AntisymmetricMatrixQ
更多信息和选项
- AntisymmetricMatrixQ 也被称为斜对称矩阵.
- 如果 m-Transpose[m],则矩阵 m 为反对称矩阵.
- AntisymmetricMatrixQ 适用于符号和数值矩阵.
- 可以给出下列选项:
-
SameTest Automatic 检验表达式相等性的函数 Tolerance Automatic 数值近似的偏差 - 对于精确和符号矩阵,如果 f[mij,mkl] 给出 True,选项 SameTest->f 表示 mij 和 mkl 这两个项相等.
- 对于近似矩阵,可以使用选项 Tolerance->t 表示所有的项 Abs[mij]≤t 均为零.
- 对于矩阵的项 Abs[mij]>t,都进行相等性比较,除最后一个
外,其中对于 MachinePrecision 矩阵,
为 $MachineEpsilon,对于 Precision 为
的矩阵,
为
.
范例
打开所有单元 关闭所有单元基本范例 (2)
范围 (10)
基础用法 (6)
m = {{0, -2.3}, {2.3, 0}};AntisymmetricMatrixQ[m]AntihermitianMatrixQ[m]m = {{0, 2 - 3I}, {-2 + 3I, 0}};AntisymmetricMatrixQ[m]{AntisymmetricMatrixQ[Re[m]], AntisymmetricMatrixQ[Im[m]]}m = (| | | |
| - | -- | -- |
| 4 | -5 | 2 |
| 3 | -3 | -3 |
| 5 | 5 | 5 |);AntisymmetricMatrixQ[m]AntisymmetricMatrixQ[(m - m^/2)]将 AntisymmetricMatrixQ 用于任意精度矩阵:
m = RandomReal[5, {3, 3}, WorkingPrecision -> 15]AntisymmetricMatrixQ[m]将 AntisymmetricMatrixQ 用于符号矩阵:
AntisymmetricMatrixQ[{{a, b}, {c, d}}]Block[{c = -b, a = d = 0}, AntisymmetricMatrixQ[{{a, b}, {c, d}}]]AntisymmetricMatrixQ 可高效处理大型数值矩阵:
m = RandomReal[1, {1000, 1000}];AbsoluteTiming[AntisymmetricMatrixQ[m]]a = m - m^;
AbsoluteTiming[AntisymmetricMatrixQ[a]]特殊矩阵 (4)
将 AntisymmetricMatrixQ 用于稀疏矩阵:
SparseArray[{i_, j_} -> (i - j) / (i + j) ^ 2, {5, 5}]AntisymmetricMatrixQ[%]将 AntisymmetricMatrixQ 用于结构化矩阵:
SymmetrizedArray[{{1, 2} -> a, {2, 3} -> b}, {3, 3}, Antisymmetric[{1, 2}]]AntisymmetricMatrixQ[%]用于 QuantityArray 结构化矩阵:
QuantityArray[{{1, 2}, {2, 5}}, "Meters"]AntisymmetricMatrixQ[%]AntisymmetricMatrixQ[IdentityMatrix[3]]HilbertMatrix 不是反对称矩阵:
AntisymmetricMatrixQ[HilbertMatrix[5]]选项 (2)
SameTest (1)
对于正实数
,矩阵是反对称的,但 AntisymmetricMatrixQ 给出 False:
m = {{0, Log[x ^ 2]}, {-2 Log[x], 0}};AntisymmetricMatrixQ[m]使用选项 SameTest 得到正确的答案:
AntisymmetricMatrixQ[m, SameTest -> (Simplify[#1 - #2, x > 0] == 0&)]Tolerance (1)
SeedRandom[12];
m = Block[{a = RandomReal[1, {3, 3}]}, a - a^];
m = m + 10^-14 RandomReal[10, {3, 3}];AntisymmetricMatrixQ[m]调整选项 Tolerance,接受这个矩阵为反对称矩阵:
AntisymmetricMatrixQ[m, Tolerance -> 10 ^ -12](m + m^)//Norm应用 (5)
f[i_, j_] := i - jf[i, j] == -f[j, i]使用 Table 生成反对称矩阵:
AntisymmetricMatrixQ[Table[f[i, j], {i, 5}, {j, 5}]]SymmetrizedArray 能够生成具有对称性的矩阵(和一般数组):
SymmetrizedArray[{{1, 2} -> a, {2, 3} -> b}, {3, 3}, Antisymmetric[{1, 2}]]AntisymmetricMatrixQ[%]r[θ_] := (| | |
| ------ | ------- |
| Cos[θ] | -Sin[θ] |
| Sin[θ] | Cos[θ] |)D[r[θ], θ].Inverse[r[θ]]//FullSimplifyAntisymmetricMatrixQ[%]rot = RotationMatrix[θ, RandomReal[1, 3, WorkingPrecision -> 5]];
