awesome-quantum-machine-learning

在这里，您可以获得所有量子机器学习基础知识、算法、学习材料、项目以及网络上项目的描述

  • 语言HTML
  • 默认分支master
  • 大小9.8 MB
  • 更新2024年5月8日
在 GitHub 打开
avatarkrishnakumarsekar
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项目介绍

krishnakumarsekar/awesome-quantum-machine-learning 是一个托管在 GitHub 上的开源项目，主要使用 HTML 编写，采用 Creative Commons Zero v1.0 Universal 许可证，目前获得 3.7k 个 Star、811 次 Fork。

仓库全名
krishnakumarsekar/awesome-quantum-machine-learning
开源许可证
Creative Commons Zero v1.0 Universal
Star 数
3.7k
Fork 数
811
未关闭 Issue
11

README 摘要

A curated list of awesome quantum machine learning algorithms,study materials,libraries and software (by language). Table of Contents INTRODUCTION Why Quantum Machine Learning? BASICS What is Quantum Mechanics? What is Quantum Computing? What is Topological Quantum Computing? Quantum Computing vs Classical Computing QUANTUM COMPUTING Atom Structure Photon wave Electron Fluctuation or spin States SuperPosition…

完整内容见 GitHub 原始 README 或本页 。

常见问题

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主要使用 HTML 编写，采用 Creative Commons Zero v1.0 Universal 许可证，目前有 3.7k 个 Star。

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可以直接克隆仓库：git clone https://github.com/krishnakumarsekar/awesome-quantum-machine-learning.git，默认分支为 master；安装与运行步骤见仓库 README。

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仓库最近一次更新为 2024年5月8日，当前有 11 个未关闭 Issue；Star 数为 3.7k，可作为社区活跃度的参考。

本页面展示项目元数据与原始 README，GitRead 中文社区 编辑团队负责选题收录。

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关于

GitHub 原始描述（英文）

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

描述取自 GitHub 官方 API，保持仓库作者书写的原文。

简要分析

热度分
5550
价值分
2489
活跃状态
活跃
aiant-colony-optimizationartificial-intelligenceartificial-neural-networksawesomeawesome-listfcmhmm-modelkmeansknn-classificationmachine-learningmachine-learning-algorithmsqmlquantumquantum-aiquantum-computingquantum-programming-languagequbitstensorflow
GitHub

语言占比

HTML

贡献者

krishnakumarsekarkrishnakumarsekar

README

Awesome Quantum Machine Learning Awesome

A curated list of awesome quantum machine learning algorithms,study materials,libraries and software (by language).

Main Architecture

Quantum Kernel

In Depth Physics Comparison

Table of Contents

INTRODUCTION

Why Quantum Machine Learning?
Machine Learning(ML) is just a term in recent days but the work effort start from 18th century.
As computing technology growing faster and faster mathematics entered into this field and makes the solution via computing to the real world . In the computing technology timeline once a certain achievements reached peoples interested to use advanced mathematical ideas such as complex numbers ,eigen etc and its the kick start for the ML field such as Artificial Neural Network ,DNA Computing etc.
Now the main question, why this field is getting boomed now a days ? , From the business perspective , 8-10 Years before during the kick start time for ML ,the big barrier is to merge mathematics into computing field . people knows well in computing has no idea on mathematics and research mathematician has no idea on what is computing . The education as well as the Job Opportunities is like that in that time . Even if a person tried to study both then the business value for making a product be not good.
Then the top product companies like Google ,IBM ,Microsoft decided to form a team with mathematician ,a physician and a computer science person to come up with various ideas in this field . Success of this team made some wonderful products and they started by providing cloud services using this product . Now we are in this stage.
So what’s next ? , As mathematics reached the level of time travel concepts but the computing is still running under classical mechanics . the companies understood, the computing field must have a change from classical to quantum, and they started working on the big Quantum computing field, and the market named this field as Quantum Information Science .The kick start is from Google and IBM with the Quantum Computing processor (D-Wave) for making Quantum Neural Network .The field of Quantum Computer Science and Quantum Information Science will do a big change in AI in the next 10 years. Waiting to see that… .(google, ibm).
References

BASICS

What is Quantum Mechanics?
In a single line study of an electron moved out of the atom then its classical mechanic ,vibrates inside the atom its quantum mechanics

What is Quantum Computing?
A way of parallel execution of multiple processess in a same time using qubit ,It reduces the computation time and size of the processor probably in neuro size

