Lecture 4. Signal Flow Graphs and recurrence relations

Size: px
Start display at page:

Download "Lecture 4. Signal Flow Graphs and recurrence relations"

Transcription

1 Lecture 4 Signal Flow Graphs and recurrence relations

2 Plan Fibonacci s rabbits and sustainable rabbit farming Signal Flow Graphs Generating functions IH Q[] Operational semantics Solving sustainable rabbit farming

3 Fibonacci (C 7 - C 25) A certain man had one pair of rabbits together in a certain enclosed place, and one wishes to know how many are created from the pair in one year when it is the nature of them in a single month to bear another pair, and in the second month those born to bear also. You can indeed see in the margin how we operated, namely that we added the first number to the second, namely the to the 2, and the second to the third, and the third to the fourth, and the fourth to the fifth, and thus one after another until we added the tenth to the eleventh, namely the 44 to the 233, and we had the above written sum of rabbits, namely 377, and thus you can in order find it for an unending number of months. (etract from Liber Abaci, chapter 2, translated from Latin by Lawrence Sigler)

4 The Fibonacci sequence, 2, 3, 5, 8 in modern presentations often given as,, 2, 3, 5, or,,, 2, 3, is an eample of a recurrence relation. All three satisfy Fn+2 Fn+ + Fn

5 Coding Fibonacci Natural to generalise Fibonacci s rabbit breeding to function of type ffib: int list -> int list # ffib [;;;;;;;];; - : int list [; 2; 3; 5; 8; 3; 2; 34] # ffib [;;;;;;;];; - : int list [; 3; 6; ; 9; 32; 53; 87] # ffib [;;-3;;-2;-4;];; - : int list [; 3; 2; 3; 4; ; 2]

6 Sustainable rabbit farming problem Suppose we want a sustainable rabbit farm, keeping four pairs of rabbits at all times is it possible? if so, how many pairs of rabbits must we add/ remove and in which months? More generally, can we obtain a solution for any (possibly variable) number of rabbits in each month?

7 Achieving sustainable rabbit breeding ffib: int list -> int list To obtain solution, one could try to compute the inverse bfib: int list -> int list bfib [4;4;4;4;4;4;4;4;4;4;4;4];;

8 Plan Fibonacci s rabbits and sustainable rabbit farming Signal Flow Graphs Generating functions IHQ[] Operational semantics Solving sustainable rabbit farming

9 Claude Shannon, The theory and design of linear differential equation machines, report to National Defence Research Council, January 942 This report deals with the general theory of machines constructed from the following five types of mechanical elements. Integrators Adders or differential gears Gear boes Shaft junctions Shafts

10 Eample eecution Input 3 Output 2 The circuit defines a function of type int list -> int list note: if I keep pumping in zeros, then eventually all registers will get zeroed out and the output will stabilise at zero - is this the case for every circuit?

11 Feedback!

12 Eample - Fibonacci

13 A little optimisation These always hold the same value ALGEBRAIC MANIPULATION, DIRECTLY ON THE CIRCUIT DIAGRAM!

14 A little optimisation 2

15 Behaviours linear subspaces ffib: int list -> int list Behaviours are closed under (pointwise) addition (pointwise) scalar multiplication

16 Plan Fibonacci s rabbits and sustainable rabbit farming Signal Flow Graphs Generating functions IHQ[] Operational semantics Solving sustainable rabbit farming

17 Polynomial Zoo Ring of polynomials Q[] Field of polynomial fractions Q() Ring of formal power series Q[[]] Field of Laurent power series Q(()) injective ring hom. Q[] Q[[]] (injective) field hom. Q() Q(())

18 Generatingfunctionology (see famous book by H. Wilf) Spec F F 2 F n+2 F n+ + F n Define F () X F n n n X n F n+2 n X F n+ n + n X F n n n F () X n F n+2 n X n F n+ n X 2 ( F n+2 n ) n X F n n F () 2 n2 F () F () 2 F () 2 X ( F n+ n ) n X n F n n F () F () + 2

19 Obtaining the coefficients k() k(()) F () + 2! (, 2, 3, 5, 8, ) Moral of the story so far : polynomial fractions are useful for reasoning about recurrence relations

20 Plan Fibonacci s rabbits and sustainable rabbit farming Signal Flow Graphs Generating functions IHQ[] Operational semantics Solving sustainable rabbit farming

21 Interacting Hopf Monoids (Bonchi, S., Zanasi, 3, 4) p p p p (p ) (cf. ZX-calculus, Coecke and Duncan 8, Baez and Erbele 4)

22 Generalising (slightly) It is straightforward to generalise from Z to arbitrary PID R We can build the theory H R by adding enough scalars to the graphical synta together with equations r r +r 2 r 2 r r 2 r 2 r The equations of IH R are the same as before Theorem. IHR LinRelff(R)

23 Equations for Q[]

24 Polynomial fractions with diagrammatic synta F ()

25 Eample As linear relation over Q() is the space generated by (, (+)/(-- 2 )) As linear relation over Q(()) is the space generated by (,,,,,2,3,5,8, )

26 Plan Fibonacci s rabbits and sustainable rabbit farming Signal Flow Graphs Generating functions IHQ[] Operational semantics Solving sustainable rabbit farming

27 Operational semantics Bonchi, S., Zanasi, Full abstraction for signal flow graphs, POPL 5 k! kk k! k l! k l! k kl l k k! l k+l! kk! k! k k kl! l k l l! k k k+l! kl! s! u k! kl v s t! v w t k lk! s ; t u! w s ; t s u! v s t u2 v2! t s t u u2! v v 2 s t Important point: all eecutions start with all registers initialised with!

