A Quantum Approximate Optimization Algorithm with Metalearning for MaxCut Problem and Its Simulation via TensorFlow Quantum

<div>A single time step of MetaQAOA, where the classical LSTM outputs parameters <svg height="18.775pt" id="M104" style="vertical-align:-2.268099pt" version="1.1" viewbox="-0.0498162 -16.5069 40.8168 18.775" width="40.8168pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M293 -169V-141C218 -131 209 -90 209 -44C209 19 222 85 222 152C222 207 198 255 139 269V273C199 286 222 334 222 388C222 454 209 523 209 588C209 632 218 671 293 681V709C234 709 148 695 148 577C147 513 155 438 155 372C155 337 152 291 64 285V256C152 250 155 204 155 169C156 105 148 31 148 -41C148 -157 234 -169 293 -169Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,4.674,-10.582)"><path d="M588 236V289H72V236H588Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.862,-10.582)"><path d="M935 263C895 299 821 372 745 456L719 439L824 289H72V236H823L719 87L745 70C821 154 895 227 935 263Z"></path></g><g transform="matrix(.013,0,0,-0.013,7.915,-2.062)"><path d="M471 401C471 442 455 448 440 448C421 448 389 439 366 424C314 390 233 331 165 242H163L187 345C193 372 197 393 197 409C197 435 189 448 174 448C146 448 80 408 23 349L40 327C64 351 97 373 107 373C115 373 118 366 111 337L29 -4L36 -12C56 -4 83 3 110 9C123 69 136 126 150 172C227 283 336 381 377 381C392 381 396 370 379 298L326 74C290 -77 273 -172 273 -197C273 -219 316 -261 346 -261L353 -246C348 -227 352 -174 374 -66L457 310C467 352 471 381 471 401Z"></path></g><g transform="matrix(.013,0,0,-0.013,17.765,0)"><path d="M95 130C70 130 46 113 46 88C46 72 54 64 59 64C93 55 121 33 121 -3C121 -41 93 -68 44 -88L55 -117C117 -98 186 -56 186 22C186 91 131 130 95 130Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,23.332,-10.582)"><path d="M588 236V289H72V236H588Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,27.52,-10.582)"><path d="M935 263C895 299 821 372 745 456L719 439L824 289H72V236H823L719 87L745 70C821 154 895 227 935 263Z"></path></g><g transform="matrix(.013,0,0,-0.013,26.266,-2.062)"><path d="M478 372C478 418 458 448 431 448C409 448 389 431 389 410C389 404 391 400 394 395C398 388 406 371 406 348C406 253 308 122 251 51H249C254 122 249 257 231 336C212 421 189 448 159 448C126 448 75 412 23 327L48 306C83 354 103 371 115 371C125 371 134 360 144 334C185 224 192 64 183 -19C146 -100 116 -202 110 -244L125 -261C154 -259 208 -234 222 -220C222 -194 225 -84 235 -23C247 -3 273 36 308 79C379 165 478 288 478 372Z"></path></g><g transform="matrix(.013,0,0,-0.013,36.161,0)"><path d="M283 255V284C195 290 192 337 192 375C192 436 200 508 200 580C200 696 116 709 54 709V681C127 671 139 634 139 588C138 524 125 452 125 387C125 333 149 286 209 272V268C148 253 125 206 125 151C126 87 139 16 139 -47C139 -92 127 -131 54 -141V-169C115 -169 200 -152 200 -41C200 32 192 104 192 164C192 202 195 249 283 255Z"></path></g></svg> dependent on the expectation value <svg height="14.0749pt" id="M105" style="vertical-align:-2.1507pt" version="1.1" viewbox="-0.0498162 -11.9242 21.8389 14.0749" width="21.8389pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M360 -163L167 270L360 703H298L106 273V267L298 -163H360Z"></path></g><g transform="matrix(.013,0,0,-0.013,7.405,-2.897)"><path d="M658 557C549 593 437 629 340 673H318C222 629 109 593 0 557L9 532C116 551 225 577 329 602C435 576 543 551 649 532L658 557Z"></path></g><g transform="matrix(.013,0,0,-0.013,5.369,0)"><path d="M828 650H570L564 622C646 614 650 609 634 524L604 366H253L281 524C296 608 308 615 382 622L388 650H132L126 622C211 615 214 609 198 524L121 122C106 42 102 35 23 28L17 0H276L282 28C196 35 191 40 206 122L243 324H597L559 123C544 42 537 35 452 28L446 0H710L716 28C632 35 628 43 643 122L719 524C735 610 741 615 822 622L828 650Z"></path></g><g transform="matrix(.013,0,0,-0.013,16.33,0)"><path d="M307 267V273L115 703H53L246 270L53 -163H115L307 267Z"></path></g></svg> by the QNN.</div>

Mathematical Problems in Engineering

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Figure 4

Figure 4: A Quantum Approximate Optimization Algorithm with Metalearning for MaxCut Problem and Its Simulation via TensorFlow Quantum 