Quantum Computing (Part-II)- Fundamentals of Quantum Computing

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Introduction to the Fundamentals of Quantum Computing and Details about the Programming Methodology done in D-Wave Systems 

Now we continue with the second part of our blog on quantum computing. Those who have missed our first blog can read it from Here. It will help to connect with this second part of the blog discussing fundamentals of quantum computing  and programming methodology done in D-wave systems.

Fundamentals of Quantum Computing

Instead of saving information using bits represented by 0s or 1s as traditional digital computers do, quantum computers use the technique of  quantum bits, or qubits, to encode information as 0s, 1s, or both at the same moment. This superposition of states—along with the other quantum mechanical methodology of entanglement and tunneling—enables quantum computers to calculate and analyse huge coalescence of states at once. A Hellenic computer has a memory build-up of bits, where each and every bit is characterized by either a one or a zero. A quantum computer, on the other hand, cultivate a sequence of qubits, which can characterize a one, a zero, or any quantum superposition of those two qubit states;[10]:13–16 a pair of qubits can be in any quantum superposition of 4 states,[10]:16 and three qubits in any superposition of 8 states. In general, a quantum computer with {\displaystyle n} n qubits can be in an capricious superposition of up to {\displaystyle 2^{n}} 2^{n} different states simultaneously[10]:17. (This compares to a normal computer that can only be in one of these {\displaystyle 2^{n}} 2^{n} states at any one time). A quantum computer conduct on its qubits using quantum gates and measurement (which also alters the observed state). An algorithm is repressed of a fixed arrangement of quantum logic gates and a problem is encoded by mounting the initial values of the qubits, equivalent to how a Hellenic computer works. The computation usually ends with a measurement, collapsing the system of qubits into one of the {\displaystyle 2^{n}} 2^{n} eigenstates, where each qubit is zero or one, decomposing into a classical state. The result can therefore be at most {\displaystyle n} n classical bits of information (or, if the algorithm did not end with a measurement, the result is an unobserved quantum state).Quantum algorithms are often probabilistic, in that they provide the correct solution only with a certain known probability. Note that the term non-deterministic computing must not be used in that case to mean probabilistic (computing), because the term non-deterministic has some other meaning in computer science. An example of an implementation of qubits of a quantum computer could start with the use of particles with two spin states: "down" and "up" (typically written {\displaystyle |{\downarrow }\rangle } |{\downarrow }\rangle  and {\displaystyle |{\uparrow }\rangle } |{\uparrow }\rangle , or {\displaystyle |0{\rangle }} |0{\rangle } and {\displaystyle |1{\rangle }} |1{\rangle }). This is true because any such system can be mapped onto an effective spin-1/2 system.

How the Programming is done in D-Wave System?

The D-Wave system uses a web application program interface with client libraries available for C/C++, Python, and MATLAB. This permits users to use the computer easily and readily as a cloud resource across a network. To program the system, a user targets and maps a problem into a search for the “lowest point in a vast landscape,” and that is equivalent to the best possible result. The quantum processing unit considers all the possibilities together to arbitrate the lowest energy required to form those relationships. The solutions are values that equivalent to the optimal configurations of qubits found, or the lowest points in the energy landscape. These values are returned to the user program over the network. Because a quantum computer is probabilistic rather than deterministic, the computer returns many very good answers in a short amount of time. This gives not only the best solution found but also best alternatives from which to choose. D-Wave systems are contracted to be used to complement classical computers. There are many examples of problems where a quantum computer can complement an HPC (high-performance computing) system. While the quantum computer is well suited to discrete optimization, for example, the HPC system is better at large-scale numerical simulations.

To be continued in the next blog...

Quantum Computing (Part-I)- Future Trends of Computing

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What are Quantum Computers and how they are going to work?

Quantum Computing is one of the greatest technological advancement in the field of complex computation which has opened the door leading to the pathway for advance scientific and technological development in almost every field thus reducing much of effort and time behind complex calculations. We will try to explore the vast and complex world of quantum computing with a series of blogs to capture the broad idea in a simple manner. This is the first blog on Quantum Computing which discuss about the basics of quantum computing that is continuously emerging as the future trend of computing.

IT and Software giants are racing to create a truly useful quantum computer. Here's what makes quantum computers different to and what they good be used for in the near future. Quantum computing takes advantage of the strange ability of subatomic particles to exist in more than one state at any time. Due to the way the tiniest of particles behave, operations can be done much more quickly and use less energy than classical computers. In classical computing, a bit is a single piece of information that can exist in two states – 1 or 0. Quantum computing uses quantum bits, or 'qubits' instead. These are quantum systems with two states. However, unlike a usual bit, they can store much more information than just 1 or 0, because they can exist in any superposition of these values. Quantum computing is computing using quantum-mechanical phenomena, such as superposition and entanglement and the device that performs quantum computing is known as Quantum Computer. They are different from binary digital electronic computers based on transistors. Whereas common digital computing requires that the data be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits, which can be in super-positions of states. A quantum Turing machine is a theoretical model of such a computer, and is also known as the universal quantum computer. The field of quantum computing was initiated by the work of Paul Benioff and Yuri Manin in 1980, Richard Feynman in 1982, and David Deutsch in 1985. As of 2018, the development of actual quantum computers is still in its infancy, but experiments have been carried out in which quantum computational operations were executed on a very small number of quantum bits. Both practical and theoretical research continues, and many national governments and military agencies are funding quantum computing research in additional effort to develop quantum computers for civilian, business, trade, environmental and national security purposes, such as cryptanalysis. A small 20-qubit quantum computer exists and is available for experiments via the IBM quantum experience project. D-Wave Systems has been developing their own version of a quantum computer that uses annealing. Large-scale quantum computers would theoretically be able to solve certain problems much more quickly than any classical computers that use even the best currently known algorithms, like integer factorization using Shor's algorithm (which is a quantum algorithm) and the simulation of quantum many-body systems. There exist quantum algorithms, such as Simon's algorithm, that run faster than any possible probabilistic classical algorithm. A classical computer could in principle (with exponential resources) simulate a quantum algorithm, as quantum computation does not violate the Church–Turing thesis. On the other hand, quantum computers may be able to efficiently solve problems which are not practically feasible on classical computers.

Continued in next blog...