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QuantumInfo.ForMathlib.SionMinimax

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theorem

`image2` is invariant under argument flipping

#image2_flip

Let f:α×βγf: \alpha \times \beta \to \gamma be a function of two variables. For any sets sαs \subseteq \alpha and tβt \subseteq \beta, the image of t×st \times s under the flipped function f~(y,x)=f(x,y)\tilde{f}(y, x) = f(x, y) is equal to the image of s×ts \times t under the original function ff. That is, {f(x,y)xs,yt}={f~(y,x)yt,xs}\{ f(x, y) \mid x \in s, y \in t \} = \{ \tilde{f}(y, x) \mid y \in t, x \in s \}.

theorem

Max-Min Inequality for Conditionally Complete Lattices (supinfinfsup\sup \inf \le \inf \sup)

#ciSup_ciInf_le_ciInf_ciSup

Let α\alpha be a conditionally complete lattice, and let ι\iota and ι\iota' be index types where ι\iota is nonempty. Let f:ι×ιαf : \iota \times \iota' \to \alpha be a function. Suppose that for every jιj \in \iota', the set {f(i,j)iι}\{f(i, j) \mid i \in \iota\} is bounded above, and for every iιi \in \iota, the set {f(i,j)jι}\{f(i, j) \mid j \in \iota'\} is bounded below. Then the supremum of the infima is less than or equal to the infimum of the suprema: \[ \sup_{i \in \iota} \inf_{j \in \iota'} f(i, j) \le \inf_{j \in \iota'} \sup_{i \in \iota} f(i, j) \]

theorem

The maximum of two functions bounded above is bounded above

#range_max

Let f,g:XRf, g: X \to \mathbb{R} (or any conditionally complete lattice) be two functions. If the range of ff is bounded above and the range of gg is bounded above, then the range of the function defined by xmax(f(x),g(x))x \mapsto \max(f(x), g(x)) is also bounded above.

theorem

Pointwise Minimum of Functions Bounded Below is Bounded Below

#range_min

Let f,g:ιαf, g: \iota \to \alpha be two functions into a conditionally complete linear order α\alpha. If the ranges of ff and gg are both bounded below, then the range of their pointwise minimum, defined by (fg)(x)=min(f(x),g(x))(f \wedge g)(x) = \min(f(x), g(x)), is also bounded below.

theorem

infSf=min(infSTf,infSTf)\inf_S f = \min(\inf_{S \cap T} f, \inf_{S \setminus T} f)

#ciInf_eq_min_cInf_inter_diff

Let f:ιRf: \iota \to \mathbb{R} (or any conditionally complete lattice) be a function and S,TιS, T \subseteq \iota be sets such that the image f(S)f(S) is bounded below. If the intersections STS \cap T and STS \setminus T are both non-empty, then the infimum of ff over SS is equal to the minimum of the infimum of ff over STS \cap T and the infimum of ff over STS \setminus T: infiSf(i)=min(infiSTf(i),infiSTf(i))\inf_{i \in S} f(i) = \min \left( \inf_{i \in S \cap T} f(i), \inf_{i \in S \setminus T} f(i) \right)

theorem

a<inffa < \inf f iff b>a\exists b > a such that bb is a lower bound of ff

#lt_ciInf_iff

Let f:ιαf: \iota \to \alpha be a function whose range is bounded below in a conditionally complete linear order α\alpha. For any aαa \in \alpha, a<infiιf(i)a < \inf_{i \in \iota} f(i) if and only if there exists some bαb \in \alpha such that a<ba < b and bf(i)b \le f(i) for all iιi \in \iota.

theorem

Supremum commutes with pointwise join: sup(fg)=(supf)(supg)\sup (f \sqcup g) = (\sup f) \sqcup (\sup g)

