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Interference, Dependence and Bells Theorem Samson Abramsky - - PowerPoint PPT Presentation

Interference, Dependence and Bells Theorem Samson Abramsky Department of Computer Science, University of Oxford Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bells Theorem 1 / 18 Our


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Interference, Dependence and Bell’s Theorem

Samson Abramsky

Department of Computer Science, University of Oxford

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 1 / 18

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Our Themes

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 2 / 18

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Our Themes

Interference and dependence are closely related concepts, the first being the observational phenomenon connected to the second. Interference refers to the behaviour of some parts of a system influencing the behaviour of another part of the system. Dependence specifies the relation which determines those parts of the system that influence the computation of another part of the system.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 2 / 18

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Our Themes

Interference and dependence are closely related concepts, the first being the observational phenomenon connected to the second. Interference refers to the behaviour of some parts of a system influencing the behaviour of another part of the system. Dependence specifies the relation which determines those parts of the system that influence the computation of another part of the system. This workshop will bring together researchers working on interference and dependence from both the modelling and programming research communities to discuss connections and challenges.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 2 / 18

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Our Themes

Interference and dependence are closely related concepts, the first being the observational phenomenon connected to the second. Interference refers to the behaviour of some parts of a system influencing the behaviour of another part of the system. Dependence specifies the relation which determines those parts of the system that influence the computation of another part of the system. This workshop will bring together researchers working on interference and dependence from both the modelling and programming research communities to discuss connections and challenges. I want to make the following points:

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 2 / 18

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Our Themes

Interference and dependence are closely related concepts, the first being the observational phenomenon connected to the second. Interference refers to the behaviour of some parts of a system influencing the behaviour of another part of the system. Dependence specifies the relation which determines those parts of the system that influence the computation of another part of the system. This workshop will bring together researchers working on interference and dependence from both the modelling and programming research communities to discuss connections and challenges. I want to make the following points: Interference and dependence are not only pervasive in Computer Science, but throughout the sciences.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 2 / 18

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Our Themes

Interference and dependence are closely related concepts, the first being the observational phenomenon connected to the second. Interference refers to the behaviour of some parts of a system influencing the behaviour of another part of the system. Dependence specifies the relation which determines those parts of the system that influence the computation of another part of the system. This workshop will bring together researchers working on interference and dependence from both the modelling and programming research communities to discuss connections and challenges. I want to make the following points: Interference and dependence are not only pervasive in Computer Science, but throughout the sciences. In fact, they play a key rˆ

  • le in fundamental results such as Bell’s theorem in

the foundations of quantum mechanics — seminal for subsequent developments in quantum information and computation.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 2 / 18

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Our Themes

Interference and dependence are closely related concepts, the first being the observational phenomenon connected to the second. Interference refers to the behaviour of some parts of a system influencing the behaviour of another part of the system. Dependence specifies the relation which determines those parts of the system that influence the computation of another part of the system. This workshop will bring together researchers working on interference and dependence from both the modelling and programming research communities to discuss connections and challenges. I want to make the following points: Interference and dependence are not only pervasive in Computer Science, but throughout the sciences. In fact, they play a key rˆ

  • le in fundamental results such as Bell’s theorem in

the foundations of quantum mechanics — seminal for subsequent developments in quantum information and computation. There is a fascinating interplay between logical structure, probability,

  • bservational ideas — with implications for the nature of physical reality!

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 2 / 18

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The Basic Scenario

a b c d · a b c d · Alice Bob

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 3 / 18

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The Basic Scenario

a b c d · a b c d · Alice Bob Think e.g. of making observations at different nodes of a network.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 3 / 18

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The Basic Scenario

a b c d · a b c d · Alice Bob Think e.g. of making observations at different nodes of a network. Different quantities which can be measured.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 3 / 18

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The Basic Scenario

a b c d · a b c d · Alice Bob Think e.g. of making observations at different nodes of a network. Different quantities which can be measured. Observations: tuples of values. Repeated observations give sets of such tuples.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 3 / 18

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The Basic Scenario

a b c d · a b c d · Alice Bob Think e.g. of making observations at different nodes of a network. Different quantities which can be measured. Observations: tuples of values. Repeated observations give sets of such tuples. Can we tell from this observational history if there is interference/dependence between different parts of the system?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 3 / 18

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The Basic Scenario

a b c d · a b c d · Alice Bob Think e.g. of making observations at different nodes of a network. Different quantities which can be measured. Observations: tuples of values. Repeated observations give sets of such tuples. Can we tell from this observational history if there is interference/dependence between different parts of the system?

