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.
This document provides an outline and introduction to algebraic foundations of quantum computing. It begins with definitions of qubits, Bloch spheres, qudits, and unitary matrices. It describes how qubits can represent quantum states as vectors on a Bloch sphere and how unitary matrices preserve inner products and represent reversible quantum operations. The document provides examples of orthonormal bases, superposition, interference, and defines key concepts like observables, measurement, and the Hadamard matrix. It contrasts classical computing with quantum computing and explains how unitary matrices allow for infinite distinct quantum states.
Unit 1: Topological spaces (its definition and definition of open sets)nasserfuzt
Learning Objectives:
1. To understand the definition of topology with examples
2. To know the intersection and union of topologies
3. To understand the comparison of topologies
Presentation on Fourier Series
contents are:-
Euler’s Formula
Functions having point of discontinuity
Change of interval
Even and Odd functions
Half Range series
Harmonic analysis
One of the basic concepts of calculus that are studied in the course “Numerical methods of economics.” More detailed information here https://ek.biem.sumdu.edu.ua/
The document discusses the calculation of work done by a force on an object moving along a curve in a vector field. It defines a vector field as a function that assigns a vector to each point in space, representing the force. For a constant force along a straight line, work is calculated as the dot product of the force and displacement vectors. This concept is generalized to calculate work for a varying force along a curved path by partitioning the curve into small line segments, taking the dot product of the force and incremental displacement vectors, and taking the limit as the segment size approaches zero, yielding a line integral formulation for work as the integral of the force dotted with velocity over the curve.
This document discusses Taylor series expansions. It defines Taylor series as the expansion of a complex function f(z) that is analytic inside and on a simple closed curve C in the z-plane. The Taylor series expresses f(z) as a power series centered at a point z0 within C. It provides examples of standard Taylor series expansions and worked illustrations of expanding various functions as Taylor series. The document also notes that the radius of convergence of a Taylor series is defined by the distance to the nearest singularity from the center point z0.
The document discusses probability distributions and their natural parameters. It provides examples of several common distributions including the Bernoulli, multinomial, Gaussian, and gamma distributions. For each distribution, it derives the natural parameter representation and shows how to write the distribution in the form p(x|η) = h(x)g(η)exp{η^T μ(x)}. Maximum likelihood estimation for these distributions is also briefly discussed.
This document provides an outline and introduction to algebraic foundations of quantum computing. It begins with definitions of qubits, Bloch spheres, qudits, and unitary matrices. It describes how qubits can represent quantum states as vectors on a Bloch sphere and how unitary matrices preserve inner products and represent reversible quantum operations. The document provides examples of orthonormal bases, superposition, interference, and defines key concepts like observables, measurement, and the Hadamard matrix. It contrasts classical computing with quantum computing and explains how unitary matrices allow for infinite distinct quantum states.
Unit 1: Topological spaces (its definition and definition of open sets)nasserfuzt
Learning Objectives:
1. To understand the definition of topology with examples
2. To know the intersection and union of topologies
3. To understand the comparison of topologies
Presentation on Fourier Series
contents are:-
Euler’s Formula
Functions having point of discontinuity
Change of interval
Even and Odd functions
Half Range series
Harmonic analysis
One of the basic concepts of calculus that are studied in the course “Numerical methods of economics.” More detailed information here https://ek.biem.sumdu.edu.ua/
The document discusses the calculation of work done by a force on an object moving along a curve in a vector field. It defines a vector field as a function that assigns a vector to each point in space, representing the force. For a constant force along a straight line, work is calculated as the dot product of the force and displacement vectors. This concept is generalized to calculate work for a varying force along a curved path by partitioning the curve into small line segments, taking the dot product of the force and incremental displacement vectors, and taking the limit as the segment size approaches zero, yielding a line integral formulation for work as the integral of the force dotted with velocity over the curve.
This document discusses Taylor series expansions. It defines Taylor series as the expansion of a complex function f(z) that is analytic inside and on a simple closed curve C in the z-plane. The Taylor series expresses f(z) as a power series centered at a point z0 within C. It provides examples of standard Taylor series expansions and worked illustrations of expanding various functions as Taylor series. The document also notes that the radius of convergence of a Taylor series is defined by the distance to the nearest singularity from the center point z0.