#ciSup_sup_eq

Let f,g:ιαf, g: \iota \to \alpha be two functions into a conditionally complete lattice α\alpha. If the ranges of ff and gg are both bounded above, then the supremum of their pointwise supremum is equal to the supremum of the individual suprema. That is, supx(f(x)g(x))=(supxf(x))(supxg(x))\sup_{x} (f(x) \vee g(x)) = \left(\sup_{x} f(x)\right) \vee \left(\sup_{x} g(x)\right) where \vee denotes the join (supremum) operation in the lattice.

theorem

Distributivity of infimum over pointwise meet: infx(f(x)g(x))=(infxf(x))(infxg(x))\inf_x (f(x) \sqcap g(x)) = (\inf_x f(x)) \sqcap (\inf_x g(x))

#ciInf_inf_eq

Let f,g:ιαf, g: \iota \to \alpha be two functions into a conditionally complete lattice α\alpha. If the ranges of ff and gg are both bounded below, then the infimum of their pointwise minimum is equal to the minimum of their individual infima: infx(f(x)g(x))=(infxf(x))(infxg(x))\inf_{x} (f(x) \sqcap g(x)) = (\inf_{x} f(x)) \sqcap (\inf_{x} g(x)) where \sqcap denotes the meet (infimum) operation and inf\inf denotes the conditionally complete infimum.

theorem

Distributivity of join over conditionally complete supremum: asupxf(x)=supx(af(x))a \vee \sup_x f(x) = \sup_x (a \vee f(x))

#sup_ciSup

Let f:ιαf: \iota \to \alpha be a function into a conditionally complete lattice α\alpha and let aαa \in \alpha be an element. If the range of ff is bounded above, then the join of aa and the supremum of f(x)f(x) is equal to the supremum of the pointwise join of aa and f(x)f(x): asupxιf(x)=supxι(af(x))a \vee \sup_{x \in \iota} f(x) = \sup_{x \in \iota} (a \vee f(x)) where \vee (or \sqcup) denotes the join operation and sup\sup (or \bigsqcup) denotes the conditionally complete supremum.

theorem

Distributivity of meet over conditionally complete infimum

#inf_ciInf

Let f:ιLf: \iota \to L be a function into a conditionally complete lattice LL, and let aLa \in L be an element. If the range of ff is bounded below, then the infimum of af(x)a \sqcap f(x) over all xx is equal to the meet of aa and the infimum of f(x)f(x) over all xx: ainfxιf(x)=infxι(af(x))a \sqcap \inf_{x \in \iota} f(x) = \inf_{x \in \iota} (a \sqcap f(x))

theorem

The join of infima is less than or equal to the infimum of pointwise joins

#ciInf_sup_ciInf_le

Let f,g:ιLf, g: \iota \to L be functions into a conditionally complete lattice LL. If the ranges of ff and gg are both bounded below, then the join (supremum) of their individual infima is less than or equal to the infimum of their pointwise join: (infiιf(i))(infiιg(i))infiι(f(i)g(i))\left( \inf_{i \in \iota} f(i) \right) \sqcup \left( \inf_{i \in \iota} g(i) \right) \leq \inf_{i \in \iota} (f(i) \sqcup g(i)) where \sqcup denotes the join (supremum) operation and inf\inf (or \sqcap) denotes the infimum (infimum) operation in the lattice.

theorem

Supremum of pointwise infimum is less than or equal to infimum of suprema

#le_ciSup_inf_ciSup

Let f,g:ιβf, g: \iota \to \beta be functions where β\beta is a conditionally complete lattice. If the ranges of ff and gg are both bounded above, then the supremum of their pointwise infimum is less than or equal to the infimum of their individual suprema: supiι(f(i)g(i))(supiιf(i))(supiιg(i))\sup_{i \in \iota} (f(i) \sqcap g(i)) \le \left(\sup_{i \in \iota} f(i)\right) \sqcap \left(\sup_{i \in \iota} g(i)\right) where \sqcap denotes the infimum (meet) operation in the lattice.