  • Cf. ‘measurement-based verification’.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 3 / 18

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A Probabilistic Model Of An Experiment

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 4 / 18

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A Probabilistic Model Of An Experiment

A B (0, 0) (1, 0) (0, 1) (1, 1) a b 1/2 1/2 a′ b 3/8 1/8 1/8 3/8 a b′ 3/8 1/8 1/8 3/8 a′ b′ 1/8 3/8 3/8 1/8

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 4 / 18

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A Probabilistic Model Of An Experiment

A B (0, 0) (1, 0) (0, 1) (1, 1) a b 1/2 1/2 a′ b 3/8 1/8 1/8 3/8 a b′ 3/8 1/8 1/8 3/8 a′ b′ 1/8 3/8 3/8 1/8 Is this ‘reasonable’ or not?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 4 / 18

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A Probabilistic Model Of An Experiment

A B (0, 0) (1, 0) (0, 1) (1, 1) a b 1/2 1/2 a′ b 3/8 1/8 1/8 3/8 a b′ 3/8 1/8 1/8 3/8 a′ b′ 1/8 3/8 3/8 1/8 Is this ‘reasonable’ or not? How can we tell?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 4 / 18

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A Probabilistic Model Of An Experiment

A B (0, 0) (1, 0) (0, 1) (1, 1) a b 1/2 1/2 a′ b 3/8 1/8 1/8 3/8 a b′ 3/8 1/8 1/8 3/8 a′ b′ 1/8 3/8 3/8 1/8 Is this ‘reasonable’ or not? How can we tell? What does reasonable mean??

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 4 / 18

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A Simple Observation

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Simple Observation

Suppose we have propositional formulas φ1, . . . , φN

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Simple Observation

Suppose we have propositional formulas φ1, . . . , φN Suppose further we can assign a probability pi to each φi.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Simple Observation

Suppose we have propositional formulas φ1, . . . , φN Suppose further we can assign a probability pi to each φi. (Story: perform experiment to test the variables in φi; pi is the relative frequency

  • f the trials satisfying φi.)

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Simple Observation

Suppose we have propositional formulas φ1, . . . , φN Suppose further we can assign a probability pi to each φi. (Story: perform experiment to test the variables in φi; pi is the relative frequency

  • f the trials satisfying φi.)

Let P be the probability of Φ :=

i φi.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Simple Observation

Suppose we have propositional formulas φ1, . . . , φN Suppose further we can assign a probability pi to each φi. (Story: perform experiment to test the variables in φi; pi is the relative frequency

  • f the trials satisfying φi.)

Let P be the probability of Φ :=

i φi.

Using elementary probability theory, we can calculate: 1 − P = Prob(¬Φ) = Prob(

  • i

¬φi) ≤

  • i

Prob(¬φi) =

  • i

(1 − pi) = N −

  • i

pi.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Simple Observation

Suppose we have propositional formulas φ1, . . . , φN Suppose further we can assign a probability pi to each φi. (Story: perform experiment to test the variables in φi; pi is the relative frequency

  • f the trials satisfying φi.)

Let P be the probability of Φ :=

i φi.

Using elementary probability theory, we can calculate: 1 − P = Prob(¬Φ) = Prob(

  • i

¬φi) ≤

  • i

Prob(¬φi) =

  • i

(1 − pi) = N −

  • i

pi. Tidying this up yields

i pi ≤ N − 1 + P.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Simple Observation

Suppose we have propositional formulas φ1, . . . , φN Suppose further we can assign a probability pi to each φi. (Story: perform experiment to test the variables in φi; pi is the relative frequency

  • f the trials satisfying φi.)