The document discusses probability distributions and their natural parameters. It provides examples of several common distributions including the Bernoulli, multinomial, Gaussian, and gamma distributions. For each distribution, it derives the natural parameter representation and shows how to write the distribution in the form p(x|η) = h(x)g(η)exp{η^T μ(x)}. Maximum likelihood estimation for these distributions is also briefly discussed.
This document discusses density operators and their use in quantum information and computing. It begins by introducing density operators and how they can be used to describe quantum systems whose state is not precisely known or composite systems. The key properties of density operators are that they must have a trace of 1 and be positive operators. The document then covers reduced density operators which describe subsystems by taking the partial trace. Finally, it discusses how the reduced density operator gives the correct measurement statistics for observations on a subsystem.
1) The document discusses Ramsey theory and its connection to the Ramsey theorem and generalized Ramsey theory involving monochromatic triangles.
2) It provides proofs for relations involving Ramsey theory, including upper bounds for Ramsey numbers and a lower bound for Rn(3) derived using Schur's problem.
3) The document explores the connection between Schur's problem of partitioning sets into sum-free subsets and Ramsey theory, showing how Schur's problem can provide a lower estimate for Ramsey numbers.
Calculas IMPROPER INTEGRALS AND APPLICATION OF INTEGRATION pptDrazzer_Dhruv
The document provides an overview of improper integrals and applications of integration. It discusses three types of improper integrals: integrals with infinite limits, integrals with discontinuous integrands, and integrals that are a combination of the first two types. It also discusses how to calculate the volume of solids of revolution using disk, washer, and cylindrical shell methods, and provides examples of each. The document is a study guide for a group project on this topic presented by 11 students.
Tutorial of topological_data_analysis_part_1(basic)Ha Phuong
This document provides an overview of topological data analysis (TDA) concepts, including:
- Simplicial complexes which represent topological spaces and holes of different dimensions
- Persistent homology which tracks the appearance and disappearance of holes over different scales
- Applications of TDA concepts like using persistent homology to analyze protein compressibility.
25 the ratio, root, and ratio comparison test xmath266
The document discusses two tests for determining if an infinite series converges or diverges: the ratio test and the root test. The ratio test checks if the limit of the ratio of successive terms is less than 1, equal to 1, or greater than 1, indicating convergence, inconclusive result, or divergence, respectively. The root test checks if the limit of the nth root of terms is less than, equal to, or greater than 1, with similar implications for convergence or divergence. Examples are provided to demonstrate how to apply each test. It is also noted that if a series cannot be directly tested, an equivalent surrogate series may be used instead.
1. The document discusses groups, subgroups, cosets, normal subgroups, quotient groups, and homomorphisms.
2. It defines cosets, proves Lagrange's theorem that the order of a subgroup divides the order of the group, and provides examples of finding cosets.
3. Normal subgroups are introduced, and it is shown that the set of cosets of a normal subgroup forms a group under a defined operation, known as the quotient group. Homomorphisms between groups are defined, and examples are given.
This document summarizes and compares several numerical methods for solving ordinary differential equations (ODEs):
- Euler's method approximates the tangent line at each step to find successive y-values. While simple, it has local truncation errors that accumulate.
- Improved Euler's method takes the average slope between the current and next steps to give a more accurate approximation.
- Runge-Kutta methods such as the fourth-order method provide much greater accuracy than Euler or improved Euler by using multiple slope estimates within each step.
An example applies each method to the ODE dy/dx = x + y to compare their results in solving for successive y-values out to x = 0.3.
(1) The document discusses inner product spaces and related linear algebra concepts such as orthogonal vectors and bases, Gram-Schmidt process, orthogonal complements, and orthogonal projections.
(2) Key topics covered include defining inner products and their properties, finding orthogonal vectors and constructing orthogonal bases, using Gram-Schmidt process to orthogonalize a set of vectors, defining and finding orthogonal complements of subspaces, and computing orthogonal projections of vectors.
(3) Examples are provided to demonstrate computing orthogonal bases, orthogonal complements, and orthogonal projections in inner product spaces.