Quantum Computing vs Classical Computing
  • LINK - Basic outline

Quantum Computing

Atom Structure
one line : Electron Orbiting around the nucleous in an eliptical format
  • YOUTUBE - A nice animation video about the basic atom structure

atom

Photon Wave
one line : Light nornmally called as wave transmitted as photons as similar as atoms in solid particles
  • YOUTUBE - A nice animation video about the basic photon 1
  • YOUTUBE - A nice animation video about the basic photon 2

Photon wave

Electron Fluctuation or spin
one line : When a laser light collide with solid particles the electrons of the atom will get spin between the orbitary layers of the atom

Spin

  • YOUTUBE - A nice animation video about the basic Electron Spin 1
  • YOUTUBE - A nice animation video about the basic Electron Spin 2
  • YOUTUBE - A nice animation video about the basic Electron Spin 3

States
one line : Put a point on the spinning electron ,if the point is in the top then state 1 and its in bottom state 0

States

  • YOUTUBE - A nice animation video about the Quantum States

SuperPosition
two line : During the spin of the electron the point may be in the middle of upper and lower position, So an effective decision needs to take on the point location either 0 or 1 . Better option to analyse it along with other electrons using probability and is called superposition

SuperPosition

  • YOUTUBE - A nice animation video about the Quantum Superposition

SuperPosition specific for machine learning(Quantum Walks)
one line : As due to computational complexity ,quantum computing only consider superposition between limited electrons ,In case to merge more than one set quantum walk be the idea

SuperPosition specific for machine learning

  • YOUTUBE - A nice video about the Quantum Walks

Classical Bits
one line : If electron moved from one one atom to other ,from ground state to excited state a bit value 1 is used else bit value 0 used

Classical Bits

Qubit
one line : The superposition value of states of a set of electrons is Qubit

Qubit

  • YOUTUBE - A nice video about the Quantum Bits 1
  • YOUTUBE - A nice video about the Bits and Qubits 2

Basic Gates in Quantum Computing
one line : As like NOT, OR and AND , Basic Gates like NOT, Hadamard gate , SWAP, Phase shift etc can be made with quantum gates

Basic Gates in Quantum Computing

  • YOUTUBE - A nice video about the Quantum Gates

Quantum Diode
one line : Quantum Diodes using a different idea from normal diode, A bunch of laser photons trigger the electron to spin and the quantum magnetic flux will capture the information

Diodes in Quantum Computing1 Diodes in Quantum Computing2 Diodes in Quantum Computing3

  • YOUTUBE - A nice video about the Quantum Diode

Quantum Transistors
one line : A transistor default have Source ,drain and gate ,Here source is photon wave ,drain is flux and gate is classical to quantum bits

Quantum Transistors1 Quantum Transistors2

  • QUORA -Discussion about the Quantum Transistor
  • YOUTUBE - Well Explained

Quantum Processor
one line : A nano integration circuit performing the quantum gates operation sorrounded by cooling units to reduce the tremendous amount of heat

Quantum Processor1 Quantum Processor2 Quantum Processor3

Quantum Registery QRAM
one line : Comapring the normal ram ,its ultrafast and very small in size ,the address location can be access using qubits superposition value ,for a very large memory set coherent superposition(address of address) be used

QRAM1 QRAM2

  • PDF - very Well Explained

QUANTUM COMPUTING MACHINE LEARNING BRIDGE

Complex Numbers
one line : Normally Waves Interference is in n dimensional structure , to find a polynomial equation n order curves ,better option is complex number

Complex Numbers1 Complex Numbers2 Complex Numbers3

  • YOUTUBE - Wonderful Series very super Explained

Tensors
one line : Vectors have a direction in 2D vector space ,If on a n dimensional vector space ,vectors direction can be specify with the tensor ,The best solution to find the superposition of a n vector electrons spin space is representing vectors as tensors and doing tensor calculus

Tensors1 Tensors2 Tensors3 Tensors4

  • YOUTUBE - Wonderful super Explained tensors basics
  • YOUTUBE - Quantum tensors basics

Tensors Network
one line : As like connecting multiple vectors ,multple tensors form a network ,solving such a network reduce the complexity of processing qubits

Tensors Network1 Tensors Network2 Tensors Network3

  • YOUTUBE - Tensors Network Some ideas specifically for quantum algorithms

QUANTUM MACHINE LEARNING ALGORITHMS

Quantum K-Nearest Neighbour
info : Here the centroid(euclidean distance) can be detected using the swap gates test between two states of the qubit , As KNN is regerssive loss can be tally using the average

