301004 | Research Preparation | Advancement In Quantum Computing

Write a report on advancement in quantum computing and its implications in future generations.

Answer:

Introduction

The field of quantum computing was started back in the 1980s. A 2-qubit quantum computer was later built in 1997 and in 2011, a five-qubit quantum computer was developed that successfully factored number fifteen. This report will explore on these advancements in quantum computing and its implications in the future generations. Major improvements have taken place in quantum computing, and currently, the largest quantum computer has few dozen qubits (Aaronson, 2013). In 2006, researchers developed new operational standards for controlling 12 qubit quantum system. The same year also saw researcher from the University of Akrnas develop molecules of quantum dot pairs which brought about a significant impact on quantum computers more so with the creation of more particles (Aspuru, Lindh & Reiher, 2018). The first Deutsch algorithm was applied in the cluster state quantum computer in 2007. Later that year, D-wave company contended to have developed the first ever working 28 –qubit quantum computers.

The aim of the Study

Objectives of the study

The two objectives of the research are to find out the advancement’s made in quantum computing and its implications that it will have in future generations.

Research Questions

1)   What is the turnaround time when using classical computers?

Scope and limitations of the study

The significance of the study

Research Methodologies

Data and Statistical Analysis

Every process in a computer makes some I/O requests, for instance to reading and writing data, making inputs and producing an outcome. The computer then executes more instruction then waits again on the I/O. These periods of computation in the I/O requests known as the CPU burst (Singh, Goyal & Batra, 2010). When the data and the computation process are intensive, it means that more time on I/O spent in the classical computers. That explains why much time spent on processing the data on classical computers. Consider a classical computer with a 2.4 GHz processor; it prosecutes about 2400 million instructions per second. In addition, quantum computers can run twenty-four million instructions in ten seconds (Singh, Goyal & Batra, 2010). One of the big improvements made in computers is increasing the overall system throughput, keep several programs running in the memory and switch the processors to run another process while waiting on the I/O process operation.

Quantum computers are proposed to have a high speed and large-scale processor with reduced operation function needed to execute the quantum algorithm. The classical computers use processes scheduler responsible for deciding whether the current running process will continue running and if not, decide on the next process. Turnaround time explain the time in which you type the command and the time it terminates. On the other hand, response time is the start time explains the time a task is executed to run and the time it actually runs on the CPU. Completion time is the time that the process comes to an end.  First Come First Serve approach is mostly used in the scheduling process in classical computers (Fujishima et al., 2003). This means that the new process goes to the end of que. The schedule begins the process that is ahead of the Que. Round robin scheduling is another version of the First Come Scheduling and uses the first Come First Serve approach only that it is allowed to run within a limited time. An interesting issue with the Round Robin scheme is that it is the length of the quantum. This means that setting the quantum too long causes context switches and lower the CPU efficiency while setting the quantum too long will cause poor response time and the first come first served.

Data Interpretation

Table

Using Table 1

P1=17

P2=13

Logic Quantum Processor

Considering a situation where 2n  bases bits exist in a quantum computer with n qubits. each base produces a complex series of base numbers and resulting in unitary transformations to the vector bases. A statistical analysis derived from (Fujishima et al, 2003) explains that 2n processing elements (PE) are needed for quantum operations. Quantum algorithms consoles of distribution of amplitude, where a PE can consist

of logic circuits. A number of the PE gates in a logic quantum processor is executed using the 8 bits fixed points. Further, in a control command, bits 0 and 1 can be used as control qubit. The Logic processor has the capability to increase the speed for the operations and processing in quantum computers and expresses probability amplitude by 1 bit. The qubits can perform trillions of calculations in a second thus giving them capabilities to solve problems in a day that the classical computers could take to solve in years (Fujishima et al, 2003). The superposition of zero and one in qubits makes it have two different teases at the same time. The building block of the quotum computers gives it the capacity to very processing speeds unlike in the classical computers.

Findings

Artificial intelligence, self-driving vehicles, and advancements in the medical field are also areas that quantum computing is likely to affect enormously. Research by Brif, Chakrabarti, and Rabitz (2010) explains that in the future almost all vehicles will be driverless, will be interconnected and real-time data will be available to everyone. This is where quantum computers will shine as large number of information is needed that not even supercomputers wouldn`t be able to handle. Quantum computers will be in a position to successfully process a massive amount of data, which will lead to efficient, and effective smooth and safe system interconnected to the driverless car system. Artificial intelligence is another area that would benefit from quantum computing which will be capable to making autonomous decisions and applying logic. This, however, requires a tremendous amount of information processing that only quantum computers would be able to provide. Brief, et al explain that researchers can use the sophisticated computer models used in quantum computing to learn how different diseases such as Cancer, Aids develop and use this information to find the cure to these diseases. Moreover, quantum computers will be able to come up with relevant answers based on the symptoms shown by the patient and make the right diagnostics. More drugs are also likely to be developed using all that computing power.

Other opportunities for quantum computing applications by industry is the financial services for risk optimization and fraud detection and smooth process of procurement, production, and distribution in manufacturing supply chain (Aaronson, 2013). The media industry will also use quantum computing for advertising scheduling and ad revenue maximization while in health care drug discovery as earlier mentioned and proteins folding will use quantum computing.

Conclusions

References

Aspuru-Guzik, A., Lindh, R., & Reiher, M. (2018). The Matter Simulation (R) evolution. ACS central science, 4(2), 144-152.

Brif, C., Chakrabarti, R., & Rabitz, H. (2010). Control of quantum phenomena: past, present,  and future. New Journal of Physics, 12(7), 075008.

Jordan, S. P., Lee, K. S., & Preskill, J. (2012). Quantum algorithms for quantum field theories. Science, 336(6085), 1130-1133.

Kassal, I., Whitfield, J. D., Perdomo-Ortiz, A., Yung, M. H., & Aspuru-Guzik, A. (2011). Simulating chemistry using quantum computers. Annual review of physical chemistry, 62, 185-207.

Singh, C. (2008). Interactive learning tutorials on quantum mechanics. American Journal of Physics, 76(4), 400-405.

Williams, C. P. (2010). Explorations in quantum computing. Springer Science & Business Media.