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11 | 11 | "We consider two lenses of scalability. First, we analyze the high-level scaling of algorithms as a function of the underlying lattice. Second, we consider the practical scalability of the algorithms after transpilation to more restrictive gate sets. In the latter, we also analyze the performance of compilation software on specific QBM instances." |
12 | 12 | ] |
13 | 13 | }, |
14 | | - { |
15 | | - "cell_type": "code", |
16 | | - "execution_count": null, |
17 | | - "metadata": {}, |
18 | | - "outputs": [], |
19 | | - "source": [ |
20 | | - "%pip install qlbm matplotlib seaborn pandas" |
21 | | - ] |
22 | | - }, |
23 | 14 | { |
24 | 15 | "cell_type": "code", |
25 | 16 | "execution_count": null, |
|
30 | 21 | "from logging import Logger, getLogger\n", |
31 | 22 | "from typing import List\n", |
32 | 23 | "\n", |
33 | | - "from pytket.extensions.qulacs import QulacsBackend as TketQulacsBackend\n", |
| 24 | + "from pytket.extensions.qiskit import AerStateBackend as TketQiskitBackend\n", |
| 25 | + "from qiskit_aer import AerSimulator\n", |
34 | 26 | "\n", |
35 | 27 | "from qlbm.components import (\n", |
36 | 28 | " CQLBM,\n", |
|
76 | 68 | " compiler_platform: List[str],\n", |
77 | 69 | " target_platform: List[str],\n", |
78 | 70 | " optimization_levels: List[int],\n", |
79 | | - " backend: TketQulacsBackend | None,\n", |
| 71 | + " backend: TketQiskitBackend | None,\n", |
80 | 72 | " num_repetitions: int = 5,\n", |
81 | 73 | ") -> None:\n", |
82 | 74 | " for rep in range(num_repetitions):\n", |
|
142 | 134 | " }, # 0 Obstacles\n", |
143 | 135 | " {\n", |
144 | 136 | " \"lattice\": {\"dim\": {\"x\": 8, \"y\": 8}, \"velocities\": {\"x\": 4, \"y\": 4}},\n", |
145 | | - " \"geometry\": [{\"x\": [5, 6], \"y\": [1, 2], \"boundary\": \"specular\"}],\n", |
| 137 | + " \"geometry\": [{\"shape\": \"cuboid\", \"x\": [5, 6], \"y\": [1, 2], \"boundary\": \"specular\"}],\n", |
146 | 138 | " }, # 1 Obstacle\n", |
147 | 139 | " {\n", |
148 | 140 | " \"lattice\": {\"dim\": {\"x\": 8, \"y\": 8}, \"velocities\": {\"x\": 4, \"y\": 4}},\n", |
149 | 141 | " \"geometry\": [\n", |
150 | | - " {\"x\": [5, 6], \"y\": [1, 2], \"boundary\": \"specular\"},\n", |
151 | | - " {\"x\": [5, 6], \"y\": [5, 6], \"boundary\": \"specular\"},\n", |
| 142 | + " {\"shape\": \"cuboid\", \"x\": [5, 6], \"y\": [1, 2], \"boundary\": \"specular\"},\n", |
| 143 | + " {\"shape\": \"cuboid\", \"x\": [5, 6], \"y\": [5, 6], \"boundary\": \"specular\"},\n", |
152 | 144 | " ],\n", |
153 | 145 | " }, # 2 Obstacles\n", |
154 | 146 | "]\n", |
|
183 | 175 | " logger,\n", |
184 | 176 | " dummy_logger,\n", |
185 | 177 | " \"QISKIT\",\n", |
186 | | - " \"QULACS\",\n", |
| 178 | + " \"QISKIT\",\n", |
187 | 179 | " [0],\n", |
188 | | - " None,\n", |
| 180 | + " AerSimulator(),\n", |
189 | 181 | " num_repetitions=1,\n", |
190 | 182 | ")" |
191 | 183 | ] |
|
203 | 195 | " logger,\n", |
204 | 196 | " dummy_logger,\n", |
205 | 197 | " \"TKET\",\n", |
206 | | - " \"QULACS\",\n", |
| 198 | + " \"QISKIT\",\n", |
207 | 199 | " [0],\n", |
208 | | - " TketQulacsBackend(),\n", |
| 200 | + " AerSimulator(),\n", |
209 | 201 | " num_repetitions=1,\n", |
210 | 202 | ")\n" |
211 | 203 | ] |
|
443 | 435 | "name": "python", |
444 | 436 | "nbconvert_exporter": "python", |
445 | 437 | "pygments_lexer": "ipython3", |
446 | | - "version": "3.12.5" |
| 438 | + "version": "3.12.10" |
447 | 439 | } |
448 | 440 | }, |
449 | 441 | "nbformat": 4, |
|
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