QUANTUM COMPUTERS: A NEW WORLD OF COMPUTERS
INTRODUCTION
As Any sufficiently advanced technology is equivalent to magic. Day by day inventions in this new world of technology, the past things becomes obsolete. There is a lot of changes in this new world. If we go to past, there were type writters but now see its being replaced with computers with internet.
In older times people used to use dove, crow, and pigeon as a medium for the purpose of communication I.e., sending mails to relatives and friends. Then came the birth of telegraph in 1843 by morse in Washington DC. Later, due to the advancement in science and technology of internet, its being replaced with emails in 1971.
Similarly in the case of quantum computers there is a hidden history. In around 2400 BC, abacus was invented. In 300 BC the binary numbers were invented. Similarly in 1492 AD, there came the 1st mechanical calculator, by 1642 Blaise Pascal invented Pascaline – a mechanical adding machine. By the coming of 19th century came the era of generation of computers, a bright mathematician, philosopher, inventor and mechanical engineer, Charles Babbage originated the concept of a digital programmable computer. That’s why, Babbage is considered by some to be "father of the computer".
By 1950, 1st generation of computers started by the invention of first electronic computer by Japan by Hideo Yamachitto. After three yrs. IBM 701 becomes available. Thus, the saga continues and in 1961, 1st industrial robot was invented in New Jersey by GM (General Motors) and in 1964 IBM lead in the market by launching its word processor.
In the year 1991, the www i.e., world wide web is launched followed by in 1998 Google, 1976 apple, 1975 Microsoft corp. came into existence in the digital era.
Thus in 20th century i.e. , the modern era , within only 14 years (1998-2012) , Google Chrome has 28% worldwide usage share of web browsers and in 2010 apple launched its first iPad.
Quantum computing is a type of computation that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, to perform calculations. The devices that perform quantum computations are known as quantum computers. Though current quantum computers are too small to outperform usual (classical) computers for practical applications, they are believed to be capable of solving certain computational problems, such as integer factorization (which underlies RSA encryption), substantially faster than classical computers. The study of quantum computing is a subfield of quantum information science.
Quantum computational complexity is an exciting new area that touches upon the foundations of both theoretical computer science and quantum physics. The computational power of quantum Turing machines (QTMs) has been explored by several researchers and many researchers and companies are working on it currently. Early work done by Deutsch and Jozsa showed how to utilize some inherently quantum mechanical features of QTMs. Their results and the later research results by Berthiaume and Brassard established the existence of oracles under which there exists some computational problems that QTMs can solve in polynomial time with certainty, whereas if we require a classical probabilistic Turing machine to produce the correct answer with certainty, then it must take exponential time on some inputs.
Architecture of Quantum Computer
The basic structure of quantum computer is Qubit.
Fig1. The Bloch sphere is an explanation of a Qubit, the basic structure of quantum computers.[5]
Qubits are more advanced than bits and can contain more information than bits. A bit can contain or store 0 or 1 but a Qubit can store all values between 0 and 1.
Fig: 2 Quantum bit
Qubits are consists of the controlled particles and the means of control.
5.1.1 Quantum Data Plane
The quantum data plane is the “heart” of a QC. It includes the physical qubits and the structures needed to hold them in place. It also must contain any support circuitry needed to measure the qubits’ state and perform gate operations on the physical qubits for a gate-based system or control the Hamiltonian for an analog computer. Control signals routed to the selected qubit(s) set the Hamiltonian it sees, which control the gate operation for a digital quantum computer. For gate-based systems, since some qubit operations require two qubits, the quantum data plane must provide a programmable “wiring” network that enables two or more qubits to interact. Analog systems often require richer communication between the qubits, which must be supported by this layer. Unlike a classical computer, where both the control plane and the data plane components use the same silicon technology and are integrated on the same device, control of the quantum data plane requires technology different from that of the qubits,2 and is done externally by a separate control and measurement layer (described next). Control information for the qubits, which is analog in nature, must be sent to the correct qubit (or qubits). In some systems, this control information is transmitted electrically using wires, so these wires are part of the quantum data plane; in others, it is transmitted with optical or microwave radiation. Transmission must be implemented in a manner that has high specificity, so it affects only the desired qubit(s), without disrupting the other qubits in the system. This becomes increasingly difficult as the number of qubits grows; the number of qubits in a single module is therefore another important parameter of a quantum data layer.
