- The document discusses Shor's algorithm, which can be used to factor large numbers.
- It introduces the quantum Fourier transform (QFT), which forms the core of Shor's algorithm. The QFT transforms the probability amplitudes of a quantum state.
- RSA encryption relies on the difficulty of factoring large numbers for its security. However, Shor's algorithm, using a quantum computer, could factorize numbers efficiently and break RSA encryption.
[01] Quantum Error Correction for Beginners Shin Nishio
This document provides an introduction to quantum error correction. It discusses the types of quantum errors including coherent errors and environmental decoherence. It then describes the 3-qubit error correction code, which can correct one bit flip error by using syndrome measurements. Finally, it covers the 9-qubit code developed by Shor, which can correct both one bit flip and one phase flip error by combining 3-qubit codes and independently correcting for bit flip and phase flip errors.
Shor's algorithm is for quantum computer. Using this algorithm any arbitrarily large number can be factored in polynomial time. which is not possible in classical computer
This seminar presentation provides an introduction to quantum computing, including its history, why it is important, how it works, potential applications, challenges, and conclusions. Specifically, it discusses how quantum computers use quantum mechanics principles like qubits and superposition to perform calculations. The history includes early proposals in 1982 and key algorithms developed in the 1990s. Applications that could benefit from quantum computing are mentioned like cryptography, artificial intelligence, and communication. Issues like error correction, decoherence, and cost are also presented. In conclusion, quantum computers may be able to simulate physical systems and even develop artificial intelligence.
This document discusses quantum cryptography and its advantages over traditional cryptography. It provides background on traditional public and private key cryptography and explains that quantum cryptography uses the principles of quantum mechanics to securely transmit encryption keys. The document outlines the basics of how quantum cryptography works, including using photon polarization to represent bits, and describes an example of how it could be implemented using MATLAB. It also lists some of the key companies working in the field of quantum cryptography.
A sequential circuit is formed from a combinational circuit and storage elements. The circuit's state is defined by the information stored at any given time. The next state depends on the current inputs and state. A synchronous sequential circuit's behavior can be described at discrete time instances. It was designed as a Moore state machine to detect the "1101" sequence, with the output associated with the state. VHDL code implements it with a process changing the state variable based on the present state and input to determine the next state and output.
This document provides an introduction to quantum cryptography. It explains that quantum cryptography uses principles of quantum mechanics like quantum entanglement and the Heisenberg uncertainty principle to securely distribute encryption keys. It notes that quantum cryptography combines the concepts of one-time pads and quantum key distribution, using quantum mechanics to detect any attempts at eavesdropping. The document also briefly discusses the history of cryptography, how quantum key distribution works, advantages and disadvantages of quantum cryptography, and its future applications.
This document outlines a presentation on quantum key distribution. The presentation covers an introduction to cryptography, classical cryptography techniques like the one-time pad, quantum cryptography concepts like photon polarization, and quantum key distribution protocols like BB84. Quantum key distribution allows two parties to detect an eavesdropper attempting to gain knowledge of an encrypted key by exploiting quantum effects. The document provides context and details for each topic that will be covered in the presentation.
[01] Quantum Error Correction for Beginners Shin Nishio
This document provides an introduction to quantum error correction. It discusses the types of quantum errors including coherent errors and environmental decoherence. It then describes the 3-qubit error correction code, which can correct one bit flip error by using syndrome measurements. Finally, it covers the 9-qubit code developed by Shor, which can correct both one bit flip and one phase flip error by combining 3-qubit codes and independently correcting for bit flip and phase flip errors.
Shor's algorithm is for quantum computer. Using this algorithm any arbitrarily large number can be factored in polynomial time. which is not possible in classical computer
This seminar presentation provides an introduction to quantum computing, including its history, why it is important, how it works, potential applications, challenges, and conclusions. Specifically, it discusses how quantum computers use quantum mechanics principles like qubits and superposition to perform calculations. The history includes early proposals in 1982 and key algorithms developed in the 1990s. Applications that could benefit from quantum computing are mentioned like cryptography, artificial intelligence, and communication. Issues like error correction, decoherence, and cost are also presented. In conclusion, quantum computers may be able to simulate physical systems and even develop artificial intelligence.
This document discusses quantum cryptography and its advantages over traditional cryptography. It provides background on traditional public and private key cryptography and explains that quantum cryptography uses the principles of quantum mechanics to securely transmit encryption keys. The document outlines the basics of how quantum cryptography works, including using photon polarization to represent bits, and describes an example of how it could be implemented using MATLAB. It also lists some of the key companies working in the field of quantum cryptography.
A sequential circuit is formed from a combinational circuit and storage elements. The circuit's state is defined by the information stored at any given time. The next state depends on the current inputs and state. A synchronous sequential circuit's behavior can be described at discrete time instances. It was designed as a Moore state machine to detect the "1101" sequence, with the output associated with the state. VHDL code implements it with a process changing the state variable based on the present state and input to determine the next state and output.
This document provides an introduction to quantum cryptography. It explains that quantum cryptography uses principles of quantum mechanics like quantum entanglement and the Heisenberg uncertainty principle to securely distribute encryption keys. It notes that quantum cryptography combines the concepts of one-time pads and quantum key distribution, using quantum mechanics to detect any attempts at eavesdropping. The document also briefly discusses the history of cryptography, how quantum key distribution works, advantages and disadvantages of quantum cryptography, and its future applications.
