From 2c668477f04d885504c53f21cc720569d7ee0406 Mon Sep 17 00:00:00 2001 From: cuda-quantum-bot Date: Sat, 16 Dec 2023 00:57:35 +0000 Subject: [PATCH] Docs preview for PR #1027. --- .../cudaq/algorithmic_primitives.rst.txt | 66 ++++++++++++++++++ pr-1027/api/languages/cpp_api.html | 13 +++- pr-1027/api/languages/python_api.html | 2 +- pr-1027/genindex.html | 2 +- pr-1027/objects.inv | Bin 34741 -> 34778 bytes pr-1027/searchindex.js | 2 +- .../cudaq/algorithmic_primitives.html | 61 ++++++++++++++++ .../cpp/algorithms/amplitude_estimation.cpp | 6 +- .../cpp/algorithms/bernstein_vazirani.cpp | 4 +- .../sphinx/examples/cpp/algorithms/grover.cpp | 6 +- .../cpp/algorithms/phase_estimation.cpp | 4 +- .../examples/cpp/algorithms/qaoa_maxcut.cpp | 2 +- .../sphinx/examples/cpp/algorithms/vqe_h2.cpp | 2 +- .../cpp/basics/cuquantum_backends.cpp | 2 +- .../cpp/basics/cutensornet_backends.cpp | 2 +- .../cpp/basics/expectation_values.cpp | 2 +- .../cpp/basics/mid_circuit_measurement.cpp | 2 +- .../basics/multi_controlled_operations.cpp | 4 +- .../examples/cpp/basics/static_kernel.cpp | 2 +- .../examples/cpp/other/compute_actions.cpp | 4 +- .../sphinx/examples/cpp/other/gradients.cpp | 2 +- .../examples/cpp/other/iterative_qpe.cpp | 2 +- .../examples/cpp/other/random_walk_qpe.cpp | 2 +- .../sphinx/examples/cpp/providers/ionq.cpp | 2 +- pr-1027/sphinx/examples/cpp/providers/iqm.cpp | 2 +- .../examples/cpp/providers/photonics.cpp | 2 +- .../examples/cpp/providers/quantinuum.cpp | 2 +- .../cudaq/algorithmic_primitives.rst | 66 ++++++++++++++++++ pr-1027/using/cpp.html | 14 ++-- 29 files changed, 243 insertions(+), 39 deletions(-) diff --git a/pr-1027/_sources/specification/cudaq/algorithmic_primitives.rst.txt b/pr-1027/_sources/specification/cudaq/algorithmic_primitives.rst.txt index 9c0e3ac350..4256436d22 100644 --- a/pr-1027/_sources/specification/cudaq/algorithmic_primitives.rst.txt +++ b/pr-1027/_sources/specification/cudaq/algorithmic_primitives.rst.txt @@ -132,6 +132,72 @@ of an NOT operation. The :code:`sample_result` returned for this sampling tasks contains the default :code:`__global__` register as well as the user specified :code:`reg1` register. +The order of the bits in the :code:`__global__` register will depend on how your +kernel is written: + +1. If no measurements appear in the kernel, or if any quantum operations occur + after the final measurements in the kernel, then the :code:`__global__` + register is formed with implicit measurements being added for *all* the + qubits defined in the kernel, and the measurements all occur at the end of + the kernel. The order of the bits in the bitstring corresponds to the *order + that the qubits were defined in the kernel*. That is - the :code:`[0]` + element in the :code:`__global__` bitstring corresponds with the first + declared qubit in the kernel. For example, + + .. code-block:: cpp + + auto kernel = []() __qpu__ { + cudaq::qubit a, b; + x(a); + }; + cudaq::sample(kernel).dump(); + + should produce + + .. code-block:: bash + + { + __global__ : { 10:1000 } + } + +2. Conversely, if any measurements appear in the kernel and the final quantum + operation of the kernel is a measurement, then the :code:`__global__` + register is formed such that the order of the bits in the bitstring + corresponds to the *order of the measurements performed in the kernel*. + However, similar to #1, the values of the sampled qubits always correspond to + the values *at the end of the kernel execution*. That is - if a qubit is + measured in the middle of a kernel and subsequent operations change the state + of the qubit, the qubit will be implicitly re-measured at the end of the + kernel, and that re-measured value is the value that will appear in the + :code:`__global__` register. For example, + + .. code-block:: cpp + + auto kernel = []() __qpu__ { + cudaq::qubit a, b; + x(a); + mz(b); + mz(a); + }; + cudaq::sample(kernel).dump(); + + should produce + + .. code-block:: bash + + { + __global__ : { 01:1000 } + } + +.. note:: + + If you don't specify any measurements in your kernel and allow the :code:`nvq++` + compiler to perform passes that introduce ancilla qubits into your kernel, it + may be difficult to discern which qubits are the ancilla qubits vs which ones + are your qubits. In this case, it is recommend that you provide explicit + measurements in your kernel in order to only receive measurements from your + qubits and silently discard the measurements from the ancillary qubits. + The API exposed by the :code:`sample_result` data type allows one to extract the information contained at a variety of levels and for each available register name. One can get the number of times a bit string was observed via diff --git a/pr-1027/api/languages/cpp_api.html b/pr-1027/api/languages/cpp_api.html index e4c1efeef5..56dcc4e6b5 100644 --- a/pr-1027/api/languages/cpp_api.html +++ b/pr-1027/api/languages/cpp_api.html @@ -1223,6 +1223,17 @@

