#!/usr/bin/env python3
"""
Spinor Langlands: Bra-Ket and the Langlands Program

GRAMMAR: term ::= |x⟩ | ⟨x| | term term
REWRITE: ⟨x|x⟩ → ─

The Langlands Program connects:
  - Galois representations (number theory)
  - Automorphic representations (harmonic analysis)
  - L-functions (bridges between them)

In bra-ket language:
  - Representations ARE operators |ρ(g)⟩⟨ρ(g)|
  - Characters ARE traces Tr(ρ) = ⟨v|ρ(g)|v⟩
  - L-functions ARE products over primes
  - The correspondence IS an isomorphism

Key insight: The Langlands correspondence is a map between
two ways of constructing representations from bra-ket pairs!
"""

from dataclasses import dataclass
from typing import Union, List, Optional, Dict, Callable, Tuple
from fractions import Fraction
import cmath


# ============================================================================
# Pure Bra-Ket Grammar
# ============================================================================

@dataclass(frozen=True)
class Ket:
    """|x⟩"""
    label: str
    def __str__(self): return f"|{self.label}⟩"
    def __repr__(self): return f"Ket({self.label!r})"
    def __format__(self, fmt): return format(str(self), fmt)


@dataclass(frozen=True)
class Bra:
    """⟨x|"""
    label: str
    def __str__(self): return f"⟨{self.label}||"
    def __repr__(self): return f"Bra({self.label!r})"
    def __format__(self, fmt): return format(str(self), fmt)


@dataclass(frozen=True)
class Juxt:
    """term term"""
    left: 'Term'
    right: 'Term'
    def __str__(self):
        l = f"({self.left})" if isinstance(self.left, Juxt) else str(self.left)
        r = f"({self.right})" if isinstance(self.right, Juxt) else str(self.right)
        return f"{l}{r}"
    def __repr__(self): return f"Juxt({self.left!r}, {self.right!r})"
    def __format__(self, fmt): return format(str(self), fmt)


@dataclass(frozen=True)
class Wire:
    """─ - identity/zero"""
    def __str__(self): return "─"
    def __repr__(self): return "Wire()"
    def __format__(self, fmt): return format(str(self), fmt)


Term = Union[Wire, Ket, Bra, Juxt]


def tensor(a: Term, b: Term) -> Term:
    if isinstance(a, Wire): return b
    if isinstance(b, Wire): return a
    return Juxt(a, b)


# ============================================================================
# Groups and Representations
# ============================================================================

@dataclass
class Group:
    """
    A group G with elements and operation.
    
    In the Langlands program, we care about:
    - Galois groups G_K = Gal(K̄/K) (number theory)
    - Reductive groups G like GL(n), SL(n) (representation theory)
    """
    name: str
    elements: List[str]
    operation: Callable[[str, str], str]
    
    def __str__(self): return f"G = {self.name}"
    def __iter__(self): return iter(self.elements)
    def mul(self, a: str, b: str) -> str: return self.operation(a, b)


def cyclic_group(n: int) -> Group:
    """Create cyclic group Z/nZ."""
    elements = [f"{i}" for i in range(n)]
    def op(a, b): return f"{(int(a) + int(b)) % n}"
    return Group(f"Z/{n}Z", elements, op)


def symmetric_group(n: int) -> Group:
    """Create symmetric group S_n (small n only)."""
    from itertools import permutations
    elements = [''.join(map(str, p)) for p in permutations(range(1, n+1))]
    def op(a, b):
        # Compose permutations
        perm_a = [int(c) for c in a]
        perm_b = [int(c) for c in b]
        result = [perm_a[perm_b[i]-1] for i in range(n)]
        return ''.join(map(str, result))
    return Group(f"S_{n}", elements, op)


# ============================================================================
# Representations as Bra-Ket Operators
# ============================================================================

@dataclass
class Representation:
    """
    A representation ρ: G → GL(V)
    
    In bra-ket: each group element g maps to an operator ρ(g)
    
    ρ(g) = Σᵢ |vᵢ⟩⟨wᵢ|
    
    The representation property: ρ(gh) = ρ(g)ρ(h)
    """
    group: Group
    dim: int
    matrices: Dict[str, List[List[complex]]]  # g -> matrix
    
    def __str__(self): return f"ρ: {self.group} → GL({self.dim})"
    
    def matrix(self, g: str) -> List[List[complex]]:
        return self.matrices.get(g, [[1 if i==j else 0 for j in range(self.dim)] 
                                      for i in range(self.dim)])
    
    def as_operator(self, g: str) -> Term:
        """
        Express ρ(g) as bra-ket operator.
        