Finding: The key properties that define the quality of a quantum data plane are the error rate of the single-qubit and two-qubit gates, the interqubit connectivity, qubit coherence times, and the number of qubits that may be contained within a single module.
5.1.2 Control and Measurement Plane
The control and measurement plane converts the control processor’s digital signals, which indicates what quantum operations are to be performed, to the analog control signals needed to perform the operations on the qubits in the quantum data plane. It also converts the analog output of measurements of qubits in the data plane to classical binary data that the control processor can handle. The generation and transmission of control signals is challenging because of the analog nature of quantum gates; small errors in control signals, or irregularities in the physical design of the qubit, will affect the results of operations.3 The errors associated with each gate operation accumulate as the machine runs.
Any imperfection in the isolation of these signals (so-called signal crosstalk) will cause small control signals to appear for qubits that should not otherwise be addressed during an operation, leading to small errors in their qubit state.4 Proper shielding of the control signals is complicated by the fact that they must be fed through the apparatus which isolates the quantum date plane from its environment by vacuum, cooling, or both; this requirement constrains the type of isolation methods which are possible.
Fortunately, both qubit manufacturing errors and signal crosstalk errors are systematic, and change slowly with the mechanical configuration of the system. Effects of these slowly changing errors can be minimized by using control pulse shapes that reduce dependence of the qubit on these factors (see Section 3.2.1), and through periodic5 system calibration, provided there is a mechanism to measure these errors and software to adjust the control signals to drive these errors to zero (system calibration). Since every control signal can potentially interact with every other control signal, the number of measurements and computation required to achieve this calibration more than doubles as the number of qubits in the system doubles.
The nature of a QC’s control signals depends on the underlying qubit technology. For example, systems using trapped ion qubits usually rely upon microwave or optical signals (forms of electromagnetic radiation) transmitted through free space or waveguides and delivered to the location of the qubits. Superconducting qubit systems are controlled using microwave and low-frequency electrical signals, both of which are communicated through wires that run into a cooling apparatus (including a “dilution refrigerator” and a “cryostat”) to reach the qubits inside the controlled environment.
Unlike classical gates, which have noise immunity and negligible error rates, quantum operations depend upon the precision with which control signals are delivered, and have nonnegligible error rates. Obtaining this precision currently requires sophisticated generators built using classical technologies.
Since no quantum gate can be faster than the control pulse that implements it, even if the quantum system in principle allows ultrafast operation, the gate speed will be limited by the time required to construct and transmit an exquisitely precise control pulse. Fortunately, the speed of today’s silicon technology is fast enough that gate speed is limited by the quantum data plane, and not the control and measurement plane. This gate speed is currently tens to hundreds of nanoseconds for superconducting qubits and one to a hundred microseconds for trapped ion qubits.
Finding: The speed of a quantum computer can never be faster than the time required to create the precise control signals needed to perform quantum operations.
5.1.3 Control Processor Plane and Host Processor
The control processor plane identifies and triggers the proper Hamiltonian or sequence of quantum gate operations and measurements (which are subsequently carried out by the control and measurement plane on the quantum data plane). These sequences execute the program, provided by the host processor, for implementing a quantum algorithm. Programs must be customized for the specific capabilities of the quantum layer by the software tool stack, as discussed in Chapter 6.
One of the most important and challenging tasks of the control processor plane will be to run the quantum error correction algorithm (if the QC is error corrected). Significant classical information processing is required to compute the quantum operations needed to correct errors based upon the measured syndrome results, and the time required for this processing may slow the operation of the quantum computer. This overhead is minimized if the error correction operations can be computed in a time comparable to that required for the quantum operations and measurements. Since this computational task grows with the size of the machine (the inputs and outputs of the function scale with the number of qubits, and the complexity scales with the “distance” of the error-correcting code), it is likely that this control processor plane will consist of multiple interconnected processing elements to handle the computational load.