Common

Nullary constructor.

+
+
+sample_result(ExecutionResult &&result)
+

The constructor, sets the global sample result.

+
+
Parameters:
+

result –

+
+
+
+
sample_result(ExecutionResult &result)
@@ -1493,7 +1504,7 @@

Common
Parameters:
    -

  • idx – Vector of indices such that newBitStr(:) = oldBitStr(idx(:))

    • +

  • idx – Vector of indices such that newBitStr(:) = oldBitStr(idx(:))

  • registerName – register name to process (defaults to global)

diff --git a/pr-1027/api/languages/python_api.html b/pr-1027/api/languages/python_api.html index 08e3363b44..96c129a7dd 100644 --- a/pr-1027/api/languages/python_api.html +++ b/pr-1027/api/languages/python_api.html @@ -3626,7 +3626,7 @@

Data Typesstatic random()
-random(qubit_count: int, term_count: int, seed: int = 2135729819) → cudaq.SpinOperator
+random(qubit_count: int, term_count: int, seed: int = 2512440913) → cudaq.SpinOperator

Return a random SpinOperator on the given number of qubits (qubit_count) and composed of the given number of terms (term_count). An optional seed value may also be provided.

diff --git a/pr-1027/genindex.html b/pr-1027/genindex.html index f062a0db11..538ab6df75 100644 --- a/pr-1027/genindex.html +++ b/pr-1027/genindex.html @@ -1085,7 +1085,7 @@

