COSC 494/594

Unconventional Computation

Fall 2015

Instructor:

Bruce MacLennan, PhD
Phone: 974-0994
Office: Min Kao 550
Office Hours: MW 1:30–2:30, or make an appointment
Email: maclennan AT utk.edu

Classes: 11:15–12:05 MWF, MK 525

Directory of Handouts, Labs, etc.

This page: http://web.eecs.utk.edu/~mclennan/Classes/494-UC
or http://web.eecs.utk.edu/~mclennan/Classes/594-UC


Information


Description

Unconventional computation (or non-standard computation) refers to the use of non-traditional technologies and computing paradigms. As we approach the limits of Moore’s Law, progress in computation will depend on going beyond binary electronics and on exploring new paradigms and technologies for information processing and control. This new course surveys some potential approaches to post-Moore’s Law computing.

Potential topics include quantum computation and quantum annealing; optical computing; analog computing; DNA, RNA, peptide, and general molecular computation; chemical computing; reaction-diffusion systems; liquid-state machines; amorphous computing; membrane computing and P systems; single organic molecule computing; computational mechanics; collision-based computing; reversible computing; spatial computation; cellular automata; cellular neural nets; neurocomputers; organic computation; natural computation; physarum computers; emergent computation; hypercomputation; non-Turing computation.


Prerequisites

I intend this course to be accessible to all upper-division undergraduate and graduate students in computer science, computer engineering, electrical engineering, mathematics, physics, and similar disciplines. To get the most out of the course, undergraduate CS majors should have completed the 300-level required courses. Students will be expected to be familiar with linear algebra. If you have any questions about whether you should take this course, please email me. Students taking the course for graduate credit (COSC 594) will be expected to do specified additional work, including an in-class presentation.


Grading

There will be a mixture of homework, simulation experiments, and a term paper. Graduate students will be expected to do an in-class presentation. Occasional pop quizzes will count for 10% of your grade.


Text

None.


Student Learning Outcomes

Click here for pdf. 


Tentative List of Topics

  1. Introduction [slides (pdf)] [LNUC I (pdf)]
    1. Post-Moore’s law computing
    2. Embodied computing
    3. Super-Turing vs. non-Turing computation
  2. Physical information processing
    1. Energy dissipation  [LNUC II.A
    2. Thermodynamics of computation [LNUC II.B.1], [LNUC II.B.2
    3.  Reversible computing [LNUC II.C
  3. Quantum computation
    1. Mathematical preliminaries [LNUC III.A]  (see also complex number review [FFC-ch4]) 
    2. Basic concepts from quantum theory
      1. Postulates of QM [LNUC III.B.1
      2. Wave-particle duality  
      3. Uncertainty principle
      4. Dynamics (optional, will not be used in class: LNUC III.B.2–4)
      5. Superposition  [LNUC III.B.5
      6. No-cloning theorem
      7. Entanglement & EPR paradox[LNUC III.B.6–7
    3. Quantum information
      1. Qubits & secure key distribution  [LNUC III.C.1
      2. Quantum gates [LNUC III.C.2
      3. Quantum circuits 
      4. Quantum gate arrays
      5. Quantum parallelism [LNUC III.C.3-5
      6. Applications: Superdense coding and quantum teleportation [LNUC III.C.6
      7. Universal quantum gates [LNUC III.C.7
    4. Quantum algorithms
      1. Deutsch-Jozsa [LNUC III.D.1
      2. Simon [LNUC III.D.2
      3. Shor [LNUC III.D.3
      4. Grover & heuristic search [LNUC III.D.4
      5. Quantum error correction [LNUC III.D.5
    5. Abrams-Lloyd theorem [LNUC III.E
    6. Universal quantum computers (optional, will not be used in class: LNUC III.F
      1. Feynman
      2. Benioff
      3. Deutsch
    7. Physical realizations (optional, will not be used in class: LNUC III.G
    8. Quantum probability in cognition (optional, will not be used in class: LNUC III.H

  4. Molecular computation
    1. Basic concepts [LNUC IV.A
      1. DNA basics
      2. DNA manipulation
    2. Filtering models
      1. Adleman [LNUC IV.B.1
      2. Lipton [LNUC IV.B.2
      3. Test tube programming language
      4. Parallel filtering model
    3. Formal models
      1. Sticker systems
      2. Splicing systems
    4. Enzymatic computation [LNUC IV.D
    5. Universal DNA computers
    6. Chemical reaction systems
    7. Membrane systems (Paun)
    8. Summary
  5. Analog computation
    1. Computational power
    2. Computational complexity
  6. Spatial computation
    1. Cellular automata
    2. Cellular neural networks
    3. Computing with solitons etc.
    4. Reaction-diffusion computing
    5. Biocomputing
    6. Physarum machines
  7. Unstructured computation
    1. Liquid-state machines
    2. Reservoir computing
    3. Amorphous computing
    4. Blob computing
    5. Self-assembling systems
  8. Other potential topics
    1. Field computation
    2. Optical computing
    3. Carbon nanotubes
    4. Spintronics
    5. Relativistic computing
    6. Abstract geometrical computation
    7. Arithmetical hierarchy
    8. Algebraic TM computation
    9. Infinite-time computation



Assignments

  1. Homework 1 due Sept. 18 (LNUC II.E). Do 1–8. Ex. 9 is extra credit.
  2. Homework 2 due Oct. 7 (LNUC III.J). Do 8, 9, 13, 22, 26.
  3. Homework 3 due Nov. 6 (LNUC III.J - Updated!). Do 31, 33–39.
  4. Topics for presentations (dates Nov. 16–30) and term papers (due Dec. 8). Slides:
    1. Physical Neural Networks (Jon Lamont) 
    2. Cellular Neural Networks (Sangamesh Ragate)
    3. Chemical Computation (Luke Bechtel) 
    4. Reaction-diffusion Computing (Isaac Sherman)
    5. D-wave Computer (Thananon Patinyasakdikul) 
    6. P Systems (Yuping Lu) 
    7. Analog Boolean Satisfiability (Jared Smith)
    8. Oracle Turing Machines - New! 


Simulations


Online Resources


Return to MacLennan’s home page
 
Send mail to Bruce MacLennan / MacLennan@utk.edu

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Last updated:  2015-11-30.