This document outlines a presentation on quantum key distribution. The presentation covers an introduction to cryptography, classical cryptography techniques like the one-time pad, quantum cryptography concepts like photon polarization, and quantum key distribution protocols like BB84. Quantum key distribution allows two parties to detect an eavesdropper attempting to gain knowledge of an encrypted key by exploiting quantum effects. The document provides context and details for each topic that will be covered in the presentation.
This document provides information about different types of counters, including asynchronous counters, synchronous counters, MSI counters, and specific counter integrated circuits. It defines counters and describes their basic characteristics. It discusses asynchronous ripple counters and their timing. It provides examples of decade and binary counters. It describes synchronous counters and MSI counters like the 74LS163 4-bit synchronous counter. Finally, it provides truth tables, logic diagrams, and application information for common counter ICs like the 7490, 7492, 7493, and 74LS163.
An 8-bit full adder was designed using Verilog HDL and simulated using the Xilinx ISE simulator. The design included behavioral Verilog code for the 8-bit full adder, a test bench to verify the design's functionality, and simulation of test cases to check the results. The simulation showed the output sums in both decimal and binary formats for different input values, demonstrating the correct operation of the 8-bit full adder design.
Quantum cryptography provides a secure way to exchange encryption keys. It uses principles of quantum mechanics like photon polarization and the uncertainty principle to detect eavesdropping. The most common protocol is BB84, where Alice encodes random bits in one of four polarization states and Bob measures them randomly. They compare bases to detect errors from eavesdropping. If no errors, the bits form a shared encryption key known only to them. Quantum key distribution exploits these effects to securely generate encryption keys between two parties.
This presentation contains the contents pertaining to the undergraduate course on Cryptography and Network Security (UITC203) at Sri Ramakrishna Institute of Technology. This covers the ElGamal Cryptosystem.
The document provides an overview of fundamental concepts in quantum computing, including quantum properties like superposition, entanglement, and uncertainty principle. It discusses how quantum bits can represent more than classical bits by being in superpositions of states. Basic quantum gates like Hadamard, Pauli X, and phase shift gates are also introduced, along with pioneers in the field like Feynman, Deutsch, Shor, and Grover. Potential applications of quantum computing are listed.
This document discusses post-quantum cryptography and code-based cryptosystems as an alternative that is secure against quantum computers. It describes the McEliece cryptosystem, which uses error correcting codes, and introduces staircase generator codes and randomly split staircase generator codes to improve efficiency and security. The randomly split staircase generator codes cryptosystem allows for both encryption and digital signatures using efficient procedures while providing 80-bit security levels against quantum attacks, though it has large key sizes of around 10 megabytes.
1. A bus is a communication system that transfers data between components inside a computer or between computers using both parallel and serial connections.
2. An Arithmetic Logic Unit (ALU) performs arithmetic and logical operations and was a core component of the earliest computer architectures proposed by John Von Neumann in 1945.
3. Logic gates are the basic building blocks of digital circuits and perform logical operations like AND, OR, and NOT on binary inputs to produce binary outputs. Common logic gates include AND, OR, NOT, NAND, NOR, XOR, and XNOR.
This document discusses quantum cryptography and its advantages over classical cryptography. It introduces the key distribution problem in classical cryptography. Quantum cryptography uses principles of quantum mechanics like quantum bits that cannot be copied and photon polarization to securely distribute keys. The document describes the BB84 protocol for quantum key distribution where Alice and Bob use different polarization bases to generate a random key and detect eavesdropping. While promising, challenges remain in scaling the technology to longer distances and developing affordable devices.
This document discusses quantum cryptography. It begins with an introduction to traditional cryptography and then defines quantum cryptography as exploiting quantum mechanical properties like the Heisenberg uncertainty principle and quantum entanglement for cryptographic tasks. It explains how quantum cryptography works by having Alice and Bob send polarized photons in randomly chosen bases and discarding mismatched bases to generate a secret key. It also covers applications like secure online voting and satellite communications, as well as limitations such as short maximum distances and inability to multiplex quantum channels.
A brief presentation on Position-Based, Device-Independent and Post Quantum Cryptographies. Detailing Position-Based QC, defining Device-Independent QC and discussing Post Device-Independent.
IIR filter realization using direct form I & IISarang Joshi
The document discusses IIR filter realization using Direct Form I and Direct Form II structures. It presents the difference equation and transfer function for an IIR filter. It also provides examples of implementing IIR filters using Direct Form I and Direct Form II structures based on a given difference equation or transfer function.
The document discusses homomorphic encryption, which allows computations to be performed on encrypted data and obtain an encrypted result without decrypting the inputs. It provides examples of partially homomorphic encryption schemes like RSA that allow only addition or multiplication, and fully homomorphic encryption introduced by Craig Gentry in 2009 that allows any computation. The document also discusses applications of homomorphic encryption like secure cloud computing and processing of sensitive encrypted medical records. It summarizes Craig Gentry's homomorphic encryption scheme and the HELib software library implementation.
