemic' mode, they might additionally catch the virus since the swapped citizens can be exposed to the contaminated environment while swapping each other. The newly possible infected state is involved to the game as superposition. Simply, a quantum SWAP gate and a Kraus operator(only for 'Mixed Quandemic' mode) which puts 0 to 1 at a fixed possibility successively applied for each pair of citizens that the player selected. Players are allowed to swap 'neighboring' citizens only. Input : write the pairs of people's indices for inspection. If you want to inspect (0,1) and (3,4) --> ex) 0,1 3,4

  • Regular Action: Send Hospital
    There are two hospitals in this city placed at the certain area.

    • The 'H' hospital
      The 'H' hospital is placed on boundaries of the city. For example, in 3x3 city, 'H' hospital is placed at position 0, 1, 2, 3, 5, 6, 7, 8. The 'H' hospital works by applying Hadamard gate if player selects its position. Be careful that it might increase probability of infection if it is used in a wrong way!

    • The Pauli's X hospital
      The Pauli's X hospital is placed at the center of the city. It acts to the citizen at the center by applying X gate. So the hospital will cure a citizen if one is infected, but it will infect a healthy one at the same time! This hospital has the perfect medicine, but it is located at the center of the city.. It is really easy to get infected via passing through the central city.

Input : write the indices of people who wants to go to the hospital. ex) 0 1 3

In each turn, the player should select which citizens to send hospital. It is only possible to send citizens that are placed on the hostpial area.

  • The last, mandatory PCR test
    This test decides whether your critical choices during the pandemic were successful or not. This very final operation measures all qubits of the system as the total survey. Even if a single 1 exists in your final state, it will move, copy itself and spread throughout your city again. No way! The game's objective is to obtain the result |00...00> and to free your city from the pandemic forever! Input : write 1(0) if you want(do not want) to do the action. ex) 1

Demonstration

Title_Image

We first select pairs of citizen to swap position, indicated as blue edges. Then, select which citizens to send hospital, indicated as light-red boxes. Press 'Next' button to progress to next step. We can either check one person's PCR testing result, or use the total PCR inspection chance (limited to once per game). Execute GUI version of the game by python3 GUI_Quandemics.py.

Captured Scene

  • Example of the 'GUI' version

Title_Image

It is the interim state of the 'GUI' version game. #0 person visited the 'H' hospital. By the way, we had inspected the PCR test for the #2 person, and his/her result was positive.
Owner
Yoonjae Chung
KAIST EE & Physics Undergraduate
Yoonjae Chung
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Apache MXNet (incubating) for Deep Learning Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m

The Apache Software Foundation 20.2k Jan 05, 2023
[NeurIPS 2021] Code for Unsupervised Learning of Compositional Energy Concepts

Unsupervised Learning of Compositional Energy Concepts This is the pytorch code for the paper Unsupervised Learning of Compositional Energy Concepts.

45 Nov 30, 2022
Code for LIGA-Stereo Detector, ICCV'21

LIGA-Stereo Introduction This is the official implementation of the paper LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based

Xiaoyang Guo 75 Dec 09, 2022
Reinforcement Learning via Supervised Learning

Reinforcement Learning via Supervised Learning Installation Run pip install -e . in an environment with Python = 3.7.0, 3.9. The code depends on MuJ

Scott Emmons 49 Nov 28, 2022
Registration Loss Learning for Deep Probabilistic Point Set Registration

RLLReg This repository contains a Pytorch implementation of the point set registration method RLLReg. Details about the method can be found in the 3DV

Felix Järemo Lawin 35 Nov 02, 2022
Simple image captioning model - CLIP prefix captioning.

Simple image captioning model - CLIP prefix captioning.

688 Jan 04, 2023
Harmonious Textual Layout Generation over Natural Images via Deep Aesthetics Learning

Harmonious Textual Layout Generation over Natural Images via Deep Aesthetics Learning Code for the paper Harmonious Textual Layout Generation over Nat

7 Aug 09, 2022
Model serving at scale

Run inference at scale Cortex is an open source platform for large-scale machine learning inference workloads. Workloads Realtime APIs - respond to pr

Cortex Labs 7.9k Jan 06, 2023
SGPT: Multi-billion parameter models for semantic search

SGPT: Multi-billion parameter models for semantic search This repository contains code, results and pre-trained models for the paper SGPT: Multi-billi

Niklas Muennighoff 182 Dec 29, 2022
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"

LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and

Adam Goodge 25 Dec 28, 2022
Code for Deep Single-image Portrait Image Relighting

Deep Single-Image Portrait Relighting [Project Page] Hao Zhou, Sunil Hadap, Kalyan Sunkavalli, David W. Jacobs. In ICCV, 2019 Overview Test script for

438 Jan 05, 2023
Reimplementation of the paper "Attention, Learn to Solve Routing Problems!" in jax/flax.

JAX + Attention Learn To Solve Routing Problems Reinplementation of the paper Attention, Learn to Solve Routing Problems! using Jax and Flax. Fully su

Gabriela Surita 7 Dec 01, 2022
DeceFL: A Principled Decentralized Federated Learning Framework

DeceFL: A Principled Decentralized Federated Learning Framework This repository comprises codes that reproduce experiments in Ye, et al (2021), which

Huazhong Artificial Intelligence Lab (HAIL) 10 May 31, 2022
This repo includes the supplementary of our paper "CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels"

Supplementary Materials for CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels This repository includes all supplementary mater

Zhiwei Li 0 Jan 05, 2022
A pytorch reprelication of the model-based reinforcement learning algorithm MBPO

Overview This is a re-implementation of the model-based RL algorithm MBPO in pytorch as described in the following paper: When to Trust Your Model: Mo

Xingyu Lin 93 Jan 05, 2023
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Daniel Bourke 3.4k Jan 07, 2023
CM building dataset Timisoara

CM_building_dataset_Timisoara Date created: Febr-2020 The Timi\c{s}oara Building Dataset - TMBuD - is composed of 160 images with the resolution of 76

Orhei Ciprian 5 Sep 07, 2022
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective

FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Official implementation of "FL-WBC: Enhan

Jingwei Sun 26 Nov 28, 2022
This is an implementation of PIFuhd based on Pytorch

Open-PIFuhd This is a unofficial implementation of PIFuhd PIFuHD: Multi-Level Pixel-Aligned Implicit Function forHigh-Resolution 3D Human Digitization

Lingteng Qiu 235 Dec 19, 2022
Weakly Supervised 3D Object Detection from Point Cloud with Only Image Level Annotation

SCCKTIM Weakly Supervised 3D Object Detection from Point Cloud with Only Image-Level Annotation Our code will be available soon. The class knowledge t

1 Nov 12, 2021