AntisymmetricMatrixQ[D[rot, θ].Inverse[rot]]{a, b, c}⨯{x, y, z} == (| | | |
| -- | -- | -- |
| 0 | -c | b |
| c | 0 | -a |
| -b | a | 0 |).{x, y, z}AntisymmetricMatrixQ[(| | | |
| -- | -- | -- |
| 0 | -c | b |
| c | 0 | -a |
| -b | a | 0 |)](| | | |
| -- | -- | -- |
| 0 | -c | b |
| c | 0 | -a |
| -b | a | 0 |).{a, b, c} == {0, 0, 0}{x, y, z}.((| | | |
| -- | -- | -- |
| 0 | -c | b |
| c | 0 | -a |
| -b | a | 0 |).{x, y, z})//Simplify(ⅆx/ⅆt) = Overscript[v, ⇀]⨯x, Overscript[v, ⇀] = {2, -1, 1}, x(0) = {1, 0, -1};vvec = {2, -1, 1};
(v = -LeviCivitaTensor[3].vvec)//MatrixFormAntisymmetricMatrixQ[v]v.{Subscript[x, 1], Subscript[x, 2], Subscript[x, 3]} == vvec⨯{Subscript[x, 1], Subscript[x, 2], Subscript[x, 3]}u[t_] := MatrixExp[v t]
x0 = {1, 0, -1};
x[t_] = u[t].x0x'[t] == v.x[t] && x[0] == x0//SimplifyOrthogonalMatrixQ[u[t]]Show[ParametricPlot3D[x[t], {t, 0., 5.}, PlotStyle -> Tube[0.02]], Graphics3D[{Opacity[.5], Sphere[{0, 0, 0}, Norm[x0]]}], PlotRange -> All]属性和关系 (15)
对于任何不是矩阵的 x,AntiymmetricMatrixQ[x] 都会返回 False:
AntisymmetricMatrixQ[Sqrt[3]]如果 m-Transpose[m],则矩阵是反对称的:
m = (| | | |
| ------ | ------- | -- |
| 0 | -2 - 2I | 3 |
| 2 + 2I | 0 | -I |
| -3 | I | 0 |);{m == -Transpose[m], AntisymmetricMatrixQ[m]}m = (| | |
| -- | -- |
| 0. | I |
| -I | 0 |);AntisymmetricMatrixQ[m]用 Diagonal 选出对角线元素:
Diagonal[m]m = (| | |
| - | -- |
| 0 | -2 |
| 2 | 0 |);{AntisymmetricMatrixQ[m], AntihermitianMatrixQ[m]}m = (| | |
| -------- | ------- |
| 0 | 2 + 2 I |
| -2 - 2 I | 0 |);{AntisymmetricMatrixQ[m], AntihermitianMatrixQ[m]}使用 Symmetrize 和对称 Antisymmetric 计算矩阵的反对称部分:
m = RandomReal[1, {3, 3}];Symmetrize[m, Antisymmetric[{1, 2}]]这等于 m 和 Transpose[m] 之间的归一化差:
% == (m - m/2)m = RandomComplex[1 + I, {3, 3}];
{sym, asym} = {(m + m) / 2, (m - m) / 2};m == sym + asym使用 SymmetricMatrixQ 检验一个矩阵是否是对称的:
{SymmetricMatrixQ[sym], AntisymmetricMatrixQ[asym]}m = Block[{a = RandomReal[1, {5, 5}]}, a - a^];{AntisymmetricMatrixQ[m], HermitianMatrixQ[I m]}实反对称 m 的 MatrixExp[m] 既是正交矩阵又是酉矩阵:
m = Symmetrize[RandomReal[1, {5, 5}], Antisymmetric[{1, 2}]];
expm = MatrixExp[m];{OrthogonalMatrixQ[expm], UnitaryMatrixQ[expm]}mc = Symmetrize[RandomComplex[1 + I, {5, 5}], Antisymmetric[{1, 2}]];
expmc = MatrixExp[mc];{OrthogonalMatrixQ[expmc], UnitaryMatrixQ[expmc]}m = Block[{a = RandomReal[1, {5, 5}]}, a - a^];{AntisymmetricMatrixQ[m], NormalMatrixQ[m]}c = (| | | |
| -- | - | - |
| 0 | 1 | I |
| -1 | 0 | 0 |
