Login Get started

Quantum Computing for Computer Scientists

Microsoft Research・71 minutes read

The text discusses Quantum Computing for Computer Scientists, focusing on quantum algorithms outperforming classical models, the importance of learning quantum computing, and the unique concepts like superposition and entanglement. The text also covers essential topics such as qubits, quantum logic gates, the Hadamard gate, and applications like Shor's algorithm for factoring RSA.

Insights

Quantum Computing for Computer Scientists focuses on the Computation Model, Quantum Algorithms, and Quantum Annealing Model, excluding physics topics like the Double-Slit Experiment.
Learning Quantum Computing offers exciting applications like Shor's algorithm and potential revolution in biological research, emphasizing the need for mathematical understanding and departure from classical intuition.
Quantum Computing involves qubits, gates like CNOT and Hadamard, and algorithms like Shor's and Grover's, with implications for entanglement, teleportation, and error correction, requiring physical qubits for logical qubits and recommendation of key textbooks for further study.

Get key ideas from YouTube videos. It’s free

Recent questions

What is Quantum Computing?
Quantum computing utilizes quantum-mechanical phenomena for computation.
Why should I learn Quantum Computing?
Learning Quantum Computing can lead to exciting opportunities and advancements.
How do Quantum Computers differ from Classical Computers?
Quantum computers utilize qubits and quantum-mechanical phenomena for computation.
What are some key Quantum Computing algorithms?
Shor's algorithm, Grover's algorithm, and Quantum cryptographic key exchange are notable algorithms.
What are some recommended resources for learning Quantum Computing?
"Quantum Computing for Computer Scientists" by David Mermin and Quantum Computing Gentle Interaction are recommended books.

Related videos

Summary

00:00

"Quantum Computing: Revolutionizing Tech with Speed"

The talk on Quantum Computing for Computer Scientists excludes physics topics like the Double-Slit Experiment and Uncertainty Principle.
The focus is on the Computation Model, particularly the Gate Quantum Computation Model, showcasing Quantum Algorithms outperforming classical models.
Quantum Annealing Model, used by D-Wave, is briefly mentioned as an alternative Computation Model.
Reasons to learn Quantum Computing include the upcoming quantum supremacy, large investments by tech giants, and exciting applications like Shor's algorithm for factoring RSA.
Quantum computers offer a speed-up in searching unordered lists and simulating quantum mechanical systems, potentially revolutionizing biological research.
Learning Quantum Computing is intellectually stimulating due to its departure from classical intuition and the need for mathematical understanding.
The presentation structure includes basic linear algebra for computation representation, Qubits, quantum logic gates, and the Deutsche Oracle problem.
Reversible Computing in Quantum Computing focuses on operations that are reversible and their potential to surpass energy efficiency limits.
The tensor product in linear algebra is explained as a way to represent multiple classical bits, with examples provided for clarity.
Multiple classical bits are represented through the tensor product, showcasing how combinations like 00 are formed in a product state.

12:07

Quantum Computing Fundamentals and Operations

Product states are represented by 01, 10, and 11, similar to single bits acting as indices in a vector array.
Each position in the vector array corresponds to a value, with the product state of n bits being a vector of size 2 to the power of n.
The CNOT gate, a fundamental operation in reversible and quantum computing, flips the target bit based on the control bit.
Applying the CNOT gate to different bit combinations results in specific outcomes, changing the product states accordingly.
Matrices are used to represent logical operations beyond simple bit flips, such as the CNOT gate.
Qubits are represented by vectors of two elements, with values constrained by a squared plus b squared equals one.
Superposition allows qubits to exist as both 0 and 1 simultaneously, with measurement collapsing them to one of the two states.
Multiple qubits are represented by tensor products, maintaining the sum of squares identity.
Operations on qubits, like negation, can be performed using matrix operators and gates, manipulating the probabilities or amplitudes of the qubits.
The Hadamard gate transforms a qubit from a zero or one state to an equal superposition state, resembling a coin flip.

