Several top quantum computing projects

A quantum computer offers much more processing power compared to classic computers.

Different projects of real application of quantum computers

This is achieved by manipulating the qubit. Creating and managing qubits is a huge challenge. the Morgan Stanley report said. In other words, quantum computing is the future.

Here is a short list of project ideas for quantum computing.


The Q-score, introduced last year by Athos, is a free open source quantum metric that applies to all programmable quantum processors. Q-score measures the efficiency of a quantum system in solving real problems that traditional computers cannot solve, instead of simply measuring its theoretical performance. It is the only metric system based on short-term available quantum algorithms and measures the ability of a quantum system to solve practical operational problems.

Open Catalist Project

The Open Catalist Project is an open source project to solve the problem of storing renewable energy using quantum mechanics. The project is a joint research effort between Facebook AI Research (FAIR) and the Department of Chemical Engineering at Carnegie Mellon University (CMU). The main goal of this project is to use artificial intelligence and quantum computing to model and discover new catalysts for use in renewable energy storage, which help address climate change.

Quantum computation in particle collision simulation

A team of researchers from Berkeley Lab used a quantum computer to simulate aspects of particle collisions that are commonly neglected in high-energy physics experiments, such as those occurring at CERN’s Large Hadron Collider. The developed quantum algorithm explains the complexity of parton showers, which are complex bursts of particles formed in collisions that involve the production and decay of particles. Researchers have constructed a “toy model”, a simplified theory that can run on a real quantum computer, and at the same time contains enough complexity that prevents its simulation by classical methods.

Detection of COVID-19 on an IBM quantum computer

Researchers Erdi Acar and Ihsan Yilmaz used the method of learning quantum transfer in various quantum real processors (IBMQx2, IBMQ-London and IBMQ-Rome) and simulators (Pennylane, Qiskit-Aer and Cirq) to detect COVID-19. Using a small number of data sets such as 126 COVID-19 and 100 normal CT images, the duo obtained a positive or negative COVID-19 classification with 90% success using classical computers and a high success rate of 94-100% using quantum computers.


The framework accelerates the development of quantum applications, providing the complete set of tools needed to interact with quantum systems and simulators.You can also execute code on multiple quantum hardware architectures, from superconducting qubits to trapped ions, and access a rich set of well-studied circuits that can be used as reference values, building blocks in more complex circuits, or as a tool for exploring quantum computational benefits.


Tequila is an extensible quantum architecture of information and learning whose main goal is to simplify and accelerate the application of new ideas for quantum algorithms. It works on abstract data structures enabling the formulation, combination, automatic differentiation and optimization of generalized goals. Tequila can perform basic values ​​of quantum expectations on modern simulators and real quantum devices.

Written by michael

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