C

  • cudaq::sample_result::reorder (C++ function)
    • -
  • cudaq::sample_result::sample_result (C++ function), [1], [2], [3], [4] +
  • cudaq::sample_result::sample_result (C++ function), [1], [2], [3], [4], [5]
  • cudaq::sample_result::serialize (C++ function)
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Quantum Algorithmic Primitives", "8. Control Flow", "9. Just-in-Time Kernel Creation", "13. Example Programs", "6. Quantum Kernels", "1. Machine Model", "2. Namespace", "5. Quantum Intrinsic Operations", "4. Quantum Operators", "10. Quantum Programming Patterns", "11. Quantum Platform", "7. Sub-circuit Synthesis", "3. Quantum Types", "Specifications", "Quake Dialect", "Advanced CUDA Quantum Topics", "CUDA Quantum and CMake", "Working with the CUDA Quantum IR", "Create your Own CUDA Quantum Compiler Pass", "Extending CUDA Quantum with a new Simulator", "CUDA Quantum in C++", "CUDA Quantum Basics", "Allocating and Using Quantum Memory in CUDA Quantum", "Creating Kernels Dynamically with the cudaq::kernel_builder", "Compiling and Executing CUDA Quantum Programs", "Generic Library Functions", "What is a CUDA Quantum Kernel?", "Taking Advantage of the Underlying Quantum Platform", "Prerequisites for a CUDA Quantum Code", "Runtime Versus Compile-time Kernels", "Variational Algorithms with CUDA Quantum", "Debugging and Verbose Simulation Output", "CUDA Quantum by Example", "CUDA Quantum Hardware Backends", "CUDA Quantum in Python", "CUDA Quantum Simulation Backends", "CUDA Quantum Tutorials", "CUDA Quantum Versions"], "terms": {"c": [0, 1, 3, 10, 11, 13, 15, 16, 18, 19, 20, 21, 22, 26, 30, 31, 36, 38, 40, 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34, 35, 36, 37, 40, 41, 44, 48, 51], "doe": [2, 3, 11, 12, 14, 26, 36, 38, 41, 51], "consid": [2, 3, 11, 19, 28, 41, 43], "valu": [2, 3, 4, 5, 6, 7, 14, 16, 18, 22, 28, 31, 36, 39, 40, 46, 48, 49], "num_qubit": 2, "num_term": 2, "get_coeffici": [2, 3, 22], "get": [2, 3, 8, 10, 12, 14, 16, 33, 34, 36, 37, 41, 47, 48, 51], "throw": [2, 36, 49], "except": [2, 3], "get_raw_data": [2, 3], "is_ident": [2, 3, 22], "void": [2, 3, 14, 16, 17, 18, 21, 22, 24, 25, 26, 31, 32, 33, 34, 36, 37, 40, 44], "dump": [2, 3, 5, 7, 8, 14, 17, 34, 39, 41, 48], "string": [2, 3, 11, 14, 16, 22, 24, 31, 34, 37, 39, 48], "standard": [2, 13, 14, 15, 16, 18, 21, 31, 32, 34, 41], "out": [2, 3, 8, 11, 14, 19, 26, 28, 30, 33, 34, 36, 38, 41, 44, 45, 48, 49], "to_str": [2, 3, 22], "printcoeffici": 2, "getdatarepresent": 2, "distribute_term": [2, 3], "numchunk": 2, "distribut": [2, 3, 7, 8, 11, 19, 48, 49], "chunk": [2, 3, 19], "for_each_term": [2, 3, 22], "give": [2, 11, 14, 34, 37, 41, 48, 50], "functor": 2, "method": [2, 3, 6, 14, 16, 41, 44, 48], "reduct": 2, "lambda": [2, 14, 18, 31, 34, 37, 40, 44, 48], "captur": [2, 18], "variabl": [2, 3, 7, 11, 18, 19, 34, 36, 41, 45, 47, 48, 49], "for_each_pauli": [2, 3, 22], "thrown": [2, 3], "than": [2, 3, 11, 21, 28, 49], "user": [2, 3, 7, 11, 14, 16, 18, 31, 33, 34, 39, 40, 47, 48], "should": [2, 3, 11, 14, 15, 18, 19, 21, 22, 24, 26, 33, 34, 37, 41, 42, 43, 47, 48, 49], "pass": [2, 3, 6, 10, 11, 13, 14, 18, 19, 22, 26, 29, 31, 34, 36, 37, 47, 48], "index": [2, 3, 19, 22, 24, 26, 28, 33, 37, 41, 48], "complex_matrix": 2, "to_matrix": [2, 3], "dens": 2, "to_sparse_matrix": [2, 