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Process theories and diagrams Quantum processes Radboud University Nijmegen Classical and quantum interaction Application: Non-locality Process Theories and Graphical Language Aleks Kissinger Institute for Computing and Information Sciences


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Process theories and diagrams Quantum processes Classical and quantum interaction Application: Non-locality

Radboud University Nijmegen

Process Theories and Graphical Language

Aleks Kissinger

Institute for Computing and Information Sciences Radboud University Nijmegen

28th June 2016

Aleks Kissinger 28th June 2016 Process Theories and Graphical Language 1 / 106

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Process theories and diagrams Quantum processes Classical and quantum interaction Application: Non-locality

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Picturing Quantum Processes

When two systems [...] enter into temporary physical interaction due to known forces between them, [...] then they can no longer be described in the same way as before, viz. by endowing each of them with a representative of its own. I would not call that one but rather the characteristic trait of quantum mechanics, the one that enforces its entire departure from classical lines of thought. — Erwin Schr¨

  • dinger, 1935.

In quantum theory, interaction of systems is everything. Diagrams are the language of interaction.

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Picturing Quantum Processes

Q: How much of quantum theory can be understood just using diagrams and diagram transformation? A: Pretty much everything!

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Outline

Process theories and diagrams Quantum processes Classical and quantum interaction Application: Non-locality

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Processes

  • A process is anything with zero or more inputs and zero or

more outputs

  • For example, this function:

f (x, y) = x2 + y ...is a process when takes two real numbers as input, and produces a real number as output.

  • We could also write it like this:

f

R R R

  • The labels on wires are called system-types or just types

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More processes

  • Similarly, a computer programs are processes
  • For example, a program that sorts lists might look like this:

quicksort

lists lists

  • These are also perfectly good processes:

binoculars

light light light light

cooking

bacon breakfast eggs food

baby

love poo noise

  • We always think of a process as something that happens
  • E.g. ‘binoculars’ represents one use of binoculars

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Diagrams

  • We can combine simple processes to make more complicted
  • nes, described by diagrams:

g f h

A D A C B A

  • The golden rule: only connectivity matters!

k k h f

=

f g h g

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Types

  • Connections are only allowed where the types match, e.g.:

A

h g

B D

  • A

C A C

h g

B D

  • D

h

A B

D

g

A = C D

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Types and Process Theories

  • Types tell us when it makes sense to plug processes together
  • Ill-typed diagrams are undefined:

noise love

baby

poo food

quicksort

?

  • In fact, these processes don’t ever sense to plug together
  • A family of processes which do make sense together is called a

process theory

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Process Theory: Definition

Definition

A process theory consists of: (i) a collection T of system-types represented by wires, (ii) a collection P of processes represented by boxes, with inputs/outputs in T, and (iii) a means of interpreting diagrams of processes as processes:

g f h

D A C B A

A A

d

C A

∈ P

A

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Special processes: states and effects

  • Processes with no inputs are called states:

ψ

Interpret as: preparing a system in a particular configuration, where we don’t care what came before.

  • Processes with no outputs are called effects:

π

Interpret as: testing for a property π, where we don’t care what happens after.

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Special processes: numbers

  • A number is a process with no inputs or outputs, written as:

λ

  • r just:

λ

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Why are “numbers” called numbers?

  • “Numbers” can be multiplied by parallel composition:

λ

·

µ

:=

λ µ

  • This is associative:

( λ ·

µ ) · ν

=

λ µ ν

=

λ

· ( µ ·

ν )

  • ...commutative:

λ µ

=

µ λ µ

=

λ µ

=

λ

=

λ µ

  • ...and has a unit, the empty diagram:

λ

· 1 :=

λ

· =

λ

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Numbers form a commutative monoid

...so numbers always form a commutative monoid, just like most numbers we know about:

  • real numbers R
  • complex numbers C
  • probabilities [0, 1] ⊂ R
  • booleans B = {0, 1}, “·” is AND
  • ...

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When a state meets and effect

  • We have seen that we can to treat processes with no

inputs/outputs as numbers. But why do we want to?

