The Physics of Theoretical Computation Course being taught this semester at CMU Physics & Computer Science 1.

Slides:



Advertisements
Similar presentations
ON TIME An Introduction into the theory behind Albert Einsteins Special Relativity.
Advertisements

Reversible Gates in various realization technologies
H.S. Physical Science Chapters 1 and 2
INST 240 Revolutions Lecture 9 Directions in Spacetime, Twin Paradox & Vectors.
The electromagnetic (EM) field serves as a model for particle fields
By: Physics Chapter 10 Nuclear Physics. Basic Concepts There are 3 different types of particles we find within the atom. These are known as the Proton,
DIGITAL ELECTRONICS, MICROPROCESSORS, AND COMPUTERS DIGITAL ELECTRONICS, MICROPROCESSORS, AND COMPUTERS By Naaimat Muhammed.
Electrostatic energy of a charge distribution.
1 FK7003 Lecture 8 ● CP -violation ● T -violation ● CPT invariance.
Two-state, Reversible, Universal Cellular Automata In Three Dimensions Authors: Daniel B. Miller & Edward Fredkin Carnegie Mellon West Computing Frontiers.
Random access memory Sequential circuits all depend upon the presence of memory. A flip-flop can store one bit of information. A register can store a single.
Solid State Physics (1) Phys3710
On Attributes and Limitations of Linear Optics in Computing A personal view Joseph Shamir Department of Electrical Engineering Technion, Israel OSC2009.
Bohr model 1. Electrons revolve around nucleus in circular paths, like planets around the sun. He called these paths orbits. 2. Each orbit has a specific.
The electromagnetic (EM) field serves as a model for particle fields  = charge density, J = current density.
Marek Perkowski Reversible Logic Models: Billiard Ball and Optical Lecture 4.
Lecture of Norm Margolus. Physical Worlds Some regular spatial systems: –1. Programmable gate arrays at the atomic scale –2. Fundamental finite-state.
Lecture 4: Computer Memory
1 Lecture 11: Digital Design Today’s topics:  Evaluating a system  Intro to boolean functions.
Memory Hierarchies for Quantum Data Dean Copsey, Mark Oskin, Frederic T. Chong, Isaac Chaung and Khaled Abdel-Ghaffar Presented by Greg Gerou.
Chapter 5.Periodicity and the Periodic Table. Many properties of the elements follow a regular pattern. In this chapter, we will look at theory that has.
Comparators  A comparator compares two input words.  The following slide shows a simple comparator which takes two inputs, A, and B, each of length 4.
9/20/2004EE 42 fall 2004 lecture 91 Lecture #9 Example problems with capacitors Next we will start exploring semiconductor materials (chapter 2). Reading:
QW *Use the light kits at your tables to perform and answer the following: Shine red, blue, and green lights at glow in the dark material 1. Which one.
Introduction Lecturer: Professor Stephen T. Thornton.
To Atomic and Nuclear Physics to Atomic and Nuclear Physics Phil Lightfoot, E47, (24533) All these slide presentations are at:
O Aim of the lecture  Introduction of Waves water as a model Radio  Light representation with rays refraction reflection o Main learning outcomes  familiarity.
Input/OUTPUT [I/O Module structure].
Computer Science 1000 Digital Circuits. Digital Information computers store and process information using binary as we’ve seen, binary affords us similar.
Digital Electronics. Introduction to Number Systems & Codes Digital & Analog systems, Numerical representation, Digital number systems, Binary to Decimal.
What is space made out of And how does it work? Franklin Hu NPA Video Conference February,
1 Properties of Light 2 Electromagnetic Waves: An electromagnetic wave is an oscillating combination of a magnetic and an electric field. It can be visualized.
Lecture 3 Need for new theory Stern-Gerlach Experiments Some doubts Analogy with mathematics of light Feynman’s double slit thought experiment.
Foundations of Computer Science Computing …it is all about Data Representation, Storage, Processing, and Communication of Data 10/4/20151CS 112 – Foundations.
Consider the statement 1000 x 100 = We can rewrite our original statement in power (index) format as 10 3 x 10 2 = 10 5 Remembering (hopefully!)
1 The Chinese University of Hong Kong Faculty of Education Diploma in Education (Part-Time) Winter 1997 Educational Communications and Technology Assignment.
Feynman Rules Feynman Diagrams Feynman Parametrization Feynman Gauge Feynman Cut-off Feynman Propagator Feynman Path integral Feynman Parton Model ….
Torque Section 8-1 Recall Equilibrium In general:Things at rest Constant uniform motion In particular:Equilibrium means that the Sum of forces acting.
© Copyright Pearson Prentice Hall Slide of 27 End Show Division page START NOTES SECTION 4.2 Please add quiz answers to notes; they were accidentally left.
It’s all done with Mirrors Many of the predictions of quantum mechanics are verified with ordinary matter particles (like electrons), but these experiments.
Physics 1202: Lecture 7 Today’s Agenda Announcements: –Lectures posted on: –HW assignments, solutions.
IT253: Computer Organization Lecture 7: Logic and Gates: Digital Design Tonga Institute of Higher Education.
Physics of Computing and the Promise and Limitations of Quantum Computing Charles H. Bennett IBM Research Yorktown Santa Cruz, 24 Oct 2005.
MODULE 1 In classical mechanics we define a STATE as “The specification of the position and velocity of all the particles present, at some time, and the.
Uncertainty Principle 1 Uncertainly Principle. Uncertainty Principle 2 Electrons that receive enough extra energy from the outside world can leave the.
Light and the Problem of Measurement 20 th Century physics changed science by realizing that you can only know something if you can measure it. In some.
The Quantum Model of the Atom Section 4.2. Bohr’s Problems Why did hydrogen’s electron exist around the nucleus only in certain allowed orbits? Why couldn’t.
Welcome to Physics--Jump in!
CO5023 Latches, Flip-Flops and Decoders. Sequential Circuit What does this do? The OUTPUT of a sequential circuit is determined by the current output.
Module 1Newtonian Relativity1 Module 1 Newtonian Relativity What do we mean by a “theory of relativity”? Let’s discuss the matter using conventional terminology.
Addition and multiplication Arithmetic is the most basic thing you can do with a computer, but it’s not as easy as you might expect! These next few lectures.
LECTURE 4 Logic Design. LOGIC DESIGN We already know that the language of the machine is binary – that is, sequences of 1’s and 0’s. But why is this?
Control units In the last lecture, we introduced the basic structure of a control unit, and translated our assembly instructions into a binary representation.
Ch. 8: Summary So Far We’re doing the “2 body”, conservative central force problem! 2 bodies (m 1 & m 2 ) with a central force directed along the line.
The first question is really "Why do you need a control system at all?” Consider the following: What good is an airplane if you are a pilot and you.
Chemistry Math Crunch Do you have what it takes?.
5-1-2 Synchronous counters. Learning Objectives: At the end of this topic you will be able to: draw a block diagram showing how D-type flip-flops can.
1924: de Broglie suggests particles are waves Mid-1925: Werner Heisenberg introduces Matrix Mechanics In 1927 he derives uncertainty principles Late 1925:
Addition and multiplication1 Arithmetic is the most basic thing you can do with a computer, but it’s not as easy as you might expect! These next few lectures.
What’s going on here? Can you think of a generic way to describe both of these?
Table of Contents 2.4 How Does Scientific Knowledge Developed? Why Do Scientist use Models? What is a system? How are Models of Systems Used? Models as.
Quantum Model of the Atom
GCSE OCR Computing A451 Binary logic Computing hardware 6.
COMP 1321 Digital Infrastructure
Models as Tools in Science
Elements of Quantum Mechanics
The Quantum Model of the Atom
Recall: ROM example Here are three functions, V2V1V0, implemented with an 8 x 3 ROM. Blue crosses (X) indicate connections between decoder outputs and.
Total Energy is Conserved.
Section 1: The Methods of Science
Presentation transcript:

The Physics of Theoretical Computation Course being taught this semester at CMU Physics & Computer Science 1

The Goals Replacing ad-hoc models of computation with: –Logic that reflects basic laws of physics –Reversibility, possible because both Physics & Computation are temporal processes amenable to reversibility –Conservation laws The object is to develop models of computation fundamentally governed by physics so that mathematics could apply to varioius aspects 2

However… Woke up at 7:30 this AM and decided to change the subject of my talk… 3

Avogadro Computation Nature is computing the future at a good pace! We would like, someday, to be able to force most atoms, in a lump of matter, into computing what we will then be interested in computing. How might this be possible? 4

Heat! Reversibility makes it possible to: –Imagine computers that dissipate very little! –Almost all computational steps can avoid all dissipation After all, QM operates without dissipation! The object is simply to make nature do our computation instead of doing its own computation –Non-reversible computation suffers from unavoidable Landauer dissipation: Log 2 k t 5

2 Designs for Computing Matter 1. We make a nearly perfect, simple crystal –Someday, the crystal ought to weigh a reasonable fraction of a kilo! –Then we make that crystal compute 2.We make a purpose built crystal, where every atom in the crystal is exactly as specified. This is much more difficult to do but this crystal computes very much faster! 6

A Salt Like Architecture As an example, we could have something similar to the Salt model It would be a 3D RUCA that is also a Universal Constructor It might use spin states for cell states –A 6 phase clock could be light pulses from the 6 faces of the cubic crystal 7

The Goals of the Salt Models A family of Computational Models that: – are computationally universal –Are Universal Constructors –have things in motion Subject to as many laws of physics as possible Conservation of Spin (angular momentum) Reversibility (Conservation of Information) Goals of exact conservation of other quantities Supports particles and waves???