Let P be the probability of Φ :=

i φi.

Using elementary probability theory, we can calculate: 1 − P = Prob(¬Φ) = Prob(

  • i

¬φi) ≤

  • i

Prob(¬φi) =

  • i

(1 − pi) = N −

  • i

pi. Tidying this up yields

i pi ≤ N − 1 + P.

Now suppose that the formulas φi are jointly contradictory; i.e. Φ is

  • unsatisfiable. Clearly, we must then have P = 0. Hence we obtain the inequality
  • i

pi ≤ N − 1.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 5 / 18

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A Curious Observation

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 6 / 18

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A Curious Observation

Quantum Mechanics tells us that we can find propositions φi describing outcomes

  • f certain measurements, which not only can but have been performed.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 6 / 18

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A Curious Observation

Quantum Mechanics tells us that we can find propositions φi describing outcomes

  • f certain measurements, which not only can but have been performed.

From the observed statistics of these experiments, we have very highly confirmed probabilities pi.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 6 / 18

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A Curious Observation

Quantum Mechanics tells us that we can find propositions φi describing outcomes

  • f certain measurements, which not only can but have been performed.

From the observed statistics of these experiments, we have very highly confirmed probabilities pi. These propositions are easily seen to be jointly contradictory.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 6 / 18

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A Curious Observation

Quantum Mechanics tells us that we can find propositions φi describing outcomes

  • f certain measurements, which not only can but have been performed.

From the observed statistics of these experiments, we have very highly confirmed probabilities pi. These propositions are easily seen to be jointly contradictory. Nevertheless, the inequality

  • i

pi ≤ N − 1 is observed to be strongly violated. In fact, the maximum violation of 1 can be achieved.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 6 / 18

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A Curious Observation

Quantum Mechanics tells us that we can find propositions φi describing outcomes

  • f certain measurements, which not only can but have been performed.

From the observed statistics of these experiments, we have very highly confirmed probabilities pi. These propositions are easily seen to be jointly contradictory. Nevertheless, the inequality

  • i

pi ≤ N − 1 is observed to be strongly violated. In fact, the maximum violation of 1 can be achieved. How can this be?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 6 / 18

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A Curious Observation

Quantum Mechanics tells us that we can find propositions φi describing outcomes

  • f certain measurements, which not only can but have been performed.

From the observed statistics of these experiments, we have very highly confirmed probabilities pi. These propositions are easily seen to be jointly contradictory. Nevertheless, the inequality

  • i

pi ≤ N − 1 is observed to be strongly violated. In fact, the maximum violation of 1 can be achieved. How can this be? We shall call an inequality

N

  • i=1

p(ϕi) ≤ N − 1 where

i ϕi is unsatisfiable a logical Bell inequality.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 6 / 18

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The Stern-Gerlach Experiment

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 7 / 18

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A crash course in qubits

  • Samson Abramsky (Department of Computer Science, University of Oxford)

Interference, Dependence and Bell’s Theorem 8 / 18

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A crash course in qubits

Classical bit register: state is 0 or 1.

  • Samson Abramsky (Department of Computer Science, University of Oxford)

Interference, Dependence and Bell’s Theorem 8 / 18

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A crash course in qubits

Classical bit register: state is 0 or 1. Qubit: complex linear combination α0|0 + α1|1, |α0|2 + |α1|2 = 1.

  • Samson Abramsky (Department of Computer Science, University of Oxford)

Interference, Dependence and Bell’s Theorem 8 / 18

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A crash course in qubits

Classical bit register: state is 0 or 1. Qubit: complex linear combination α0|0 + α1|1, |α0|2 + |α1|2 = 1. Measurement (in |0, |1 basis): get |i with probability |αi|2.