The document discusses initial value problems for first order differential equations and Euler's method for solving such problems numerically. It provides an example problem where Euler's method is used to find successive y-values for the differential equation dy/dx = x with the initial condition y(0) = 1. The y-values found using Euler's method are then compared to the actual solution, showing small errors that decrease as the step size h is reduced.
This document outlines the 7 steps for sketching the curve of a function: 1) Determine the domain, 2) Find critical points, 3) Determine graph direction and max/min, 4) Use the second derivative to find concavity and points of inflection, 5) Find asymptotes, 6) Find intercepts and important points, 7) Combine evidence to graph the function. Key tests are outlined for max/min, concavity, and points of inflection using the first and second derivatives.
- Quiz 4 will be tomorrow covering sections 3.3, 5.1, and 5.2 of the textbook. It will include 3 problems on Cramer's rule, finding eigenvectors given eigenvalues, and finding characteristic polynomials/eigenvalues of 2x2 and 3x3 matrices. Students must show all work.
- Chapter 6 objectives include extending geometric concepts like length, distance, and perpendicularity to Rn. These concepts are useful for least squares fitting of experimental data to a system of equations.
- The inner product of two vectors u and v in Rn is defined as their dot product, which is the sum of the component-wise products of corresponding elements in u and v.
This document is the preface and contents for a set of notes on complex analysis. It was prepared by Charudatt Kadolkar for MSc students at IIT Guwahati in 2000 and 2001. The notes cover topics such as complex numbers, functions of complex variables, analytic functions, integrals, series, and the theory of residues and its applications. The contents section provides an outline of the chapters and topics to be covered.
The document discusses polar coordinates and graphs. Polar coordinates (r, θ) can be used to specify the location of a point P by giving the distance r from the origin and the angle θ. Conversion formulas allow changing between polar (r, θ) and rectangular (x, y) coordinates. Polar equations relate r and θ, and common ones like r = c (a circle) and θ = c (a line) are examined. Graphing polar equations involves plotting the r and θ values specified by the equation.
The document discusses the bisection method for finding roots of equations. It begins by outlining the basis of the bisection method, which is that if a continuous function changes sign between two points, there is a root between those points. It then provides the step-by-step algorithm for implementing the bisection method to iteratively find a root. An example application to finding the resistance of a thermistor at a given temperature is also included. The document concludes by discussing the advantages and drawbacks of the bisection method.
This document discusses density operators and their use in quantum information and computing. It begins by introducing density operators and how they can be used to describe quantum systems whose state is not precisely known or composite systems. The key properties of density operators are that they must have a trace of 1 and be positive operators. The document then covers reduced density operators which describe subsystems by taking the partial trace. Finally, it discusses how the reduced density operator gives the correct measurement statistics for observations on a subsystem.
1) The document discusses Ramsey theory and its connection to the Ramsey theorem and generalized Ramsey theory involving monochromatic triangles.
2) It provides proofs for relations involving Ramsey theory, including upper bounds for Ramsey numbers and a lower bound for Rn(3) derived using Schur's problem.
3) The document explores the connection between Schur's problem of partitioning sets into sum-free subsets and Ramsey theory, showing how Schur's problem can provide a lower estimate for Ramsey numbers.
Calculas IMPROPER INTEGRALS AND APPLICATION OF INTEGRATION pptDrazzer_Dhruv
The document provides an overview of improper integrals and applications of integration. It discusses three types of improper integrals: integrals with infinite limits, integrals with discontinuous integrands, and integrals that are a combination of the first two types. It also discusses how to calculate the volume of solids of revolution using disk, washer, and cylindrical shell methods, and provides examples of each. The document is a study guide for a group project on this topic presented by 11 students.
Tutorial of topological_data_analysis_part_1(basic)Ha Phuong
This document provides an overview of topological data analysis (TDA) concepts, including:
- Simplicial complexes which represent topological spaces and holes of different dimensions
- Persistent homology which tracks the appearance and disappearance of holes over different scales
- Applications of TDA concepts like using persistent homology to analyze protein compressibility.
25 the ratio, root, and ratio comparison test xmath266
The document discusses two tests for determining if an infinite series converges or diverges: the ratio test and the root test. The ratio test checks if the limit of the ratio of successive terms is less than 1, equal to 1, or greater than 1, indicating convergence, inconclusive result, or divergence, respectively. The root test checks if the limit of the nth root of terms is less than, equal to, or greater than 1, with similar implications for convergence or divergence. Examples are provided to demonstrate how to apply each test. It is also noted that if a series cannot be directly tested, an equivalent surrogate series may be used instead.
