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outline.txt
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function conventional view is extensional
f (5) = 7; it just is
In CS, we have this operational view
f(5) -> suc (suc 5) -> suc 6 -> 7
or
f(5) -> 5! - 113 -> (5 * 4!) - 113 -> ... -> 120 - 113 -> 7
An equivalence is given using the extensional view of functions
A path is given using the operational view of functions
Univalence says these two views are equivalent
--
Obvious: computations are physical processes bounded in space, time,
and energy.
Foundational model of computation must not violate fundamental
physical limits/laws. Turing understood that: quotes from
Turing. Earlier Boole understood that: quote from Bool. Girard
understands that: quote from Girard. In some sense we all understand
that and we can all agree about that. But of course when we design
abstractions we can disagree. Which is a good abstraction of a human:
several pictures. But someone might step back and ask: why bother?
"business as usual seems to work". Aaronson's puzzle. Something is
really really really wrong. The foundations of some major disciplines,
all successful, all checked, and double checked, and verified
empirically, are deeply incompatible.
Proposal: Foundational model of computation should be time symmetric,
i.e., based on isomophisms, equivalences, injective functions,
etc. Forces computation to respect resources, subsumes in some sense
liner logic; compatible with quantum physics, quantum information,
quantitative information flow, differential privacy, no duplication,
no deletion, and of course compatible with the spirit of HoTT, with
proofs being represented as reversible deformations of topological
spaces. This connects with a fascinating approach to quantum
computing, called topological quantum computing, that was pioneered by
faculty at IU and is now at the heart of Microsoft's approach to QC.
Details: Information Effects; Rig Groupoids; may be Fractional Types
Future work, open problems, etc:
--
Physics => information as resource; no focus on information
processing; write physical processes in a way that is not obviously
computable
CS => information-processing; but write algorithms and computations in
a way that does not obviously preserve the information resource
Quantum computing: where these two meet and CLASH
Aaronson three claims:
- if foundations of physics wrong, we can fix by making it
computational
- if foundations of cs wrong, we should revisit and embrace extended
CT-thesis
--
Foundations of QM <= understanding information flow
--
Featherweight HoTT (or something cute)
A personal journey first about HoTT
Research in PL: man-made; beauty in studying nature;
computing in nature and what can we learn from it
Girard quote etc.
Conservation of information
Finite communicable evidence
Aaronson three claims:
- if foundations of physics wrong, we can fix by making it
computational
- if foundations of cs wrong, we should revisit and embrace extended
CT-thesis
--
Featherweight HoTT
equivalences (iso) -- two levels at least for Pi
identity types
univalence
HITs
--
A Confluence of Ideas
Quantum Computing
Homotopy Type Theory
Is 3 = 3
Is 2 + 1 = 7 - 4
N = N x N
E = M C^2
Nobel prize to explain the process
When I hear process, I hear computation
So when we see = let's think computation back and forth
Sometimes trivial; sometimes kaboom
;;
Observational Equivalence Story ???
;;
computing: device + data
used to be one device (centralized) and clean small data
Data growing: dirty, inconsistent, evolving, huge, …
Devices: getting smaller, more numerous, more distributed, more embedded
Slides for talk :-)
--
MFPS: let's say Math foundations of computations
What kind of math should be use for semantics of computations
church: set theory; functions
long story; cpos; full abstraction for pcf; sequential; a+b not the
same as b+a; linear logic; resources; physics
two principles: conservation of energy; finite communicable resources;
leads to monoidal categories; HoTT; weak equivalences; etc.