Computação Quântica - Fundamentos e Aplicações - Aula 06

Summary

The video explores the current state of quantum computing, focusing on the Noisy Intermediate-Scale Quantum (NISQ) era, where quantum computers have limited qubits (100–400) and are affected by external noise. Despite these challenges, algorithms like VQE and QAOA are utilized for molecular modeling and optimization tasks. The video also touches on adiabatic quantum computing, a non-programmable approach for solving quadratic problems. Lastly, quantum computing programming relies heavily on Python, with libraries such as Qiskit and Q# offering tools for practical applications, marking significant progress in a still-developing field.

Takeaways

• 😀 Quantum computing is currently in the Noisy Intermediate-Scale Quantum (NISQ) era, characterized by systems with hundreds of qubits but not yet enough to fully realize advanced quantum algorithms.
• 😀 NISQ era computers face significant challenges due to interference (or 'noise') from the environment, making it difficult to scale and perform operations with high precision.
• 😀 Quantum computers today typically feature 100 to 400 qubits, far from the tens of thousands needed to solve complex problems efficiently.
• 😀 Two widely used quantum algorithms in the NISQ era are the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA), both of which work with a limited number of qubits and can deliver some results despite noise.
• 😀 VQE helps model molecules by calculating the lowest energy state, which is essential in fields like chemistry and material science.
• 😀 QAOA is used for optimization problems, adjusting the quantum state to approximate the optimal solution in fields like logistics, finance, and machine learning.
• 😀 Quantum adiabatic computing is another approach that slowly adjusts the energy of a system to reach the lowest energy state, used for solving quadratic problems but is not as flexible as gate-based quantum computing.
• 😀 Quantum adiabatic computers are not fully programmable, as they come with predefined structures that can only solve specific problems.
• 😀 Python is the primary language used for quantum computing, with popular libraries such as Qiskit and Cirq allowing developers to create and manipulate quantum circuits.
• 😀 Other programming tools for quantum computing include domain-specific languages like OpenQASM, which are used to define quantum commands and interfaces with quantum hardware.

Q & A

What is the current phase of quantum computing as described in the transcript?

The current phase of quantum computing is called the Noisy Intermediate-Scale Quantum (NISQ) era. This phase is characterized by quantum computers having 100 to 400 qubits, but still facing challenges due to noise and environmental interference.

What does 'Noisy' in NISQ refer to in the context of quantum computing?

'Noisy' refers to the interference from the environment that affects the quantum systems, making them less stable and precise. Quantum computers today still suffer from this noise, which limits the accuracy of quantum operations.

What is the significance of qubits in quantum computing, and how many are currently available in quantum computers?

Qubits are the fundamental units of quantum computing, analogous to bits in classical computing, but they can represent both 0 and 1 simultaneously due to quantum superposition. Currently, quantum computers have between 100 and 400 qubits, which is still far from the tens of thousands needed for more efficient solutions.

What are some of the key algorithms used in the NISQ era of quantum computing?

The key algorithms used in the NISQ era include the Variational Quantum Eigensolver (VQE), which is used for molecular modeling, and the Quantum Approximate Optimization Algorithm (QAOA), which is used for general optimization problems.

How does the Variational Quantum Eigensolver (VQE) algorithm work?

VQE is based on finding the lowest energy state of a quantum system, which can represent a solution to a problem, particularly in molecular modeling where it is used to understand the energy states of atoms within molecules.

What role does noise play in the NISQ era of quantum computing?

Noise in quantum computing refers to the disruptions caused by external environmental factors, which interfere with qubits' ability to maintain their quantum states. This noise impacts the reliability of quantum algorithms, making them less precise and harder to scale.

What is adiabatic quantum computing, and how does it differ from traditional quantum computing?

Adiabatic quantum computing is a method where a system gradually evolves towards its lowest energy state in a controlled manner. It is primarily used for solving optimization problems, unlike traditional quantum computing, which often relies on gate-based operations.

What challenges are currently faced in scaling quantum computing?

Scaling quantum computing is difficult due to several factors, such as the need to maintain a high level of isolation and precise environmental control to protect qubits from interference. Additionally, more qubits are required for larger-scale computations, but current technology struggles to maintain stability and coherence across many qubits.

How is quantum programming typically done today?

Quantum programming is primarily done using Python, utilizing libraries like Qiskit, Cirq, and Q#, which provide tools to create and manipulate quantum circuits. These platforms help facilitate the interaction between the user and quantum hardware.

What is OpenCASMA, and how does it relate to quantum computing?

OpenCASMA is a quantum programming language designed to define commands for quantum circuits. It is an open-source language that allows for the creation of quantum algorithms and interactions with quantum systems, making it easier to implement quantum solutions.