1. The document discusses groups, subgroups, cosets, normal subgroups, quotient groups, and homomorphisms.
2. It defines cosets, proves Lagrange's theorem that the order of a subgroup divides the order of the group, and provides examples of finding cosets.
3. Normal subgroups are introduced, and it is shown that the set of cosets of a normal subgroup forms a group under a defined operation, known as the quotient group. Homomorphisms between groups are defined, and examples are given.
This document summarizes and compares several numerical methods for solving ordinary differential equations (ODEs):
- Euler's method approximates the tangent line at each step to find successive y-values. While simple, it has local truncation errors that accumulate.
- Improved Euler's method takes the average slope between the current and next steps to give a more accurate approximation.
- Runge-Kutta methods such as the fourth-order method provide much greater accuracy than Euler or improved Euler by using multiple slope estimates within each step.
An example applies each method to the ODE dy/dx = x + y to compare their results in solving for successive y-values out to x = 0.3.
(1) The document discusses inner product spaces and related linear algebra concepts such as orthogonal vectors and bases, Gram-Schmidt process, orthogonal complements, and orthogonal projections.
(2) Key topics covered include defining inner products and their properties, finding orthogonal vectors and constructing orthogonal bases, using Gram-Schmidt process to orthogonalize a set of vectors, defining and finding orthogonal complements of subspaces, and computing orthogonal projections of vectors.
(3) Examples are provided to demonstrate computing orthogonal bases, orthogonal complements, and orthogonal projections in inner product spaces.
The document discusses initial value problems for first order differential equations and Euler's method for solving such problems numerically. It provides an example problem where Euler's method is used to find successive y-values for the differential equation dy/dx = x with the initial condition y(0) = 1. The y-values found using Euler's method are then compared to the actual solution, showing small errors that decrease as the step size h is reduced.
This document outlines the 7 steps for sketching the curve of a function: 1) Determine the domain, 2) Find critical points, 3) Determine graph direction and max/min, 4) Use the second derivative to find concavity and points of inflection, 5) Find asymptotes, 6) Find intercepts and important points, 7) Combine evidence to graph the function. Key tests are outlined for max/min, concavity, and points of inflection using the first and second derivatives.
- Quiz 4 will be tomorrow covering sections 3.3, 5.1, and 5.2 of the textbook. It will include 3 problems on Cramer's rule, finding eigenvectors given eigenvalues, and finding characteristic polynomials/eigenvalues of 2x2 and 3x3 matrices. Students must show all work.
- Chapter 6 objectives include extending geometric concepts like length, distance, and perpendicularity to Rn. These concepts are useful for least squares fitting of experimental data to a system of equations.
- The inner product of two vectors u and v in Rn is defined as their dot product, which is the sum of the component-wise products of corresponding elements in u and v.
This document is the preface and contents for a set of notes on complex analysis. It was prepared by Charudatt Kadolkar for MSc students at IIT Guwahati in 2000 and 2001. The notes cover topics such as complex numbers, functions of complex variables, analytic functions, integrals, series, and the theory of residues and its applications. The contents section provides an outline of the chapters and topics to be covered.
The document discusses polar coordinates and graphs. Polar coordinates (r, θ) can be used to specify the location of a point P by giving the distance r from the origin and the angle θ. Conversion formulas allow changing between polar (r, θ) and rectangular (x, y) coordinates. Polar equations relate r and θ, and common ones like r = c (a circle) and θ = c (a line) are examined. Graphing polar equations involves plotting the r and θ values specified by the equation.
The document discusses the bisection method for finding roots of equations. It begins by outlining the basis of the bisection method, which is that if a continuous function changes sign between two points, there is a root between those points. It then provides the step-by-step algorithm for implementing the bisection method to iteratively find a root. An example application to finding the resistance of a thermistor at a given temperature is also included. The document concludes by discussing the advantages and drawbacks of the bisection method.
