The construction of a conventional computer is relatively easy, and most parts can be purchased online. However, a quantum computer requires special parts that can be difficult or expensive to acquire. Furthermore, the dilution refrigerators required to keep the computer at absolute zero cannot be substituted with other components. As a result, the price of a quantum computer is extremely high, despite the potential for enormous benefits. In order to build a quantum computer, you must be knowledgeable about basic PC setup, however.
Creating a commercial-grade quantum computer
While commercial-grade quantum computers are still years away, they may be more accurate than conventional computers and solve some problems faster than ever. Unlike traditional computers, which store information as zeros and ones, quantum computers store and represent information in a complicated mix of zeros and ones. While the current chip used by Google is called Sycamore, many more will follow. As with conventional computers, commercial-grade quantum computers would require additional monitoring devices and conventional computers.
The automotive industry is a prime candidate for quantum applications. By reducing manufacturing costs, shortening cycle times, and improving path planning in complex multirobot processes, quantum computing can improve efficiency and lower costs. The automotive industry currently spends about $500 billion on manufacturing costs, and a two to five percent improvement could create a $10 to $25-billion-per-year value. Regardless of the costs associated with quantum computing, business leaders should be ready to prepare now for when the technology matures.
While the cost of creating a commercial-grade quantum computer is still a long way off, IBM has already launched a free cloud computing service, the IBM Q Experience. This software provides a virtual environment for developers to practice building quantum algorithms. It has over 40,000 registered users in more than 100 countries. The IBM Q Network has over 100 members, and over 130 billion executions have been performed since the programme began.
The cost of a single quantum qubit is currently as high as $10 million, which is a fraction of the total cost of a commercial-grade quantum computer. Even if it can be produced for under $5 million, it will likely still remain out of reach for the average consumer. And it is unlikely to be in reach for a Black Friday sale, either. Despite this, the cost of developing a commercial-grade quantum computer is expected to remain out of reach until at least 20 years.
Google has announced plans to offer commercial-grade quantum computing services on the cloud. The company has outlined its goal of building commercial-grade quantum computers by 2029. While the company is focused on developing energy-efficient batteries, making fertilizer with less carbon dioxide, and speeding up machine-learning training, it is also interested in building commercial-grade quantum computers to speed up these applications. To build such a machine, Google needs a million-qubit quantum computer. However, their current systems are only a few hundred qubits.
In addition to the aforementioned benefits, quantum computing can also improve the research and development of the chemical industry. Improved catalyst designs can help make chemicals more efficient, and may even boost energy savings. One catalyst could gain up to 15 percent efficiency. This technology could also allow the replacement of petrochemicals, and break down carbon for use as fertilizer. This could result in an estimated $35 to $75 billion in annual operating income for the chemicals industry.
Scaling up from 50 qubits to several million qubits
The next challenge is scaling up from 50 qubits to several million. A quantum computer with a few hundred qubits is already the state-of-the-art technology, but scaling it up to several million qubits is a challenge. The current state of the art quantum computer uses silicon and superconductor-based qubits, but the potential is enormous. In addition to improving the consistency of these qubits, refrigerators that chill them will need to be made smaller and more energy-efficient. Topological qubits will also need to be invented.
The complexity of controlling an ensemble of trapped ions increases with the number of ions squared. That’s why adding more ions to the ensemble would be impractical. Instead, scientists are developing modular traps with 20 ions. Certain qubits in each module will be hubs, allowing them to share information with other modules. This arrangement will protect most of the qubits from external interference.
Despite the difficulties in scaling up quantum devices, it’s possible to make them larger with similar designs. Computer chips, for example, are made up of billions of silicon-based transistors that are controlled by metal wiring. While silicon-based transistors are the powerhouses of binary computation, the same materials can be used to create larger, higher-density arrays.
A large-scale quantum computer could be built using silicon. The semiconductors used to make classical computers are no longer as efficient as their silicon-based counterparts. The next challenge is achieving a high-density quantum computer. Silicon qubits are a viable solution because they use the same gates and dielectrics as classical ones. These qubits can be made to scale from 50 to several million qubits on a quantum computer.
A quantum computer will be disruptive to many industries. Google is one of the leaders in this field. It has developed a nine-qubit machine and is working on a system with 49 qubits. This is a critical threshold because it would mean quantum supremacy. The term, coined by John Preskill, describes quantum computers that can perform tasks beyond the capabilities of conventional computers.
Currently, the cost of a single qubit is $10 billion, before R&D costs, and a useful universal quantum computer would cost tens of billions of dollars. To become a viable alternative, the cost per qubit will need to be drastically reduced. While academics have speculated on stacking devices, the National Academy of Sciences is less optimistic.
For a quantum computer to become useful, its hardware will need to scale up from 50 to several million qubits. Current quantum computers have a limited number of qubits and are designed to perform simple tasks. But once the hardware improves, millions of qubits will likely be necessary. If you want a truly useful quantum computer, it will likely have millions of robust qubits.
Logic error-correction in quantum computing
Logic error-correction in quantum computers allows systems to perform computations with less probability of error. A universal set of gates can approximate all quantum calculations, but it is difficult to program for more complicated systems. A recent demonstration demonstrated the use of Schrodinger-cat states encoded in a superconducting resonator. While error-correction is difficult, it is essential for the development of quantum computers.
One of the biggest challenges in quantum computing is that classical methods of error correction do not work. Since quantum information cannot be copied, it can only be measured. The logical state of a qubit cannot be copied, so measuring it would destroy it. Therefore, errors would occur in flipped bits or phases of waves. Because of this, quantum computers need to implement a system that can detect such errors and avoid them from ruining the process.
The classical method of error correction uses redundancy. One approach is the repetition code. The repetition code stores information multiple times and takes the majority vote. However, a noisy error can corrupt a three-bit state. In this case, one bit may be zero, two bits might be one, and so on. In order to correct for this error, the error rate of a system must be below a threshold.
Logic error-correction in quantum computers can be accomplished through a method known as monitoring parity. The process works by averaging noisy voltage traces against the logical subspaces of the system. The noise is then correlated to stabilizer eigenvalues. As the monitoring parity stabilizers stabilize the logical subspaces, the observer receives a continuous stream of noisy information that correlates with the stability of the system.
To achieve successful quantum computing, the hardware and theory must be in sync. A quantum computer’s quantum circuits must be configured to accommodate the engineering constraints of the machine. This is the biggest challenge to overcome in developing error-correction. A quantum error correction code includes qubits encoding logical quantum information and overhead resources to perform stabilizer measurements. A quantum computer can’t be fault-tolerant without fault-tolerant, scalable, and error-corrected components.
Earlier research has focused on detecting single-qubit errors and developing methods for correcting them. But the team has also demonstrated how to detect and correct two distinct types of quantum errors. They are close to the breaking point. If they can show that the error rate per quantum error-correction cycle is lower than the largest physical error, they’ll be able to achieve breakeven. However, further development will be required to reach this goal.
In order to implement QEC, scientists have implemented an approach called entangled qubits. These qubits entangle with a subset of data qubits, allowing them to detect errors. They are then measured after entanglement. By analyzing the resulting data, they can infer the corrective action that the data qubits should take. This scheme is a major step toward building a large-scale quantum computer.