  • Samson Abramsky (Department of Computer Science, University of Oxford)

Interference, Dependence and Bell’s Theorem 8 / 18

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A crash course in qubits

Classical bit register: state is 0 or 1. Qubit: complex linear combination α0|0 + α1|1, |α0|2 + |α1|2 = 1. Measurement (in |0, |1 basis): get |i with probability |αi|2. Geometric picture: the Bloch sphere

  • 1

1

  • i

i

N S P x z (a) (b) y P’ θ ϕ

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 8 / 18

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SLIDE 41

A crash course in qubits

Classical bit register: state is 0 or 1. Qubit: complex linear combination α0|0 + α1|1, |α0|2 + |α1|2 = 1. Measurement (in |0, |1 basis): get |i with probability |αi|2. Geometric picture: the Bloch sphere

  • 1

1

  • i

i

N S P x z (a) (b) y P’ θ ϕ

Things get interesting with n-qubit registers

  • i

αi|i, i ∈ {0, 1}n.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 8 / 18

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Quantum Entanglement

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 9 / 18

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SLIDE 43

Quantum Entanglement

Bell state: |00 + |11 EPR state: |01 + |10

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 9 / 18

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Quantum Entanglement

Bell state: |00 + |11 EPR state: |01 + |10 Compound systems are represented by tensor product: H1 ⊗ H2. Typical element:

  • i

λi · φi ⊗ ψi Superposition encodes correlation.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 9 / 18

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SLIDE 45

Quantum Entanglement

Bell state: |00 + |11 EPR state: |01 + |10 Compound systems are represented by tensor product: H1 ⊗ H2. Typical element:

  • i

λi · φi ⊗ ψi Superposition encodes correlation. Einstein’s ‘spooky action at a distance’. Even if the particles are spatially separated, measuring one has an effect on the state of the other.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 9 / 18

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Quantum Entanglement

Bell state: |00 + |11 EPR state: |01 + |10 Compound systems are represented by tensor product: H1 ⊗ H2. Typical element:

  • i

λi · φi ⊗ ψi Superposition encodes correlation. Einstein’s ‘spooky action at a distance’. Even if the particles are spatially separated, measuring one has an effect on the state of the other. Bell’s theorem: QM is essentially non-local.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 9 / 18

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The Bell Model

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 10 / 18

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SLIDE 48

The Bell Model

(0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1/2 1/2 (a, b′) 3/8 1/8 1/8 3/8 (a′, b) 3/8 1/8 1/8 3/8 (a′, b′) 1/8 3/8 3/8 1/8

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 10 / 18

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SLIDE 49

The Bell Model

(0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1/2 1/2 (a, b′) 3/8 1/8 1/8 3/8 (a′, b) 3/8 1/8 1/8 3/8 (a′, b′) 1/8 3/8 3/8 1/8 Generated by a Bell state |00 + |11 √ 2 , subjected to measurements in the XY -plane, at relative angle π/3.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 10 / 18

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SLIDE 50

Logical analysis of the Bell table

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 11 / 18

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SLIDE 51

Logical analysis of the Bell table

(0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1/2 1/2 (a, b′) 3/8 1/8 1/8 3/8 (a′, b) 3/8 1/8 1/8 3/8 (a′, b′) 1/8 3/8 3/8 1/8

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 11 / 18

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Logical analysis of the Bell table

(0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1/2 1/2 (a, b′) 3/8 1/8 1/8 3/8 (a′, b) 3/8 1/8 1/8 3/8 (a′, b′) 1/8 3/8 3/8 1/8 If we read 0 as true and 1 as false, the highlighted positions in each row of the table are represented by the following propositions: ϕ1 = a ∧ b ∨ ¬a ∧ ¬b = a ↔ b ϕ2 = a ∧ b′ ∨ ¬a ∧ ¬b′ = a ↔ b′ ϕ3 = a′ ∧ b ∨ ¬a′ ∧ ¬b = a′ ↔ b ϕ4 = ¬a′ ∧ b′ ∨ a′ ∧ ¬b′ = a′ ⊕ b′.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 11 / 18