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states and become entangled. Shor's algorithm shows how a quantum computer could factor large numbers much faster than a classical computer by using quantum parallelism and the quantum Fourier transform. It works by first preparing the input in a superposition, applying a modular exponentiation operation, measuring the output qubit to partially collapse the input, applying a quantum Fourier transform to reveal periodicity, and using the period to determine the factors of the original number. This algorithm demonstrates the power of quantum computing for certain problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum bits (qubits) that can exist in superpositions of states and become entangled. Shor's algorithm shows how a quantum computer could factor large numbers much faster than a classical computer by using quantum parallelism and the quantum Fourier transform. It works by first preparing the input in a superposition, applying a modular exponentiation operation, measuring the output qubit to partially collapse the input, applying a quantum Fourier transform to reveal periodicity, and using the period to determine the factors of the original number. This algorithm demonstrates the power of quantum computing for certain problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
Quantum computing uses quantum mechanics principles to perform calculations. A qubit can represent a 1, 0, or superposition of both simultaneously. Operations are performed by reversible logic gates like CNOT. Shor's algorithm shows quantum computers can factor large numbers faster by using quantum parallelism and Fourier transforms to find the period of a function, revealing the factors. While progress is being made, challenges remain in building larger quantum computers and developing new algorithms to solve other hard problems.
This document presents several theorems related to establishing the existence and uniqueness of a common fixed point for nonlinear contractive mappings in Hilbert spaces. It begins by introducing the background and motivation for studying fixed point theory and various generalizations of the Banach contraction principle. It then lists several existing theorems that establish fixed point results for mappings satisfying different contraction conditions in complete metric and Hilbert spaces. The main part of the document presents new fixed point theorems for continuous self-mappings on closed subsets of a Hilbert space, proving the existence and uniqueness of a fixed point when the mappings satisfy certain rational-type contraction conditions.
This document contains information about data structures and algorithms taught at KTH Royal Institute of Technology. It includes code templates for a contest, descriptions and implementations of common data structures like an order statistic tree and hash map, as well as summaries of mathematical and algorithmic concepts like trigonometry, probability theory, and Markov chains.
1. The document discusses characteristic time scales and approximations for time-dependent transport phenomena problems, including the quasi-steady state approximation (QSSA) and penetration approximation.
2. It uses the example of diffusion through a membrane pore to illustrate the QSSA and penetration solutions. For the QSSA, it assumes concentrations equilibrate rapidly within the pore. For the penetration approximation, it assumes the pore length is effectively infinite at short times.
3. It also covers regular perturbation techniques, where a small parameter is introduced and solutions are found order-by-order in the parameter. An example of heat transfer along a heated wire is presented.
Identification of the Mathematical Models of Complex Relaxation Processes in ...Vladimir Bakhrushin
The approach to solving the problem of complex relaxation spectra is presented.
Presentation for the XI International Conference on Defect interaction and anelastic phenomena in solids. Tula, 2007.
HiPEAC'19 Tutorial on Quantum algorithms using QX - 2019-01-23Aritra Sarkar
The document provides an overview of quantum algorithms and quantum computing concepts. It discusses quantum teleportation, superdense coding, Shor's factoring algorithm, Grover's search algorithm, and quantum key distribution protocols. The document is intended as a tutorial on using the QX quantum computer simulator to demonstrate these quantum algorithms and experiments.
1. The document describes the finite element formulation for 2D problems using constant strain triangles.
2. It involves dividing the body into finite elements connected at nodes, then approximating displacements within each element using shape functions of the nodes.
3. Strains and stresses are then approximated based on the displacements. This allows setting up the element stiffness matrix and load vector to solve for the unknown node displacements.
Quantum computing - A Compilation of ConceptsGokul Alex
Excerpts of the Talk Delivered at the 'Bio-Inspired Computing' Workshop conducted by Department of Computational Biology and Bioinformatics, University of Kerala.
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/
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
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
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
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/
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
1. AP3421: Fundamentals of Quantum Information
Week 3
Version: 2019/10/04
Multiple qubits:
states, gates
& measurements.
Photo:A.Bruno
2. 2
Class announcements
● Homework #1 will be due at start of class on Friday.
TUD students:
- please staple all the papers you hand in.
Twente students:
- please submit in pdf format only.
