We are discussing a novel way of incorporating physics into computers. Phenomena of silicon and semiconductor have long dominated device architecture and hardware, so we change gears and come around with a brand different computer unfamiliar to our predecessors. Google and NASA have paired up to create this paradigm change and the results will be mind-boggling as planned. Google and NASA developed a Quantum computer, built by D-Wave Systems and mounted at NASA-California.
Our classical computers have been around for a long time but the latest development is Quantum computers. If we go through Moore’s Law then the processor capacity doubles every 18 months; in that case, we can only imagine the amount of processing power that is required by this century. Thanks to Paul Bernioff, as he theorized the quantum computers in 1981 at Argonne National Laboratory.
He came up with Quantum Turing Machine where you can store as qubits in the bits. Qubits are in essence the effects of quantum mechanics being superimposed. Within our modern classical machine, at a specific memory location, a bit can have a value of either 0 or 1 while qubits can have values of both 0 and 1. This allows for multiple parallel calculations at the same time on the CPU.
Different values can be used for different calculations as a memory location can have multiple values at any point in time, thus allowing for inherent parallelism. We don’t want to go into too much detail about the timeline for the development of quantum computers after 1982 as that would make this article an informative pure history. Instead, we aim to make it more interesting.
BACKGROUND AND CONCEPTS
As mentioned earlier, we will need the circuits on the microprocessor measured on an atomic scale by Moore’s law by the year 2020 or 2030. The next generation will then naturally take us to quantum computers where we manipulate the strength of atoms and molecules to execute memory and computing tasks. Top Application Development Companies use many quantum mechanics principles that are discussed as below:
As already discussed in the opening, we store the data as qubits with QC (we will refer to quantum computers as QC henceforth) where the memory can have values 0 or 1 or 0 and 1. Also, the superposition is the symbols 0 and 1 and all the points in between. With a QC, at the same time, they can have several states and can be stronger multi folds unlike the classical structures of today. This can be quantified with a fact like this: a 30-qubit system is tantamount to 10 teraflops of the typical desktop system of today.
When we try to look at a qubit in superposition we can only find out if the value is 0 or 1 whereas the values would be both. So in such a case, we may not be looking directly at the qubit value. We need some indirect means to know a qubit’s value. As the law of entanglement goes, by applying an external force to two atoms, we can establish two atoms closely related. The second atom takes upon itself the properties of the first atom when this happens. And from the second atom, we can know the value of our atom of interest by applying some methods of quantum physics.
Quantum computation does not refute the notion of a parallel universe but instead encourages it. John Gribbin, a popular science writer, believes QC can work because some other parallel universe gives them its processing power. This being said, you should view it as if you are constructing a quantum computer effectively, you have all the machines from that other world at your fingertips. Well, it may seem a little vague to us as we don’t know the cosmology behind all of this; yet what should fascinate us is the processing power of these QCs.
It is often stated that the concept of quantum tunneling, i.e. a representation of Heisenberg’s uncertainty principle which ships the data to some other universe, is used in the design of quantum computers. It is seen that the atoms, electrons, photons, or other such subatomic particles cross a boundary without seeming to have crossed it. The MIT Technology Review reports that Quantum Tunneling was simulated on a QC. In other words, one computer’s mathematical behavior is reproduced on the other so looking at one system tells you all how another would behave.
There are best-augmented reality development companies that are targeted at the use of Quantum computers as the newest research development. We don’t know the right kind of question to ask this machine, as many field researchers believe too. The technologies that can potentially exploit the computational power of this size are still not completely understood to us. One of the other technologies giants such as Google are creating is that Google plans to use them to improve its online search and advertisement capability.
Given the large amount of data generated in search and advertisements, Google is optimistic that this computing power will be used correctly. Since Google earns more than two-thirds of its revenue from advertising, it is keen to ensure that its advertising technology can outperform any other mobile app development company. In mathematics, the largest and most complex problem is factorizing a large number into two prime numbers. This is an important issue since almost all methods of encryption are based on this problem.
The quantum machine needs to be able to classify these prime numbers easily. The existing authentication and encryption algorithms are likely to fail if quantum computers are widely available, which certainly won’t happen early. Currently, the protection algorithms we are using, be it RSA or SHA, are just constrained by the computations they require. But they can quickly break-in to with this amount of computational power.
Google has given our favorite and a magnificent example in a short video they made to introduce this concept to the world. You want to travel from Delhi to Mumbai and you want to route to multiple towns. Now, this is something of a classic problem of optimization.
The route can now be decided based on several parameters: the cheapest ticket, the least amount of time, the least number of tolls, the shortest route, traveling in buses with good legroom, traveling in vehicles providing seamless Wi-Fi connectivity, depending on the best weather to visit a specific city, the carbon footprint of cities, minimum layover times, meals provided, pet restrictions, seat availability and liability. This will produce huge quantities of data, and then aggregate it and generate results. When these are the number of parameters we want to remember otherwise the data-processing goes beyond our existing device capability.
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For QC various problems are foreseen. Yeah, we’re not exceptional to name all of them, but based on the knowledge and case studies conducted to compose this post, we can name a few to give you a sample of them all.
- One problem is because you are dealing with the subatomic particles, you can inherently change their values without even knowing it. Thus the integrity of the data becomes critical. If we try to look at a qubit in superposition, CSI Communications February 2015 30www.csi-India.orgit will return to us the values either 0 or 1 where the values should be between 0 and 1 or both.
- Quantum computers can only run probabilistic algorithms and that too with a rigid limit that with high probability, the answer/solution is correct. Therefore, the classical algorithms we used up until now cannot be used explicitly, not even the largely computational portion of classical algorithms can be accelerated.
- The current 16-qubit QC developed by D-Wave systems requires to maintain a stringent temperature regulation on the chip. And so, in terms of dimensions, thought the chip is quite small, the housing is quite huge. And therefore expensive to manage and run.
- Some people doubt if QC, designed and manufactured by D-Wave systems, actually works as a QC or not. Since we cannot look inside the hood of quantum computing because that would disturb the reason for the computation being that when we see the state of the atom which is its spin then the superposition is disturbed as explained above), these doubts are raised and so far no way out is found to prove it. And this also calls into question quantum state stability.
- This computer programming has driven D-Wave systems towards modern architecture and the language of the device. As already noted, each algorithm fed in should be probabilistic one. At Microsoft Research, too, Microsoft takes an interest in the same. For this project, Cambridge’s David Wecker is associated with Microsoft and has already implemented a software architecture called LIQUi that translated a high-level program representing a quantum algorithm into a lower-level technology-specific program.
We take the macro to the micro-level; or in fact, we take the Universe phenomena to the computer chips. Of course, the computers that are currently built are of the size of a room, keeping their ancestors’ legacy going. But they’ll finally grow to fit into our notebooks. We don’t live anymore in an era where we see or need a whole lifetime to see the work production materialize particularly if it’s to create a computer.