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逐步
Circuit: 设置optimize=False则读入完全不优化的线路(默认为 True)，system: "IBM" 或者 "Surface"，读入的数据的平台信息mapper.execute时候不设置strategy默认精确匹配circuit.save: 新加system参数指定输出平台的种类
from qcpm import Mapper, Circuit
# Step 1. init mapper
mapper = Mapper()
# Step 2. load and int circuit
circuit = Circuit('data.qasm', optimize=True, system='IBM')
# Step 3. execute mapping
mapper.execute(circuit, strategy='MCM')
# Step 4. save results.
circuit.save('data_mapped.qasm', system='Surface')QCPM.execute的参数:from,to可以是文件也可以是文件夹路径。strategy默认不指定为精确匹配。system可以：1.system="IBM"指定一个平台格式，这时候输入输出都为同一格式，不指定默认为 "IBM"。2.system=["IBM", "Surface"]，列表，分别是读入格式与输出格式。
from qcpm import QCPatternMapper
QCPM = QCPatternMapper()
QCPM.execute(circuit_path, './circuit_after',
strategy='MCM', system=['IBM', 'Surface'])
# QCPM.execute(circuit_path, './circuit_after',
# strategy='MCM', system='IBM')-
circuit data: (.qasm)
example.qasm:OPENQASM 2.0; include "qelib1.inc"; qreg q[16]; creg c[16]; cx q[4],q[1]; t q[4]; t q[2]; q[0]; ... -
pattern data: (.json)
pattern.json:[ { "src": [ ["cx", [0, 1]], ["cx", [1, 2]], ["cx", [0, 1]] ], "dst": [ ["cx", [0, 2]], ["cx", [1, 2]] ] }, ... ]上述 pattern 描述了如下映射：
|0>: - o ----- o - | | |1>: - X - o - X - | |2>: ----- X -----到
|0>: - o ----- | |1>: - | - o - | | |2>: - X - X - -
用于 Reduction/Commutation 的模式也按相同的语法描述。例如
commutation.json:[ { "src": [ ["h", [0]], ["s", [0]], ["h", [0]] ], "dst": [ ["sdg", [0]], ["h", [0]], ["sdg", [0]] ] }, ...相关文件在
qcpm/optimization/rules下
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逐步手动运行
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Mapper从 json 文件表示的映射关系中构建映射模式，用于内部的映射处理。 -
Circuit从 qasm 中读入数据并构建对象。 -
mapper.execute(circuit): 在线路 circuit 上应用映射 mapper -
circuit.save(circuit_output_path): 将处理后的 Circuit 对象以 qasm 数据的格式输出至指定文件。
from qcpm import Mapper, Circuit mapper = Mapper(pattern_path) # ./.json circuit = Circuit(circuit_path) # ./.qasm mapper.execute(circuit) circuit.save(circuit_output) # ./.qasm
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使用封装的
QCPatternMapper运行其中
log=参数给定日志文件的输出路径。不设置的情况下默认为标准输出。execute函数的参数分别为输入的 qasm 文件路径与输出的 qasm 路径(处理后)。不设置的情况下则不保存映射后的结果。from qcpm import QCPatternMapper QCPM = QCPatternMapper(pattern_path, log=log_path) QCPM.execute(circuit_path, circuit_output)
测试结果的输出见 log.txt
包括：
根据输入构建的映射模式：
Pattern 1
cx [0, 1]
cx [1, 2]
cx [0, 1]
=>
cx [0, 2]
cx [1, 2]
...
线路根据对应模式查找的可替换的候选项：
Pattern: 1
pos: 73 # 匹配处的第一个门操作在序列中的位置
# 以下是匹配到的对应的门操作序列
No: 73, cx [4, 1]
No: 74, cx [1, 2]
No: 75, cx [4, 1]
...
# 所有候选项的匹配位置
Candidate:
[73, 75]
候选替换方案生成：
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按节约(saving)成本的排序输出所有可能的备选替换方案(排除冲突)(old)：
Rank: 1 Plan: 1 [Pos: 54 xx => I, Pos: 76 cc => c, Pos: 78 cc => c, Pos: 130 cc => I, Pos: 133 cc => I, Pos: 194 cc => c, Pos: 230 xcx => c] Change: 7, Saving: 18 Rank: 2 Plan: 2 [Pos: 54 xx => I, Pos: 76 cc => c, Pos: 78 cc => c, Pos: 130 cc => I, Pos: 133 cc => I, Pos: 195 cc => c, Pos: 230 xcx => c] Change: 7, Saving: 18 ...... Total Plans: 36其中
Change为该方案需实际替换的模式数量(非替换的门数量)，Saving为该方案所能节省的成本(用门的深度来衡量) -
使用蒙特卡洛模拟的情况下的候选方案输出日志如下(当前实现)：
********************** * * * Generate Plans * * * ********************** Sorted Candidates: [Pos: [1, 4] cc => c, Pos: [1, 4, 5] ccc => cc, Pos: [4, 5] cc => c, Pos: [5, 6] cc => c, Pos: [5, 8] cc => I, Pos: [5, 6, 8] ccc => cc, Pos: [6, 7] cc => c, Pos: [7, 9] cc => c, Pos: [7, 10] cc => I, Pos: [7, 9, 10] ccc => cc, Pos: [15, 16] cc => c, Pos: [16, 17] cc => c, Pos: [22, 25] xx => I, Pos: [33, 37] xx => I, Pos: [35, 36] cc => c, Pos: [40, 42] xx => I, Pos: [41, 43] cc => I, Pos: [43, 44] cc => c] Monte Carlo-based plan searching ------------ Expansion: Candidates size: 3 Pos: [1, 4] cc => c Pos: [1, 4, 5] ccc => cc Pos: [4, 5] cc => c Selected: Pos: [1, 4] cc => c ... xchxccccccccxxcccchc ... target: ^ ^ ---------- Expansion: Candidates size: 4 Pos: [5, 6] cc => c Pos: [5, 8] cc => I Pos: [5, 6, 8] ccc => cc Pos: [6, 7] cc => c Selected: Pos: [5, 8] cc => I ... cccccccxxcccchcRhxcc ... target: ^ ^ ...... Complete Plan: Pos: [1, 4] cc => c Pos: [5, 8] cc => I Pos: [7, 10] cc => I Pos: [16, 17] cc => c Pos: [22, 25] xx => I Pos: [33, 37] xx => I Pos: [35, 36] cc => c Pos: [40, 42] xx => I Pos: [41, 43] cc => I Total Saving: 24
根据选择的最优方案进行映射：
**************************
* *
* Apply Mapping Plan *
* *
**************************
Selected Best Plan:
[Pos: [1, 4] cc => c,
Pos: [5, 8] cc => I,
Pos: [7, 10] cc => I,
Pos: [16, 17] cc => c,
Pos: [22, 25] xx => I,
Pos: [33, 37] xx => I,
Pos: [35, 36] cc => c,
Pos: [40, 42] xx => I,
Pos: [41, 43] cc => I]
Change: 9, Saving: 24
Circuit before: xchxccccccccxxcccchcRhxccxcchRhchxcccxchxcxccch
---------------
Apply: Pos: [1, 4] cc => c
Apply: Pos: [5, 8] cc => I
Apply: Pos: [7, 10] cc => I
Apply: Pos: [16, 17] cc => c
Apply: Pos: [22, 25] xx => I
Apply: Pos: [33, 37] xx => I
Apply: Pos: [35, 36] cc => c
Apply: Pos: [40, 42] xx => I
Apply: Pos: [41, 43] cc => I
---------------
Circuit after: xchxcccxxccchcRhcccchRhchccchcch