An open API service aggregating public data about GitHub Sponsors.

the-singularity-research

View JSON Representation

Naturphilosoph, Alchemistische Mathematikerin, Computational Artist

Funding Links: https://github.com/sponsors/The-Singularity-Research

GitHub Sponsors Profile

The Project
Much of this project is centered around researching, developing, and communicating quantum technologies. Many of the notebooks are implementations of research articles and textbook material on quantum computing using one of several available libraries and software developed by IBM, Google, Microsoft, Rigetti, or Xanadu. These projects will look at many different research articles on quantum computing and aim to implement the ideas in these articles on actual quantum computers. One of the primary goals is also to communicate these ideas effectively with many different examples and with ample background material. Applications being researched and implemented are quantum error correction, circuit optimization, cryptography, machine learning, Natural Language Processing (NLP), Computer Vision, and combinatorial problems. Let's discuss in more depth what that means.
Quantum Computing
Quantum Computing uses quantum physics and atomic scale structures to process information in a way that is fundamentally different from your laptop or smartphone. Instead of using bits, quantum computers use qubits, which can exist in a superposition, or combination, of both 0 and 1 at the same time. Quantum computers also use entanglement, which is a statistical correlation between the states of the qubits. They also use interference, much like the interference patters we observe when waves of water, light, or sound interfere with each others and either cancel each other out, or add to each others intensity. Quantum computing has many applications such as machine learning, optimization problems, solving linear equations, combinatorial problems, cryptography, drug discovery, protein folding, modeling molecular interactions, and modeling quantum physics and quantum gravity.
Quantum Error Correction
Quantum Error Correction is a collection of techniques used to mitigate noise and environmental decoherence of quantum computers. Some examples are the repetition code, graph states, stabilizer codes, surface codes, and machine learning techniques. We will be investigating and implementing all of these and will be working on developing software packages specifically for error correction, which will be a necessary long term tool in quantum computing and will likely be useful and important for quite some time if not indefinitely.
Circuit Optimization and Gate Synthesis
We will be working on algorithms used to in the synthesis of arbitrary unitary gates, and on optimizing quantum circuits using transpilers. This is a fundamental problem that is necessary for quantum computing and will be important to implementing a universal gate set on universal quantum computers. For more information see this StackOverflow page, and the related paper.
Quantum Machine Learning
Quantum Machine Learning is a variety of machine learning techniques that use quantum computers to perform certain computational tasks. One example of this is quantum neural networks, which are also known as quantum variational circuits. These train quantum circuits in much the same way neural networks are trained. Quantum circuits can also replace layers of traditional neural networks, or serve as kernels to convolutional neural networks.
Quantum Cryptography
Understanding how quantum computing interacts with the field of cryptography is a hot topic. Due to talk of quantum computers being able to "break RSA public key encryption" as well as some algorithms which apply to elliptic curve cryptography, quantum computers are seen as a potential threat to security and privacy. Understanding these algorithms, implementing them, and also studying applications of quantum computing to other forms of cryptography which take advantage of quantum physics is an important endeavor. Some of the currently available material on this topic include the "phase finding algorithm", an implementation of Shor's algorithm for factoring, which is applied to break RSA public key cryptography, along with implementations of "blind quantum computing" protocols. Blind quantum computing is a method whereby a client can securely send a computation to a server to run on a remote quantum computer via the cloud.
Quantum Gravity
Quantum Gravity is an attempt to develop a theory of gravity based on quantum physics. One of the most promising attempts in this direction involve the AdS/CFT correspondence of Juan Maldacena. There are quantum information interpretations of this theory which can be implemented on a quantum computer. Developing examples of implementations of this theory may give new insights into applications to versions of the Alcubierre warp drive researched by NASA for interstellar space travel.

Featured Works

The-Singularity-Research/quantum-fourier-transform

This notebook covers the Quantum Fourier Transform

Language: Jupyter Notebook - Stars: 5
The-Singularity-Research/graph-state-quantum-cryptography

A Jupyter notebook on the quantum cryptography application of blind quantum computation using graph states

Language: Jupyter Notebook - Stars: 8
The-Singularity-Research/entanglement

A Jupyter notebook that covers Bell states (EPR states), entanglement, GHZ states, W states, and graph states.

Language: Jupyter Notebook - Stars: 4
The-Singularity-Research/error-correction

Quantum Error Correction

Language: Jupyter Notebook - Stars:
The-Singularity-Research/FinTech-Time-Series

Quantum Machine Learning for FinTech and Time Series Data

Language: Jupyter Notebook - Stars: 22
The-Singularity-Research/universal-classifier

Single qubit data reuploading universal binary classifier modified from Penny Lane

Language: Jupyter Notebook - Stars: 5
Active Sponsors
Past Sponsors
Sponsor Breakdown