Face Centered Cubic 3x3x3 Na + Subarray

FCC offset 1 unit in x, y & z Cl - Subarray

The two put together… CUBIC Known as Table Salt Na + Cl -

Idealized Newtonian Billiard Balls 12 x velocity =  1, y velocity =  1

13 The Billiard Ball Model A B A  B The Billiard Ball Model was dreamt up to answer critics that claimed that there was no possible physical realization of conservative logic because it seemed (to the critics) that any implementation had to violate the 2 nd law of thermodynamics!

14 The Feynman-Ressler Gate Two BBM Gates and 2 reflectors make one Feynman-Ressler Gate, also known as the Selector Gate. The schematic diagram for the Feynman-Ressler Gate is on the right. ABAB A BA ABAB B AA ABAB ABAB

SALT Molecular Computing This work was supported by a grant from the National Science Foundation

Gliders Interact When two gliders meet, depending on their phase and orientation, they may interact in such a way as to produce two new gliders on paths that lie on a plane orthogonal to the plane of the original paths.

Testing the Crystal We introduce 1 test CPU. It builds 2 copies –This process continues giving exponential growth to the CPU build process Next, Each CPU tests cells in its local area Errors are reported back When all crystal errors are known, a similar process fills the good parts of the crystal with a network of CPUs 17

Each CPU makes 2 copies 18

The Result? Cheap matter that computes as an array of RUCA systems Very much faster for some problems Much slower than dedicated logic (10 -8 ) –Real gates and wires as opposed to CA However – Very cheap and easy to build and test 19

We Build a Planar Seed We start with a conventional planar system It is put into a nutrient bath Local sites select atoms to add to the crystal As it grows, new circuits are tested and if faulty those atoms are returned to solution and the local process starts over again A full Avogadro crystal might take a number of yeare to complete 20

Growing a Designed Crystal Every Atom is as Specified! 21

We know that Non-Dispative Logic is Possible! CL does not violate basic laws of physics –Reversibility implicit in all well formed CL circuits → conservation of information –Conservation of bits (the signaling tokens) –The Billiard Ball Model (a version of CL) –Not ruled out are: Conservation of energy Conservation of momentum Conservation of angular momentum 22

The Mystery of Reversibility Aspects of reversibility are counter intuitive 40 or so years ago, 99% of all computer scientists were certain that any reversible process had to be trivial. Back then when Wolfram was asked “Why didn’t you demonstrate any reversible CA during your lecture?” he replied “Because they are all trivial!” Today he can’t believe he said that. 23

24 Reversible Logic & Garbage RL circuits can always get rid of Garbage Cleanup can be local in time & space Every function that conserves bits and information can be implemented with nothing extraneous needed or produced Almost everyone misunderstands issues as to when a reversible computer must dissipate! IO is a good example

Food and Waste Reversible CA needs sources of constants and ways to get rid of garbage 2 Methods: –Pipelines to the outside –Caches of known data (constants) --“Food” Garbage left behind -- “Waste” 25

2 nd Order Systems Natural representation of Dynamic State Systems of Reversible Difference Equations –Computational equivalent to Differential Equations –When programmed properly: Exactly reversible despite roundoff & truncation error Otherwise as accurate as ordinary difference equations Reversible Cellular Automata –Similar capabilities as compared to arbitrary CA –Does not interfere with capabilities or universality 26

The Point The simplest of particle interactions –Can be made to compute! Ballistic computing could involve very little dissipation. 27

28 Physics as Computation Particles or states remember by not decaying Particles communicate by moving Particles or states compute by interacting The Billiard Ball Model is a good example Computation is really a fundamental process in our world. We normally think of it as implemented in some technologies (I.e. Silicon ICs, Magnetic Recording). But if we ask “What are the fundamental atomic actions within computation?”, they are more than coincidentally similar to the fundamental processes in physics.

29 Bits as Particles or States Think of a bit as a particle or a state. It shouldn’t decay on its own. It needs to get from here to there. –In a wire, a bit is like a wave It needs to interact with other bits –Interaction takes place in gates In QED, which is the model that explains most of the physics (other than gravity), the fundamental processes involve a particle (electron or photon) going from here to there, and interactions, where a photon is absorbed or emitted by an electron.

30 Particles as Bits Think of a particle as a bit in a computer. It shouldn’t decay. It gets from here to there. –In a wire, a bit is like a wave It needs to compute (interact) with other bits –Interaction takes place in gates In a sense, what physics is doing is taking the present state of things and computing the future state. When nothing is happening, a particle is like a bit in memory or moving down a wire. In a QED type of interaction, we have a process that is similar to what happens in a gate.

How to do dissipationless IO A data swap of 2 equal size blocks is always a reversible process. INPUT: From a jump drive, swap input data from the jump drive with a equal size block of data from the computer. OUTPUT: At the end of the computation, swap the results into the jump drive with the original data from the computer Computer restored to original state 31

32 THE END