- please send to TA list: TA_AP3421-TNW@tudelft.nl
Can you LaTeX your response? Yes, but that is not required!
If you handwrite your response, please write as legibly as you can!
● Quiz #1 graded back to you today.
- Please pick up yours during break.
- We gave 2 points to everyone to compensate for the confusion with
two of the questions.
- In the future, please ask any of teaching staff for clarification during
the quiz. That way, we can rectify on the spot.
4. 4
Outline of today’s lecture
2&4
Multi-qubit states ( )
1
2
10 10+
Multi-qubit gates
Multi-qubit measurement
mˆM
m
ˆM
1
5. 5
00
01
00 01 10 11
10
11
00 0 1 10 1 1
α
α
α α α α
α
α
Ψ= + +
+
00 01 10 11, , , Cα α α α ∈
2 2 2 2
00 01 10 11 1α α α α+ + + =
Is there a simple, convenient geometric way to visualize
two-qubit states in analogy to the Bloch vector?
Not really.
Global phase is not relevant.
The state of two qubits
6 real parameters to fully specify 2-qubit state.
6. 6
Computational basis of 2 qubits
{ , , }0 10 0 1 , 10 1
A basis for the space of 2 qubits can be obtained as a composite
of individual qubit bases:
Examples:
the 2-qubit computational basis
(the most common)
{ , , , }++ −−+ −+ −
{ , , }0 1 ,0 1+ + − − the individual bases need not match.
7. 7
Quantum registers with n qubits
A collection of n qubits is called a quantum register of size n.
Conventions:
In a n=2 qubit register, the state “3” is
There are N=2n states of this kind, representing all binary strings of length n
or numbers from 0 to N -1.
3 11 11= ⊗ =
2 01 10= ⊗ =
and the state “2” as
number of states: N=2n
number of qubits: n
LSQMSQ
8. 8
n-qubit states
● How many real-valued coefficients does it take to specify the
quantum state of n qubits?
● Imagine you discretize these real coefficients using 4 bytes for
each. How much classical memory (in bytes) does it take to specify
the state of a register with n=100 bits?
Answer: 2(2 1)n
−
3
Answer: 2(2 1) 4 bytes 2 bytesn n+
− × ≈
10. 10
ϕ ψΨ = ⊗
Two qubits are entangled when their joint states cannot possibly
be separated into a product of individual qubit states
Some common terms:
Entangled = non-separable = non-product state
Unentangled = separable = product state
ϕψϕ ψΨ = ⊗ + ⊗ ′′vs
When are two qubits entangled?
11. 11
How to tell if two qubits are entangled or not
,0 1 ψα ψ βΨ ⊗ ⊗ ′= +
2 2
1α β+ =
You can always write the state of two qubits in the form
where , and are normalized,ψ ψ ′
Is ?ψ ψ= ′
no
entangled
yes
separable
( ) ( )
1 1 2 1
20 2
5 5 5 5
0 1 01 1= ⊗ + + ⊗ +
so not entangled!
( ) ( )0 1 0
1
1
1
2 2
5 5
= + ⊗ +
Example:
0 1
1 2 2 4
5 5 5
0 1
5
10 10+ + +
12. 12
How to tell if two qubits are entangled or not
2 2
1α β+ =
You can always write the state of two qubits in the form
where , and are normalized,ψ ψ ′
Is ?ψ ψ= ′
no
entangled
yes
separable
Note:
You can interchange the roles of red and green qubits if you like.
,0 1 ψα ψ βΨ ⊗ ⊗ ′= +
13. 13
( )
1
2
10 10−
( )0 1
1
2
10 0 1 10− + −
Quantifying 2-qubit entanglement
( ) 00 11 01 102C α α α α≡ −Ψ
00 01 10 110 10 0 10 11α α α αΨ= + + +
Two qubits in the state
are entangled if and only if (iff) they have nonzero concurrence
0C =
1C =
1C =( )0 1
1
2
10 0 1 10+ − +
( )0 0
3
0 1
1
1 1+ + 2 / 3C =
14. 14
The Bell states
( )
( )
( )
( )
0 1
0
0 1
0 1
1
2
1
2
1
2
1
2
1
1 00 1
11 00
+
−
+
−
Φ= +
Φ= −
Ψ= +
Ψ= −
These states form a basis for the 4-dimensional Hilbert space of 2 qubits.