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SLIDE 53

Logical analysis of the Bell table

(0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1/2 1/2 (a, b′) 3/8 1/8 1/8 3/8 (a′, b) 3/8 1/8 1/8 3/8 (a′, b′) 1/8 3/8 3/8 1/8 If we read 0 as true and 1 as false, the highlighted positions in each row of the table are represented by the following propositions: ϕ1 = a ∧ b ∨ ¬a ∧ ¬b = a ↔ b ϕ2 = a ∧ b′ ∨ ¬a ∧ ¬b′ = a ↔ b′ ϕ3 = a′ ∧ b ∨ ¬a′ ∧ ¬b = a′ ↔ b ϕ4 = ¬a′ ∧ b′ ∨ a′ ∧ ¬b′ = a′ ⊕ b′. These propositions are easily seen to be contradictory.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 11 / 18

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Logical analysis of the Bell table

(0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1/2 1/2 (a, b′) 3/8 1/8 1/8 3/8 (a′, b) 3/8 1/8 1/8 3/8 (a′, b′) 1/8 3/8 3/8 1/8 If we read 0 as true and 1 as false, the highlighted positions in each row of the table are represented by the following propositions: ϕ1 = a ∧ b ∨ ¬a ∧ ¬b = a ↔ b ϕ2 = a ∧ b′ ∨ ¬a ∧ ¬b′ = a ↔ b′ ϕ3 = a′ ∧ b ∨ ¬a′ ∧ ¬b = a′ ↔ b ϕ4 = ¬a′ ∧ b′ ∨ a′ ∧ ¬b′ = a′ ⊕ b′. These propositions are easily seen to be contradictory. The violation of the logical Bell inequality is 1/4.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 11 / 18

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SLIDE 55

Example: the Hardy model

The support of the Hardy model: (0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1 1 1 1 (a′, b) 1 1 1 (a, b′) 1 1 1 (a′, b′) 1 1 1

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 12 / 18

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SLIDE 56

Example: the Hardy model

The support of the Hardy model: (0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1 1 1 1 (a′, b) 1 1 1 (a, b′) 1 1 1 (a′, b′) 1 1 1 If we interpret outcome 0 as true and 1 as false, then the following formulas all have positive probability: a ∧ b, ¬(a ∧ b′), ¬(a′ ∧ b), a′ ∨ b′.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 12 / 18

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SLIDE 57

Example: the Hardy model

The support of the Hardy model: (0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1 1 1 1 (a′, b) 1 1 1 (a, b′) 1 1 1 (a′, b′) 1 1 1 If we interpret outcome 0 as true and 1 as false, then the following formulas all have positive probability: a ∧ b, ¬(a ∧ b′), ¬(a′ ∧ b), a′ ∨ b′. However, these formulas are not simultaneously satisfiable.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 12 / 18

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SLIDE 58

Example: the Hardy model

The support of the Hardy model: (0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1 1 1 1 (a′, b) 1 1 1 (a, b′) 1 1 1 (a′, b′) 1 1 1 If we interpret outcome 0 as true and 1 as false, then the following formulas all have positive probability: a ∧ b, ¬(a ∧ b′), ¬(a′ ∧ b), a′ ∨ b′. However, these formulas are not simultaneously satisfiable. In this model, p2 = p3 = p4 = 1.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 12 / 18

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SLIDE 59

Example: the Hardy model

The support of the Hardy model: (0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1 1 1 1 (a′, b) 1 1 1 (a, b′) 1 1 1 (a′, b′) 1 1 1 If we interpret outcome 0 as true and 1 as false, then the following formulas all have positive probability: a ∧ b, ¬(a ∧ b′), ¬(a′ ∧ b), a′ ∨ b′. However, these formulas are not simultaneously satisfiable. In this model, p2 = p3 = p4 = 1. Hence the Hardy model achieves a violation of p1 = Prob(a ∧ b) for the logical Bell inequality.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 12 / 18

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SLIDE 60

Example: the Hardy model

The support of the Hardy model: (0, 0) (1, 0) (0, 1) (1, 1) (a, b) 1 1 1 1 (a′, b) 1 1 1 (a, b′) 1 1 1 (a′, b′) 1 1 1 If we interpret outcome 0 as true and 1 as false, then the following formulas all have positive probability: a ∧ b, ¬(a ∧ b′), ¬(a′ ∧ b), a′ ∨ b′. However, these formulas are not simultaneously satisfiable. In this model, p2 = p3 = p4 = 1. Hence the Hardy model achieves a violation of p1 = Prob(a ∧ b) for the logical Bell inequality.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 12 / 18

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SLIDE 61

What is going on?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 62

What is going on?