| -I | 0 | 0 |);{AntisymmetricMatrixQ[c], NormalMatrixQ[c]}m = Block[{a = RandomReal[1, {4, 4}]}, a - a];AntisymmetricMatrixQ[m]使用 Eigenvalues 求特征值:
Eigenvalues[m]//Chopc = (| | | | |
| -- | ------ | -- | ----- |
| 0 | I | -I | I |
| -I | 0 | 1 | 1 - I |
| I | -1 | 0 | -1 |
| -I | -1 + I | 1 | 0 |);AntisymmetricMatrixQ[c]Eigenvalues[c]m = Block[{a = RandomReal[1, {4, 4}]}, a - a];CharacteristicPolynomial[m,x] 仅包含 x 的偶数次幂:
CharacteristicPolynomial[m, x]//Chopm = Block[{a = RandomReal[1, {5, 5}]}, a - a];CharacteristicPolynomial[m, x]//Chopm = Block[{a = RandomReal[1, {3, 3}]}, a - a];AntisymmetricMatrixQ[m]DiagonalizableMatrixQ[m]使用 Eigenvectors 求得必要的复值特征向量:
Eigenvectors[m]//Chopc = (| | | |
| - | -- | -- |
| 0 | 0 | -I |
| 0 | 0 | 1 |
| I | -1 | 0 |);{AntisymmetricMatrixQ[c], DiagonalizableMatrixQ[c]}奇数维反对称 m 的 Det[m] 为零:
m = Block[{a = RandomComplex[1 + I, {5, 5}]}, a - a];{AntisymmetricMatrixQ[m], Det[m]//Chop}m = Block[{a = RandomReal[1, {6, 6}]}, a - a];{AntisymmetricMatrixQ[m], Det[m] >= 0}m = Block[{a = RandomComplex[1 + I, {4, 4}]}, a - a];AntisymmetricMatrixQ[Inverse[m]]m = Block[{a = RandomComplex[1 + I, {3, 3}, WorkingPrecision -> 5]}, a - a];AntisymmetricMatrixQ[MatrixPower[m, 9]]SymmetricMatrixQ[MatrixPower[m, 8]]可能存在的问题 (1)
AntisymmetricMatrixQ 对实值矩阵和复值矩阵都使用定义
:
c = (| | | |
| -- | - | - |
| 0 | 1 | I |
| -1 | 0 | 0 |
| -I | 0 | 0 |);{AntisymmetricMatrixQ[c] , c == -c}这些复数矩阵不必为正规矩阵也不必具有许多斜伴随(实反对称)矩阵的性质:
NormalMatrixQ[c]AntihermitianMatrixQ 为斜伴随 (skew-adjoint) 矩阵检验条件
:
AntihermitianMatrixQ[c]antisymmetricMatrixQ[m_] := AntisymmetricMatrixQ[m] && Element[m, Reals]antisymmetricMatrixQ[c]相关指南
-
▪
- 矩阵判断
文本
Wolfram Research (2014),AntisymmetricMatrixQ,Wolfram 语言函数,https://reference.wolfram.com/language/ref/AntisymmetricMatrixQ.html.
CMS
Wolfram 语言. 2014. "AntisymmetricMatrixQ." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/ref/AntisymmetricMatrixQ.html.
APA
Wolfram 语言. (2014). AntisymmetricMatrixQ. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/AntisymmetricMatrixQ.html 年
BibTeX
@misc{reference.wolfram_2026_antisymmetricmatrixq, author="Wolfram Research", title="{AntisymmetricMatrixQ}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/AntisymmetricMatrixQ.html}", note=[Accessed: 19-August-2026]}
BibLaTeX
@online{reference.wolfram_2026_antisymmetricmatrixq, organization={Wolfram Research}, title={AntisymmetricMatrixQ}, year={2014}, url={https://reference.wolfram.com/language/ref/AntisymmetricMatrixQ.html}, note=[Accessed: 19-August-2026]}