The Qubit. Manufacturing, challenges, and applications.

What is a Qubit?

A qubit, or quantum bit, is the basic unit of information used to encode data in quantum computing and can be best understood as the quantum equivalent of the traditional bit used by classical computers to encode information in binary.

The term “qubit” is attributed to American theoretical physicist Benjamin Schumacher. Qubits are generally, although not exclusively, created by manipulating and measuring quantum particles (the smallest known building blocks of the physical universe), such as photons, electrons, trapped ions, superconducting circuits, and atoms.

Enabled by the unique properties of quantum mechanics, quantum computers use qubits to store more data than traditional bits, vastly improve cryptographic systems, and perform very advanced computations that would take thousands of years (or be impossible) for even classical supercomputers?to complete.

Powered by qubits, quantum computers may soon prove pivotal in addressing many of humanity’s greatest challenges, including cancer and other medical research, climate change, machine learning, and artificial intelligence (AI).?

Qubits vs Bits

There are many different types of bits and qubits, but all qubits must adhere to the laws of quantum physics and be able to exist in a quantum superposition.

A classical bit can only exist in either a 0 position or a 1 position. Qubits, however, can also occupy a third state known as a superposition. A superposition represents 0, 1, and all the positions in between taken at once, for a total of three separate positions.

While qubits can encode three separate positions, they are still used to convey information through a binary system. In such systems, the term bit can refer to either the material or process used to represent a 0 or 1, or the measurement of that bit (i.e., a 0 or a 1).?

Understanding Bits

In traditional or classical computing, a single bit can be thought of as a piece of binary information, notated as either a 0 or a 1. Modern computers typically represent bits as either an electrical voltage or current pulse (or by the electrical state of a flip-flop circuit).

In these systems, when there is no current flowing, the circuit can be considered to be off, and this state is represented as a 0. When current is flowing, the circuit is considered on, and this state is represented as a 1.

The term “bit” is itself a portmanteau for “binary digit,” and binary bits are the foundational basis of all computing. Whether recording a digital video, animating a 3D model or using a calculator app—all data from operating systems to software are built out of binary code, which is a collection of bits. A computer byte consists of eight bits, which is the minimum number of bits needed to convey a single textual character in binary.?

Bits can be represented electrically, by running (or not running) current through a silicon chip, for example. Bits can also be represented physically, as a hole or the absence of a hole in a piece of paper, as was used in antiquated punch-card computing. Any two-level system in which the state of the system can be described in only one of two potential positions (e.g., up or down, left or right, on or off) can be used to represent a bit.?

Understanding Qubits

While quantum technologies do use binary code, the quantum data derived from a quantum system—such as a qubit—encodes data differently from traditional bits, with a few remarkable advantages. Researchers have established a variety of ways to either create qubits or use naturally occurring quantum systems as qubits. However, in nearly all instances, quantum computers require extreme refrigeration to isolate qubits and prevent interference.?

Theoretically, any two-level quantum system can be used to make a qubit. A quantum system is described as two-level when certain system properties can be measured in binary positions, such as up or down. Multi-level quantum systems can be used to create qubits, as well, as long as two aspects of that system can be effectively isolated to produce a binary measurement. Just as traditional computers can use multiple types of bits—such as electrical current, electrical charge, or holes punched (or not punched) in a piece of paper for punch-card computing—quantum computers can use multiple types of bits. Certain bits are better suited to certain functions, and an advanced quantum computer will likely use a combination of bit types to achieve different operations.

Since each bit can represent either a 0 or a 1, by pairing two bits of information, we can create up to four unique binary combinations:

1. 0 0
2. 0 1
3. 1 0
4. 1 1

While each bit can be either a 0 or a 1, a single qubit can be either a 0, a 1, or a superposition. A quantum superposition can be described as both 0 and 1, or as all the possible states between 0 and 1 because it actually represents the probability of the qubit’s state.?

On the quantum level, qubit probability is measured as a wave function. The probability amplitude of a qubit can be used to encode more than one bit of data and carry out extremely complex calculations when combined with other qubits.

When processing a complex problem, such as factoring a large prime number, traditional bits become bound up by holding large quantities of information. Quantum bits behave differently. Because qubits can hold a superposition, a quantum computer using qubits can calculate a much larger volume of data.?

