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Highlights
- Quantum technologies will prove to be a significant disruptor and will revolutionize the field of computing. Quantum Computing leverages quantum mechanics to exponentially boost processing power.
- Quantum computers will have significant implications for industries that rely on optimization to assess various potential outcomes, each with numerous dependencies and constraints.
- Another significant area of application for quantum computing could be routing for autonomous vehicles.
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Understanding QC and the limitations of classical computers
In the coming years, quantum technology will likely be a potent technological disruptor that may change the entire computing framework.
Countries that gain an upper hand in this field will enjoy an early advantage and leadership position. With this goal in mind, the Government of India (GOI), in its 2020 Union Budget, announced a National Mission on Quantum Technologies & Applications (NM-QTA) with an outlay of Rs 8,000 crore for five years.
Quantum technologies will revolutionize the computing field. Quantum Computing (QC) leverages quantum mechanics or particle principles to boost processing power by using superposition and entanglement properties.
Classical computers use binary bits (0 or 1) to process information, whereas quantum computers use quantum bits or qubits. The binary bits use transistors that can hold only one value at a time (0 or 1). Even though the transistor size is reducing yearly, we are gradually reaching the limit where classical computers can’t process any faster.
On the other hand, qubits can hold any value between 0 and 1 with a certain probability, called superposition, where qubits can hold both (0 and 1) states at the same time before it is measured. Another QC property is entanglement, where qubits are closely related, which allows QCs to solve complex problems that are difficult to do with classical computers. Superposition gives exponential computing power, whereas entanglement powers it to solve complex problems even at the molecular level.
The following figures depict the classical and quantum bits.
How classical bit works.
Illustration of a quantum bit or Qubit.
To make the quantum computer function and process the data, it must hold an object for sufficient time in a superposition state. However, a quantum computer needs to be cooled to near Absolute Zero to hold the superposition and entanglement states. Present-day quantum computers are prone to high error rates due to multiple external factors such as noise, vibration, and temperature change.
Applying QC to manufacturing industry
The following infographic depicts the challenges, enablers, and applications of QC in the manufacturing industry.
Impact of quantum computing in optimizing manufacturing process.
Use Case 1: Supply chain network optimization
The following figure illustrates the selection of the best potential sites or routes to equip with services to satisfy demand within a particular area while minimizing costs.
Use of quantum computing in supply chain network optimization
Quantum computers will likely have significant implications for industries that rely on optimization to assess various potential outcomes, each with numerous dependencies and constraints.
Figure 4 depicts a straightforward supply chain network. There are two plants from which materials must be routed to three distribution centres to fulfil demand from each site. If transportation cost (C) is fixed for each route, then the unit can minimize the overall cost (Z) by optimizing the material part flow (X).
But the actual scenario could be different. Manufacturing plants could be 20 to 30 in number, and distribution centers could be around 200 to 400. In that case, the above equation becomes lengthy. Classical computers will take longer to render the optimized solutions, which may sometimes lead to opportunity loss. Suppose other dependencies like variable fuel cost, variable demand, new processes, and new distribution sites are to be added. In that case, it may become impossible for the present day's computer to process it. So, we must utilize the computing capacity of the quantum computer here to facilitate optimized solutions and real-time decision-making.
Use-case 2: Routing in autonomous vehicles
The following table highlights real-time decision-making by autonomous vehicles.
Real-time decision making by autonomous vehicles
We can use QCs to deal with real-time routing problems. It uses live data from connected vehicles, roads and railways, weather satellites, and other data feeds.
Table 1 showcases the ecosystem of autonomous vehicles where trajectory choices are made. The best route can be picked based on analyzing the current position and past experiences (by analyzing time series data using Machine Learning). With the path planning system, QC can help constantly recalibrate the vehicle's path in real time.