This basis is called The Bell basis.
The singlet.
The even-parity Bell states.
The odd-parity Bell states.
C=1 for all these states.
15. 15
Definition: a transformation is unitary ifU † †
U U UU I= =
Ψ
Φ
′Ψ
′Φ
U
For unitary :U
†
U U′ ′ ′Φ Ψ = Φ Ψ = Φ Ψ
preservation of inner product
Also works in other direction, thus
U unitary iff inner product preserved.
U
Review: unitary transformations
16. 16
Catalog of 1-qubit gates
I
1 0ˆ
0 1
I
Identity
Z
1 0ˆ
0 1
Z
−
Pauli Z
0 1ˆ
1 0
X
XPauli X
0ˆ
0
i
Y
i
−
YPauli Y
1 11ˆ
1 12
H
−
HHadamard
ˆ ˆ( ) cos( / 2) sin( / 2)nR I i nθ θ θ σ= − ⋅
( )nR θRotations
{ }ˆ ˆ ˆ, ,X Y Zσ =
/2
1 0ˆ
0 i
S
eπ
SS
/4
1 0ˆ
0 i
T
eπ
TT
17. 17
Products of single-qubit unitaries
V
U
Ψ V U⊗ Ψ
a b
V
c d
e f
U
g h
e f e f e f e f
g h g h g h g h
U
e f e fe f e f
g h g
a a b b
a b
a a b b
V
c c d d
c d
c c d hh g h dg
⊗
in the composite basis.
18. 18
rg
1 0 0 0
0 1 0 0
0 0 0
C
1
0 0 1 0
-NOT
Controlled-NOT gate (C-NOT)
00
01
10
11
a
b b
a b⊕
2-qubit gates (Part 1)
00 11
gr
1 0 0 0
0 0 0 1
0 0 1
C
0
0 1 0 0
-NOT
a
b a b⊕
a
=
X
01 10
control
target
19. 19
How to make a Bell state
0 0 00
1 1 1 1
2 2 2 2
1 0 1
+ = +
0
0 H
00 1
2
00
1 1
2
1+
How to make the other 3 Bell states?
?
? H
Starting from different
computational states produces
different Bell states!
20. 20
1 0 0 0
0 1 0 0
0 0 1
C PHAS
0
E
0
0 0 i
e
ϕ
ϕ
−
b
a a
b
Controlled-Phase
A 2-qubit gates (Part 2)
=
Z
Z
=π
ϕ ( )i ab
eϕ
×
Note about convention: when the phase is not specified, it is π.
21. 21
H H
=
H H
=
Simplifying/realizing a quantum circuit
The process of simplifying a quantum circuit and/or finding a quantum circuit
that implements a particular unitary using a specific set of gates is called
quantum compiling.
Can compile C-NOT from CPHASE and
viceversa by ‘dressing’ with Hadamard
gates.
H Z H X=
H H I=
H X H Z=
To see this, refer to these identities:
22. 22
Universal set of gates
4.5.2
A set of gates that can be used to implement an arbitrary unitary operation on any number of
qubits is said to be universal.
An arbitrary operation on n qubits can be implemented using a circuit
containing O(n24n) single-qubit and C-NOT gates.
Examples:
,n θ
( )nR θ
(1) Arbitrary single-qubit rotations + C-NOT
any
(2) Arbitrary rotations around x and around y axes + C-NOT
θ
( )xR θ
any θ
( )yR θ
any
23. 23
Euler angle decomposition of single-qubit gates
( ) ( ) ( )ˆ ˆ ˆn m nU R R Rβ γ δ=
An arbitrary single-qubit gate may be written asU
up to an irrelevant global phase,
provided and are non-parallel unit vectors, and
for appropriate choices of .
ˆn ˆm
, ,β γ δ
24. 24
A universal discrete set of gates
T
C-NOT
1 0 0 0
0 1 0 0
C-NOT
0 0 0 1
0 0 1 0
A standard choice is:
Hadamard
1 11
1 12
H
−
/4
1 0
0 i
T
eπ
From just these three gates, you can do any unitary on n qubits
(Warning: it may require many of these three gates!)