  • Answer:

ψ π

effect state number

ψ π

test state probability

  • state + effect = number. A probability!
  • This is called the (generalised) Born rule

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Process theories in general

Q: What kinds of behaviour can we study using just diagrams, and nothing else? A: (Non-)separability

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Separability of processes

  • A process f ◦-separates if there exists a state φ and effect π

such that:

f

=

φ π

  • If we apply this process to any other state, we always

(basically) get φ:

ψ

f

π ψ φ

= =

π ψ φ

= λ

φ

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Trivial process theories

Hence: all processes ◦-separate = ⇒ nothing ever happens!

Definition

A process theory is called trivial if all processes ◦-separate.

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Separable states

  • States can be on a single system, two systems, or many

systems:

ψ

ψ ψ ...

  • A state ψ on two systems is ⊗-separable if there exist ψ1, ψ2

such that: ψ =

ψ1 ψ2

  • Intuitively: the properties of the system on the left are

independent from those on the right

  • Classically, we expect all states to ⊗-separate

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Characterising non-separability

  • ...which is why non-separable states are way more interesting!
  • But, how do we know we’ve found one?
  • i.e. that there do not exist states ψ1, ψ2 such that:

ψ =

ψ1 ψ2

  • Problem: Showing that something doesn’t exist can be hard.

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Characterising non-separability

Solution: Replace a negative property with a postive one:

Definition

A state ψ is called cup-state if there exists an effect φ, called a cap-effect, such that: φ ψ = ψ φ =

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Cup-states

  • By introducing some clever notation:

:= ψ := φ

  • Then these equations:

φ ψ = ψ φ =

  • ...look like this:

= =

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Yank the wire!

= =

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A no-go theorem for separability

Theorem

If a process theory (i) has cup-states for every type and (ii) every state separates, then it is trivial.

  • Proof. Suppose a cup-state separates:

=

ψ1 ψ2

Then for any f :

f

=

f

=

ψ2 ψ1

f

=

ψ1

f

ψ2

=:

φ π

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Transpose

f

A B

∼ =

← →

f

B A

=: f T

f

=

f

i.e. (f T)T = f

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Tranpose = rotation

A bit of a deformation:

f

  • f

allows some clever notation: f := f

= = = =

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Tranpose = rotation

Specialised to states: ψ := ψ ψ = Aleks Bob Aleks Bob ψ as soon as Aleks obtains ψ Bob’s system will be in state ψ

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State/effect correspondence

states of system A ∼ = effects for correlated system B ψ ψ transpose But what about... states of system A ∼ = effects for system A ψ ψ adjoint

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Adjoints

ψ

→ ψ state ψ testing for ψ Extends from states/effects to all processes:

B A

f

→ f

A B ψ f = φ = ⇒ ψ φ f =

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Normalised states and isometries

  • Adjoints increase expressiveness, for instance can say when ψ

is normalised: ψ ψ =

  • U is an isometry:

U U =

A A A B

  • ...and unitary, self-adjoint, positive, etc.

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Conjugates

If we:

...we get horizontal reflection.The conjugate: f → f := f

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4 kinds of box

f f f f

adjoint adjoint conjugate conjugate transpose A A B B A A B B

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Quantum teleportation: take 1

Can we fill in ‘?’ to get this? = Bob Bob ψ Aleks Aleks ψ

? ?

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Quantum teleportation: take 1

Here’s a simple solution: = Bob Bob ψ Aleks Aleks ψ Problem: ‘cap’ can’t be performed deterministically

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Quantum teleportation: take 1

= Ui Bob Bob ψ Aleks Aleks ψ

error Bob’s problem now!

Ui

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Quantum teleportation: take 1

Solution: Bob fixes the error. Ui ψ Ui

error fix

ψ =

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Quantum teleportation: take 1

ψ Ui Aleks Bob Ui ψ Ui Aleks Bob Ui Aleks Bob

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Hilbert space

The starting point for quantum theory is the process theory of linear maps, which has:

1 systems: Hilbert spaces 2 processes: complex linear maps

...in particular, numbers are complex numbers.

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Hilbert space

Looking at the ‘Born rule’ for linear maps, we have a problem: ψ φ effect state complex number= probability!

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Doubling

Solution: multiply by the conjugate: ψ φ

  • ψ

φ ψ φ Then, for normalised ψ, φ: 0 ≤ ψ φ ψ φ ≤ 1 (i.e. the ‘usual’ Born rule: φ|ψφ|ψ = |φ|ψ|2)

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Doubling

New problem: We lost this:

ψ π

test state probability ...which was the basis of our interpretation for states, effects, and numbers.