3], "row": [2, 3], "col": 2, "static": [2, 3, 14, 22, 26, 31, 36, 37, 43], "random": [2, 3, 7, 41, 48, 49], "nterm": 2, "unsign": 2, "int": [2, 3, 6, 14, 17, 25, 26, 31, 33, 34, 36, 39, 40, 41, 43, 48], "seed": [2, 3, 7, 48, 49], "random_devic": 2, "act": [2, 4, 28, 49], "specifi": [2, 3, 5, 11, 14, 18, 19, 22, 24, 25, 31, 33, 34, 36, 38, 41, 47, 48, 49], "overrid": [2, 14, 32, 49], "repeat": [2, 14, 48], "from_word": [2, 3], "pauliword": 2, "input": [2, 3, 6, 7, 14, 16, 18, 25, 26, 34, 37, 39, 40, 43, 44, 48], "word": [2, 3, 48], "g": [2, 3, 11, 14, 15, 18, 21, 22, 28, 30, 31, 33, 34, 38, 41, 47], "xyx": [2, 3], "3rd": 2, "second": [2, 3, 34, 44], "typenam": [2, 14, 16, 17, 18, 21, 25], "qualifiedspinop": 2, "struct": [2, 14, 16, 17, 18, 21, 25, 31, 32, 34, 36, 37, 40, 43, 44], "constexpr": [2, 16, 26], "dyn": [2, 26, 34, 36], "level": [2, 14, 19, 21, 22, 30, 31, 33, 36, 40], "qudit": [2, 18, 19, 21, 22, 36], "d": [2, 3, 11, 17, 19, 26, 34, 47, 48], "system": [2, 3, 7, 14, 19, 24, 26, 28, 30, 32, 34, 41, 47, 48, 49], "inlin": [2, 14, 31], "new": [2, 3, 10, 11, 14, 16, 28, 29, 31], "uniqu": [2, 3, 13, 14, 19, 21, 26, 35], "enable_if_t": 2, "A": [2, 3, 7, 11, 14, 21, 28, 32, 33, 40, 47, 48], "contain": [2, 3, 14, 18, 19, 24, 28, 31, 33, 34, 36, 41, 48, 49], "dynam": [2, 3, 15, 16, 19, 26, 31, 34, 36], "time": [2, 3, 5, 7, 8, 10, 11, 13, 14, 17, 19, 23, 26, 27, 31, 34, 35, 36, 39, 48, 49], "By": [2, 14, 39, 41, 47, 48, 49], "like": [2, 3, 5, 7, 11, 14, 26, 30, 31, 33, 34, 36, 38, 41, 43, 44, 48], "paramet": [2, 3, 4, 6, 7, 9, 14, 21, 26, 33, 34, 36, 37, 39, 43, 44, 47, 48], "value_typ": 2, "indic": [2, 3, 18, 21, 22, 26, 33, 34, 36, 40, 48], "underli": [2, 3, 14, 24, 26, 33, 36, 47], "auto": [2, 14, 15, 16, 17, 18, 22, 25, 26, 31, 32, 34, 36, 37, 39, 40, 41, 43, 44], "interfac": [2, 26, 33, 49], "idx": [2, 6, 22, 26], "qspan": [2, 17, 18, 25, 36, 39, 40], "front": [2, 17, 25, 26, 34, 36], "count": [2, 3, 6, 7, 14, 16, 17, 22, 26, 31, 33, 34, 39, 41, 48], "back": [2, 7, 11, 17, 26, 28, 34, 48], "last": [2, 26, 41, 48], "slice": [2, 3, 22, 26, 36], "clear": [2, 3, 14, 26, 33, 40], "destroi": [2, 26], "postcondit": [2, 26], "observe_result": [2, 3, 14, 34], "encapsul": [2, 6, 14, 26], "observ": [2, 3, 4, 6, 7, 17, 33, 34, 37, 39, 41, 42, 44, 47, 48, 49], "call": [2, 3, 4, 5, 7, 14, 16, 18, 19, 25, 31, 33, 34, 36, 37, 40, 44, 48, 49], "includ": [2, 3, 11, 12, 14, 17, 31, 32, 33, 34, 38, 42, 48, 51], "measur": [2, 3, 5, 8, 14, 15, 17, 18, 19, 21, 28, 31, 33, 34, 39, 41, 48, 49], "execut": [2, 7, 10, 11, 12, 14, 16, 18, 19, 24, 25, 30, 31, 33, 34, 40, 41, 45, 47, 48, 49, 51], "ansatz": [2, 4, 9, 14, 34, 37, 39, 41, 44, 48], "circuit": [2, 3, 6, 7, 10, 13, 14, 15, 18, 19, 22, 23, 27, 28, 31, 32, 36, 37, 38, 41, 43, 47, 48, 49], "global": [2, 3, 14, 18, 36], "expect": [2, 3, 4, 5, 6, 7, 9, 11, 14, 39, 46, 48, 49], "h": [2, 3, 5, 6, 7, 9, 14, 16, 17, 22, 25, 26, 28, 31, 32, 33, 34, 37, 39, 41, 42, 43, 44, 47, 48], "precomput": 2, "psi": [2, 4, 5, 14, 17], "sample_result": [2, 3, 14, 34], "If": [2, 3, 5, 6, 7, 11, 14, 28, 30, 39, 48, 49], "wa": [2, 3, 14, 30, 31, 34, 39, 41], "shot": [2, 3, 14, 17, 33, 34, 39, 47], "base": [2, 3, 9, 11, 12, 13, 14, 16, 20, 21, 31, 33, 38, 41, 44, 48, 49, 51], "raw_data": [2, 14], "raw": [2, 3, 6], "convers": 