28 Eample : :

29 Signal flow graphs as string diagrams Easy - get rid of directions on the wires!

30 Realisability and Full Abstraction Realisability Every diagram can be put in a form where the direction of signal flow is consistent Full abstraction Operational equality (in terms of behaviour, given by operational semantics) coincides with denotational equality (the denoted linear relation) on diagrams with consistent signal flow

31 Plan Fibonacci s rabbits and sustainable rabbit farming Signal Flow Graphs Generating functions IHQ[] Operational semantics Solving sustainable rabbit farming

32 Which we know can be directed from left to right

33 Which can be directed from right to left - -

34 Solving sustainable rabbit farming # rfib [4;4;4;4;4;4;4;4;4;4;4;4;4];; - : int list [4; -4; ; -4; ; -4; ; -4; ; -4; ; -4; ]

35 Bibliography Bonchi, S., Zanasi - Interacting Bialgebras are Frobenius, FoSSaCS 4 Bonchi, S., Zanasi - Interacting Hopf Algebras, J Pure Applied Algebra 22:44 84, 27 Bonchi, S., Zanasi - The Calculus of Signal Flow Diagrams I: Linear Relations on Streams, Inf Comput 252:2 29, 27 Bonchi, S., Zanasi - A categorical semantics of signal flow graphs, CONCUR 23 Bonchi, S., Zanasi - Full abstraction for signal flow graphs, PoPL 26 Zanasi - Interacting Hopf Algebras: The theory of linear systems, PhD Thesis, ENS Lyon, 25 Bonchi, S., Zanasi - Lawvere Theories as composed PROPs, CMCS 26 Fong, Rapisarda, S. - A categorical approach to open and interconnected dynamical systems, LiCS 26 Bonchi, Gadducci, Kissinger, S. - Rewriting modulo symmetric monoidal structure, LiCS 26 Bonchi, Gadducci, Kissinger, S. - Confluence of Graph Rewriting with Interfaces, ESOP 27 graphicallinearalgebra.net

PROGRAMMING RECURRENCE RELATIONS

PROGRAMMING RECURRENCE RELATIONS PAWEL SOBOCINSKI U. SOUTHAMPTON, U. HAWAI I AT MĀNOA PROGRAMMING RECURRENCE RELATIONS and other compositional stuff Compositionality Workshop, Simons Institute, 9 December 2016 COLLABORATORS Dusko Pavlovic

More information

Applied Category Theory. John Baez

Applied Category Theory. John Baez Applied Category Theory John Baez In many areas of science and engineering, people use diagrams of networks, with boxes connected by wires: In many areas of science and engineering, people use diagrams

More information

CATEGORIES IN CONTROL. John Baez Canadian Mathematical Society Winter Meeting 5 December 2015

CATEGORIES IN CONTROL. John Baez Canadian Mathematical Society Winter Meeting 5 December 2015 CATEGORIES IN CONTROL John Baez Canadian Mathematical Society Winter Meeting 5 December 2015 To understand ecosystems, ultimately will be to understand networks. B. C. Patten and M. Witkamp We need a good

More information

Categories in Control John Baez and Jason Erbele

Categories in Control John Baez and Jason Erbele Categories in Control John Baez and Jason Erbele Categories are great for describing processes. A process with input x and output y is a morphism F : x y, and we can draw it like this: F We can do one

More information

CATEGORIES IN CONTROL. John Baez, Jason Erbele & Nick Woods Higher-Dimensional Rewriting and Applications Warsaw, 28 June 2015

CATEGORIES IN CONTROL. John Baez, Jason Erbele & Nick Woods Higher-Dimensional Rewriting and Applications Warsaw, 28 June 2015 CATEGORIES IN CONTROL John Baez, Jason Erbele & Nick Woods Higher-Dimensional Rewriting and Applications Warsaw, 28 June 2015 We have left the Holocene and entered a new epoch, the Anthropocene, when the

More information

Baby's First Diagrammatic Calculus for Quantum Information Processing

Baby's First Diagrammatic Calculus for Quantum Information Processing Baby's First Diagrammatic Calculus for Quantum Information Processing Vladimir Zamdzhiev Department of Computer Science Tulane University 30 May 2018 1 / 38 Quantum computing ˆ Quantum computing is usually

More information

The Mathematics of Open Reaction Networks

The Mathematics of Open Reaction Networks The Mathematics of Open Reaction Networks Y John Baez U. C. Riverside / Centre for Quantum Technologies Dynamics, Thermodynamics and Information Processing in Chemical Networks June 13, 2017 In many areas

More information

Interacting Bialgebras are Frobenius

Interacting Bialgebras are Frobenius Interacting Bialgebras are Frobenius Filippo Bonchi, Pawe l Sobociński and Fabio Zanasi ENS de Lyon, Université de Lyon, CNRS, INRIA, France University of Southampton, UK Abstract. Bialgebras and Frobenius

More information

Fibonacci Numbers. By: Sara Miller Advisor: Dr. Mihai Caragiu

Fibonacci Numbers. By: Sara Miller Advisor: Dr. Mihai Caragiu Fibonacci Numbers By: Sara Miller Advisor: Dr. Mihai Caragiu Abstract We will investigate various ways of proving identities involving Fibonacci Numbers, such as, induction, linear algebra (matrices),