Quantum K-Means
info : Two Approaches possible ,1. FFT and iFFT to make an oracle and calculate the means of superposition 2. Adiobtic Hamiltonian generation and solve the hamiltonian to determine the cluster
  • PDF1 - Applying Quantum Kmeans on Images in a nice way
  • PDF2 - Theory
  • PDF3 - Explaining well the K-means clustering using hamiltonian
  • Matlab - Yet to come soon
  • Python - Yet to come soon

Quantum Fuzzy C-Means
info : As similar to kmeans fcm also using the oracle dialect ,but instead of means,here oracle optimization followed by a rotation gate is giving a good result

Quantum Support Vector Machine
info : A little different from above as here kernel preparation is via classical and the whole training be in oracles and oracle will do the classification, As SVM is linear ,An optimal Error(Optimum of the Least Squares Dual Formulation) Based regression is needed to improve the performance
  • PDF1 - Nice Explanation but little hard to understand :)
  • PDF2 - Nice Application of QSVM
  • Matlab - Yet to come soon
  • Python - Yet to come soon

Quantum Genetic Algorithm
info : One of the best algorithm suited for Quantum Field ,Here the chromosomes act as qubit vectors ,the crossover part carrying by an evaluation and the mutation part carrying by the rotation of gates

Flow Chart

  • PDF1 - Very Beautiful Article , well explained and superp
  • PDF2 - A big theory :)
  • PDF3 - Super Comparison
  • Matlab - Simulation
  • Python1 - Simulation
  • Python2 - Yet to come

Quantum Hidden Morkov Models
info : As HMM is already state based ,Here the quantum states acts as normal for the markov chain and the shift between states is using quantum operation based on probability distribution

Flow Chart

  • PDF1 - Nice idea and explanation
  • PDF2 - Nice but a different concept little
  • Matlab - Yet to come
  • Python1 - Yet to come
  • Python2 - Yet to come

Quantum state classification with Bayesian methods
info : Quantum Bayesian Network having the same states concept using quantum states,But here the states classification to make the training data as reusable is based on the density of the states(Interference)

Bayesian Network Sample1
Bayesian Network Sample2
Bayesian Network Sample3

Quantum Ant Colony Optimization
info : A good algorithm to process multi dimensional equations, ACO is best suited for Sales man issue , QACO is best suited for Sales man in three or more dimension, Here the quantum rotation circuit is doing the peromene update and qubits based colony communicating all around the colony in complex space

Ant Colony Optimization 1

Quantum Cellular Automata
info : One of the very complex algorithm with various types specifically used for polynomial equations and to design the optimistic gates for a problem, Here the lattice is formed using the quatum states and time calculation is based on the change of the state between two qubits ,Best suited for nano electronics

Quantum Cellular Automata

QAUNTUM NEURAL NETWORK

QNN 1

one line : Its really one of the hardest topic , To understand easily ,Normal Neural Network is doing parallel procss ,QNN is doing parallel of parallel processess ,In theory combination of various activation functions is possible in QNN ,In Normal NN more than one activation function reduce the performance and increase the complexity

Quantum perceptrons
info : Perceptron(layer) is the basic unit in Neural Network ,The quantum version of perceptron must satisfy both linear and non linear problems , Quantum Concepts is combination of linear(calculus of superposition) and nonlinear(State approximation using probability) ,To make a perceptron in quantum world ,Transformation(activation function) of non linearity to certain limit is needed ,which is carrying by phase estimation algorithm

Quantum Perceptron 1
Quantum Perceptron 2
Quantum Perceptron 3 Quantum Perceptron 4 Quantum Perceptron 5

QAUNTUM STATISTICAL DATA ANALYSIS

quantumstatistics1 quantumstatistics2 quantumstatistics3 quantumstatistics4 quantumstatistics5 quantumstatistics6

one line : An under research concept ,It can be seen in multiple ways, one best way if you want to apply n derivative for a problem in current classical theory its difficult to compute as its serialization problem instead if you do parallelization of differentiation you must estimate via probability the value in all flows ,Quantum Probability Helps to achieve this ,as the loss calculation is very less . the other way comparatively booming is Quantum Bayesianism, its a solution to solve most of the uncertainity problem in statistics to combine time and space in highly advanced physical research