Building a control processor plane for large quantum machines is challenging, and an active area of research. One approach splits the plane into two parts. The first part is simply a classical processor, which “runs” the quantum program. The second part is a scalable custom hardware
block6 that directly interfaces with the control and measurement plane, and combines the higher level “instructions” output by the main controller with the syndrome measurements to compute the next operations to be performed on the qubits. The challenge is in creating scalable custom hardware that is fast enough and can scale with machine size, and in creating the right high-level instruction abstraction.
The control processor plane operates at a low level of abstraction: it converts compiled code to commands for the control and measurement layer. As a result, a user will not interact with (or need to understand) the control processor plane directly. Rather, the user will interact with a host computer. This plane will attach to that computer and act to accelerate the execution of some applications. This type of architecture is widely used in today’s computers, with “accelerators” for everything from graphics to machine learning to networking. Such accelerators generally have a high-bandwidth connection to the host processor, usually through shared access to part of the host processor’s memory, which can be used to transfer both the program the control processor should run, and the data it should use during the run.
The host processor is a classical computer, running a conventional operating system with standard supporting libraries for its own operation. This computing system provides all of the software development tools and services users expect from a computer system. It will run the software development tools necessary to create applications to be run on the control processor, which are different from those used to control today’s classical computers, as well as provide storage and networking services that a quantum application might require while running. Attaching a quantum processor to a classical computer allows it to utilize all of its features without needing to start entirely from scratch.
5.1.4 Qubit Technologies
After the discovery of Shor’s algorithm in 1994, serious efforts were launched to find an adequate physical system in which to implement quantum logic operations. The rest of this chapter reviews the current candidate qubit technology choices upon which to base a quantum computer. For the two furthest developed quantum technologies, superconducting and trapped ion qubits, this discussion includes details of the qubit and control planes in use in prototypical computers at the time of publication of this report (2018), the current challenges that must be overcome for each technology, and an assessment of the prospects for scale-up to very large processor sizes in the long term. The review of other emerging technologies provides a sense of their current status, and potential advantages if they are developed further.
5.2 TRAPPED ION QUBITS
The first quantum logic gate was demonstrated in 1995 using trapped atomic ions , following a theoretical proposal earlier in the same year . Since the original demonstration, technical advances in qubit control have enabled experimental demonstration of fully functional processors at small scale and implementation of a wide range of simple quantum algorithms.
Despite success in small-scale demonstrations, the task of constructing scalable and quantum computers considered viable by current computing industry standards out of trapped ions remains a significant challenge. Unlike the very large scale integration (VLSI) of transistors enabled by the integrated circuit (IC), building a quantum computer based upon trapped ion qubits requires integration of technologies from a wide range of domains, including vacuum, laser, and optical systems, radio frequency (RF) and microwave technology, and coherent electronic controllers [3-5]. A path to a viable quantum computer must address these integration challenges.
A trapped ion quantum data plane comprises the ions that serve as qubits and a trap that holds them in specific locations. The control and measurement plane includes a very precise laser (or microwave) source that can be directed at a specific ion to affect its quantum state, another laser to “cool” and enable measurement of the ions, and a set of photon detectors to “measure” the state of the ions by detecting the photons that they scatter. Appendix B provides a technical overview of current strategies for constructing a trapped ion quantum data plane and its associated control and measurement plane.
5.2.1 Current Trapped Ion Quantum “Computers”
Based on the high-fidelity component operations demonstrated to date, small-scale ion trap systems have been assembled where a universal set of quantum logic operations can be implemented on a 5-20 qubit system in a programmable manner , forming the basis of a general-purpose quantum computer. Not surprisingly, at 2-5 percent for two-qubit gates, the error rates of individual quantum logic operations in these fully functional 5-20 qubit systems lag behind the 10–2 to 10–3 range for state-of-the-art demonstrations of two-qubit systems, pointing to the challenge of maintaining the high fidelity across all qubits as the system grows in size. Nonetheless, the versatility of these prototype systems has enabled a variety of quantum algorithms and tasks to be implemented on them. Fully programmable small-scale (three to seven qubit) trapped ion systems have been used to implement Grover’s search algorithm , Shor’s factoring algorithm , quantum Fourier transform , and others.
