Whether its a astrophysical operations, weather prognosis, or explorations for locating oil and gas resources, powerful super computers are now ready to assist the computation of the most complex problems.
Yet there are some challenges that even the fastest computing machines in the world have been unable to solve, namely the simulation of molecular structures, which has left many professionals in the medical and chemical industry scratching their heads. The development of effective drugs against illnesses, as well as better quality fertilizer to help fight world hunger, is largely dependent on the ability to perform the relevant calculations.
Another example is optimization. A rucksack can hold up to 20 kilograms. If we take several objects all with a specific weight and use, a specific number of objects must be selected that does not exceed the maximum weight of the rucksack but maximizes the value. Inventory management frequently encounters these sorts of challenges, yet mathematical evidence shows that these problems cannot be solved satisfactorily using conventional computers.
This all comes down to how computers are built. The smallest possible storage unit (a bit) can have a value of either 0 or 1. Bits are physically represented by two voltage potentials that correspond to the states 0 and 1. This binary representation of information pushes it to the brink of its capabilities to perform certain tasks.
Qubits: Superposition and Entanglement
In 1981, Nobel Prize-winning physicist Richard Feynman claimed that a so-called quantum computer could be used to perform computations. This theoretical concept went on to generate a wealth of interest and has since become a broad field of research and development.
A quantum computer works with quantum bits, or qubits. In contrast to a traditional computer system, the states of qubits can overlap. In other words, they do not merely represent 0 or 1, but can achieve a mixed state where they are both 0 and 1 at the same time. This is known as a superposition. When measured however, Qubits behave like classical bits and yield the value of 0 or 1.
If various qubits are added together, they do not have a defined state but exist as a qubit entirety. In quantum mechanics, this process is known as entanglement, and refers to how the measurement of two qubits is dependent on the other. For instance, if two qubits are measured and the first measures as 1, the state of the second qubit is already known.
Overcoming Quantum Decoherence
Together, superposition and entanglement form the decisive difference from which quantum computers are said to benefit: with a given number of qubits, numerous sequences of conventional bits can also be displayed. This calculation is therefore equal to the calculation of all bit sequences simultaneously. For certain problems, this quantum parallelism ensures a decisive speed advantage compared to regular computers.
Decoherence nevertheless remains a challenge for researchers. As soon as closed quantum systems start interacting with their environment, the system and environment state are changed irreversibly and errors can occur if this happens during the calculation process.
To ensure that the operations are conducted without mistakes or errors, the quantum computer qubits should preferably be decoupled from their environment which, in turn, minimizes the time to decoherence. This can lead to a possible conflict of objectives, since it is also necessary that the state of an individual qubit can be changed from the outside.
The number of qubits also plays an important technical role the higher the number, the greater the expected speed advantage. At the same time, this increases the number of obstacles to avoid decoherence with each individual qubit.
Five Criteria for Quantum Computers
Based on these ideas, in 1996 physicist David DiVincenzo formulated five criteria that he deemed sufficient for a quantum computer:
So far, no one has succeeded in developing a system that fulfills all these requirements. This is partly due to the lack of clarity surrounding the most appropriate candidates able to physically implement qubits. The energy level of an atom and the angular moment of electrons are currently under discussion, although many other possibilities are also under research.
Applications for Quantum Computing
Further progress continues to be made in the development of quantum computers. To date, none of the prototypes have shown any definitive advantages compared against traditional super computers. This predominantly comes down to the number of qubits used. The widespread view suggests that 50 or more qubits should show a benefit a number that has been officially announced but never achieved.
Experts expect that the first standard quantum computer will appear at some point in the next 10 years. Yet for those who are expecting to have a device under their desks at home may be disappointed; for the foreseeable future, this technology will most likely only be used to perform tasks on a large scale.
Quantum Cryptography: Already in Use
Beyond the development of quantum computers, other technologies benefiting from quantum mechanical effects have sparked interest. An example of this is quantum cryptography, which has been under development since the 1970s, and is now ready for implementation.
Data is the fuel of the 21st century. The world can hugely benefit from the distribution of more devices that interconnectedly generate and analyze data. At the same time, security risks such as data theft and data abuse continue to rise. Experts have estimated that cybercrime cost the economy $454 billion in 2016.
Compared to the solutions already available, quantum cryptographic processes can provide an additional level of safety and security. Discoveries in quantum physics reveal that such encryptions are not only difficult to hack, but downright impossible if they have been implemented correctly.
The aforementioned qualities of quantum systems form the basis for this level of security. Individual light particles transfer a code that is used in message encryption. The particles cannot be intercepted and measured without disruption. If someone were to try and intercept, they would not be able to access the code without being detected.
Progress in quantum computing development is the main motivation to continue developing quantum cryptography. Current encryption processes, such as RSA, rely on the assumption that there is no process in existence fast enough for the prime factorization of large numbers. Yet in 1994, Peter Shor demonstrated that this type of algorithm can be achieved on a quantum computer. The first team to produce an adequately-sized standard quantum computer can therefore hack all such security systems.
Yet this development is still a long way away from the projected 1,000 qubits that would be needed to hack RSA. In areas where secure communication and data transfers are extremely important, quantum cryptography can already offer solutions to safeguard against current and future attacks.
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