More information

Streams and Coalgebra Lecture 2

Streams and Coalgebra Lecture 2 Streams and Coalgebra Lecture 2 Helle Hvid Hansen and Jan Rutten Radboud University Nijmegen & CWI Amsterdam Representing Streams II, Lorentz Center, Leiden, January 2014 Tutorial Overview Lecture 1 (Hansen):

More information

Abstract structure of unitary oracles for quantum algorithms

Abstract structure of unitary oracles for quantum algorithms Abstract structure o unitary oracles or quantum algorithms William Zeng 1 Jamie Vicary 2 1 Department o Computer Science University o Oxord 2 Centre or Quantum Technologies, University o Singapore and

More information

Introduction to Techniques for Counting

Introduction to Techniques for Counting Introduction to Techniques for Counting A generating function is a device somewhat similar to a bag. Instead of carrying many little objects detachedly, which could be embarrassing, we put them all in

More information

Egyptian Fraction. Massoud Malek

Egyptian Fraction. Massoud Malek Egyptian Fraction Massoud Malek Throughout history, different civilizations have had different ways of representing numbers. Some of these systems seem strange or complicated from our perspective. The

More information

CS61c: Representations of Combinational Logic Circuits

CS61c: Representations of Combinational Logic Circuits CS61c: Representations of Combinational Logic Circuits J. Wawrzynek March 5, 2003 1 Introduction Recall that synchronous systems are composed of two basic types of circuits, combination logic circuits,

More information

NETWORK THEORY. John Baez Categorical Foundations of Network Theory Institute for Scientific Interchange, Turin, Italy 25 May 2015

NETWORK THEORY. John Baez Categorical Foundations of Network Theory Institute for Scientific Interchange, Turin, Italy 25 May 2015 NETWORK THEORY John Baez Categorical Foundations of Network Theory Institute for Scientific Interchange, Turin, Italy 25 May 2015 We have left the Holocene and entered a new epoch, the Anthropocene, when

More information

Encoding!-tensors as!-graphs with neighbourhood orders

Encoding!-tensors as!-graphs with neighbourhood orders Encoding!-tensors as!-graphs with neighbourhood orders David Quick University of Oxford david.quick@cs.ox.ac.uk Diagrammatic reasoning using string diagrams provides an intuitive language for reasoning

More information

Math 192r, Problem Set #3: Solutions

Math 192r, Problem Set #3: Solutions Math 192r Problem Set #3: Solutions 1. Let F n be the nth Fibonacci number as Wilf indexes them (with F 0 F 1 1 F 2 2 etc.). Give a simple homogeneous linear recurrence relation satisfied by the sequence

More information

Rewriting measurement-based quantum computations with generalised flow

Rewriting measurement-based quantum computations with generalised flow Rewriting measurement-based quantum computations with generalised flow Ross Duncan 1 and Simon Perdrix 2 1 Oxford University Computing Laboratory ross.duncan@comlab.ox.ac.uk 2 CNRS, LIG, Université de

More information

Verifying the Steane code with Quantomatic

Verifying the Steane code with Quantomatic Verifying the Steane code with Quantomatic Ross Duncan University of Strathclyde Glasgow, UK ross.duncan@strath.ac.uk Maxime Lucas Université Libre de Bruxelles Brussels, Belgium mlucas@ulb.ac.be In this

More information

UC Berkeley College of Engineering, EECS Department CS61C: Representations of Combinational Logic Circuits

UC Berkeley College of Engineering, EECS Department CS61C: Representations of Combinational Logic Circuits 2 Wawrzynek, Garcia 2004 c UCB UC Berkeley College of Engineering, EECS Department CS61C: Representations of Combinational Logic Circuits 1 Introduction Original document by J. Wawrzynek (2003-11-15) Revised

More information

MATH39001 Generating functions. 1 Ordinary power series generating functions

MATH39001 Generating functions. 1 Ordinary power series generating functions MATH3900 Generating functions The reference for this part of the course is generatingfunctionology by Herbert Wilf. The 2nd edition is downloadable free from http://www.math.upenn. edu/~wilf/downldgf.html,

More information

We wish the reader success in future encounters with the concepts of linear algebra.

We wish the reader success in future encounters with the concepts of linear algebra. Afterword Our path through linear algebra has emphasized spaces of vectors in dimension 2, 3, and 4 as a means of introducing concepts which go forward to IRn for arbitrary n. But linear algebra does not

More information

Linear Algebra. Mark Dean. Lecture Notes for Fall 2014 PhD Class - Brown University

Linear Algebra. Mark Dean. Lecture Notes for Fall 2014 PhD Class - Brown University Linear Algebra Mark Dean Lecture Notes for Fall 2014 PhD Class - Brown University 1 Lecture 1 1 1.1 Definition of Linear Spaces In this section we define the concept of a linear (or vector) space. The

More information

Generalization of Fibonacci sequence

Generalization of Fibonacci sequence Generalization of Fibonacci sequence Etienne Durand Julien Chartrand Maxime Bolduc February 18th 2013 Abstract After studying the fibonacci sequence, we found three interesting theorems. The first theorem

More information

Recurrences COMP 215

Recurrences COMP 215 Recurrences COMP 215 Analysis of Iterative Algorithms //return the location of the item matching x, or 0 if //no such item is found. index SequentialSearch(keytype[] S, in, keytype x) { index location

More information

CORELATIONS ARE THE PROP FOR EXTRASPECIAL COMMUTATIVE FROBENIUS MONOIDS

CORELATIONS ARE THE PROP FOR EXTRASPECIAL COMMUTATIVE FROBENIUS MONOIDS Theory and Applications of Categories, Vol. 32, No. 11, 2017, pp. 380 395. CORELATIONS ARE THE PROP FOR EXTRASPECIAL COMMUTATIVE FROBENIUS MONOIDS BRANDON COYA AND BRENDAN FONG Abstract. Just as binary

More information

Every subset of {1, 2,...,n 1} can be extended to a subset of {1, 2, 3,...,n} by either adding or not adding the element n.

