tequila
qiskit
tequila | qiskit | |
---|---|---|
7 | 23 | |
344 | 4,614 | |
1.2% | 2.9% | |
7.7 | 9.8 | |
6 days ago | 3 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tequila
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CUDA Quantum
Which of the Quantum circuit simulator back ends supported by tequila are accelerateable with CUDA quantum?
src/tequila/simulators: https://github.com/tequilahub/tequila/tree/master/src/tequil...
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New neural network architecture inspired by neural system of a worm
> Once you stop caring about the brain and neurons and you find out that almost every cell in the body has gap junctions and voltage-gated ion channels which for all intents and purposes implement boolean logic and act as transistors for cell-to-cell communication, biology appears less as something which has been overcome and more something towards which we must strive with our primitive technologies: for instance, we can only dream of designing rotary engines as small, powerful, and resilient as the ATP synthase protein [2].
But what of wave function(s); and quantum chemistry at the cellular level? https://github.com/tequilahub/tequila#quantumchemistry
Is emergent cognition more complex than boolean entropy, and are quantum primitives necessary to emulate apparently consistently emergent human cognition for whatever it's worth?
[Church-Turing-Deutsch, Deutsch's Constructor theory]
Is ATP the product of evolutionary algorithms like mutation and selection? Heat/Entropy/Pressure, Titration/Vibration/Oscillation, Time
From the article:
> The next step, Lechner said, “is to figure out how many, or how few, neurons we actually need to perform a given task.”
Notes regarding Representational drift* and remarkable resilience to noise in BNNs) from "The Fundamental Thermodynamic Cost of Communication: https://news.ycombinator.com/item?id=34770235
It's never just one neuron.
And furthermore, FWIU, human brains are not directed graphs of literally only binary relations.
In a human brain,
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Common Lisp Names All Sixteen Possible Binary Logic Gates
https://github.com/tequilahub/tequila/blob/master/src/tequil...
Pauli matrices > Quantum information: https://en.wikipedia.org/wiki/Pauli_matrices#Quantum_informa...
From Quantum_information#Quantum_information_processing https://en.wikipedia.org/wiki/Quantum_information#Quantum_in... :
> The state of a qubit contains all of its information. This state is frequently expressed as a vector on the Bloch sphere. This state can be changed by applying linear transformations or quantum gates to them. These unitary transformations are described as rotations on the Bloch Sphere. While classical gates correspond to the familiar operations of Boolean logic, quantum gates are physical unitary operators.
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Quantum Algorithm Implementations for Beginners
> Tequila is an Extensible Quantum Information and Learning Architecture where the main goal is to simplify and accelerate implementation of new ideas for quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state of the art simulators as well as on real quantum devices.
https://github.com/tequilahub/tequila#quantum-backends
Quantum Backends currently supported by tequilahub/tequila: Qulacs, Qibo, Qiskit, Cirq, PyQuil, QLM, myQLM)
tequila-tutorials/Quantum_Calculator.ipynb https://github.com/tequilahub/tequila-tutorials/blob/main/Qu... :
> Welcome to the Tequila Calculator Tutorial. In this tutorial, you will learn how to create a quantum circuit that simulates addition using Tequila. We also compare the performance of various backends that Tequila uses.
- Compostable fungi-based replacement for styrofoam
- Deep Learning Poised to ‘Blow Up’ Famed Fluid Equations
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quantumcat - Need feedback
a) have you heard of tequila? seems pretty similar
qiskit
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Library for Machine learning and quantum computing
Qiskit
- Reorientation vers metiers de l'informatique quantique
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Basic question about quantum operations
Hello, guys. I am a newbie to quantum computing. I got a question when reading the textbook on Qiskit.org.
- Calcul quantique
- Mio padre sta diventando un complottaro. Internet corrompe i boomer
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Meetup Announcement: Quantum Computing meets Data Science, 6th of June, 2023
Second talk: Gesture Classification on a Smartphone Web-App using a Quantum ComputerDavid Alber and Olaf Hahn will demonstrate that Quantum enhanced Support Vector Machines (QSVMs) can be utilized to classify gestures made by a conventional smartphone. They will showcase how developers can utilize the Qiskit Python framework and provision IBM Cloud and IBM Quantum resources to integrate such models in a traditional application environment seamlessly.Machine learning and quantum are promising technologies with the potential to address yet intractable problems. The hybrid nature of QSVMs makes it possible to deploy such models already today. We will show you how.
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p=np is a hardware problem maybe
Also, see Shor's algorithm for a quantum approach to prime factorization, and maybe have a play with qiskit
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Qiskit #0
Qiskit
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Which programming language is best to simulate a quantum computer?
I think Python would be a more mainstream choice and so you'll find modules like qiskit or [qutip(https://qutip.org/) already exist and will make life easier.
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How much would I benefit if I started working on my coding skills before uni?
If you want to be a bit more physics-focused in your coding, it might help to dig up a course or textbook on numerical methods in physics. Being able to numerically solve differential equations is probably the most generally applicable skill in physics. Machine learning methods are pretty ''hot right now'' and might be fun to have a look into. And for quantum technology in particular, you might enjoy having a look at some python packages like Kwant for quantum transport, QuTiP for quantum dynamics and Qiskit for quantum computing. You won't understand the physics for this for quite some time, they might help serve as a bit of inspiration and an indication as to what physicists can use programming for.
What are some alternatives?
quantumcat - quantumcat is a platform-independent, open-source, high-level quantum computing library, which allows the quantum community to focus on developing platform-independent quantum applications without much effort.
QuTiP - QuTiP: Quantum Toolbox in Python
CfC - Closed-form Continuous-time Neural Networks
mitiq - Mitiq is an open source toolkit for implementing error mitigation techniques on most current intermediate-scale quantum computers.
beso - BioElectric Simulation Orchestrator
pyquil - A Python library for quantum programming using Quil.
pyquirk - A simple python program to convert graphical circuits to quantikz figures.
qiskit-tutorials - A collection of Jupyter notebooks showing how to use the Qiskit SDK
beets - music library manager and MusicBrainz tagger
pyzx - Python library for quantum circuit rewriting and optimisation using the ZX-calculus
cqasm_development_interface - Framework for writing and running cQASM files against any Quantum Inspire's emulator backend via their API
qiskit-symb - Python package for symbolic quantum computation in Qiskit