        For a matrix M, we decompose:
        M = Σᵢⱼ Mᵢⱼ |eᵢ⟩⟨eⱼ|
        
        where |eᵢ⟩ are basis vectors.
        """
        M = self.matrix(g)
        result = Wire()
        for i, row in enumerate(M):
            for j, val in enumerate(row):
                if abs(val) > 1e-10:
                    # |e_i⟩⟨e_j| weighted by M_ij
                    op = tensor(Ket(f"e_{i}"), Bra(f"e_{j}"))
                    # In reality we'd weight, but for structure just show it
                    result = tensor(result, op)
        return result


def trivial_representation(G: Group) -> Representation:
    """1-dimensional trivial representation: ρ(g) = 1 for all g."""
    return Representation(G, 1, {g: [[1]] for g in G})


def sign_representation() -> Representation:
    """
    Sign representation of S_n: ρ(σ) = sign(σ) = ±1
    
    This is a 1-dimensional representation.
    """
    S3 = symmetric_group(3)
    
    def sign(perm: str) -> int:
        # Count inversions
        n = len(perm)
        inv = 0
        for i in range(n):
            for j in range(i+1, n):
                if perm[i] > perm[j]:
                    inv += 1
        return -1 if inv % 2 else 1
    
    matrices = {g: [[sign(g)]] for g in S3}
    return Representation(S3, 1, matrices)


def standard_representation() -> Representation:
    """
    Standard representation of S_3 as 2x2 matrices.
    
    S_3 acts on R³ by permuting coordinates, with subspace x+y+z=0.
    """
    S3 = symmetric_group(3)
    
    # Permutation matrices projected to 2D
    # Standard basis: v1 = (1, -1, 0)/√2, v2 = (1, 1, -2)/√6
    # Actually use simpler 2D realization
    
    matrices = {
        "123": [[1, 0], [0, 1]],      # identity
        "132": [[1, 0], [0, -1]],     # (2 3)
        "213": [[-1, 0], [0, 1]],     # (1 2)
        "231": [[0, 1], [-1, -1]],    # (1 2 3)
        "312": [[-1, -1], [1, 0]],    # (1 3 2)
        "321": [[-1, 0], [0, -1]],    # (1 3)
    }
    
    return Representation(S3, 2, matrices)


# ============================================================================
# Characters as Traces
# ============================================================================

def character(repn: Representation, g: str) -> complex:
    """
    Character: χ(g) = Tr(ρ(g))
    
    In bra-ket: χ(g) = Σᵢ ⟨eᵢ|ρ(g)|eᵢ⟩
    
    The character is a class function: χ(ghg⁻¹) = χ(h)
    """
    M = repn.matrix(g)
    return sum(M[i][i] for i in range(repn.dim))


def character_table(repn: Representation) -> Dict[str, complex]:
    """Compute character table for representation."""
    return {g: character(repn, g) for g in repn.group}


# ============================================================================
# L-Functions from Bra-Ket
# ============================================================================

def local_L_factor(repn: Representation, p: int, s: complex) -> complex:
    """
    Local L-factor at prime p.
    
    L_p(s, ρ) = det(I - p^{-s} ρ(Frob_p))^{-1}
    
    where Frob_p is the Frobenius element at p.
    
    In bra-ket terms:
    L_p(s, ρ) = 1/det(I - p^{-s} |ρ(Frob)⟩⟨id|)
    
    For 1-dimensional representation:
    L_p(s, ρ) = 1/(1 - χ(Frob_p) p^{-s})
    """
    # Simplified: use p as proxy for Frobenius
    chi_p = complex(p ** (-s.real))
    
    # For trivial representation: L_p = 1/(1 - p^{-s})
    if repn.dim == 1:
        M = list(repn.matrices.values())[0]
        a = M[0][0]
        return 1.0 / (1 - a * chi_p)
    
    # For higher dim: det(I - p^{-s} M)^{-1}
    M = repn.matrix(str(p % len(repn.group.elements)))
    n = repn.dim
    
    # Compute det(I - chi_p * M)
    # For 2x2: (1 - chi*a)(1 - chi*d) - chi^2 * b*c
    if n == 2:
        a, b = M[0]
        c, d = M[1]
        det_val = (1 - chi_p * a) * (1 - chi_p * d) - (chi_p * b) * (chi_p * c)
        return 1.0 / det_val
    
    return 1.0


def L_function(repn: Representation, s: complex, primes: List[int]) -> complex:
    """
    Global L-function: L(s, ρ) = ∏_p L_p(s, ρ)
    
    This is the Euler product representation.
    