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Doubling

Solution: Make a new process theory with doubling ‘baked in’: ψ ψ :=

  • ψ

φ φ :=

  • φ

Then: test state probability ψ ψ φ φ := :=

  • ψ
  • φ

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Doubling

The new process theory has doubled systems H := H ⊗ H: := and processes: double   f   := =

  • f

f f

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Doubling preserves diagrams

f g h = k l = ⇒

  • g
  • h
  • f

=

  • k
  • l

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...but kills global phases

λ λ

= (i.e. λ = eiα) = ⇒

double   λ f   = f

λ λ

f = f f =

  • f

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Discarding

Doubling also lets us do something we couldn’t do before: throw stuff away!

  • ψ

How? Like this: :=

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Discarding

For normalised ψ, the two copies annihilate:

  • ψ

= ψ ψ = ψ ψ =

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Quantum maps

Definition

The process theory of quantum maps has as types (doubled) Hilbert spaces H and as processes:

  • f

. . .

  • . . .

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Purification

Theorem

All quantum maps are of the form: f f := f f

  • f

= for some linear map f .

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Purification

  • Proof. Pretty much by construction:
  • f
  • g
  • h

  • g
  • f
  • h

then note that:

... :=

  • H1 ⊗ . . . ⊗

Hn

  • H1
  • H2
  • Hn

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Causality

A quantum map is called causal if: Φ = If we discard the output of a process, it doesn’t matter which process happened. causal ⇐ ⇒ deterministically physically realisable

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Consequence: no cap effect ☹

Consequence: there is a unique causal effect, discarding: e = Hence ‘deterministic quantum teleportation’ must fail: Aleks Bob Bob Aleks = ρ ρ

?

Aleks ρ

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Consequence: no signalling ☺

ρ Claire Bob Aleks Ψ Φ ρ Claire Bob Aleks Ψ Φ Aleks Φ

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Stinespring’s theorem ☺

Lemma

Pure quantum maps U are causal if and only if they are isometries.

  • Proof. Unfold the causality equation:

U U = and bend the wire: U U = = U U =

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Stinespring’s theorem ☺

Theorem (Stinespring)

For any causal quantum map Φ, there exists an isometry f such that: Φ =

  • f
  • Proof. Purify Φ, then apply the lemma to

f .

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Double vs. single wires

   quantum :=    =   classical :=  

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Classical values

i

:= ‘providing classical value i’

i

:= ‘testing for classical value i’

i j

=

  • 1

if i = j if i = j (⇒ ONB)

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Classical states

General state of a classical system:

p

:=

i

pi

i

← probability distributions Hence:

i

← point distributions

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Copy and delete

Unlike quantum states, classical values can be copied:

i

=

i i

and deleted:

j

=

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Copy and delete

These satisfy some equations you would expect: = = = =

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Other classical maps

:=

i i i i

:=

i i

:=

i i i i

:=

i i

:=

i i i

:=

i i i

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...satisfying lots of equations

= = = = = = = ... When does it end???

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Spiders

All of these are special cases of spiders:

m n

... ... :=

i i i i i i

  • i

n m

... ...

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Spiders

The only equation you need to remember is this one: ... ...

...

= ... ... ... ... When spiders meet, they fuse together.

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Spider reasoning

= For example: = =

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Spider reasoning ⇒ string diagram reasoning

= = =

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How do we recognise spiders?

Suppose we have something that ‘behaves like’ a spider: Do we know it is one?

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Spiders = ‘diagrammatic ONBs’

Yes!         

m n

... ...         

m,n

← →

  • i
  • i

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Classical and quantum interaction

Classical values can be encoded as quantum states, via doubling: ::

i

i

:=

i i

This is our first classical-quantum map, encode. It’s a copy-spider in disguise:

i

:=

i i i

=

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Measuring quantum states

The adjoint of encode is measure: ρ

quantum state probability distribution

This represents measuring w.r.t.

  • i
  • i

...where probabilities come from the Born rule: P(i|ρ) := ρ

i

= ρ

i

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Classical-quantum maps

Definition

The process theory of cq-maps has as processes diagrams of quantum maps and encode/decode: Φ

. . .

  • . . .