This document provides an overview of an Internet of Things workshop that teaches participants how to connect sensors and actuators to microcontrollers and the internet. The workshop covers getting started with hardware like Arduino boards, measuring sensor values and controlling actuators, connecting devices to the internet using WiFi and Ethernet, and using cloud services like Xively to monitor sensors and control devices remotely. Hands-on activities include blinking an LED, reading a pushbutton switch, and sending sensor data to Xively to be displayed on a data dashboard.
Quantum computing uses quantum mechanics phenomena like superposition and entanglement to perform calculations exponentially faster than classical computers for certain problems. While quantum computers have shown promise in areas like optimization, simulation, and encryption cracking, significant challenges remain in scaling up quantum bits and reducing noise and errors. Current research aims to build larger quantum registers of 50+ qubits to demonstrate quantum advantage and explore practical applications, with the future potential to revolutionize fields like artificial intelligence, materials design, and drug discovery if full-scale quantum computers can be realized.
Slides for a college cryptography course at CCSF. Instructor: Sam Bowne
Based on: Understanding Cryptography: A Textbook for Students and Practitioners by Christof Paar, Jan Pelzl, and Bart Preneel, ISBN: 3642041000 ASIN: B014P9I39Q
See https://samsclass.info/141/141_F17.shtml
Quantum computing provides an alternative computational model based on quantum mechanics. It utilizes quantum phenomena such as superposition and entanglement to perform computations using quantum logic gates on qubits. This allows quantum computers to potentially solve certain problems exponentially faster than classical computers. However, building large-scale quantum computers remains a challenge. In the meantime, smaller quantum systems are being developed and quantum algorithms are being experimentally tested on these devices. Researchers are also working on methods to efficiently simulate quantum computations on classical computers.
HW 5-RSA/ascii2str.m
function str = ascii2str(ascii)
% Convert to string
str = char(ascii);
HW 5-RSA/bigmod.m
function remainder = bigmod (number, power, modulo)
% modulo function for large numbers, -> number^power(mod modulo)
% by bennyboss / 2005-06-24 / Matlab 7
% I used algorithm from this webpage:
% http://www.disappearing-inc.com/ciphers/rsa.html
% binary decomposition
binary(1,1) = 1;
col = 2;
while ( binary(1, col-1) <= power-binary(1, col-1) )
binary(1, col) = 2*binary(1, col-1);
col = col + 1;
end
% flip matrix
binary = fliplr(binary);
% extract binary decomposition from number
result = power;
cols = length(binary);
extracted_binary = zeros(1, cols);
index = zeros(1, cols);
for ( col=1 : cols )
if( result-binary(1, col) > 0 )
result = result - binary(1, col);
extracted_binary(1, col) = binary(1, col);
index(1, col) = col;
elseif ( result-binary(1, col) == 0 )
extracted_binary(1, col) = binary(1, col);
index(1, col) = col;
break;
end
end
% flip matrix
binary = fliplr(binary);
% doubling the powers by squaring the numbers
cols2 = length(extracted_binary);
rem_sqr = zeros(1, cols);
rem_sqr(1, 1) = mod(number^1, modulo);
if ( cols2 > 1 )
for ( col=2 : cols)
rem_sqr(1, col) = mod(rem_sqr(1, col-1)^2, modulo);
end
end
% flip matrix
rem_sqr = fliplr(rem_sqr);
% compute reminder
index = find(index);
remainder = rem_sqr(1, index(1, 1));
cols = length(index);
for (col=2 : cols)
remainder = mod(remainder*rem_sqr(1, index(1, col)), modulo);
end
HW 5-RSA/EGCP447-Lecture No 10.pdf
RSA Encryption
RSA = Rivest, Shamir, and Adelman (MIT), 1978
Underlying hard problem
– Number theory – determining prime factors of a given
(large) number
e.g., factoring of small #: 5 -) 5, 6 -) 2 *3
– Arithmetic modulo n
How secure is RSA?
– So far remains secure (after all these years...)
– Will somebody propose a quick algorithm to factor
large numbers?
– Will quantum computing break it? -) TBD
RSA Encryption
In RSA:
– P = E (D(P)) = D(E(P)) (order of D/E does not matter)
– More precisely: P = E(kE, D(kD, P)) = D(kD, E(kE, P))
Encryption: C = Pe mod n KE = e
– n is the key length
– Note, P is turned into an integer using a padding
scheme
– Given C, it is very difficult to find P without knowing
KD
Decryption: P = Cd mod n KD = d
We will look at this algorithm in detail next time
RSA Algorithm
1. Key Generation
– A key generation algorithm
2. RSA Function Evaluation
– A function F, that takes as an input a point x and a
key k and produces either an encrypted result or
plaintext, depending on the input and the key
Key Generation
The key generation algorithm is the most
complex part of RSA
The aim of the key generation algorithm is to
generate both th ...
The document discusses the RSA cryptosystem. It begins by explaining that RSA is an important public-key cryptosystem based on the difficulty of factoring large integers. It then provides examples of how RSA works, including choosing prime numbers p and q to generate the public and private keys, and using modular exponentiation to encrypt and decrypt messages. The document also discusses the importance of integer factorization for the security of RSA, and considerations for designing a secure RSA system, such as choosing sufficiently large prime numbers.