    In bra-ket:
    L(s, ρ) = ∏_p 1/det(I - p^{-s} |ρ(Frob_p)⟩⟨id|)
    
    The L-function encodes representation data in analytic form!
    """
    result = 1.0
    for p in primes:
        result *= local_L_factor(repn, p, s)
    return result


def riemann_zeta(s: complex, primes: List[int]) -> complex:
    """
    Riemann zeta: ζ(s) = ∏_p 1/(1 - p^{-s})
    
    This is L(s, 1) for the trivial representation!
    
    In bra-ket terms, it's the L-function of the identity operator.
    """
    result = 1.0
    for p in primes:
        result *= 1.0 / (1 - p ** (-s.real))
    return result


# ============================================================================
# Automorphic Forms
# ============================================================================

@dataclass
class AutomorphicForm:
    """
    Automorphic form: a function on G\\G(A) satisfying certain properties.
    
    In the Langlands correspondence, these correspond to Galois representations.
    
    Key examples:
    - Modular forms (for GL(2))
    - Maass forms
    - Eisenstein series
    """
    name: str
    level: int
    weight: int
    
    def __str__(self): return f"{self.name} (level {self.level}, weight {self.weight})"


def modular_form_fourier_coeffs(form: AutomorphicForm, n_terms: int) -> List[int]:
    """
    Fourier coefficients of a modular form.
    
    f(z) = Σ a_n e^{2π i n z}
    
    For cusp forms, these encode the corresponding Galois representation!
    
    Famous example: Δ = Σ τ(n) q^n (Ramanujan tau function)
    """
    # Simplified: return example coefficients
    if form.name == "Delta":
        # Ramanujan tau function
        tau = [0, 1, -24, 252, -1472, 4830, -6048, -16744, 
               84480, -113643, -115920, 534612, -370944]
        return tau[:n_terms]
    elif form.name == "Eisenstein":
        # Eisenstein series G_k
        coeffs = [0] + [n ** (form.weight - 1) for n in range(1, n_terms)]
        return coeffs
    else:
        return list(range(n_terms))


# ============================================================================
# The Langlands Correspondence
# ============================================================================

@dataclass
class LanglandsCorrespondence:
    """
    The (local) Langlands correspondence:
    
    {Representations of Galois group} ↔ {Representations of GL_n}
    
    In bra-ket:
    Galois side: |σ⟩⟨σ| for σ ∈ Gal(K̄/K)
    GL_n side:   |π⟩⟨π| for π automorphic
    
    The correspondence maps:
    - L-functions match: L(s, ρ) = L(s, π)
    - Characters match: χ_ρ ↔ χ_π
    - Frobenius ↔ Satake parameters
    """
    galois_repn: Representation
    automorphic_form: AutomorphicForm
    
    def __str__(self):
        return f"ρ: {self.galois_repn.group} ↔ π: {self.automorphic_form}"
    
    def verify_L_match(self, s: complex, primes: List[int]) -> Tuple[complex, complex]:
        """
        Verify that L-functions match under the correspondence.
        
        L(s, ρ) should equal L(s, π) where both are computed
        from their respective sides.
        """
        L_galois = L_function(self.galois_repn, s, primes)
        # L_automorphic would be computed from Fourier coefficients
        # Simplified for demonstration
        coeffs = modular_form_fourier_coeffs(self.automorphic_form, len(primes) + 1)
        L_auto = sum(coeffs[n] * (n+1) ** (-s.real) for n in range(1, len(coeffs)))
        
        return (L_galois, L_auto)


# ============================================================================
# Functoriality (The Heart of Langlands)
# ============================================================================

def functoriality(repn: Representation, phi: Callable) -> Representation:
    """
    Functoriality principle:
    