Every subset of {1, 2,...,n 1} can be extended to a subset of {1, 2, 3,...,n} by either adding or not adding the element n. 11 Recurrences A recurrence equation or recurrence counts things using recursion. 11.1 Recurrence Equations We start with an example. Example 11.1. Find a recurrence for S(n), the number of subsets of

More information

SECTION 2: BLOCK DIAGRAMS & SIGNAL FLOW GRAPHS

SECTION 2: BLOCK DIAGRAMS & SIGNAL FLOW GRAPHS SECTION 2: BLOCK DIAGRAMS & SIGNAL FLOW GRAPHS MAE 4421 Control of Aerospace & Mechanical Systems 2 Block Diagram Manipulation Block Diagrams 3 In the introductory section we saw examples of block diagrams

More information

Digitalteknik EIT020. Lecture 18: Linear Sequential Circuits (Time Domain)

Digitalteknik EIT020. Lecture 18: Linear Sequential Circuits (Time Domain) Digitalteknik EIT020 Lecture 18: Linear Sequential Circuits (Time Domain) November 16, 2014 Linear Boolean functions Denition (Linearity) A function f is said to be linear if f (x y) = f (x) f (y) (L 1

More information

Introduction to Lucas Sequences

Introduction to Lucas Sequences A talk given at Liaoning Normal Univ. (Dec. 14, 017) Introduction to Lucas Sequences Zhi-Wei Sun Nanjing University Nanjing 10093, P. R. China zwsun@nju.edu.cn http://math.nju.edu.cn/ zwsun Dec. 14, 017

More information

Generating Functions

Generating Functions Generating Functions Prachi Pendse January 9, 03 Motivation for Generating Functions Question How many ways can you select 6 cards from a set of 0? ( + ) 0 = ( + )( + )( + )... = 0 + 0 9 + 4 8 + 0 ( )

More information

f(x) = lim x 0 + x = lim f(x) =

f(x) = lim x 0 + x = lim f(x) = Infinite Limits Having discussed in detail its as x ±, we would like to discuss in more detail its where f(x) ±. Once again we would like to emphasize that ± are not numbers, so if we write f(x) = we are

More information

Analyzing Functions Maximum & Minimum Points Lesson 75

Analyzing Functions Maximum & Minimum Points Lesson 75 (A) Lesson Objectives a. Understand what is meant by the term extrema as it relates to functions b. Use graphic and algebraic methods to determine extrema of a function c. Apply the concept of extrema

More information

Section 7.2: One-to-One, Onto and Inverse Functions

Section 7.2: One-to-One, Onto and Inverse Functions Section 7.2: One-to-One, Onto and Inverse Functions In this section we shall developed the elementary notions of one-to-one, onto and inverse functions, similar to that developed in a basic algebra course.

More information

A few bridges between operational and denotational semantics of programming languages

A few bridges between operational and denotational semantics of programming languages A few bridges between operational and denotational semantics of programming languages Soutenance d habilitation à diriger les recherches Tom Hirschowitz November 17, 2017 Hirschowitz Bridges between operational

More information

Reverse Fibonacci Segllence. found the Fibonacci sequence to be interesting and wanted to do something with it. First, when I

Reverse Fibonacci Segllence. found the Fibonacci sequence to be interesting and wanted to do something with it. First, when I Marie Neubrander October 19,2011 3B Mrs. Johnson Reverse Fibonacci Segllence I was prompted to do this project when in math this year we had to write a report about a mathematician of our choice. Some

More information

Lecture three: Automata and the algebra-coalgebra duality

Lecture three: Automata and the algebra-coalgebra duality Lecture three: Automata and the algebra-coalgebra duality Jan Rutten CWI Amsterdam & Radboud University Nijmegen IPM, Tehran - 13 January 2016 This lecture will explain two diagrams: 1 x c ε σ A r x X

More information

Course Summary. The course cannot be summarized in one lecture.

Course Summary. The course cannot be summarized in one lecture. Course Summary Unit 1: Introduction Unit 2: Modeling in the Frequency Domain Unit 3: Time Response Unit 4: Block Diagram Reduction Unit 5: Stability Unit 6: Steady-State Error Unit 7: Root Locus Techniques

More information

Math 1314 Lesson 4 Limits

Math 1314 Lesson 4 Limits Math 1314 Lesson 4 Limits What is calculus? Calculus is the study of change, particularly, how things change over time. It gives us a framework for measuring change using some fairly simple models. In

More information

A ZX-Calculus with Triangles for Toffoli-Hadamard, Clifford+T, and Beyond

A ZX-Calculus with Triangles for Toffoli-Hadamard, Clifford+T, and Beyond A ZX-Calculus with Triangles for Toffoli-Hadamard, Clifford+T, and Beyond Renaud Vilmart Université de Lorraine, CNRS, Inria, LORIA, F 5000 Nancy, France renaud.vilmart@loria.fr We consider a ZX-calculus

More information

INFINITE SUMS. In this chapter, let s take that power to infinity! And it will be equally natural and straightforward.

