PhyslibAlpha.AlgebraicFramework.OrderUnit.State.Discrimination
State discrimination
i. Overview
A system is prepared in state `ω₀` with prior probability `p₀`, or `ω₁` with prior `p₁`. Guess which from a single yes/no test (an effect `e`): guess `0` if `e` clicks, `1` otherwise. The optimal guess succeeds with probability
`optimalSuccessProb ω₀ ω₁ p₀ p₁ = p₁ + sup_e (p₀ * ω₀ e - p₁ * ω₁ e)` (`optimalSuccessProb_eq`)
— the Helstrom bound, in the same spirit as the familiar `(1 + ‖p₀ρ₀ - p₁ρ₁‖₁) / 2` trace-distance formula, here with the effect supremum playing the trace norm's role directly.
ii. Key definitions and results
- `successProb`, `optimalSuccessProb`
- `optimalSuccessProb_eq`
iii. Table of contents
- A. Success probability of a fixed test
- B. Optimal success probability
- C. The abstract Helstrom formula
A. Success probability of a fixed test
B. Optimal success probability
C. The abstract Helstrom formula
23 declarations
Success probability for state discrimination
The success probability of discriminating between two states and with respective prior probabilities and using a binary test is defined as where is an effect (an element such that ) and is its complement. This value represents the probability of correctly identifying the state by guessing when the effect occurs and guessing when its complement occurs.
Success Probability Equals Prior plus Discrimination Advantage
Let be an ordered additive commutative group with a unit element . For two states (represented as unital positive linear maps) and prior probabilities , the success probability of a binary test (where ) is given by: This formula expresses the success probability as the prior probability of guessing state () plus the discrimination advantage provided by the test .
Optimal success probability
Given two states (represented as unital positive linear maps from an ordered additive commutative group with a unit to ) and their respective prior probabilities , the **optimal success probability** is defined as the supremum of the success probabilities over all possible effects (): This value represents the maximum possible probability of correctly identifying whether the system is in state or based on a single binary test.
The discrimination advantage is bounded by
Let be an ordered additive commutative group with a unit element . For any unital positive linear maps , non-negative real numbers , and any effect (defined such that ), the discrimination advantage satisfies the inequality:
The advantage is bounded above
Let be a type equipped with an additive commutative group structure, a partial order, and a unit element . Let and be states (unital positive linear maps from to ), and let and be non-negative real prior probabilities. Then the set of values , representing the "advantage" or distinguishing power of an effect , is bounded above in .
The abstract Helstrom bound:
Let be an ordered additive commutative group with a unit element . Let be states (unital positive linear maps) and be their respective prior probabilities. The optimal success probability for distinguishing and is given by where the supremum is taken over all effects (elements satisfying ). This formula, known as the abstract Helstrom bound, expresses the maximum probability of correctly identifying a state as plus the maximum "advantage" provided by a single binary test.
Base norm of the weighted difference
Let be an ordered additive commutative group with a unit element . Given two states (unital positive linear maps) and real weights , the `weightedStateBaseNorm` is the base norm of the signed functional . Operationally, it is defined as where the supremum is taken over all effects (elements satisfying ). This quantity is normalized such that if , the optimal success probability for distinguishing the states is given by the abstract Helstrom formula .
for non-negative weights
Let be an ordered additive commutative group with a unit element . Let be two states, defined as unital positive linear maps. For any non-negative weights , the operational base norm of the weighted difference satisfies: where the base norm is defined as , with the supremum taken over all effects .
The operational base norm dominates the weight difference
Let be an ordered additive commutative group with a unit element . Let and be two states on (represented as unital positive linear maps to ). For any non-negative real weights , the absolute difference between the weights is bounded by the operational base norm of the weighted difference of the states: where the operational base norm is defined as and the supremum is taken over all effects satisfying .
Abstract Helstrom Formula:
Let be an ordered additive commutative group with a unit element . Let be two states on , represented as unital positive linear maps to . For any non-negative prior probabilities such that , the optimal success probability for discriminating between the two states is given by the abstract Helstrom formula: where is the operational base norm of the weighted difference between the states.
Data processing inequality for maximal effect advantage:
Let be a unital positive linear map between spaces with ordered structures and unit elements. Let be states on and be non-negative real weights. The maximal weighted advantage obtained by choosing an effect (where ) for the pullback states and is less than or equal to the maximal weighted advantage obtained by choosing an effect in : where the pullback state maps to .
Data processing inequality for weighted base norm:
Let be a unital positive linear map between spaces with an ordered structure and a unit element. Let be states on (i.e., unital positive linear maps ) and be non-negative real weights. Let and denote the pullback states on . Then the base norm of the weighted difference of the pullback states is less than or equal to the base norm of the weighted difference of the original states: where the weighted base norm is defined as .
Data processing inequality:
Let and be ordered additive commutative groups with unit elements. Let be a unital positive linear map (representing a channel in the Heisenberg picture). For any two states on and non-negative prior probabilities , the optimal success probability for discriminating the states after the action of the channel (the pullback states and ) is less than or equal to the optimal success probability for discriminating the original states: where the optimal success probability is defined as the supremum over all effects ():
Operational distance between states and
The operational distance between two states is defined as the supremum of the absolute difference between the probabilities they assign to the same effect, expressed as , where the supremum is taken over all effects such that .
The probability gap for any two states and an effect
Let be an ordered additive commutative group with a unit element . For any two states (unital positive linear maps from to ) and any effect (where ), the absolute difference between the values assigned to the effect by the two states satisfies
The set of effect probability gaps is bounded above
Let be a type equipped with an additive commutative group structure, a partial order, and a unit element . Let and be unital positive linear maps from to . An effect is defined as an element of such that . Then the set of values is bounded above.
The operational distance between states is non-negative ()
Let be an ordered additive commutative group with a unit element. For any two states (unital positive linear maps from to ), the operational distance between them is non-negative: The operational distance is defined as the supremum of the absolute difference between the probabilities the states assign to the same effect , expressed as , where the supremum is taken over all effects such that .
Let be an ordered additive commutative group with a unit element . For any two states (defined as unital positive linear maps from to ), the operational distance between them is at most : The operational distance is defined as the supremum of the absolute difference between the values assigned by the states to the same effect , expressed as , where ranges over all effects in such that .
For any state (a unital positive linear map from to ), the operational distance from the state to itself is zero:
Symmetry of the Operational Distance:
For any two states , the operational distance between and is equal to the operational distance between and : where the operational distance is defined as the supremum of the absolute difference between the probabilities assigned to an effect by the two states, .
The operational distance between states and is if and only if
For any two states , the operational distance between them is zero if and only if the states are identical (). Here, the operational distance is defined as , where the supremum is taken over all effects .
Triangle Inequality for Operational Distance between States
For any states , the operational distance satisfies the triangle inequality: where the operational distance between two states is defined as the supremum of the absolute difference between the probabilities they assign to the same effect , i.e., .
Data Processing Inequality for Operational Distance
Let and be spaces and be a unital positive linear map (representing a quantum channel in the Heisenberg picture). For any two states on , the operational distance between their pullback states and on is less than or equal to the operational distance between and : where the operational distance is defined as , with the supremum taken over all effects .