As a helpful analogy for understanding bits vs. qubits, imagine you are standing in the center of a complicated maze. To escape the maze, a traditional computer would have to “brute force” the problem, trying every possible combination of paths to find the exit. This kind of computer would use bits to explore new paths and remember which ones are dead ends. Comparatively, a quantum computer might, figuratively speaking, at once derive a bird’s-eye view of the maze, testing multiple paths simultaneously and revealing the correct solution. However, qubits do not “test multiple paths” at once. Instead, quantum computers measure the probability amplitudes of qubits to determine an outcome. As these amplitudes function like waves, they also overlap and interfere with each other. When asynchronous waves overlap, it effectively eliminates possible solutions to complex problems and the realized coherent wave or waves present the solution.

Manufacturing Qubits at scale. What are the challenges?

1. Fidelity at Scale: Maintaining high levels of qubit quality (fidelity) while increasing qubit count and computational power for complex algorithms is a significant challenge in quantum computing. High fidelity is crucial for the accuracy and reliability of quantum computations.
2. Computation Speed: Individual qubits can retain their quantum state (coherence) for only a limited time. To enable complex computations before qubits lose coherence, gate operations must occur quickly enough. Ensuring fast gate operations is essential for the efficiency and effectiveness of quantum computations.
3. Multiqubit Networking: Linking multiple qubits to perform gate operations is essential for implementing quantum computing algorithms and enhancing the power of quantum computers. Establishing efficient multiqubit networking is crucial for scaling up quantum computing systems.
4. Control over Individual Qubits at Scale: As the number of qubits in a quantum computing system increases, controlling individual qubits becomes increasingly complex. Ensuring precise control over individual qubits at scale is a key challenge in quantum computing.
5. Cooling and Environmental Control: Most qubit technologies require extensive cooling equipment, both in terms of size and power, which may exceed the feasibility of currently available equipment. Managing the cooling and environmental control requirements for qubits at scale poses a significant challenge.
6. Manufacturing: Some qubit designs use existing production technology, while others require new manufacturing techniques. The production of full-scale quantum computers will necessitate automated manufacturing and testing for components at scale. Developing scalable manufacturing processes for qubits is crucial for the mass production of quantum computing systems.

Nowadays five main qubit technologies are competing to build a scalable universal quantum computer.

• Photonics Network: Occupation of a photonic waveguide. Start-up funding = USD 1.362 Billion
• Superconducting Circuits: Difference in energy states of Cooper pairs between two sides of a Josephson tunnel junction. Start-up Funding = USD 732 Million + Tech Players Funding= USD 2.0 Billion
• Spin-Qubits: Electron spins of different materials (eg, an electron trapped within a silicon quantum dot or a color center in an insulator, controlled by laser light or microwave radiation). Start-up Funding = USD 93 Million + Tech Players Funding = USD $200 Million
• Neural Atoms: Internal energy levels of neutral atoms trapped by laser fields. Start-up Funding = USD 145 Million
• Trapped Ions: Internal energy levels of ions trapped by electromagnetic fields. Start-up Funding = USD 1.423 Billion + Tech Players = USD 200 Million

To take the best advantage of qubits, industries can leverage the unique properties of quantum mechanics to solve complex problems that are currently unsolvable or require an impractical amount of time with classical computers. Some of the key areas where qubits can bring significant benefits include:

1. Pharmaceuticals: Quantum computing can revolutionize the research and development of molecular structures, making it more efficient and less reliant on trial and error.
2. Chemicals: Quantum computing can improve catalyst design, leading to savings on existing production processes and enabling the replacement of petrochemicals with more sustainable feedstock.
3. Mobility: Quantum computing can facilitate the rapid and smooth exchange of vast amounts of data between in-vehicle computers and computers elsewhere, enabling a fully connected, intelligent, and environmentally friendly mobility ecosystem.
4. Automotive: Quantum computing can be applied to decrease manufacturing costs by optimizing complex multi robot processes, such as welding, gluing, and painting.
5. Finance: Quantum computing has long-term promise in finance, particularly in portfolio and risk management.

To fully harness the power of qubits, industries need to invest in research and development, collaborate with academia and other stakeholders, and develop strategies for integrating quantum computing into their operations.