INFINITE SUMS. In this chapter, let s take that power to infinity! And it will be equally natural and straightforward. EXPLODING DOTS CHAPTER 7 INFINITE SUMS In the previous chapter we played with the machine and saw the power of that machine to make advanced school algebra so natural and straightforward. In this chapter,

More information

2 Difference equations and modularity

2 Difference equations and modularity 2 Difference equations and modularity 2.1 Modularity: Making the input like the output 17 2.2 Endowment gift 21 2.3 Rabbits 25 The goals of this chapter are: to illustrate modularity and to describe systems

More information

1 Examples of Weak Induction

1 Examples of Weak Induction More About Mathematical Induction Mathematical induction is designed for proving that a statement holds for all nonnegative integers (or integers beyond an initial one). Here are some extra examples of

More information

Fibonacci Sequence. January 19, 2014

Fibonacci Sequence. January 19, 2014 Fibonacci Sequence January 19, 2014 Today we will learn about the Fibonacci sequence, one of the most famous sequences of numbers in mathematics. To construct it, we will look at the pattern of growth

More information

Fourth Lecture: 11/4

Fourth Lecture: 11/4 Fourth Lecture: 11/4 Definition 4.1. A sequence a n ) n=1 of complex numbers is said to be defined recursively, or to satsify a recurrence relation, if there exists a fixed k N, called the degree of the

More information

15 DIFFERENCE EQUATIONS 2

15 DIFFERENCE EQUATIONS 2 5 DIFFERENCE EQUATIONS 2 Chapter 5 Difference Equations 2 Objectives After studying this chapter you should be able to obtain the solution of any linear homogeneous second order difference equation; be

More information

When is a number Fibonacci?

When is a number Fibonacci? When is a number Fibonacci? Phillip James Department of Computer Science, Swansea University March 6, 009 Abstract This article looks into the importance of the Fibonacci numbers within Computer Science,

More information

Complexity. Complexity Theory Lecture 3. Decidability and Complexity. Complexity Classes

Complexity. Complexity Theory Lecture 3. Decidability and Complexity. Complexity Classes Complexity Theory 1 Complexity Theory 2 Complexity Theory Lecture 3 Complexity For any function f : IN IN, we say that a language L is in TIME(f(n)) if there is a machine M = (Q, Σ, s, δ), such that: L

More information

12 Sequences and Recurrences

12 Sequences and Recurrences 12 Sequences and Recurrences A sequence is just what you think it is. It is often given by a formula known as a recurrence equation. 12.1 Arithmetic and Geometric Progressions An arithmetic progression

More information

SOLUTION SETS OF RECURRENCE RELATIONS

SOLUTION SETS OF RECURRENCE RELATIONS SOLUTION SETS OF RECURRENCE RELATIONS SEBASTIAN BOZLEE UNIVERSITY OF COLORADO AT BOULDER The first section of these notes describes general solutions to linear, constant-coefficient, homogeneous recurrence

More information

Linear Algebra Prof. Dilip P Patil Department of Mathematics Indian Institute of Science, Bangalore

Linear Algebra Prof. Dilip P Patil Department of Mathematics Indian Institute of Science, Bangalore Linear Algebra Prof. Dilip P Patil Department of Mathematics Indian Institute of Science, Bangalore Lecture 01 Introduction to Algebraic Structures - Rings and Fields Welcome to this course on Linear Algebra.

More information

209 Sponsored by NC Math and Science Education Network

209 Sponsored by NC Math and Science Education Network Module 8: Using Recursively- Defined Functions to Module and Solve Problems Prepared by Dr. Cos Fi, UNC Greensboro Stephanie Gallop, Guilford County Schools Chapter 8 8.1. North Carolina Standard Course

More information

UNIVERSITY OF CALIFORNIA RIVERSIDE. Circuits, Bond Graphs, and Signal-Flow Diagrams: A Categorical Perspective

UNIVERSITY OF CALIFORNIA RIVERSIDE. Circuits, Bond Graphs, and Signal-Flow Diagrams: A Categorical Perspective UNIVERSITY OF CALIFORNIA RIVERSIDE Circuits, Bond Graphs, and Signal-Flow Diagrams: A Categorical Perspective A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor

More information

CPSC 467b: Cryptography and Computer Security

CPSC 467b: Cryptography and Computer Security CPSC 467b: Cryptography and Computer Security Michael J. Fischer Lecture 3 January 22, 2013 CPSC 467b, Lecture 3 1/35 Perfect secrecy Caesar cipher Loss of perfection Classical ciphers One-time pad Affine

More information

Semantics for algebraic operations

Semantics for algebraic operations MFPS 17 Preliminary Version Semantics for algebraic operations Gordon Plotkin and John Power 1 Laboratory for the Foundations of Computer Science University of Edinburgh King s Buildings, Edinburgh EH9

More information

Streams and Coalgebra Lecture 1

Streams and Coalgebra Lecture 1 Streams and Coalgebra Lecture 1 Helle Hvid Hansen and Jan Rutten Radboud University Nijmegen & CWI Amsterdam Representing Streams II, Lorentz Center, Leiden, January 2014 Tutorial Overview Lecture 1 (Hansen):