    Given a map of L-groups: ᵐG → ᵐH
    
    There exists a transfer:
    Rep(G) → Rep(H)
    
    In bra-ket: if ρ_G = |v⟩⟨w|, then ρ_H = ϕ(|v⟩⟨w|)
    
    This is DEEPLY bra-ket in nature:
    - Representations are operators
    - Transfers are maps on operators
    - The structure is preserved
    """
    # Placeholder: the actual functoriality is very complex
    return repn


# ============================================================================
# Visualization
# ============================================================================

def show_representation_as_bra_ket():
    """Show how representations are bra-ket operators."""
    print("\n" + "="*60)
    print("REPRESENTATIONS AS BRA-KET OPERATORS")
    print("="*60)
    
    print("""
  A representation ρ: G → GL(V) assigns to each g ∈ G
  an operator ρ(g) ∈ GL(V).
  
  In bra-ket:
    ρ(g) = Σᵢⱼ Mᵢⱼ |eᵢ⟩⟨eⱼ|
  
  where M = [Mᵢⱼ] is the matrix and |eᵢ⟩ are basis vectors.
  
  The representation property:
    ρ(gh) = ρ(g)ρ(h)
  
  In bra-ket:
    |ρ(gh)⟩⟨ρ(gh)| = |ρ(g)⟩⟨ρ(g)| |ρ(h)⟩⟨ρ(h)|
""")

    # Example: trivial representation
    print("  Example: Trivial representation")
    print("  ρ(g) = 1 = |e⟩⟨e|  for all g")
    
    # Example: sign representation
    sign = sign_representation()
    print("\n  Example: Sign representation of S₃")
    for g in sign.group.elements[:3]:
        M = sign.matrix(g)
        print(f"  ρ({g}) = {M[0][0]} = {'|e⟩⟨e|' if M[0][0] == 1 else '-|e⟩⟨e|'}")


def show_character_as_trace():
    """Show characters as traces (contractions)."""
    print("\n" + "="*60)
    print("CHARACTERS AS TRACES (CONTRACTIONS)")
    print("="*60)
    
    print("""
  The character is: χ(g) = Tr(ρ(g))
  
  In bra-ket:
    χ(g) = Σᵢ ⟨eᵢ|ρ(g)|eᵢ⟩
  
  This is a CONTRACTION (yanking!) of the operator.
  
  Characters are class functions:
    χ(ghg⁻¹) = χ(h)
  
  because trace is invariant under conjugation.
""")
    
    std = standard_representation()
    print("  Character table for standard rep of S₃:")
    for g in std.group.elements:
        chi = character(std, g)
        print(f"    χ({g}) = {chi}")


def show_L_function():
    """Show L-functions from bra-ket."""
    print("\n" + "="*60)
    print("L-FUNCTIONS FROM BRA-KET")
    print("="*60)
    
    print("""
  The L-function is an analytic encoding of representation:
  
  L(s, ρ) = ∏_p det(I - p^{-s} ρ(Frob_p))^{-1}
  
  In bra-ket:
    L(s, ρ) = ∏_p 1/det(I - p^{-s} |ρ(Frob_p)⟩⟨id|)
  
  For 1-dim:
    L(s, ρ) = ∏_p 1/(1 - χ(Frob_p) p^{-s})
  
  The Riemann zeta is L(s, 1):
    ζ(s) = ∏_p 1/(1 - p^{-s})
  
  This is the L-function of the TRIVIAL representation!
""")
    
    # Compute some values
    primes = [2, 3, 5, 7, 11, 13]
    s = 2.0 + 0j
    
    zeta_val = riemann_zeta(s, primes)
    print(f"  ζ(2) ≈ {zeta_val:.4f} (true value: π²/6 ≈ 1.6449)")


def show_langlands_correspondence():
    """Show the core Langlands correspondence."""
    print("\n" + "="*60)
    print("THE LANGLANDS CORRESPONDENCE")
    print("="*60)
    
    print("""
  The Langlands Program connects TWO worlds:
  
  ┌─────────────────────────────────────────────────────┐
  │                                                     │
  │   NUMBER THEORY          REPRESENTATION THEORY      │
  │   ─────────────          ────────────────────      │
  │                                                     │
  │   Galois group G         Reductive group GL_n       │
  │   Galois reps ρ          Automorphic reps π         │
  │   L(s, ρ)                L(s, π)                    │
  │   χ_ρ                    χ_π                        │
  │   Frobenius              Satake parameters          │
  │                                                     │
  └─────────────────────────────────────────────────────┘
  