All of the prototype general-purpose trapped-ion quantum computer systems demonstrated to date consist of a chain of 5 to 20 static ions in a single potential well. In these machines, each single qubit gate operation takes 0.1-5 μs, and a multiqubit gate operation takes 50-3,000 μs depending on the nature of the gates used. Each ion in the chain interacts with every other ion in the chain due to the strong Coulomb interaction in a tight trap through motional degree of freedom that is shared among the ions. This interaction can be leveraged to realize quantum logic gates between nonadjacent ions, leading to dense connectivity among the qubits in a single ion chain. In one approach, a global entangling gate is applied to all qubits in the chain, where a subset of qubits are “hidden” from the others by changing their internal states, rendering them insensitive to the motion . An alternative approach is to induce a two-qubit gate between an arbitrary pair of ions in the chain by illuminating specific ions with tightly focused and carefully tailored control signals, such that only the desired ions move—many control signals are used to make the force on all the other ions cancel out . Using either approach, one can realize a general-purpose quantum processor with fully connected qubits , meaning that two-qubit gates may be implemented between arbitrary pairs of qubits in the system ; these capabilities are expected to scale to over 50 qubits in a relatively straightforward way .
The table shows the comparison of classical computing with quantum computing.
LITERATURE SURVEY
HISTORY OF QUANTUM COMPUTING
In 1982, the Nobel Prize winner physics scientist Richard Feynman thought up the idea of a quantum computer. He thought it as a computer that can use the effects of quantum mechanics to its advantage [23]. A quantum computer would be able to crack the codes more speedily than any ordinary classical computer. In 2000 March, Scientists from Los Alamos National Laboratory announced that they have succeeded to develop a 7-qubit quantum computer with a single drop of liquid. In 2001 IBM and Stanford University scientists successfully experienced Shor's Algorithm on a quantum computer. The Shor's Algorithm is used to find the prime factors of numbers. These scientists used a 7-qubit computer to calculate the factors of number 15. The computer correctly calculated that the prime factors were 3 and 5. In 2006 Scientists in Waterloo and Massachusetts establish ways to control a 12-qubit system. They found that Quantum computation related control becomes more and more complex as we increase the number of Qubits. In 2007 Canadian base quantum computer manufacturing company D-Wave created a 16- qubit quantum computer. This quantum computer solved many pattern matching problems
QUANTUM LANGUAGES QCL
(Quantum Computer Language) is the most advanced implemented quantum programming language. Its syntax is similar to the syntax of the C programming language and classical data types are similar to data types in C. Quantum Computation involves some new concepts which are related to the movement of the particles like entanglement.
CAPABILITIES AND LIMITATIONS
Quantum computers are much powerful than classical computers. The Quantum computer can solve problems with no time which a classical computer can take years to solve. Quantum computers can perform multiple transactions at one time as compared to the classical computers. This increases their power very much. The making of quantum computers will be revolutionary for whole mankind. It will reduce workload and solve problems with no time which now we can solve in days or weeks.
As the coin has two sides, lets see its flip side . On the other hand the quantum computers are still a dream and they are not as much scalable yet. We should not be too optimistic regarding quantum computers because they might let us down. Because this is too early to guess what will they do. Noise distortion can lead to information corruption. Different implementations of Quantum Computers have been developed but they are of limited use and are made only for certain type of demonstration.
Conclusion
The quantum computers are the future of computing. Quantum computing is a great prospect and it will solve many problems which cannot be solved by classical computing. It will also decrease the time of problem solving for the problems which are now solvable by classical computing. The hardware and programs related to Quantum computing are not yet built completely. These are evolving but soon it will become a reality and will change the technology worldwide. Many technology giants like Google, IBM, Microsoft and the giant of processors intel is also working on quantum computing and they are spending millions of dollars on research. They are researching on building hardware and algorithms for the quantum computers. The work is also being done in relation to the security and complexity of the quantum computation in order to get secure and reliable quantum systems. The hardware, programming languages and algorithms will also change.