More information

Physics, Language, Maths & Music

Physics, Language, Maths & Music Physics, Language, Maths & Music (partly in arxiv:1204.3458) Bob Coecke, Oxford, CS-Quantum SyFest, Vienna, July 2013 ALICE f f = f f = f f = ALICE BOB BOB meaning vectors of words does not Alice not like

More information

Conservation of Information

Conservation of Information Conservation of Information Amr Sabry (in collaboration with Roshan P. James) School of Informatics and Computing Indiana University May 8, 2012 Amr Sabry (in collaboration with Roshan P. James) (IU SOIC)

More information

Counting problems in Number Theory and Physics

Counting problems in Number Theory and Physics Counting problems in Number Theory and Physics Hossein Movasati IMPA, Instituto de Matemática Pura e Aplicada, Brazil www.impa.br/ hossein/ Encontro conjunto CBPF-IMPA, 2011 A documentary on string theory

More information

Part III, Sequences and Series CS131 Mathematics for Computer Scientists II Note 16 RECURRENCES

Part III, Sequences and Series CS131 Mathematics for Computer Scientists II Note 16 RECURRENCES CS131 Part III, Sequences and Series CS131 Mathematics for Computer Scientists II Note 16 RECURRENCES A recurrence is a rule which defines each term of a sequence using the preceding terms. The Fibonacci

More information

Graphs: ubiquitous and beautiful. Graphical Reasoning in Symmetric Monoidal Categories for Quantum Information. Graphs: UML

Graphs: ubiquitous and beautiful. Graphical Reasoning in Symmetric Monoidal Categories for Quantum Information. Graphs: UML Graphs: ubiquitous and beautiul Graphical Reasonin in Smmetric Monoidal Cateories or Quantum Inormation Lucas Dion, Universit o Edinburh (Joint ork Ross Duncan and Aleks Kissiner) Abstracts over detail

More information

Sequences and Summations. CS/APMA 202 Rosen section 3.2 Aaron Bloomfield

Sequences and Summations. CS/APMA 202 Rosen section 3.2 Aaron Bloomfield Sequences and Summations CS/APMA 202 Rosen section 3.2 Aaron Bloomfield 1 Definitions Sequence: an ordered list of elements Like a set, but: Elements can be duplicated Elements are ordered 2 Sequences

More information

CALCULUS II - Self Test

CALCULUS II - Self Test 175 2- CALCULUS II - Self Test Instructor: Andrés E. Caicedo November 9, 2009 Name These questions are divided into four groups. Ideally, you would answer YES to all questions in group A, to most questions

More information

Lecture 1 - Preliminaries

Lecture 1 - Preliminaries Advanced Algorithms Floriano Zini Free University of Bozen-Bolzano Faculty of Computer Science Academic Year 2013-2014 Lecture 1 - Preliminaries 1 Typography vs algorithms Johann Gutenberg (c. 1398 February

More information

PROPS IN NETWORK THEORY

PROPS IN NETWORK THEORY Theory and Applications of Categories, Vol. 33, No. 25, 2018, pp. 727 783. PROPS IN NETWORK THEORY JOHN C. BAEZ, BRANDON COYA, FRANCISCUS REBRO Abstract. Long before the invention of Feynman diagrams,

More information

Fourier transforms from strongly complementary observables

Fourier transforms from strongly complementary observables Fourier transforms from strongly complementary observables Stefano Gogioso William Zeng Quantum Group, Department of Computer Science University of Oxford, UK stefano.gogioso@cs.ox.ac.uk william.zeng@cs.ox.ac.uk

More information

Sequential Circuits. Circuits with state. Silvina Hanono Wachman Computer Science & Artificial Intelligence Lab M.I.T. L06-1

Sequential Circuits. Circuits with state. Silvina Hanono Wachman Computer Science & Artificial Intelligence Lab M.I.T. L06-1 Sequential Circuits Circuits with state Silvina Hanono Wachman Computer Science & Artificial Intelligence Lab M.I.T. L06-1 Combinational circuits A 0 A 1 A n-1. Sel lg(n) O Mux A B Comparator Result: LT,

More information

MATH 1231 MATHEMATICS 1B Calculus Section Sequences.

MATH 1231 MATHEMATICS 1B Calculus Section Sequences. MATH 1231 MATHEMATICS 1B 2009. Calculus Section 4.2 - Sequences. S1: Motivation S2: What is a sequence? S3: Limit of a sequence S4: Geometric interpretation S5: Methods for evaluating limits S6: Divergence

More information

(Co)Algebraic Characterizations of Signal Flow Graphs

(Co)Algebraic Characterizations of Signal Flow Graphs (Co)Algebraic Characterizations of Signal Flow Graphs Henning Basold 1,3, Marcello Bonsangue 2,3, Helle H. Hansen 1,3, Jan Rutten 3,1 1 Radboud University Nijmegen 2 Leiden University 3 CWI Amsterdam Abstract

More information

CIRCUITS, CATEGORIES AND REWRITE RULES. John Baez & Brendan Fong Higher-Dimensional Rewriting and Applications Warsaw, 29 June 2015

CIRCUITS, CATEGORIES AND REWRITE RULES. John Baez & Brendan Fong Higher-Dimensional Rewriting and Applications Warsaw, 29 June 2015 CIRCUITS, CATEGORIES AND REWRITE RULES John Baez & Brendan Fong Higher-Dimensional Rewriting and Applications Warsaw, 29 June 2015 If mathematicians want to understand networks, a good place to start is