  The correspondence: L(s, ρ) = L(s, π)
  
  In bra-ket:
    Galois:    |σ⟩⟨σ| for σ ∈ Gal(K̄/K)
    Automorphic: |π⟩⟨π| for π ∈ Aut(GL_n)
    
    The correspondence maps bra-ket structures ISOMORPHICALLY!
""")


def show_functoriality():
    """Show functoriality principle."""
    print("\n" + "="*60)
    print("FUNCTORIALITY")
    print("="*60)
    
    print("""
  Functoriality: the "transfers" between groups.
  
  Given L-group homomorphism: ᵐG → ᵐH
  
  There exists transfer: Rep(G) → Rep(H)
  
  Example transfers:
  - Base change: Rep(GL_n/F) → Rep(GL_n/K) for extension K/F
  - Automorphic induction: Rep(GL_n) → Rep(GL_m)
  - Symmetric powers: Sym^n ρ from ρ
  
  In bra-ket:
    Transfer = map on operators |ρ(g)⟩⟨ρ(g)|
    
    Structure preserved: L-functions, characters match!
""")


def show_bra_ket_essence():
    """Show why bra-ket is the essence of Langlands."""
    print("\n" + "="*60)
    print("WHY BRA-KET IS THE LANGUAGE OF LANGLANDS")
    print("="*60)
    
    print("""
  The Langlands Program is about REPRESENTATIONS.
  Representations ARE operators.
  Operators ARE bra-ket pairs.
  
  ┌─────────────────────────────────────────────────────┐
  │                                                     │
  │   Representation ρ  =  Σᵢⱼ |vᵢ⟩⟨wⱼ|               │
  │                                                     │
  │   Character χ(g)   =  Tr(ρ(g)) = Σᵢ ⟨eᵢ|ρ(g)|eᵢ⟩  │
  │                                                     │
  │   L-function       =  ∏_p det(I - p^{-s}ρ)^{-1}    │
  │                     =  ∏_p ∏ eigenvalues λᵢ       │
  │                        1/(1 - λᵢ p^{-s})          │
  │                                                     │
  │   Eigenvalue λᵢ    =  ⟨v|ρ|v⟩ for eigenvector     │
  │                                                     │
  └─────────────────────────────────────────────────────┘
  
  The correspondence maps:
  
    Galois reps          Automorphic reps
    |σ⟩⟨σ|      ↔       |π⟩⟨π|
    
  BOTH are bra-ket structures!
  
  The yanking rule ⟨x|x⟩ → ─ IS the trace operation.
  Traces give characters. Characters give L-functions.
  
  The entire Langlands Program lives in bra-ket!
""")


# ============================================================================
# Demo
# ============================================================================

def demo():
    print("="*60)
    print("SPINOR LANGLANDS")
    print("="*60)
    print()
    print("GRAMMAR: term ::= |x⟩ | ⟨x| | term term")
    print("REWRITE: ⟨x|x⟩ → ─")
    print()
    print("The Langlands Program connects:")
    print("  Number Theory ↔ Representation Theory")
    print("  Galois reps ↔ Automorphic forms")
    print("  Via L-functions")
    print()
    
    show_representation_as_bra_ket()
    show_character_as_trace()
    show_L_function()
    show_langlands_correspondence()
    show_functoriality()
    show_bra_ket_essence()
    
    print("\n" + "="*60)
    print("THE GRAND PICTURE")
    print("="*60)
    print()
    print("  ONE GRAMMAR: |x⟩ ⟨x| and juxtaposition")
    print("  ONE RULE: ⟨x|x⟩ → ─")
    print()
    print("  Emerges:")
    print("    • Integers, rationals, complex numbers")
    print("    • Vectors, matrices, operators")
    print("    • Tensor calculus")
    print("    • Representations and characters")
    print("    • L-functions")
    print("    • THE LANGLANDS CORRESPONDENCE")
    print()
    print("  All of mathematics from spinors!")
    print()


if __name__ == "__main__":
    import sys
    
    if len(sys.argv) > 1 and sys.argv[1] == "--demo":
        demo()
    else:
        demo()
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