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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

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32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

About

32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

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32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

About

32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

Topics

Resources

Stars

1 star

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

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32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

About

32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

Topics

Resources

Stars

1 star

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0 watching

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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

About

32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

Topics

Resources

Stars

1 star

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Languages

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dyadic-examples

32 runnable examples for dyadic — the Six-Axiom 2-Adic Operator Calculus library.

cmake -B build && cmake --build build && cmake --build build --target run

What This Is

dyadic is a header-only C++20 library for arithmetic and calculus over the 2-adic integers ℤ₂ and the ring of formal power series ℤ₂[[t]]. This companion project provides 32 runnable examples covering the full dyadic API, including its four extension headers (<dyadic/dynamic_polynomial.h>, <dyadic/pade.h>, <dyadic/continued_fractions.h>, <dyadic/matrix.h>) which live in the dyadic repository under include/dyadic/.

Extensions

Four extension headers shipped with the dyadic library, drop-in ready — just #include <dyadic/dynamic_polynomial.h> (or whichever) in your project:

HeaderWhat It AddsDepends On
<dyadic/dynamic_polynomial.h>Heap-allocated polynomial with runtime-variable degreedyadic.h
<dyadic/pade.h>Padé approximant construction in ℤ₂[[t]]dyadic.h
<dyadic/continued_fractions.h>Continued fraction expansion and convergent evaluation in ℤ₂[[t]]dyadic.h, dynamic_polynomial.h
<dyadic/matrix.h>Generic M×N matrix over ℤ/2^Wℤ with linear algebradyadic.h

dynamic_polynomial.h

Runtime-degree polynomial — the same eval, formal derivative, forward difference, and basis-conversion operations as the compile-time Polynomial<N,W,Basis>, but with heap-allocated storage so the degree is determined at runtime.

DynamicPolynomial<uint32_t> p({1, 2, 3}); // 1 + 2x + 3x²auto df = formal_derivative(p); // 2 + 6xauto taylor = change_basis<TaylorBasis>(p);
// Convert to/from compile-time Polynomial
Polynomial<4, uint32_t> static_p{{1, 2, 3, 4}};
auto dyn = to_dynamic(static_p);
auto back = to_static<4>(dyn);

Arithmetic (+, , *) works between DynamicPolynomial values of any degree; mixed-degree operations auto-resize the result.


pade.h

Constructs the [m/n] Padé approximant P(t)/Q(t) from the first m+n+1 terms of a formal power series A(t) = Σ a_i t^i, matching A(t) to order O(t^{m+n}). Uses Gaussian elimination over ℤ₂ to solve for Q's coefficients (requires a_m odd for a unique normal solution with Q(0)=1).

// Geometric series: 1 + t + t²
Polynomial<3, uint32_t> geom{{1, 1, 1}};
auto [P, Q] = pade_approximant<1, 1>(geom);
// P = 1, Q = 1 − t → 1/(1-t) recovered

Works at compile time — all operations are constexpr.


continued_fractions.h

Expands a power series A(t) into the continued fraction form

A(t) = c₀ + t / (c₁ + t / (c₂ + t / (...)))

by repeated constant-term extraction and degree reduction. The k-th convergent P_k/Q_k is computed via the recurrence:

P₋₁ = 1, P₀ = c₀, Q₋₁ = 0, Q₀ = 1
P_k = c_k · P_{k-1} + t · P_{k-2}
Q_k = c_k · Q_{k-1} + t · Q_{k-2}
DynamicPolynomial<uint32_t> geom({1, 1, 1, 1, 1, 1, 1, 1});
auto c = cf_expand(geom, 6); // {1, 1, 1, 1, 1, 1}auto [P, Q] = cf_convergent(c, 3); // 3rd convergent
W val = P.eval(2) * modinv_odd(Q.eval(2)); // evaluate at t=2

Rational functions produce finitely terminating CF expansions; transcendental series give infinite ones.


matrix.h

Generic Matrix<M, N, W> over ℤ/2^Wℤ with Gaussian elimination using odd-pivot selection (invertible elements in ℤ₂ are exactly the odd integers).

Matrix<3, 3, uint32_t> A{{{ {1, 2, 3}, {0, 1, 4}, {5, 6, 0} }}};
auto det = A.determinant();
auto inv = A.inverse(); // M×M, Gauss-Jordanauto x = A.solve({7, 11, 13}); // linear systemint r = A.rank(); // Gaussian elimination mod 2

All operations (+, , *, determinant, rank, inverse, solve, transpose, trace, rref) are constexpr.


The 32 Examples

Each example is a self-contained .cpp file in examples/. Build and run them all with cmake --build build --target run.