More information

Props in Network Theory

Props in Network Theory Props in Network Theory John C. Baez Brandon Coya Franciscus Rebro baez@math.ucr.edu bcoya001@ucr.edu franciscus.rebro@gmail.com January 22, 2018 Abstract Long before the invention of Feynman diagrams,

More information

Sequences of Real Numbers

Sequences of Real Numbers Chapter 8 Sequences of Real Numbers In this chapter, we assume the existence of the ordered field of real numbers, though we do not yet discuss or use the completeness of the real numbers. In the next

More information

INSPECT Algebra I Summative Assessment Summary

INSPECT Algebra I Summative Assessment Summary and Quantity The Real System Quantities Seeing Structure in Use properties of rational and irrational numbers. Reason quantitatively and use units to solve problems. Interpret the structure of expressions.

More information

Tutorial 3. Then for any R-module M, we have a bijection

Tutorial 3. Then for any R-module M, we have a bijection Tutorial 3 Topic 1: Group Algebras. We have now done much of this in class. 1. Let R be a commutative ring, and let X be a set. The free R- module on X (also free R-module with basis X ), denoted RX consists

More information

MATH 250 TOPIC 11 LIMITS. A. Basic Idea of a Limit and Limit Laws. Answers to Exercises and Problems

MATH 250 TOPIC 11 LIMITS. A. Basic Idea of a Limit and Limit Laws. Answers to Exercises and Problems Math 5 T-Limits Page MATH 5 TOPIC LIMITS A. Basic Idea of a Limit and Limit Laws B. Limits of the form,, C. Limits as or as D. Summary for Evaluating Limits Answers to Eercises and Problems Math 5 T-Limits

More information

Algebraic Functions, Equations and Inequalities

Algebraic Functions, Equations and Inequalities Algebraic Functions, Equations and Inequalities Assessment statements.1 Odd and even functions (also see Chapter 7)..4 The rational function a c + b and its graph. + d.5 Polynomial functions. The factor

More information

Power series and Taylor series

Power series and Taylor series Power series and Taylor series D. DeTurck University of Pennsylvania March 29, 2018 D. DeTurck Math 104 002 2018A: Series 1 / 42 Series First... a review of what we have done so far: 1 We examined series

More information

MATRICES AND LINEAR RECURRENCES IN FINITE FIELDS

MATRICES AND LINEAR RECURRENCES IN FINITE FIELDS Owen J. Brison Departamento de Matemática, Faculdade de Ciências da Universidade de Lisboa, Bloco C6, Piso 2, Campo Grande, 1749-016 LISBOA, PORTUGAL e-mail: brison@ptmat.fc.ul.pt J. Eurico Nogueira Departamento

More information

Algebra I Curriculum Crosswalk

Algebra I Curriculum Crosswalk Algebra I Curriculum Crosswalk The following document is to be used to compare the 2003 North Carolina Mathematics Course of Study for Algebra I and the State s for Mathematics Algebra I course. As noted

More information

POG Modeling of Automotive Systems

POG Modeling of Automotive Systems POG Modeling of Automotive Systems MORE on Automotive - 28 Maggio 2018 Prof. Roberto Zanasi Graphical Modeling Techniques Graphical Techniques for representing the dynamics of physical systems: 1) Bond-Graph

More information

Towards a formal description of models and workflows

Towards a formal description of models and workflows Towards a formal description of models and workflows Heinz A Preisig Process Systems Engineering @ Chemical Engineering NTNU, Trondheim, Norway MoDeNa - FP7 ++ Computational engineering The vision that

More information

Multivariate calculus

Multivariate calculus Multivariate calculus Lecture note 5 Outline 1. Multivariate functions in Euclidean space 2. Continuity 3. Multivariate differentiation 4. Differentiability 5. Higher order derivatives 6. Implicit functions

More information

Preuves de logique linéaire sur machine, ENS-Lyon, Dec. 18, 2018

Preuves de logique linéaire sur machine, ENS-Lyon, Dec. 18, 2018 Université de Lorraine, LORIA, CNRS, Nancy, France Preuves de logique linéaire sur machine, ENS-Lyon, Dec. 18, 2018 Introduction Linear logic introduced by Girard both classical and intuitionistic separate

More information

TenMarks Curriculum Alignment Guide: GO Math! Grade 8

TenMarks Curriculum Alignment Guide: GO Math! Grade 8 GO Math! Unit 1: Real, Exponents, and Scientific Module 1: Real Rational and Irrational Identifying Rational and Irrational Classifying and Representing Rational and Irrational Converting Fractions to

More information

Fibonacci Numbers. November 7, Fibonacci's Task: Figure out how many pairs of rabbits there will be at the end of one year, following rules.

Fibonacci Numbers. November 7, Fibonacci's Task: Figure out how many pairs of rabbits there will be at the end of one year, following rules. Fibonacci Numbers November 7, 2010 Fibonacci's Task: Figure out how many pairs of rabbits there will be at the end of one year, following rules. Rules: 1. Start with a pair of new rabbits, born in December.

