Quantum Computing

Quantum computing is an area of computer science that uses the principles of quantum theory at the atomic and subatomic levels. It uses subatomic particles, such as electrons or photons. Classical computers, which include smartphones and laptops, encode information in binary “bits” that can either be 0s or 1s. In a quantum computer, the basic unit of memory is a quantum bit or qubit. Quantum bits, or qubits, allow the subatomic particles to exist in more than one state at the same time.

Theoretically, linked qubits can exploit the superposition, entanglement and interference between their wave-like quantum states to perform calculations that might otherwise take millions of years.

Key Principles of Quantum Computing

Quantum computers are based on these key principles of quantum physics that enable new approaches to information processing:

Key principle	Description
Superposition	- The fundamental principle that enables the power of quantum computing is 'quantum superposition'.  - Unlike traditional bits used in classical computers that can exist in only one state (either 0 or 1), quantum bits or 'qubits' can exist in a superposition of 0 and 1 simultaneously.
Quantum Entanglement	- Quantum Entanglement is where quantum particles interact physically in ways such that the quantum state of each cannot be described independently. - Measuring one particle instantaneously affects the others even over long distances. - This enables quantum systems to exhibit correlations stronger than any possible classical behaviour.
Quantum Interference	- The wave-like characteristics of quantum particles cause interference effects between different probability states that can result in constructive or destructive interference analogous to the interference effects seen in waves. This effect is harnessed in quantum algorithms.
Quantum Tunneling	- Quantum tunnelling refers to the ability of particles to tunnel through barriers when according to classical physics they do not have enough energy to do so.  This principle is critical for the functioning of quantum computer hardware like quantum dots.

Quantum Computer Hardware

The hardware components underlying current quantum computers include:  
 

• Qubits: As the basic units for information representation and processing, different physical systems are engineered to serve as qubits. The most common in use today are:
  • Superconducting circuits are maintained at very low temperatures.
  • Trapped ions are manipulated using lasers and kept at an ultrahigh vacuum.
  • Defects in diamond crystals provide stability at room temperature.
• Quantum Logic Gates: As the counterparts of logic gates used in classical computing, quantum logic gates manipulate qubits to perform computational operations.
  • Common single and multi-qubit gates include the Hadamard, CNOT, and SWAP gates.
• Qubits need to be maintained in a delicate state through isolation, extremely low temperatures and manipulation using precision lasers or microwave pulses applied for extremely short durations.
• The fragility severely limits the number of sequential operations that can be performed reliably.

Difference between Classical and Quantum Computing

While both quantum and classical systems encode and process data, they have fundamental differences:

• These contrasts between classical binary and quantum paradigms give quantum computers potential advantages in solving specific problems intractable via conventional means.

Quantum Supremacy

Quantum supremacy is the experimental demonstration of a quantum computer's dominance and advantage over classical computers by performing well-defined calculations previously impossible at unmatched speeds.

• The term “Quantum Supremacy” was coined by John Preskill in 2011.
• It is a milestone of the exceptional computing capability of quantum computers to perform some exceptional computational tasks.
  • In 2019, Google officially announced the achievement of quantum supremacy using its 53-qubit quantum processor named Sycamore.
  • The computer solved a sampling problem considered practically impossible for classical systems in about 200 seconds which even the fastest supercomputers would take 10,000 years to execute.

Advantages of Quantum Computing

Quantum computing has significant applications that offer prospects of scalability. It can accelerate various fields such as:

• Search and optimisation: Grover's algorithm for database search offers quadratic speedup - a database of 4 entries takes 1 lookup on a quantum computer versus 4 lookups classically.
  • This could enable ultra-fast search of large real-time financial, healthcare or classified datasets.
• Chemical simulation: Quantum computers with 50-100 qubits could precisely simulate complex enzyme mechanisms and chemical processes for the industrial production of fertilizers, polymers and biomass.
  • This may enable the designing of better catalysts and materials.
• Artificial intelligence: Japanese researchers designed a quantum neural network that detects credit card fraud with 63% accuracy versus 50% for classical networks. 
  • This demonstrates the potential for quantum machine learning.
• Financial analysis: Massively enhanced portfolio optimization, price modelling, risk analysis and economic forecasting can be achieved to alter financial services, investment strategies and economic policy.
• Secure communication: All widespread public-key cryptography is vulnerable to attacks using quantum algorithms negating the security of communication channels and protocols like online banking, messaging and sensitive database access.
  • China recently demonstrated (QUESS) satellite-based quantum key distribution for hack-proof military communications.
• Healthcare advancement: Precision modelling of protein folding mechanisms, gene sequencing, disease pathology simulations, personalised medicine and drug discovery can transform healthcare and life sciences through quantum computing.
• Climate change science: NASA plans to use quantum computing for very high-resolution regional and global scale climate modelling by assimilating large datasets using quantum neural networks.

Limitations of Quantum Computing

Quantum computing emerged as one of the most promising technologies, however, there are the following limitations:

• Hardware fragility: Google's 72-qubit quantum computer requires temperatures near absolute zero inside vacuum chambers, with vibration dampening and magnetic shielding increasing complexity.
• Decoherence: IBM researchers reported the coherence time for a 27-qubit system was 47 microseconds - too short for practical error correction schemes.
• Lack of standards: Currently no standards exist for quantum programming languages and software tools.
  •  Recently IBM and Microsoft clashed over how fidelity benchmarks are defined across superconducting, ion trap and photonics hardware.
• Qubit scalability: Intel's 49-qubit superconducting quantum chip Pushan is a high watermark.
  • However, the company hasn't elaborated a roadmap for the millions of qubits likely needed for quantum advantage in domains like machine learning or chemical simulation.

Applications of Quantum Computing

Quantum Computing has a myriad of applications in various walks of life such as secure communication, optimising industrial processes, complex chemical simulation etc.

• Drug Designing: QCs overcome the limitations of existing computational methods to know the behaviour of particles. It could employ entanglement and superposition to leverage and handle all the possible permutations of molecular behaviour of drugs efficiently.
  • For example: Pharma research outfits such as SRI International, and AstraZeneca explore QC’s potential in modeling protein.
• Artificial Intelligence and Machine Learning: Quantum computers have the potential to accelerate or improve machine learning relative to classical performance. It harnesses statistical distribution to tackle machine-learning problems efficiently.
  • For example: IBM came up with a promising machine-learning classification algorithm- a quantum-classical hybrid.
• Optimisation: Quantum computing can improve research and development, production processes, and supply-chain optimization.
  • For example- quantum computing decreases manufacturing process–related costs and also reduces cycle times by optimizing elements such as path planning in complex processes.
• Financial sector: quantum optimization of loan portfolios so that lenders can make better decisions, free up capital, lower interest rates, and improve their offerings.
• Auto-industry: QCs’ potential to simulate quantum mechanics could be equally transformative in other chemistry-related realms.
  • E.g.,- The auto industry wants to harness the technology to build better car batteries.
• Cryptography: QCs’ enabled encryption ensures hack-free data transmission by using superdense coding -secure quantum communication protocol.
• Astronomy: Quantum computing could reveal the mystery of unique processes of the universe such as the Big Bang and black holes, due to its ability to simulate molecules, and molecular processes of the universe.

Quantum Computing in India

India is gearing up to accelerate indigenous efforts around the development of quantum computing:

• Budget 2023: Rs 6000 crore (USD 800 million) allocated towards a National Mission on Quantum Computing and Technology spanning 5 years.
• TCS National Qualifier Test 2023: Conducted a first-of-its-kind online test to identify talent for building quantum computing skills and knowledge across India’s universities.
• MeitY Initiatives: Launched Quantum Computing Applications Lab on AWS Cloud focused on developing tools and methods to leverage quantum for critical national applications.
• Indian Institute of Science: Establishing a dedicated Quantum Technologies and Application Centre to conduct research around NISQ computing software and hybrid quantum-classical algorithms.
• Indian Institute of Technology Madras: Undertaking fundamental R&D across quantum cryptography, communication, sensing, and networks while also establishing the Centre for Quantum Information, Communication and Computing.