What is the invalid step in our ‘simple argument’?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 63

What is going on?

What is the invalid step in our ‘simple argument’? Or is there a direct conflict between logic and experience?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 64

What is going on?

What is the invalid step in our ‘simple argument’? Or is there a direct conflict between logic and experience? The argument we gave for the logical Bell inequality is valid as long as there is a joint distribution defined on all the variables which yields the empirically

  • bserved probabilities as marginals.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 65

What is going on?

What is the invalid step in our ‘simple argument’? Or is there a direct conflict between logic and experience? The argument we gave for the logical Bell inequality is valid as long as there is a joint distribution defined on all the variables which yields the empirically

  • bserved probabilities as marginals.

This is a canonical form of ‘(local) hidden variable theory’. That is, global assignments of values to each of the measurement variables, independently of which other variables it is measured with.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 66

What is going on?

What is the invalid step in our ‘simple argument’? Or is there a direct conflict between logic and experience? The argument we gave for the logical Bell inequality is valid as long as there is a joint distribution defined on all the variables which yields the empirically

  • bserved probabilities as marginals.

This is a canonical form of ‘(local) hidden variable theory’. That is, global assignments of values to each of the measurement variables, independently of which other variables it is measured with. Violation of the Bell inequalities means that no such assignment can exist.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 67

What is going on?

What is the invalid step in our ‘simple argument’? Or is there a direct conflict between logic and experience? The argument we gave for the logical Bell inequality is valid as long as there is a joint distribution defined on all the variables which yields the empirically

  • bserved probabilities as marginals.

This is a canonical form of ‘(local) hidden variable theory’. That is, global assignments of values to each of the measurement variables, independently of which other variables it is measured with. Violation of the Bell inequalities means that no such assignment can exist. Moral: observable values have to be taken as inherently contextual: dependent

  • n the measurement context.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 68

What is going on?

What is the invalid step in our ‘simple argument’? Or is there a direct conflict between logic and experience? The argument we gave for the logical Bell inequality is valid as long as there is a joint distribution defined on all the variables which yields the empirically

  • bserved probabilities as marginals.

This is a canonical form of ‘(local) hidden variable theory’. That is, global assignments of values to each of the measurement variables, independently of which other variables it is measured with. Violation of the Bell inequalities means that no such assignment can exist. Moral: observable values have to be taken as inherently contextual: dependent

  • n the measurement context.

This is ‘physical reality’ we are talking about!

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 13 / 18

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SLIDE 69

General Setting

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 14 / 18

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SLIDE 70

General Setting

Observing compound systems (many parts, distributed).

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 14 / 18

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SLIDE 71

General Setting

Observing compound systems (many parts, distributed). What can we infer about the global state from (necessarily) local observations?

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 14 / 18

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SLIDE 72

General Setting

Observing compound systems (many parts, distributed). What can we infer about the global state from (necessarily) local observations? Entanglement induces correlations between observed behaviour of subsystems.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 14 / 18

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SLIDE 73

General Setting

Observing compound systems (many parts, distributed). What can we infer about the global state from (necessarily) local observations? Entanglement induces correlations between observed behaviour of subsystems. Also, since observations act on (interfere with) the system, we cannot perform all observations together, even in principle.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 14 / 18

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SLIDE 74

General Setting

Observing compound systems (many parts, distributed). What can we infer about the global state from (necessarily) local observations? Entanglement induces correlations between observed behaviour of subsystems. Also, since observations act on (interfere with) the system, we cannot perform all observations together, even in principle. This leads to contextual behaviour: it matters which measurement context we are referring to.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 14 / 18