theorem

Quasiconvexity is preserved on convex subsets

#subset

Let EE be an additive commutative monoid and k\mathbf{k} be a semiring equipped with a partial order, such that EE is a k\mathbf{k}-module (via a scalar multiplication \cdot). Let ss and tt be subsets of EE, and β\beta be a type with a less-than-or-equal-to relation \leq. If f:Eβf: E \to \beta is a quasiconvex function on ss with respect to k\mathbf{k}, tt is a subset of ss (tst \subseteq s), and tt is a convex set, then ff is also quasiconvex on tt.

theorem

Quasiconvexity implies f(z)f(x)f(y)f(z) \leq f(x) \sqcup f(y) for zz in the segment [x,y][x, y]

#mem_segment_le_max

Let k\mathbf{k} be a semiring with a partial order, EE be an additive commutative monoid with a scalar multiplication by k\mathbf{k}, and β\beta be a semilattice-sup (a partially ordered set where any two elements a,ba, b have a least upper bound aba \sqcup b). Let ss be a set in EE and f:Eβf: E \to \beta be a quasiconvex function on ss. For any x,ysx, y \in s and any zz belonging to the segment connecting xx and yy, the value of the function at zz is less than or equal to the maximum (supremum) of the values at the endpoints, i.e., f(z)f(x)f(y)f(z) \leq f(x) \sqcup f(y).

theorem

Quasiconcave functions satisfy f(x)f(y)f(z)f(x) \land f(y) \le f(z) on segments [x,y][x, y]

#min_le_mem_segment

Let EE be an additive commutative monoid equipped with a scalar multiplication by a semiring k\mathbb{k}, where k\mathbb{k} has a partial order. Let sEs \subseteq E be a set and f:Eβf: E \to \beta be a function into a semilattice-inf β\beta. If ff is quasiconcave on ss, then for any points x,ysx, y \in s and any point zz lying in the segment [x,y][x, y], it holds that f(x)f(y)f(z)f(x) \land f(y) \le f(z), where \land denotes the infimum (meet) in β\beta.

theorem

A lower semicontinuous function on a compact set is bounded below

#bddBelow

Let SS be a subset of a topological space α\alpha, and let g:αRg: \alpha \to \mathbb{R} be a real-valued function. If gg is lower semicontinuous on SS and SS is compact, then the image of SS under gg, denoted by g(S)g(S), is bounded below.

theorem

The pointwise maximum of two lower semicontinuous functions is lower semicontinuous.

#max

Let XX be a topological space and SXS \subseteq X be a set. Let f,g:XRf, g: X \to \mathbb{R} be real-valued functions. If ff and gg are both lower semicontinuous on SS, then their pointwise maximum xmax(f(x),g(x))x \mapsto \max(f(x), g(x)) is also lower semicontinuous on SS.

theorem

Lower semicontinuity on a closed set ss is equivalent to the closedness of sf1((,y])s \cap f^{-1}((-\infty, y]) for all yy

#lowerSemicontinuousOn_iff_isClosed_preimage

Let f:αγf: \alpha \to \gamma be a function from a topological space α\alpha to a linearly ordered topological space γ\gamma, and let ss be a closed subset of α\alpha. The function ff is lower semicontinuous on ss if and only if for every yγy \in \gamma, the set s{xf(x)y}s \cap \{x \mid f(x) \le y\} is closed.

theorem

The line segment between aa and bb is connected.

#isConnected

Let EE be a topological vector space over the real numbers R\mathbb{R} (specifically, a type with an additive commutative group structure, a module structure over R\mathbb{R}, and a topology such that addition and scalar multiplication are continuous). For any two points a,bEa, b \in E, the line segment connecting them, defined as segment R a b={(1t)a+tb0t1}\text{segment } \mathbb{R} \ a \ b = \{ (1-t)a + tb \mid 0 \le t \le 1 \}, is a connected set.

theorem

If f(S,T)f(S, T) is bounded, then {infxSf(x,y)yT}\{ \inf_{x \in S} f(x, y) \mid y \in T \} is bounded above.