This document provides information about different types of counters, including asynchronous counters, synchronous counters, MSI counters, and specific counter integrated circuits. It defines counters and describes their basic characteristics. It discusses asynchronous ripple counters and their timing. It provides examples of decade and binary counters. It describes synchronous counters and MSI counters like the 74LS163 4-bit synchronous counter. Finally, it provides truth tables, logic diagrams, and application information for common counter ICs like the 7490, 7492, 7493, and 74LS163.
An 8-bit full adder was designed using Verilog HDL and simulated using the Xilinx ISE simulator. The design included behavioral Verilog code for the 8-bit full adder, a test bench to verify the design's functionality, and simulation of test cases to check the results. The simulation showed the output sums in both decimal and binary formats for different input values, demonstrating the correct operation of the 8-bit full adder design.
Quantum cryptography provides a secure way to exchange encryption keys. It uses principles of quantum mechanics like photon polarization and the uncertainty principle to detect eavesdropping. The most common protocol is BB84, where Alice encodes random bits in one of four polarization states and Bob measures them randomly. They compare bases to detect errors from eavesdropping. If no errors, the bits form a shared encryption key known only to them. Quantum key distribution exploits these effects to securely generate encryption keys between two parties.
This presentation contains the contents pertaining to the undergraduate course on Cryptography and Network Security (UITC203) at Sri Ramakrishna Institute of Technology. This covers the ElGamal Cryptosystem.
The document provides an overview of fundamental concepts in quantum computing, including quantum properties like superposition, entanglement, and uncertainty principle. It discusses how quantum bits can represent more than classical bits by being in superpositions of states. Basic quantum gates like Hadamard, Pauli X, and phase shift gates are also introduced, along with pioneers in the field like Feynman, Deutsch, Shor, and Grover. Potential applications of quantum computing are listed.
This document discusses post-quantum cryptography and code-based cryptosystems as an alternative that is secure against quantum computers. It describes the McEliece cryptosystem, which uses error correcting codes, and introduces staircase generator codes and randomly split staircase generator codes to improve efficiency and security. The randomly split staircase generator codes cryptosystem allows for both encryption and digital signatures using efficient procedures while providing 80-bit security levels against quantum attacks, though it has large key sizes of around 10 megabytes.
1. A bus is a communication system that transfers data between components inside a computer or between computers using both parallel and serial connections.
2. An Arithmetic Logic Unit (ALU) performs arithmetic and logical operations and was a core component of the earliest computer architectures proposed by John Von Neumann in 1945.
3. Logic gates are the basic building blocks of digital circuits and perform logical operations like AND, OR, and NOT on binary inputs to produce binary outputs. Common logic gates include AND, OR, NOT, NAND, NOR, XOR, and XNOR.
This document discusses quantum cryptography and its advantages over classical cryptography. It introduces the key distribution problem in classical cryptography. Quantum cryptography uses principles of quantum mechanics like quantum bits that cannot be copied and photon polarization to securely distribute keys. The document describes the BB84 protocol for quantum key distribution where Alice and Bob use different polarization bases to generate a random key and detect eavesdropping. While promising, challenges remain in scaling the technology to longer distances and developing affordable devices.
This document discusses quantum cryptography. It begins with an introduction to traditional cryptography and then defines quantum cryptography as exploiting quantum mechanical properties like the Heisenberg uncertainty principle and quantum entanglement for cryptographic tasks. It explains how quantum cryptography works by having Alice and Bob send polarized photons in randomly chosen bases and discarding mismatched bases to generate a secret key. It also covers applications like secure online voting and satellite communications, as well as limitations such as short maximum distances and inability to multiplex quantum channels.
A brief presentation on Position-Based, Device-Independent and Post Quantum Cryptographies. Detailing Position-Based QC, defining Device-Independent QC and discussing Post Device-Independent.
IIR filter realization using direct form I & IISarang Joshi
The document discusses IIR filter realization using Direct Form I and Direct Form II structures. It presents the difference equation and transfer function for an IIR filter. It also provides examples of implementing IIR filters using Direct Form I and Direct Form II structures based on a given difference equation or transfer function.
The document discusses homomorphic encryption, which allows computations to be performed on encrypted data and obtain an encrypted result without decrypting the inputs. It provides examples of partially homomorphic encryption schemes like RSA that allow only addition or multiplication, and fully homomorphic encryption introduced by Craig Gentry in 2009 that allows any computation. The document also discusses applications of homomorphic encryption like secure cloud computing and processing of sensitive encrypted medical records. It summarizes Craig Gentry's homomorphic encryption scheme and the HELib software library implementation.
This document provides an overview of an Internet of Things workshop that teaches participants how to connect sensors and actuators to microcontrollers and the internet. The workshop covers getting started with hardware like Arduino boards, measuring sensor values and controlling actuators, connecting devices to the internet using WiFi and Ethernet, and using cloud services like Xively to monitor sensors and control devices remotely. Hands-on activities include blinking an LED, reading a pushbutton switch, and sending sensor data to Xively to be displayed on a data dashboard.
