Quantum computing is a new paradigm that will play a big role in accelerating tasks for AI. It will offer researchers and developers access to open source frameworks and computing power that can operate beyond classical capabilities. Quantum computing has the capacity to solve problems that today’s computers probably never can. Moreover, the Moore’s law is nearing its limitation and soon we require a next generation computing power to solve complex problems of the future.
For example If you want to simulate a molecule which has 160 electrons, it would require a computer that’s 1/10th the volume of our planet. But that can be done with a quantum computer the size of a small room.
Quantum computing is essentially harnessing and exploiting the amazing laws of quantum mechanics to process information. A traditional computer uses long strings of “bits,” which encode either a zero or a one. A quantum computer, on the other hand, uses quantum bits, or qubits. A qubit is a quantum system that encodes the zero and the one into two distinguishable quantum states. But, because qubits behave quantumly, we can capitalize on the phenomena of "superposition" and "entanglement."
Superposition is essentially the ability of a quantum system to be in multiple states at the same time — that is, something can be “here” and “there,” or “up” and “down” at the same time.
Entanglement is an extremely strong correlation that exists between quantum particles — so strong, in fact, that two or more quantum particles can be inextricably linked in perfect unison, even if separated by great distances. The particles remain perfectly correlated even if separated by great distances.
How would the algorithms for a quantum computer differ from today’s algorithms?
The algorithms for quantum computing is about finding the minimum energy function of a Hamiltonian. This is not something that we can visualize. You can visualise X+Y or solving a quadratic equation. But with quantum computing it isn’t the same algorithms at all. There’s no perfect quantum computer. There are errors in physical infrastructure of a quantum computer. At least for the next decade, most quantum computers will have these errors underneath.
In order to increase the computational power of quantum computing systems, improvements are needed along two dimensions. One is qubit count; the more qubits we have, the more states can in principle be manipulated and stored. The second is to achieve lower error rates. We need to be able to manipulate the qubit states accurately and perform sequential operations that provide answers, not noise.
Combining these two concepts, we can create a single measure of a quantum computer’s power called quantum volume. Quantum volume measures the relationship between number and quality of qubits, circuit connectivity, and error rates of operations. Building larger systems with lower error rates will lead to discovering the first instances of quantum advantage, or applications where quantum computers can offer a computational advantage for solving real problems.
IBM Q Network Initiative
IBM is the front runner in developing the Quantum computers today. They have reached 5 qubits and 16 qubits in 2017. Looking at that progression, at somewhere between 50 and 100 qubits, is achievable within next five years, and we’ll find significant commercial uses of quantum computers.
IBM Q Network is a worldwide community of leading Fortune 500 companies, startups, academic institutions, and national research labs working with IBM to advance quantum computing and explore practical applications for business and science. They have formed a community that brings together researchers and quantum enthusiasts to share, connect and collaborate.
QISKit
QISKIT is an open-source quantum computing framework for leveraging today's quantum processors in research, education, and business which is available in the GitHub. It’s completely a python-based development kit. Currently the community is sharing codes, applications for the developers to learn and experience quantum computing.
We are living through an amazing period, witnessing the birth of a technology that involves the creation of a new paradigm in computation. In my opinion, the opening of the experiments and their programming tools to everybody not only democratizes science but also boosts its progress.
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