#ExampleWhat It Demonstrates
01basis_conversionMonomial ↔ FallingFactorial ↔ Taylor roundtrip
02formal_derivativeD = d/dt, Dⁿ annihilates deg N-1 polynomials
03forward_differenceΔ = e^D − I, identity ΔP = P(t+1) − P(t)
04taylor_shiftP(t) → P(t + δ) in monomial and FF bases
05indefinite_sumΣ = Δ⁻¹, exact inverse in FF basis
06witt_vectorsWitt addition/multiplication, ghost map, Frobenius, Verschiebung
07adams_teichmullerAdams operations ψⁿ, Teichmüller lifts
08compose_reversionPower series composition P(Q(t)), Lagrange inversion
09carry_chainC = (I−N)⁻¹, one-pass carry propagation
102adic_primitivesv₂, modinv_odd, exact_divide, Artin-Schreier ℘(x)
11stirling_numbersS₂(n,k), s₁(n,k),
12polynomial_arithmetic+, −, ×, eval in all three bases
13log_exp_seriesBinomial series (1+t)^α, geometric series
14newton_iterationNewton's method for sqrt, cuberoot in ℤ₂
15pade_approximantsRational evaluation, geometric series in ℤ₂[[t]]
16bernoulli_numbersBₙ via generating function, Σ C(n+1,k)B_k = 0
17eulerian_numbersA(n,k) table, Worpitzky identity
18bell_numbersBₙ via Stirling sum, recurrence B_{n+1} = Σ C(n,k)B_k
19hensel_liftingRoot lifting mod 2^k for polynomials over ℤ₂
20witt_divisionWitt vector inverse a⁻¹, ghost inverse verification
21resultant_discriminantResultant, discriminant via Sylvester matrix
22continued_fractionsCF expansion, convergent P/Q, finite CF for rationals
23benchmark_precisionTiming across word sizes (uint8–uint64), precision analysis
24compiletime_benchmarksCompile-time vs runtime operation timing
25csv_outputGenerates CSV files for Stirling/Witt/precision visualization
26witt_log_expWitt inverse, exp/log homomorphisms, Adams compose
27dynamic_polynomialRuntime-degree polynomial, basis conversion, D, Δ
28hardware_arithmeticadc, add_overflow, mul_overflow, carry chain integration
29pade_approximantPadé [1/1], [2/2], rational recovery, constexpr usage
30matrixMatrix operations, determinant, inverse, rank, solve
31discrete_hedgingΔ/Σ operators in finance: daily returns, discrete gamma, cumulative P&L, continuous vs discrete hedge ratios
32extension_verifyConformance tests for all four extension headers (49 checks)

Build

Dependencies

  • C++20 compiler (GCC 12+, Clang 17+)
  • dyadic — expected at ../dyadic relative to this repo (include path to ../dyadic and ../dyadic/include)

Quick start

cmake -B build
cmake --build build
# Run all 32 examples (returns 0 on pass, non-zero if any example fails)
cmake --build build --target run
# Run a single example
./build/01_basis_conversion

The run target runs every example in sequence and prints PASS/FAIL results. Example 32_extension_verify returns exit code 0 when all conformance checks pass, 1 otherwise.

Project integration

If you already have a CMake project, link against the dyadic interface target:

add_subdirectory(path/to/dyadic-examples)
target_link_libraries(my_appPRIVATEdyadic)

This gives you the -I paths for both <dyadic.h> and <dyadic/...> extension headers in a single step.

Project Structure

dyadic-examples/
├── CMakeLists.txt # Build system for all 32 examples
├── cmake/
│ └── run_all.sh # Script invoked by `--target run`
├── examples/
│ ├── 01_basis_conversion.cpp
│ ├── 02_formal_derivative.cpp
│ ├── ... # (32 .cpp files total)
│ ├── 30_matrix.cpp
│ ├── 31_discrete_hedging.cpp
│ └── 32_extension_verify.cpp
├── LICENSE # MIT
└── README.md

Design Notes

DynamicPolynomial Edge Cases

  • degree() returns -1 for empty polynomials: An empty polynomial (default-constructed with no coefficients) has degree -1. Its eval() returns 0. Multiplying an empty polynomial with any other polynomial returns an empty polynomial.
  • operator+= doesn't resize this to o's size: If o.size() > this->size(), *this is resized. But *this is never truncated if o is shorter — the extra coefficients remain.
  • All-zero DynamicPolynomial is non-empty: Constructing with DynamicPolynomial<W>({0, 0, 0}) gives a degree-0 polynomial (the trailing zeros are not trimmed). Use coeff.resize(degree() + 1) to trim.
  • Carry-chain operator*: Uses poly_mul (same as static Polynomial), NOT coefficient-wise multiplication. Use poly_mul_cw on the internal coeff array for coefficient-wise.
  • to_static<N>(dyn) truncates: If dyn.degree() >= N, the top coefficients are silently dropped.

Continued Fractions

  • All-zero series: cf_expand on an all-zero series yields all-zero CF coefficients (not an error).
  • Single-term series: A series with only a constant term produces a single CF coefficient equal to that constant.
  • cf_convergent(k) for k=0: Returns P_0 = c_0, Q_0 = 1.

Matrix

  • Singular inputs: inverse() returns the zero matrix for singular inputs (no exception). solve() returns a zero vector for singular systems. This matches the "no exceptions" design of the core library.
  • Rectangular matrices: rank(), transpose(), and operator ==/!= work on arbitrary M×N dimensions. Determinant and inverse are only defined for square matrices.

Related

License

MIT — see LICENSE.

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32 runnable examples and extension headers (dynamic polynomials, Padé approximants, continued fractions, matrices) for the dyadic 2-Adic Operator Calculus library

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