Quantum computing uses quantum mechanics phenomena like superposition and entanglement to perform calculations exponentially faster than classical computers for certain problems. While quantum computers have shown promise in areas like optimization, simulation, and encryption cracking, significant challenges remain in scaling up quantum bits and reducing noise and errors. Current research aims to build larger quantum registers of 50+ qubits to demonstrate quantum advantage and explore practical applications, with the future potential to revolutionize fields like artificial intelligence, materials design, and drug discovery if full-scale quantum computers can be realized.
Slides for a college cryptography course at CCSF. Instructor: Sam Bowne
Based on: Understanding Cryptography: A Textbook for Students and Practitioners by Christof Paar, Jan Pelzl, and Bart Preneel, ISBN: 3642041000 ASIN: B014P9I39Q
See https://samsclass.info/141/141_F17.shtml
Quantum computing provides an alternative computational model based on quantum mechanics. It utilizes quantum phenomena such as superposition and entanglement to perform computations using quantum logic gates on qubits. This allows quantum computers to potentially solve certain problems exponentially faster than classical computers. However, building large-scale quantum computers remains a challenge. In the meantime, smaller quantum systems are being developed and quantum algorithms are being experimentally tested on these devices. Researchers are also working on methods to efficiently simulate quantum computations on classical computers.
HW 5-RSA/ascii2str.m
function str = ascii2str(ascii)
% Convert to string
str = char(ascii);
HW 5-RSA/bigmod.m
function remainder = bigmod (number, power, modulo)
% modulo function for large numbers, -> number^power(mod modulo)
% by bennyboss / 2005-06-24 / Matlab 7
% I used algorithm from this webpage:
% http://www.disappearing-inc.com/ciphers/rsa.html
% binary decomposition
binary(1,1) = 1;
col = 2;
while ( binary(1, col-1) <= power-binary(1, col-1) )
binary(1, col) = 2*binary(1, col-1);
col = col + 1;
end
% flip matrix
binary = fliplr(binary);
% extract binary decomposition from number
result = power;
cols = length(binary);
extracted_binary = zeros(1, cols);
index = zeros(1, cols);
for ( col=1 : cols )
if( result-binary(1, col) > 0 )
result = result - binary(1, col);
extracted_binary(1, col) = binary(1, col);
index(1, col) = col;
elseif ( result-binary(1, col) == 0 )
extracted_binary(1, col) = binary(1, col);
index(1, col) = col;
break;
end
end
% flip matrix
binary = fliplr(binary);
% doubling the powers by squaring the numbers
cols2 = length(extracted_binary);
rem_sqr = zeros(1, cols);
rem_sqr(1, 1) = mod(number^1, modulo);
if ( cols2 > 1 )
for ( col=2 : cols)
rem_sqr(1, col) = mod(rem_sqr(1, col-1)^2, modulo);
end
end
% flip matrix
rem_sqr = fliplr(rem_sqr);
% compute reminder
index = find(index);
remainder = rem_sqr(1, index(1, 1));
cols = length(index);
for (col=2 : cols)
remainder = mod(remainder*rem_sqr(1, index(1, col)), modulo);
end
HW 5-RSA/EGCP447-Lecture No 10.pdf
RSA Encryption
RSA = Rivest, Shamir, and Adelman (MIT), 1978
Underlying hard problem
– Number theory – determining prime factors of a given
(large) number
e.g., factoring of small #: 5 -) 5, 6 -) 2 *3
– Arithmetic modulo n
How secure is RSA?
– So far remains secure (after all these years...)
– Will somebody propose a quick algorithm to factor
large numbers?
– Will quantum computing break it? -) TBD
RSA Encryption
In RSA:
– P = E (D(P)) = D(E(P)) (order of D/E does not matter)
– More precisely: P = E(kE, D(kD, P)) = D(kD, E(kE, P))
Encryption: C = Pe mod n KE = e
– n is the key length
– Note, P is turned into an integer using a padding
scheme
– Given C, it is very difficult to find P without knowing
KD
Decryption: P = Cd mod n KD = d
We will look at this algorithm in detail next time
RSA Algorithm
1. Key Generation
– A key generation algorithm
2. RSA Function Evaluation
– A function F, that takes as an input a point x and a
key k and produces either an encrypted result or
plaintext, depending on the input and the key
Key Generation
The key generation algorithm is the most
complex part of RSA
The aim of the key generation algorithm is to
generate both th ...
The document discusses the RSA cryptosystem. It begins by explaining that RSA is an important public-key cryptosystem based on the difficulty of factoring large integers. It then provides examples of how RSA works, including choosing prime numbers p and q to generate the public and private keys, and using modular exponentiation to encrypt and decrypt messages. The document also discusses the importance of integer factorization for the security of RSA, and considerations for designing a secure RSA system, such as choosing sufficiently large prime numbers.
My presentation at University of Nottingham "Fast low-rank methods for solvin...Alexander Litvinenko
Overview of my (with co-authors) low-rank tensor methods for solving PDEs with uncertain coefficients. Connection with Bayesian Update. Solving a coupled system: stochastic forward and stochastic inverse.
The document discusses the RSA encryption algorithm. It begins by explaining how to generate the public and private keys, including choosing two prime numbers p and q, computing phi(n) as (p-1)(q-1), and selecting the public and private exponents e and d. It then explains how RSA encryption and decryption work using these keys. The document also discusses some ways RSA can be broken, such as with a quantum computer using Shor's algorithm to find the prime factors of n through periodicity. It provides examples to illustrate RSA key generation and encryption/decryption.