QUANTUM PROGRAMMING LANGUAGES , TOOLs and SOFTWARES

All
info : All Programming languages ,softwares and tools in alphabetical order

QUANTUM HOT TOPICS

Deep Quantum Learning
why and what is deep learning?
In one line , If you know deep learning you can get a good job :) ,Even a different platform undergraduated and graduated person done a master specialization in deep learning can work in this big sector :), Practically speaking machine learning (vector mathematics) , deep learning (vector space(Graphics) mathematics) and big data are the terms created by big companies to make a trend in the market ,but in science and research there is no word such that , Now a days if you ask a junior person working in this big companies ,what is deep learning ,you will get some reply as “doing linear regression with stochastic gradient for a unsupervised data using Convolutional Neural Network :)” ,They knows the words clearly and knows how to do programming using that on a bunch of “relative data” , If you ask them about the FCM , SVM and HMM etc algorithms ,they will simply say these are olden days algorithms , deep learning replaced all :), But actually they dont know from the birth to the till level and the effectiveness of algorithms and mathematics ,How many mathematical theorems in vector, spaces , tensors etc solved to find this “hiding the complexity technology”, They did not played with real non relative data like medical images, astro images , geology images etc , finding a relation and features is really complex and looping over n number of images to do pattern matching is a giant work , Now a days the items mentioned as deep learning (= multiple hidden artifical neural network) is not suitable for that
why quantum deep learning or deep quantum learning?
In the mid of Artificial Neural Network Research people realised at the maximum extreme only certain mathematical operations possible to do with ANN and the aim of this ANN is to achieve parallel execution of many mathematical operations , In artificial Intelligence ,the world intelligence stands for mathematics ,how effective if a probem can be solvable is based on the mathematics logic applying on the problem , more the logic will give more performance(more intelligent), This goal open the gate for quantum artificial neural network, On applying the ideas behind the deep learning to quantum mechanics environment, its possible to apply complex mathematical equations to n number of non relational data to find more features and can improve the performance

Quantum Machine Learning vs Deep Learning

Its fun to discuss about this , In recent days most of the employees from Product Based Companies Like google,microsoft etc using the word deep learning ,What actually Deep Learning ? and is it a new inventions ? how to learn this ? Is it replacing machine learning ? these question come to the mind of junior research scholars and mid level employees
The one answer to all questions is deep learning = parallel “for” loops ,No more than that ,Its an effective way of executing multiple tasks repeatly and to reduce the computation cost, But it introduce a big cap between mathematics and computerscience , How ?
All classical algorithms based on serial processing ,Its depends on the feedback of the first loop ,On applying a serial classical algorithm in multiple clusters wont give a good result ,but some light weight parallel classical algorithms(Deep learning) doing the job in multiple clusters and its not suitable for complex problems, What is the solution for then?
As in the title Quantum Machine Learning ,The advantage behind is deep learning is doing the batch processing simply on the data ,but quantum machine learning designed to do batch processing as per the algorithm
The product companies realised this one and they started migrating to quantum machine learning and executing the classical algorithms on quantum concept gives better result than deep learning algorithms on classical computer and the target to merge both to give very wonderful result
References

QUANTUM MEETUPS

  • Meetup 1 - Quantum Physics
  • Meetup 2 - Quantum Computing London
  • Meetup 3 - Quantum Computing New York
  • Meetup 4 - Quantum Computing Canada
  • Meetup 5 - Quantum Artificial Intelligence Texas
  • Meetup 6 - Genarl Quantum Mechanics , Mathematics New York
  • Meetup 7 - Quantum Computing Mountain View California
  • Meetup 8 - Statistical Analysis New York
  • Meetup 9 - Quantum Mechanics London UK
  • Meetup 10 - Quantum Physics Sydney Australia
  • Meetup 11 - Quantum Physics Berkeley CA
  • Meetup 12 - Quantum Computing London UK
  • Meetup 13 - Quantum Mechanics Carmichael CA
  • Meetup 14 - Maths and Science Group Portland
  • Meetup 15 - Quantum Physics Santa Monica, CA
  • Meetup 16 - Quantum Mechanics London
  • Meetup 17 - Quantum Computing London
  • Meetup 18 - Quantum Meta Physics ,Kansas City , Missouri ,US
  • Meetup 19 - Quantum Mechanics and Physics ,Boston ,Massachusetts ,US
  • Meetup 20 - Quantum Physics and Mechanics ,San Francisco ,California
  • Meetup 21 - Quantum Mechanics ,Langhorne, Pennsylvania
  • Meetup 22 - Quantum Mechanics ,Portland

QUANTUM BASED DEGREES

Available Courses
Quantum Mechanics for Science and Engineers
Quantum Physics

  • Online

    • MIT - Super Explanation and well basics
    • NPTEL - Nice Series of Courses to understand ba

README 内容过长，已截取前 64 KB。完整内容请前往 GitHub 仓库查看。

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