#range_inf_of_image2

Let MM and NN be sets, and let α\alpha be a conditionally complete linear order. Let f:M×Nαf: M \times N \to \alpha be a function. Suppose SMS \subseteq M and TNT \subseteq N are subsets such that the set of values f(S,T)={f(x,y)xS,yT}f(S, T) = \{f(x, y) \mid x \in S, y \in T\} is bounded above and bounded below. Then the set of values {infxSf(x,y)yT}\{\inf_{x \in S} f(x, y) \mid y \in T\} is bounded above.

theorem

If f(S,T)f(S, T) is bounded, then {supxSf(x,y)yT}\{ \sup_{x \in S} f(x, y) \mid y \in T \} is bounded below.

#range_sup_of_image2

Let MM and NN be sets, and let α\alpha be a conditionally complete linear order. Let f:M×Nαf: M \times N \to \alpha be a function. Suppose SMS \subseteq M and TNT \subseteq N are subsets such that the set of values f(S,T)={f(x,y)xS,yT}f(S, T) = \{f(x, y) \mid x \in S, y \in T\} is bounded above and bounded below. Then the set of values {supxSf(x,y)yT}\{\sup_{x \in S} f(x, y) \mid y \in T\} is bounded below.

theorem

inftfinfsf\inf_{t} f \le \inf_{s} f for sts \subseteq t

#ciInf_le_ciInf_of_subset

Let α\alpha be a conditionally complete lattice and f:βαf: \beta \to \alpha be a function. For any subsets s,tβs, t \subseteq \beta such that ss is non-empty, sts \subseteq t, and the image f(t)f(t) is bounded below, the infimum of ff over tt is less than or equal to the infimum of ff over ss: infxtf(x)infxsf(x)\inf_{x \in t} f(x) \le \inf_{x \in s} f(x)

theorem

Lower semicontinuity of a function extended by \top over a closed relative domain

#dite_top

Let XX be a topological space and YY be a preordered space with a top element \top. Let SXS \subseteq X be a subset and pp be a decidable predicate on XX. Suppose ff is a function that, for each xx satisfying p(x)p(x), assigns a value in YY. Let hh be the function defined on SS such that h(x)=f(x)h(x) = f(x) if p(x)p(x) is true, and h(x)=h(x) = \top otherwise. If the restriction of ff to the subtype {xp(x)}\{x \mid p(x)\} is lower semicontinuous on the set {xsubtypeval(x)S}\{x \in \text{subtype} \mid \text{val}(x) \in S\}, and there exists a closed set UXU \subseteq X such that SU={xSp(x)}S \cap U = \{x \in S \mid p(x)\}, then hh is lower semicontinuous on SS.

theorem

Composition of a Lower Semicontinuous Function and a Continuous Function is Lower Semicontinuous

#comp_continuousOn

Let XX and YY be topological spaces and ZZ be a preordered set. Let f:XYf : X \to Y be a function and g:YZg : Y \to Z be another function. Let SXS \subseteq X and TYT \subseteq Y such that the image of SS under ff is contained in TT (f(S)Tf(S) \subseteq T). If gg is lower semicontinuous on TT and ff is continuous on SS, then the composition gfg \circ f is lower semicontinuous on SS.

theorem

Composition of an Upper Semicontinuous Function and a Continuous Function is Upper Semicontinuous

#comp_continuousOn

Let XX and YY be topological spaces and ZZ be a preordered set. Let f:XYf: X \to Y be a function and g:YZg: Y \to Z be another function. Suppose sXs \subseteq X and tYt \subseteq Y are sets such that f(s)tf(s) \subseteq t. If gg is upper semicontinuous on tt and ff is continuous on ss, then the composition gfg \circ f is upper semicontinuous on ss.

theorem

Lower Semicontinuity of a Function Extended by \top over a Relatively Closed Set

#ite_top

Let XX be a topological space and YY be a preordered space with a greatest element \top. Let SXS \subseteq X be a set and PP be a predicate on XX. Let f:XYf: X \to Y be a function. Suppose that: 1. ff is lower semicontinuous on the set S{xP(x)}S \cap \{x \mid P(x)\}. 2. The set S{xP(x)}S \cap \{x \mid P(x)\} is relatively closed in SS, i.e., there exists a closed set UXU \subseteq X such that SU=S{xP(x)}S \cap U = S \cap \{x \mid P(x)\}. Then the function g:XYg: X \to Y defined by g(x)={f(x)if P(x)otherwiseg(x) = \begin{cases} f(x) & \text{if } P(x) \\ \top & \text{otherwise} \end{cases} is lower semicontinuous on SS.