More information

Diagrammatic Methods for the Specification and Verification of Quantum Algorithms

Diagrammatic Methods for the Specification and Verification of Quantum Algorithms Diagrammatic Methods or the Speciication and Veriication o Quantum lgorithms William Zeng Quantum Group Department o Computer Science University o Oxord Quantum Programming and Circuits Workshop IQC, University

More information

MATH The Derivative as a Function - Section 3.2. The derivative of f is the function. f x h f x. f x lim

MATH The Derivative as a Function - Section 3.2. The derivative of f is the function. f x h f x. f x lim MATH 90 - The Derivative as a Function - Section 3.2 The derivative of f is the function f x lim h 0 f x h f x h for all x for which the limit exists. The notation f x is read "f prime of x". Note that

More information

Skills Practice Skills Practice for Lesson 10.1

Skills Practice Skills Practice for Lesson 10.1 Skills Practice Skills Practice for Lesson.1 Name Date Higher Order Polynomials and Factoring Roots of Polynomial Equations Problem Set Solve each polynomial equation using factoring. Then check your solution(s).

More information

Ex. Here's another one. We want to prove that the sum of the cubes of the first n natural numbers is. n = n 2 (n+1) 2 /4.

Ex. Here's another one. We want to prove that the sum of the cubes of the first n natural numbers is. n = n 2 (n+1) 2 /4. Lecture One type of mathematical proof that goes everywhere is mathematical induction (tb 147). Induction is essentially used to show something is true for all iterations, i, of a sequence, where i N.

More information

Generating Functions

Generating Functions Generating Functions Karen Ge May, 07 Abstract Generating functions gives us a global perspective when we need to study a local property. We define generating functions and present its applications in

More information

Outline. EECS150 - Digital Design Lecture 4 - Boolean Algebra I (Representations of Combinational Logic Circuits) Combinational Logic (CL) Defined

Outline. EECS150 - Digital Design Lecture 4 - Boolean Algebra I (Representations of Combinational Logic Circuits) Combinational Logic (CL) Defined EECS150 - Digital Design Lecture 4 - Boolean Algebra I (Representations of Combinational Logic Circuits) January 30, 2003 John Wawrzynek Outline Review of three representations for combinational logic:

More information

Lecture 7: Indeterminate forms; L Hôpitals rule; Relative rates of growth. If we try to simply substitute x = 1 into the expression, we get

Lecture 7: Indeterminate forms; L Hôpitals rule; Relative rates of growth. If we try to simply substitute x = 1 into the expression, we get Lecture 7: Indeterminate forms; L Hôpitals rule; Relative rates of growth 1. Indeterminate Forms. Eample 1: Consider the it 1 1 1. If we try to simply substitute = 1 into the epression, we get. This is

More information

Math 345 Intro to Math Biology Lecture 1: Biological Models using Difference Equations

Math 345 Intro to Math Biology Lecture 1: Biological Models using Difference Equations Math 345 Intro to Math Biology Lecture 1: Biological Models using Difference Equations Junping Shi College of William and Mary, USA Population of James City County, Virginia Population is often recorded

More information

CALCULUS APPLICATIONS OF DIFFERENTIATION LESSON PLAN. C3 Topic Overview

CALCULUS APPLICATIONS OF DIFFERENTIATION LESSON PLAN. C3 Topic Overview CALCULUS C3 Topic Overview C3 APPLICATIONS OF DIFFERENTIATION Differentiation can be used to investigate the behaviour of a function, to find regions where the value of a function is increasing or decreasing

More information

Curriculum Scope & Sequence. Subject/Grade Level: MATHEMATICS/HIGH SCHOOL (GRADE 7, GRADE 8, COLLEGE PREP)

Curriculum Scope & Sequence. Subject/Grade Level: MATHEMATICS/HIGH SCHOOL (GRADE 7, GRADE 8, COLLEGE PREP) BOE APPROVED 9/27/11 Curriculum Scope & Sequence Subject/Grade Level: MATHEMATICS/HIGH SCHOOL Course: ALGEBRA I (GRADE 7, GRADE 8, COLLEGE PREP) Unit Duration Common Core Standards / Unit Goals Transfer

More information

Model Traditional Pathway: Model Algebra I Content Standards [AI]

Model Traditional Pathway: Model Algebra I Content Standards [AI] Model Traditional Pathway: Model Algebra I Content Standards [AI] Number and Quantity The Real Number System AI.N-RN A. Extend the properties of exponents to rational exponents. 1. Explain how the definition

More information

Fun with Semirings. A functional pearl on the abuse of linear algebra. Stephen Dolan

Fun with Semirings. A functional pearl on the abuse of linear algebra. Stephen Dolan A functional pearl on the abuse of linear algebra Computer Laboratory University of Cambridge stephen.dolan@cl.cam.ac.uk September 25, 2013 Linear algebra is magic If your problem can be expressed as vectors

More information

Advanced Counting Techniques

Advanced Counting Techniques . All rights reserved. Authorized only for instructor use in the classroom. No reproduction or further distribution permitted without the prior written consent of McGraw-Hill Education. Advanced Counting

More information

DEFINITE INTEGRALS - AREA UNDER A CURVE

DEFINITE INTEGRALS - AREA UNDER A CURVE Mathematics Revision Guides Definite Integrals, Area Under a Curve Page of M.K. HOME TUITION Mathematics Revision Guides Level: A-Level Year / AS DEFINITE INTEGRALS - AREA UNDER A CURVE Version :. Date:

More information

Dublin City Schools Mathematics Graded Course of Study Algebra I Philosophy

Dublin City Schools Mathematics Graded Course of Study Algebra I Philosophy Philosophy The Dublin City Schools Mathematics Program is designed to set clear and consistent expectations in order to help support children with the development of mathematical understanding. We believe

More information