This document discusses two algorithms: divide-and-conquer and dynamic programming. Divide-and-conquer breaks problems into independent subproblems, solves the subproblems, and combines their solutions. Dynamic programming solves subproblems once and saves their solutions in a table to solve the original problem more efficiently. Examples include computing the Fibonacci sequence and matrix chain multiplication.
Hierarchical matrix techniques for maximum likelihood covariance estimationAlexander Litvinenko
1. We apply hierarchical matrix techniques (HLIB, hlibpro) to approximate huge covariance matrices. We are able to work with 250K-350K non-regular grid nodes.
2. We maximize a non-linear, non-convex Gaussian log-likelihood function to identify hyper-parameters of covariance.
The document describes the syllabus for a course on design analysis and algorithms. It covers topics like asymptotic notations, time and space complexities, sorting algorithms, greedy methods, dynamic programming, backtracking, and NP-complete problems. It also provides examples of algorithms like computing greatest common divisor, Sieve of Eratosthenes for primes, and discusses pseudocode conventions. Recursive algorithms and examples like Towers of Hanoi and permutation generation are explained. Finally, it outlines the steps for designing algorithms like understanding the problem, choosing appropriate data structures and computational devices.
This document provides a summary of a quantum information lecture on multiple qubit states, gates, and measurements. It outlines the topics to be covered, including multi-qubit states represented by coefficients, multi-qubit gates like CNOT, and multi-qubit measurements. It also discusses how to determine if two qubits are entangled and defines universal gate sets that can implement any unitary operation on qubits.
The document discusses difference equations, z-transforms, and discrete Fourier transforms. It provides examples of applying difference equations to electrical circuits and finding the total, homogeneous, and particular solutions. It also gives examples of using z-transforms to find the z-transform of sequences and the inverse z-transform. Examples of finding the transfer function and impulse response from a given difference equation are provided. The document also discusses discrete Fourier transforms and provides an example of finding the Fourier series representation of a given sequence.
Approximation of large Matern covariance functions in the H-matrix format. We computed relative errors in spectral, Frobenius norms as well as the Kullback-Leibler divergence. Storage and computational costs are drastically reduced.
This document discusses low-density parity-check (LDPC) codes and their decoding using belief propagation on factor graphs. It introduces LDPC codes and their representation by sparse parity-check matrices and Tanner graphs. It describes irregular and regular LDPC codes, degree distributions, code ensembles, and decoding using belief propagation on factor graphs and the sum-product algorithm. Examples of decoding a LDPC code over a binary-input additive white Gaussian noise channel are also presented.
RSA and OAEP
Diffe-Hellman Key Exchange and its Security Aspects
Model of Asymmetric Key Cryptography
Factorization and other methods for Public Key Cryptography
The document discusses divide and conquer algorithms and merge sort. It provides details on how merge sort works including: (1) Divide the input array into halves recursively until single element subarrays, (2) Sort the subarrays using merge sort recursively, (3) Merge the sorted subarrays back together. The overall running time of merge sort is analyzed to be θ(nlogn) as each level of recursion contributes θ(n) work and there are logn levels of recursion.
The document describes several block ciphers including DES, AES (Rijndael), and others. It provides details on:
- DES such as its Feistel structure, S-boxes, modes of operation, and cryptanalysis techniques like differential and linear cryptanalysis.
- AES/Rijndael including its SPN structure, security and efficiency compared to Triple DES, and its selection as the AES standard over other finalists like Serpent and Twofish.
- Other block ciphers mentioning characteristics like linear and confusion layers.
Public-Key Cryptography.pdfWrite the result of the following operation with t...FahmiOlayah
Write the result of the following operation with the correct number of significant figure of 0.248?Write the result of the following operation with the correct number of signi
This file contains the contents about dynamic programming, greedy approach, graph algorithm, spanning tree concepts, backtracking and branch and bound approach.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
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Cytokines and their role in immune regulation.pptx
Week5 ap3421 2019_part1
1. AP3421 Fundamentals of Quantum Information
Week 5
Version: 2019/10/04
Shor’s algorithm
Photocredit:ErikLucero
1
2. 2
Class anouncements
● We will plan the optional evening lab tour for the week of Oct. 14-18. Please be
on the lookout for a Doodle signup. To be announced shortly on BrightSpace.
● Graded Quiz #2 back to you today. Please pick up during break or right after class.
We just decided in class that the tour will happen on Wednesday, October 16.
3. 3
Outline of today’s lecture
5
Quantum Fourier Transform
RSA encryption
Shor’s algorithm
H
H
H
H
2
π
4
π
2
π
π
π
π
QFTU
+ optional reading (Mermin’s slides) on BrightSpace3
4. 4
The quantum Fourier transform (QFT)
H
H
H
H
2
π
4
π
2
π
π
π
π
21 1
out in
0 0
1
i lkN N
N
l k
e l k
N
π− −
= =
Ψ= Ψ
∑ ∑
21
0
1
i lkN
N
l k
k
e
N
π
α α
−
=
′ = ∑
inΨ outΨ
QFTU
QFT on n qubits:
2n
N =Recall:
Note: this transformation
performs a QFT on the
probability amplitudes
1
in
0
N
k
k
kα
−
=
Ψ =∑ 1
'
out
0
N
k
k
kα
−
=
Ψ =∑
5. 5
The quantum Fourier transform (QFT)
2
1
i lk
N
lkU e
N
π
=
QFT on n qubits:
2 4 6
4 8 12
6 12 18
1 1 1 1 1
1
1
1
1
i i i
N N N
i i i
N N N
i i i
N N NQFT
e e e
e e e
U e e eN
π π π
π π π
π π π
Question: What condition do you need to check to know that this transformation
can be realized by a circuit of gates on a qubit register?