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Quantum processes

Causality generalises to cq-maps: = Φ quantum processes := causal cq-maps

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Special case: classical processes

Classical processes are quantum processes with no quantum inputs/outputs: f := Φ These correspond exactly to stochastic maps. Positivity comes from doubling, and normalisation from causality:

p

= f =

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Special case: quantum measurements

A measurement is any quantum process from a quantum system to a classical one: Φ

∼ =

← → POVMs Special case: ONB-measurement :=

  • U

unitary

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Special case: controlled-operations

A quantum process with a classical input is a controlled

  • peration:

Φ

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Special case: controlled-operations

A controlled isometry furthermore satisfies:

  • U

=

  • U

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Special case: controlled-operations

Suppose we can use a single U to build a controlled isometry:

  • U

...and an ONB measurement:

  • U

unitary measurement

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Quantum teleportation: take 2

...then teleportation is a snap! ρ Aleks Bob

? ?

ρ Aleks Bob

  • U

?

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Quantum spiders

Doubling a classical spider gives a quantum spider: ... ... := double

  • ...

...

  • =

... ...

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Quantum spiders

Since doubling preserves diagrams, these fuse when they meet: ... ... ... ...

...

= ... ...

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Quantum meets classical

Q: What happens if a quantum spider meets a classical spider, via measure or encode?

... ... ... ...

A: Bastard spiders!

... ... ... ... =: ... ... ... ... ... ... ... ... =

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Bastard spider fusion

... ...

...

= ... ... ... ...

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Phase states

1

α

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Phase spiders

α

... ... :=

α

... ...

α

... =

β

... ... ... ...

α+β

... ...

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Example: phase gates

phase gate :=

α β α

=

α+β

  • α

α

=

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Complementary bases

1 1

π

= =

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Complementary bases

        

m n

... ...         

m,n

← →

  • i
  • i

        

m n

... ...         

m,n

← →

  • i
  • i

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Complementarity

=

Interpretation: (encode in ) THEN (measure in ) = (no data flow)

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Consequence: Stern-Gerlach

N S

S N

S N

blocked!

=

X-measurement 1st Z-measurement 2nd Z-measurement

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Strong complementarity

= ... ... = ... ... Interpretation: Mathematically: Fourier transform. Operationally: ???

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Consequences

  • strong complementarity =

⇒ complementarity

  • ONB of

forms a subgroup of phase states, e.g.

  • =

,

1

=

π

  • α
  • α∈[0,2π)
  • GHZ/Mermin non-locality

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The setup

P

1 3 2

Z Y Z Y Z Y

P

1 3 2

Z Y Z Y Z Y Z Y

1 ZZZ 2 ZYY 3 YZY 4 YYZ

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A locally realistic model

1st system

  • zA

yA 2nd system

  • zB

yB 3rd system

  • zC

yC

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A locally realistic model

ZZZ

yB

i

yA

i

zC

i

yC

i

zA

i

zB

i

zA

i

zB

i

zC

i

yA

i

yB

i

yC

i

ZYY YZY YYZ ZZZ

zB

i

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A quantum model

α γ β GHZ state measurements

Z-measurement := Y -measurement :=

π 2

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A quantum model

π 2 π 2 π 2 π 2 π 2 π 2

YYZ ZYY YZY ZZZ

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Deriving the contradiction

We prove the correlations from the quantum model are inconsistent with any locally realistic one, by computing: parity := ...

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Deriving the contradiction

zA

i

yA

i

yB

i

zB

i

zC

i

yC

i

zA

i

y

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Deriving the contradiction

π 2 π 2 π 2 π 2 π 2 π 2 Aleks Kissinger 28th June 2016 Process Theories and Graphical Language 104 / 106

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Deriving the contradiction

=

1

= ⇒ Quantum theory is non-local!

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Applications: the expanded menu

  • foundations
  • strong complementarity ⇒ GHZ/Mermin non-locality
  • phase groups distinguish Spekkens’ toy theory and stabilizer

QM

  • quantum computation
  • graphical calculus ⇒ circuit/MBQC transformation
  • complementarity ⇔ quantum oracles
  • strong complementarity ⇒ graphical HSP
  • quantum resource theories
  • resource theories := ‘re-branded’ process theories
  • graphical characterisations for convertibility relations (purity,

entanglement)

  • 3 qubit SLOCC-classification ⇒ two kinds of ‘spider-like

arachnids’

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