25. 25
Rotations around non-parallel axes
( )nTHTH R θ=
( )mHTHT R θ=
cos ,sin ,cos
8 8 8
n
π π π ∝
cos , sin ,cos
8 8 8
m
π π π ∝ −
( )( )1 2
2cos cos / 8
0.174443 2
θ π
π
−
=
= ×
An irrational
multiple of 2π
x
y
z
Irrationality of theta is critical:
Can reach any desired rotation about
to any desired accuracy by repeating THTH
as many times as needed.
Can reach any desired rotation about
by repeating HTHT as many times as needed.
n
m
26. 26
Arbitrary rotations around either axis
For any , there exists an integer such thatε l
( ) ( )( ),
3
l
n nE R R
ε
δ θ <
( )( , ) maxE U V U V
ψ
ψ≡ −
1
ε
1
( )ε −
Θ
27. 27
Solovay-Kitaev theorem
An arbitrary single-qubit gate may be approximated to an accuracy
using gates from a discrete set, where .ε
App.
3
1
(log ( ))c
ε −
Θ 2c ≈
Can do much better than that!
(Don’t worry about the proof!)
31. 31
C-C-Phase decomposition into 1- and 2-qubit gates
4
00 01 10 1100 10 1 11 0α α α αψ ψ ψ ψΨ= ⊗ ′ ′′+ ⊗ + ⊗ + ⊗ ′′′
Without loss of generally, we can write
the input state of the three qubits as:
Let’s consider the action of this gate on each of the four terms:
= S
T
†
T
T
†
T T †
T
†
T
π
Claim:
32. 0
0
ψ
T
T†
T T †
T
S†
T
†
T
0
0
ψ
0
1
ψ ′
T
†
T T T
†
T
S†
T
†
T
X X
0
1
ψ ′
1
0
ψ ′′
T
T †
T
S†
T
†
T
X X
X X4
i
e T
π
−
/4
1i
e π+
/4
0i
e π−
ψ ′′T†
T
† 4
i
XT X e T
π
−
=
33. 1
1
ψ ′′′
T
T†
T T †
T
S†
T †
TX X
X XX X iZ−
/4
1i
e π+
/4
1i
e π+
iZ ψ− ′′′4
i
e T
π
−
4
i
e T
π
−
4
i
e T
π
−
1
1
Z ψ ′′′
35. 35
Problem 4.4: (Minimal Toffoli construction) (Research)
(1) What is the smallest number of two qubit gates that can
be used to implement the Toffoli gate?
(2) What is the smallest number of one-qubit gates and C-NOT gates
that can be used to implement the Toffoli gate?
(3) What is the smallest number of one qubit gates and
controlled-Z gates that can be used to implement the Toffoli gate?
Lanyon et al., Nature Phys (2008)
Is this the most efficient decomposition?
37. 37
Summary of Part 1
You should be able to:
● Understand the concepts universal set of gates, and discrete set of universal gates.
● Easily determine whether a two-qubit state is entangled or not.
● Compile simple quantum circuits involving 1-qubit and CNOT/CPHASE gates.
● Analyze (not design) quantum circuits involving 1-qubit and CNOT/CPHASE gates.
38. 38
The generalized Born rule
Ψ
jλ
jm λ=
2
jα
jϕ
with probabilityˆM
ˆ jjjM λ λ λ=where
where form the basis for measurement,
are normalized but not necessarily orthogonal,
and .
j j j
j
α ϕ λΨ =∑
● Without loss of generality, can always write 2-qubit state
jϕ
2
1j
j
α =∑
jλ
43. 43
Example: measuring both qubits
jλ
1
ˆM
Ψ 1 jm λ=
jλ ′
2
ˆM 2 jm λ ′′=
11
ˆ ˆIm M=Ψ Ψ
22
ˆ ˆMm I=Ψ Ψ
22 11
ˆ ˆm m M M=Ψ Ψ
(since order
doesn’t matter)
● As previous example shows, the statistics of measurement outcomes do not
depend on the order of measurements.
● Expectation values of measurement outcomes:
44. 44
Summary of Part 2
You should be able to:
● Apply the generalized Born rule to calculate probabilities of measurement
outcomes and the post-measurement states when some or all qubits in a register
are measured.