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SLIDE 75

Formal properties of probability (and relational) models

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 15 / 18

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SLIDE 76

Formal properties of probability (and relational) models

  • 1. No-Signalling

p(xA|a, b) = p(xA|a, b′)

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 15 / 18

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SLIDE 77

Formal properties of probability (and relational) models

  • 1. No-Signalling

p(xA|a, b) = p(xA|a, b′)

  • 2. Locality

p(xA, yB|a, b) = p(xA|a)p(yB|b)

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 15 / 18

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SLIDE 78

Formal properties of probability (and relational) models

  • 1. No-Signalling

p(xA|a, b) = p(xA|a, b′)

  • 2. Locality

p(xA, yB|a, b) = p(xA|a)p(yB|b) Quantum information tries to understand Local ⊂ Quantum ⊂ No-Signalling

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 15 / 18

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SLIDE 79

Formal properties of probability (and relational) models

  • 1. No-Signalling

p(xA|a, b) = p(xA|a, b′)

  • 2. Locality

p(xA, yB|a, b) = p(xA|a)p(yB|b) Quantum information tries to understand Local ⊂ Quantum ⊂ No-Signalling A subtle set sandwiched between two simpler sets (polytopes).

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 15 / 18

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SLIDE 80

Strong Contextuality

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 81

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 82

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform. This value may be influenced by some unseen factors, and hence our measurements yield only frequencies, not certain outcomes. Nevertheless, these definite, objective values should exist.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 83

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform. This value may be influenced by some unseen factors, and hence our measurements yield only frequencies, not certain outcomes. Nevertheless, these definite, objective values should exist. From this perspective, the following fact is truly shocking:

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 84

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform. This value may be influenced by some unseen factors, and hence our measurements yield only frequencies, not certain outcomes. Nevertheless, these definite, objective values should exist. From this perspective, the following fact is truly shocking: It is not possible to assign definite values to all measurements, independently of the selected measurement context (i.e. the set of measurements which we perform), consistently with the predictions of quantum mechanics.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 85

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform. This value may be influenced by some unseen factors, and hence our measurements yield only frequencies, not certain outcomes. Nevertheless, these definite, objective values should exist. From this perspective, the following fact is truly shocking: It is not possible to assign definite values to all measurements, independently of the selected measurement context (i.e. the set of measurements which we perform), consistently with the predictions of quantum mechanics. Equivalently, the corresponding has no global section contained in its support.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 86

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform. This value may be influenced by some unseen factors, and hence our measurements yield only frequencies, not certain outcomes. Nevertheless, these definite, objective values should exist. From this perspective, the following fact is truly shocking: It is not possible to assign definite values to all measurements, independently of the selected measurement context (i.e. the set of measurements which we perform), consistently with the predictions of quantum mechanics. Equivalently, the corresponding has no global section contained in its support. Note that this is a very weak requirement: just that some assignment is possible. This is much weaker than Locality.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 87

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform. This value may be influenced by some unseen factors, and hence our measurements yield only frequencies, not certain outcomes. Nevertheless, these definite, objective values should exist. From this perspective, the following fact is truly shocking: It is not possible to assign definite values to all measurements, independently of the selected measurement context (i.e. the set of measurements which we perform), consistently with the predictions of quantum mechanics. Equivalently, the corresponding has no global section contained in its support. Note that this is a very weak requirement: just that some assignment is possible. This is much weaker than Locality. The negative result is correspondingly very strong.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 88

Strong Contextuality

If we wish to maintain a realistic view of the nature of physical reality, then when we measure a system with respect to some quantity, there should be a definite value possessed by the system for this quantity, independent of the measurement which we perform. This value may be influenced by some unseen factors, and hence our measurements yield only frequencies, not certain outcomes. Nevertheless, these definite, objective values should exist. From this perspective, the following fact is truly shocking: It is not possible to assign definite values to all measurements, independently of the selected measurement context (i.e. the set of measurements which we perform), consistently with the predictions of quantum mechanics. Equivalently, the corresponding has no global section contained in its support. Note that this is a very weak requirement: just that some assignment is possible. This is much weaker than Locality. The negative result is correspondingly very strong. We shall prove that such models are realizable in QM, using the GHZ states.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 16 / 18