Answer: Unitarity!
6. 6
The quantum Fourier transform
21 1
out in
0 0
1
i lkN N
N
l k
e l k
N
π− −
= =
Ψ= Ψ
∑ ∑
21
0
1
i lkN
N
l k
k
e
N
π
α α
−
=
′ = ∑
QFT on n qubits:
2n
N =Recall:
H
H
H
H
4
π
8
π
4
π
2
π
2
π
2
π
inΨ outΨ
7. 7
The swap gate
As the name implies, the SWAP gate
swaps the state between two qubits:
SWAPU ψ ψ ψ ψ′ ′⊗ = ⊗
SWAP
1 0 0 0
0 0 1 0
0 1 0 0
0 0 0 1
U
=
in the 2-qubit computational basis
= =
Question: Do you think the SWAP gate can generate entanglement from
a product state?
Answer: No!
8. 8
QFT simple examples
Case N=2:
1 11
1 12
QFTU
= −
1 1 1 1
1 11
?
1 1 1 14
1 1
QFT
i i
U
i i
+ − −
= =
− −
− − +
Case N=4:
H
H
2
π
H
H
2
π
HH=
10. 10
The quantum Fourier transform
A quantum circuit is said to be efficient if the number of elementary operations taken to execute it
increases no faster than a polynomial function of the number of qubits n.
QFT requires 1+2+3+4+…+n=n(n+1)/2 gates, so it is O(n2).
Constructing the QFT from another universal set of gates only affects the circuit size by a multiplicative
constant which does not affect the quadratic scaling.
H
H
H
H
4
π
8
π
4
π
2
π
2
π
2
π
inΨ outΨ
11. 11
Context: Public key encryption (nothing to do with quantum)
Diffie & Hellman, late 1970s
( ) ( )e dE M P D P M=
● Xavi publicly announces the encryption method and the public key e.
Holds on super tightly to his private key d.
● Mohammad encrypts his message M, and publicly sends the result P.
● Xavi decrypts using his private key d.
The key point: Anyone can encrypt using the public key,
but only the holder of the private key (Xavi) can decrypt.
confidential message M
Mohammad Xavi
Goal:
12. 12
RSA encryption
Xavi takes 2 prime numbers and computes their product,p q
(Rivest, Shamir and Adleman, 1977)
N pq=
Xavi chooses coprime withe ( )( )1 1p q− −
Xavi announces public key: ,N e
Encryption: ( )( ) mod
e
i iP M N=
Decoding key:
( )( ) mod
d
i iM P N=
( ) ( )( )( )such that mod 1 1 1d de p q− − =
Checking if chosen e is coprime with (p-1)(q-1) is efficient using Euclid’s algorithm O(n3).
Finding the modular inverse of e modulo (p-1)(q-1) as well.
To crack RSA: factor N into its prime factors p and q
How it works:
13. 13
RSA encryption: trivial example
15N =
3, 5p q= =
( 1)( 1) 8p q− − =
Xavi choose e=3, which is indeed co-prime with 8.
M P M
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
0
1
8
12
4
5
6
13
2
9
10
11
3
7
14
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
( ) mode
M N ( ) modd
P N
Notice that this
is a one-to-one
map
Notice that this
is also a one-to-
one map
3e = 3d =
encryption decryption
For this choice of e, d=3 as (3e) mod 8=1.
14. 14
(check )
RSA encryption example (slightly less trivial as N=143)
_ A B C D E F G H I J K L M N O
00000 00001 00010 00011 00100 00101 00110 00111 01000 01001 01010 01011 01100 01101 01110 01111
P Q R S T U V W X Y Z ’ , ; . :
10000 10001 10010 10011 10100 10101 10110 10111 11000 11001 11010 11011 11100 11101 11110 11111
Mohammad uses a simple 5-bit digital alphabet:
M= 01001 01011 00000 01000 01111 10101 00100 00000 10110 00001 01110 00000 00100 00101 11010 00101 00000 00011 10101 10010 10011 10101 10011
Privately, Xavi chooses 11, 13, 17p q e= = =
143, 17N e= =
gcd[ ,( 1)( 1)] 1e p q− − =
2log ( ) 7N = bits
Mi= 0100101 0110000 0010000 1111101 0100100 0000010 1100000 1011100 0000001 0000101 1101000 1010000 0000111 0101100 1010011 1010110 0110000
37 48 16 125 36 2 96 92 1 5 104 80 7 44 83 86 48
Pi= 137 16 113 60 108 84 57 27 1 135 91 97 50 44 96 125 16
( )
17
mod 143i iP M=
Mohammad wants to send a very private message to Xavi.
and publicly announces
Mohammad divides his message into packets of
and computes
Mohammad publicly sends the encrypted packets to Xavi.