24:38

Quantum Computing: Superposition, Reversibility, and Oracles

The Hadamard device is used to achieve superposition in quantum computing.
A negative sign in the bottom right corner of a matrix is necessary for reversibility in quantum computations.
Superposition in qubits means they exist in both states of 0 and 1 simultaneously.
The quantum and classical worlds differ in how they interpret qubit states.
The Hadamard gate transitions qubits out of superposition into classical bits.
Algorithms like Shor's may not always provide the correct answer, unlike the deterministic property of the problem discussed.
The unit circle represents qubit operations, with the bit flip operator having specific effects.
The Hadamard gate transitions qubits between states, forming a state machine on the unit circle.
Quantum circuit notation illustrates the application of operations on qubits, leading to reversible computations.
The Deutsch oracle problem showcases how quantum computers can outperform classical ones in determining constant or variable functions with fewer queries.

37:06

"Quantum Computation: Input to Output Rewiring"

Quantum computation involves input bits being written to output bits, with the output bits then measured.
The model requires rewiring with two wires, one for input and one for output, assuming the output wire initializes to zero.
The input wire remains unchanged, while the function is calculated and written to the output wire.
The black box must be rewired for proper functionality.
The algorithm values are not always used, but the input wire is crucial for the quantum circuit.
The input wire is always assumed to be zero for circuit construction.
Constant zero results in a straight wire circuit with no modifications.
Constant one involves a bit flip operation to achieve the desired output.
Identity involves a CNOT gate where the control bit determines the output.
The process of solving on a quantum computer involves initializing qubits to zero, applying gates, sending them through the black box, and post-processing with Hadamard gates before measurement.

50:31

Quantum CNOT Gate and Entanglement Revolutionized

CNOT is a complex operation where the input bit is the control bit and the output bit is the target bit.
The action of CNOT is to change the input qubit, which is unusual as the control bit should remain unchanged.
Applying the CNOT gate to specific states results in a matrix transformation, flipping rows and changing values.
The output of the CNOT gate shows the unchanged least significant bit and the altered input bit.
Quantum computing allows for changing the action of logic gates by being in different states.
A generalized version of the CNOT problem was found, showcasing exponential speedup in quantum computing.
Simon's periodicity problem led to Shor's algorithm for factoring large integers, revolutionizing the field.
Quantum entanglement involves qubits coordinating across vast distances instantaneously.
Entangled qubits synchronize their states faster than light, without actual communication of information.
Hidden variable theory and Bell's work explain the coordination of entangled qubits, challenging traditional concepts of locality and communication speed limits.

01:02:57

Quantum Coordination and Communication in Teleportation

Collapse of one universe leads to the collapse of another, with no information transfer possible.
Faster-than-light coordination is acceptable, but communication is not.
Coordination involves transferring information, while communication is a technical term for specific data transfer.
Entangled qbits instantly collapse when one is measured.
Determining if a qbit is in superposition would collapse it.
Quantum computation cannot reveal if a qbit has collapsed or not.
Coordinating qbits does not violate causality, unlike communication.
Quantum teleportation involves transferring qubit states using entangled qbits.
The no-cloning theorem prohibits copying qubit states.
Quantum teleportation requires exchanging two classical bits, not faster-than-light communication.

01:15:38

Quantum Computing Essentials: Algorithms, Error Correction, Qubits

Shor's algorithm, Grover's algorithm, Quantum cryptographic key exchange are recommended for learning.
Understanding the physical implementation of these algorithms is suggested.
Quantum error correction is crucial due to potential cosmic ray interference.
Theoretical requirement of five physical qubits for a single logical qubit is noted.
In practice, around one to two hundred qubits may be needed for a 100% probability qubit.
Google's 30 qubit computer may not signify significant progress due to the quality of qubits.
Recommended textbooks include "Quantum Computing for Computer Scientists" by David Mermin.
Quantum Computing Gentle Interaction is another recommended book.
The Quantum Development kit offers a Quantum Computing Simulator and Q Sharp.

Try it yourself — It’s free.