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SLIDE 89

Example: GHZ

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 17 / 18

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SLIDE 90

Example: GHZ

We consider the tripartite GHZ state |000 + |111

√ 2

, with X and Y measurements.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 17 / 18

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SLIDE 91

Example: GHZ

We consider the tripartite GHZ state |000 + |111

√ 2

, with X and Y measurements. The relevant part of the support table: 000 001 010 011 100 101 110 111 abc 1 1 1 1 ab′c′ 1 1 1 1 a′bc′ 1 1 1 1 a′b′c 1 1 1 1

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 17 / 18

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SLIDE 92

Example: GHZ

We consider the tripartite GHZ state |000 + |111

√ 2

, with X and Y measurements. The relevant part of the support table: 000 001 010 011 100 101 110 111 abc 1 1 1 1 ab′c′ 1 1 1 1 a′bc′ 1 1 1 1 a′b′c 1 1 1 1 Given boolean variables x, y, z, we define Ψxyz := x ⊕ y ⊕ z. The support for each row can be specified by the following formulas: ϕ1 := ¬Ψabc, ϕ2 := Ψab′c′, ϕ3 := Ψa′bc′, ϕ4 := Ψa′b′c.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 17 / 18

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SLIDE 93

Example: GHZ

We consider the tripartite GHZ state |000 + |111

√ 2

, with X and Y measurements. The relevant part of the support table: 000 001 010 011 100 101 110 111 abc 1 1 1 1 ab′c′ 1 1 1 1 a′bc′ 1 1 1 1 a′b′c 1 1 1 1 Given boolean variables x, y, z, we define Ψxyz := x ⊕ y ⊕ z. The support for each row can be specified by the following formulas: ϕ1 := ¬Ψabc, ϕ2 := Ψab′c′, ϕ3 := Ψa′bc′, ϕ4 := Ψa′b′c. These formulas are not simultaneously satisfiable; thus this model achieves a maximal violation of a logical Bell inequality.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 17 / 18

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SLIDE 94

General Perspective

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 18 / 18

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SLIDE 95

General Perspective

We use the mathematical language of sheaf theory to show that non-locality and contextuality can be characterized precisely in terms of the existence of

  • bstructions to global sections.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 18 / 18

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SLIDE 96

General Perspective

We use the mathematical language of sheaf theory to show that non-locality and contextuality can be characterized precisely in terms of the existence of

  • bstructions to global sections.

The same methods and structures can be applied to the study of notions of locality and contextuality in other areas, e.g. relational databases, logics of independence, social choice theory.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 18 / 18

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SLIDE 97

General Perspective

We use the mathematical language of sheaf theory to show that non-locality and contextuality can be characterized precisely in terms of the existence of

  • bstructions to global sections.

The same methods and structures can be applied to the study of notions of locality and contextuality in other areas, e.g. relational databases, logics of independence, social choice theory. Perhaps also program analysis??

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 18 / 18

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SLIDE 98

General Perspective

We use the mathematical language of sheaf theory to show that non-locality and contextuality can be characterized precisely in terms of the existence of

  • bstructions to global sections.

The same methods and structures can be applied to the study of notions of locality and contextuality in other areas, e.g. relational databases, logics of independence, social choice theory. Perhaps also program analysis?? Papers:

  • S. Abramsky and A. Brandenburger. The sheaf-theoretic structure of

non-locality and contextuality. New Journal of Physics, 13(2011):113036, 2011.

  • S. Abramsky, S. Mansfield and R. Soares Barbosa, The Cohomology of

Non-Locality and Contextuality, in Proceedings of QPL 2011, Electronic Proceedings in Theoretical Computer Science, 2011.

  • S. Abramsky, Relational Hidden Variables and Non-Locality. To appear in

Studia Logica 2012.

  • S. Abramsky and L. Hardy. Logical Bell Inequalities. arXiv:1203.1352.

Samson Abramsky (Department of Computer Science, University of Oxford) Interference, Dependence and Bell’s Theorem 18 / 18