theorem

Composition of a Monotone Left Order Continuous Function with a Lower Semicontinuous Function is Lower Semicontinuous

#comp_lowerSemicontinuousOn_strong_assumptions

Let XX, YY, and ZZ be topological spaces where YY and ZZ are equipped with a linear order, the order topology, and are densely ordered. Let sXs \subseteq X be a set, f:XYf: X \to Y be a function that is lower semicontinuous on ss, and g:YZg: Y \to Z be a monotone function that is left order continuous. Then the composite function gfg \circ f is lower semicontinuous on ss.

theorem

Upper Semicontinuity Preserves Strict Inequality f(z)<cf(z) < c under Limits

#frequently_lt_of_tendsto

Let XX and YY be topological spaces and ZZ be a preordered set. Let f:XZf : X \to Z be a function that is upper semicontinuous on a subset TXT \subseteq X. Let zTz \in T and cZc \in Z be such that f(z)<cf(z) < c. Suppose {zs}sS\{z_s\}_{s \in S} is a net (or more generally, a filter ll is given) such that zszz_s \to z, and for all ss, zsTz_s \in T. Then, eventually along the filter ll, it holds that f(zs)<cf(z_s) < c.

theorem

infa{x}tf(a)=f(x)infatf(a)\inf_{a \in \{x\} \cup t} f(a) = f(x) \sqcap \inf_{a \in t} f(a) for finite tt

#ciInf_insert

Let α\alpha be a type with decidable equality and let β\beta be a conditionally complete lattice. For any non-empty finite set tαt \subseteq \alpha, any element xαx \in \alpha, and any function f:αβf : \alpha \to \beta, the infimum of ff over the set t{x}t \cup \{x\} is equal to the infimum (greatest lower bound) of f(x)f(x) and the infimum of ff over tt. That is: infa{x}tf(a)=f(x)infatf(a)\inf_{a \in \{x\} \cup t} f(a) = f(x) \sqcap \inf_{a \in t} f(a) where \sqcap denotes the meet (infimum) operator in the lattice.

theorem

supa{x}tf(a)=f(x)supatf(a)\sup_{a \in \{x\} \cup t} f(a) = f(x) \sqcup \sup_{a \in t} f(a)

#ciSup_insert

Let α\alpha be a type with decidable equality and β\beta be a conditionally complete lattice. For any non-empty finite set tαt \subseteq \alpha, any element xαx \in \alpha, and any function f:αβf: \alpha \to \beta, the supremum of ff over the set t{x}t \cup \{x\} is equal to the join (least upper bound) of f(x)f(x) and the supremum of ff over tt. That is, \[ \sup_{a \in t \cup \{x\}} f(a) = f(x) \sqcup \sup_{a \in t} f(a) \]

theorem

Sion's Minimax Theorem: infxsupyf(x,y)=supyinfxf(x,y)\inf_x \sup_y f(x, y) = \sup_y \inf_x f(x, y)

#sion_minimax

Let f:M×NRf: M \times N \to \mathbb{R} be a function, and let SMS \subseteq M and TNT \subseteq N be sets such that the image f(S,T)f(S, T) is both bounded above and bounded below. Under the conditions of Sion's Minimax Theorem (typically that SS and TT are compact convex sets and ff satisfies appropriate semi-continuity and quasi-concavity/convexity conditions), the following equality holds: infxSsupyTf(x,y)=supyTinfxSf(x,y)\inf_{x \in S} \sup_{y \in T} f(x, y) = \sup_{y \in T} \inf_{x \in S} f(x, y) where the boundedness assumptions ensure that the conditional suprema and infima are well-defined and do not take "junk values."