How Quantum Computing Evolved?
The roots of quantum computing come from quantum mechanics, which deals with atomic and subatomic level energy interactions. Quantum mechanics can explain unsolved theoretical physics, chemistry, and technology problems mathematically. Thus, it is considered the steppingstone for the unified theory of the Universe.
The major challenge when dealing with quantum mechanics is its inability to simulate the quantum models. A simple quantum system with few interactions requires enormous computing power to simulate. Richard Feynman and Yuri Manin studied this knowledge gap, and they postulated a new genre of computing known as quantum computing. Their introduction to quantum computing relies on the Controlled NOT (CNOT) gate, which can simulate any arbitrary quantum circuit.
What is Quantum Computing?
When the problem is very complex, and the system needs to process massive data, quantum computers can show the magic. The prominent feature of quantum computing is leveraging the uncertainties, whereas classical computing cannot accept uncertainties. Conventional computing relies on bits with two states, 1 and 0. Quantum computing leverages the Qubits (Quantum bits), taking the states 0, 1, and quantum superpositions of 0 and 1.
Arguably, the increased states can increase the computational delay, thus reducing the processing speed. Considering a single operation, this argument is valid, and it may take more time. But the number of processes required for solving a computationally intricate problem can be significantly reduced. That’s how quantum computers can successfully simulate subatomic particle interactions. Apart from Qubits, many other quantum principles such as superposition, quantum entanglement, interference, and coherence are also utilized in quantum architecture.
What Change Can Quantum Computing Bring?
Even though Quantum computing is in the infant stage, as the technology evolves, it can produce significant advancements in machine learning, material science, Theoretical physics, nuclear physics, chemistry, energy, medicine design, etc.
One of the significant threats that scientists are expecting is information security. When quantum computers are in full swing, our existing cryptographic techniques built on the complexity of the mathematical problem will become a cakewalk for quantum computers. This scenario demands a complete restructuring of our information security architecture and existing cryptocurrency architecture.
How to Get Your Hands on Quantum Computing?
Many cloud-based quantum computing solutions are available for users. The major players are IBM quantum, Google Quantum Computing Service (Cirq), Amazon Bracket, and Microsoft Azure Quantum. Azure quantum is the only service that is not limited to single quantum hardware for implementing your quantum logic. Azure quantum computing service has been in its public preview since early 2021.
Why Azure Quantum?
Azure quantum computing can present you Quantum Development kit, the best development environment out of the whole spectra of quantum services. The flexibility and adaptability of multiple quantum hardware usages are significant advantages.
Quantinum, IONQ, Pasqal, Rigetti, And Quantum circuits are the major quantum service providers in Azure Quantum. In Azure quantum, You can work with popular quantum programming frameworks such as Cirq, Qiskit, and Q#. It provides Quantum Inspired Optimization (QIO), apart from quantum computing service. The major QIO service providers in Azure Quantum are IQbit, Microsoft QIO, and Toshiba SBM.
What is Quantum Development Kit?
Microsoft Quantum Development Kit (QDK) is the open-source environment for your Microsoft Azure Quantum. You can use python-based SDKs like Qiskit or Cirq. Otherwise, users can leverage the high-level quantum programing language Q#. The resource estimator facility will help you forecast the cost of running your code.
How to Develop a Quantum Application Using Azure Quantum?
As a baby step, let us consider the creation of random binary bits 0 and 1 in a qubit place holder.
Step 1: – Create Azure Quantum workspace.
Open Quantum workspace from Azure portal
For free usage, you can select the Quick create option. Advanced create contains a few paid hardware services. Azure quantum pricing is significantly less than other quantum computing services in the cloud computing environment.
Populate the required detail fields
Click on create and wait for deployment
Step 2: – Create Jupyter notebook in Azure quantum workspace.
Select Notebooks from the Operations section of the left blade. You can select the sample jobs from the sample gallery.
For a new notebook, click on the three dots near my notebooks
Select new notebook
You can select Kernel type, either IPython or IQ#, and provide a file name.
Step 3: – Import Workspace
Here the coding is based on Python and Q#. The new notebook will contain the code to connect to your quantum workspace by default. You can use connect function to connect to the workspace.
You can see the available target instances using the code given below and verify that the required hardware is available.
Step 4: – Implement your quantum logic
The next step is to build your business logic using quantum programming languages such as Q#, Cirq, and Qiskit. The given example generates a random bit using Q#.
We utilized the Measurement, Arrays, and Convert modules for random qubit generation.
We submit the job to IonQ hardware, a general-purpose trapped ion quantum computer that executes the function. Before selecting the target, make sure the in the available target list ionq simulator is available.
Wait until the job is succeeded. For a better understanding of the result, we can plot the probability of 1 and 0 bits using matplotlib.
The process is similar in all the languages like Qiskit and Cirq.
For Further Study
- Azure Documentation: https://docs.microsoft.com/en-us/azure/quantum/
- MS Learn: https://docs.microsoft.com/en-us/learn/paths/quantum-computing-fundamentals/
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