| 346 | |
| 347 | |
| 348 | qmatrix getRandomUnitary(int numQb) { |
| 349 | DEMAND( numQb >= 1 ); |
| 350 | |
| 351 | // create Z ~ random complex matrix (distribution not too important) |
| 352 | size_t dim = getPow2(numQb); |
| 353 | qmatrix matrZ = getRandomMatrix(dim); |
| 354 | qmatrix matrZT = getTranspose(matrZ); |
| 355 | |
| 356 | // create Z = Q R (via QR decomposition) ... |
| 357 | qmatrix matrQT = getOrthonormalisedRows(matrZ); |
| 358 | qmatrix matrQ = getTranspose(matrQT); |
| 359 | qmatrix matrR = getZeroMatrix(dim); |
| 360 | |
| 361 | // ... where R_rc = (columm c of Z) . (column r of Q) = (row c of ZT) . (row r of QT) = <r|c> |
| 362 | for (size_t r=0; r<dim; r++) |
| 363 | for (size_t c=r; c<dim; c++) |
| 364 | matrR[r][c] = getInnerProduct(matrQT[r], matrZT[c]); |
| 365 | |
| 366 | // create D = normalised diagonal of R |
| 367 | qmatrix matrD = getZeroMatrix(dim); |
| 368 | for (size_t i=0; i<dim; i++) |
| 369 | matrD[i][i] = matrR[i][i] / std::abs(matrR[i][i]); |
| 370 | |
| 371 | // create U = Q D |
| 372 | qmatrix matrU = matrQ * matrD; |
| 373 | |
| 374 | DEMAND( isApproxUnitary(matrU) ); |
| 375 | return matrU; |
| 376 | } |
| 377 | |
| 378 | |
| 379 | qmatrix getRandomDiagonalUnitary(int numQb) { |
no test coverage detected