15. 15
RSA decryption example
( )
113
mod 143i iM P=
17 mod 120 1d × = 113d⇒ =( 1)( 1) 120p q− − =
M= Ik houd van deze cursus
Xavi, who knows privately that p=11, q=13 and e=17, calculates d
Xavi receives the packets.
To decrypt the packets, Xavi calculates
M= 01001 01011 00000 01000 01111 10101 00100 00000 10110 00001 01110 00000 00100 00101 11010 00101 00000 00011 10101 10010 10011 10101 10011
Mi= 0100101 0110000 0010000 1111101 0100100 0000010 1100000 1011100 0000001 0000101 1101000 1010000 0000111 0101100 1010011 1010110 0110000
Mi= 37 48 16 125 36 2 96 92 1 5 104 80 7 44 83 86 48
Pi= 137 16 113 60 108 84 57 27 1 135 91 97 50 44 96 125 16
So, what was Mohammad’s message?
16. 16
Some serious stuff.
The very great computational effort required by all known classical factorization
techniques underlies the security of the widely used RSA method. Any computer
that can efficiently find periods would be an enormous threat to the security of
both military and commercial communications. This is why research into the
feasibililty of quantum computers is a matter of considerable interest in the
worlds of war and business.
-N.D. Mermin
RSA is practically safe only because factoring is hard to do.
17. 17
The challenge of factoring large numbers
RSA-704
Van Meter (2006)
RSA-768
From Wikipedia:
19. 19
The period, r, called the order of a modulo N, satisfies
Preliminaries to Shor: Some number theory.
( ) ( )modx
f x a N=
( ) mod 1r
a N =
is a periodic function of integer x, provided a and N are coprime.
r N≤
( )1 mod 0r
a N− =
Note: the following also has nothing to do with quantum mechanics.
(a and N coprime iff gcd(a,N)=1)
Either or is a trivial multiple of N,
Or and are non-trivial factors
( )( )/2 /2
1 1 mod 0r r
a a N + − =
( )/2
1r
a + ( )/2
1r
a −
( )/2
gcd 1,r
a N+ ( )/2
gcd 1,r
a N−
If r is even:
25. 25
Shor’s period finding algorithm.
Measure
all t qubits
Measure
all l qubits
( )2
O t
22 log +1 bitst N=
2log bitsl N=
( )3
O l
Modular
exponentiation
( )O t
0...0
0...0
ˆZ
ˆZ
t
H ⊗
fU
( )( ) modx
f x a N=
QFT
tm′
1m′
lm
1m
1. initialize 2. superpose 3. evaluate 4. process 5. measure
26. 26
Shor’s period finding algorithm.
0...0
0...0
1
0
1
0
T
x
x
T
−
=
∑
1
0
1
( )mod
T
x
x
x a N
T
−
=
∑
1s.t. ( )mod ....x
lx a N m m
x
=
∑
finalx s
T r
≈
for some integer s
ˆZ
ˆZ
fU
( )( ) modx
f x a N=
QFT
tm′
1m′
lm
1m
finalxt
H ⊗
30. 30
Fourier transform of pulse trains
or mr+
( )
2
'
0
ox r mr
i
T
x
m
e
π
α
+
=
= ∑
2 2
0
oxr xrm
i i
T T
m
e e
π π
=
= ∑
2
22'
0
xrm
i
T
x
m
e
π
α
=
= ∑
Large probability
(constructive interference)
for x such that
is close to an integer.
QFT
xr
T
5a =
xα
36. 36
Back to factoring N=143 with Shor’s
( )gcd 9765626, 143 13=
( )gcd 9765624, 143 11=
Online continued fraction calculator:
http://www.maths.surrey.ac.uk/hosted-sites/R.Knott/Fibonacci/cfCALC.html
Discard as
denominator is odd
For top-register
measurement result
xfinal=101
101
estimate of :
2048
finalx
T
Continued fractions: 1/20, 3/61, 4/81, 7/142 …
/2
1 9765626r
a + =Try r=20.
/2
1 9765624r
a − =
SUCCESS!
5a =
37. 37
Back to factoring N=143 with Shor’s
1331
estimate of :
2048
finalx
T
Continued fractions: 1/2, 2/3, 11/17, 13/20…
Try r=2.
Try r=20.
( )/2
gcd 1, {1,1}r
a N± =
( )/2
gcd 1, {13,11}r
a N± =
Discard as
denominator is odd
SUCCESS!
FAIL.
For top-register
measurement result
xfinal=1331
5a =
Online continued fraction calculator:
http://www.maths.surrey.ac.uk/hosted-sites/R.Knott/Fibonacci/cfCALC.html
40. 40
Summary points
● Shor’s quantum algorithm finds periods. Period!
● Period finding is non-trivial for functions that look like random
noise within a period.
● The problem of factoring can be reduced to the problem of
finding the period of a function that looks random.
● The QFT for n qubits is built from O(n2) gates, each of which acts
on either one qubit or a pair of qubits. The QFT is efficient but the
classical FFT is not.
● The bottleneck in Shor’s algorithm is the modular exponentiation,
requiring O(n3) gates. Shor’s algorithm is efficient.