2, "simpli": [2, 11, 48], "ignor": [2, 49], "fine": [2, 14, 34], "grain": [2, 14, 34], "explicitli": [2, 28, 31, 47, 49], "request": [2, 11, 14, 49], "oppos": [2, 37], "observe_data": 2, "spinoptyp": [2, 14], "sub": [2, 3, 13, 14, 17, 18, 27, 36, 44], "id_coeffici": [2, 14], "executioncontext": 2, "abstract": [2, 14, 16, 21, 22, 24, 26, 37, 41], "how": [2, 4, 7, 11, 12, 14, 16, 30, 31, 33, 34, 35, 43, 46, 48, 49, 51], "name": [2, 3, 7, 11, 14, 16, 21, 24, 30, 31, 33, 34, 38, 39, 48], "shots_": 2, "member": [2, 18], "basic": [2, 4, 10, 11, 23, 38], "sampl": [2, 3, 7, 8, 11, 16, 33, 34, 39, 41, 42, 47, 48, 49], "option": [2, 3, 11, 14, 16, 21, 24, 33, 34, 38, 48], "result": [2, 3, 4, 5, 7, 8, 11, 14, 15, 16, 17, 19, 28, 31, 33, 34, 39, 41, 47, 48, 49], "invoc": [2, 3, 16, 24, 33, 38, 41, 44, 49], "expectationvalu": 2, "nullopt": 2, "hasconditionalsonmeasureresult": 2, "fals": [2, 6, 11, 48], "being": [2, 3, 4, 8, 14, 28, 34, 48, 49], "ha": [2, 3, 7, 8, 9, 11, 14, 28, 34, 36, 47, 48, 49], "statement": [2, 14, 15, 19], "noise_model": [2, 3, 8, 34, 48], "noisemodel": [2, 3, 8, 48], "nullptr": 2, "current": [2, 3, 11, 12, 14, 24, 33, 36, 44, 47, 48, 49, 51], "canhandleobserv": 2, "flag": [2, 11, 31, 32, 34, 38, 41, 47, 49], "handl": [2, 3, 33, 34, 41, 47, 48, 49], "task": [2, 14, 22, 23, 31, 33, 41], "under": [2, 11, 32, 33, 47], "asyncexec": 2, "occur": [2, 3, 19, 34, 48], "asynchron": [2, 3, 7, 14, 24, 34, 48], "detail": [2, 11, 19, 33, 40, 47], "futur": [2, 3, 7, 11, 14, 34, 41, 47, 48, 49], "futureresult": 2, "store": [2, 3, 7, 19, 26, 31, 34, 41], "simulationdata": 2, "mechan": [2, 14, 16, 22, 26, 28, 32, 39, 45], "simul": [2, 4, 5, 7, 10, 12, 13, 14, 29, 31, 38, 41, 46, 47, 51], "client": [2, 14], "extract": [2, 3, 6, 14, 16, 17, 22, 28, 31, 36, 44, 48], "resourc": [2, 11, 23, 24, 38, 49], "kernelresourc": 2, "run": [2, 3, 6, 7, 11, 13, 14, 30, 31, 33, 34, 38, 47, 48, 49], "tracer": 2, "persist": [2, 14, 19], "trace": 2, "kernelnam": 2, "batchiter": 2, "batch": [2, 6, 7, 19], "observe_n": 2, "sample_n": 2, "totaliter": 2, "registernam": [2, 14], "mid": [2, 3, 49], "mode": [2, 5, 31, 38], "keep": [2, 14, 49], "track": [2, 14], "job": [2, 11, 14, 34, 48], "identifi": [2, 11, 19], "qpu": [2, 3, 14, 19, 24, 33, 41, 47, 48], "ani": [2, 3, 7, 8, 11, 14, 18, 23, 25, 26, 33, 34, 37, 39, 40, 42, 45, 47, 48, 49], "extra": [2, 28, 34, 47, 48], "configur": [2, 11, 18, 24, 30, 31, 33, 34, 38, 39, 40, 47, 49], "inform": [2, 3, 11, 12, 14, 19, 21, 24, 26, 31, 34, 36, 41, 47, 48, 49, 51], "need": [2, 5, 7, 8, 11, 28, 30, 33, 37, 41, 44, 47, 48, 49], "retriev": [2, 3, 14, 48], "later": [2, 14, 34, 41, 48], "server": [2, 11, 47, 48], "file": [2, 7, 11, 14, 30, 31, 32, 33, 34, 38, 41, 42, 45, 47, 48], "read": [2, 3, 34, 48], "wrap": [2, 14, 16, 28], "t": [2, 3, 11, 17, 18, 22, 36, 37, 39, 48], "case": [2, 3, 8, 14, 28, 34, 37, 41, 48], "must": [2, 3, 5, 14, 18, 23, 26, 28, 32, 33, 34, 36, 38, 39, 40, 42, 44, 47, 48, 49], "some": [2, 3, 11, 14, 18, 28, 30, 31, 32, 33, 37, 40, 41], "point": [2, 3, 14, 18, 21, 31, 33, 36, 38, 39, 40, 41, 47, 49], "within": [2, 3, 11, 14, 18, 20, 22, 23, 26, 30, 32, 34, 48, 49], "same": [2, 3, 11, 14, 28, 31, 33, 34, 36, 41, 47, 48], "runtim": [2, 10, 11, 16, 19, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 47, 49], "move": [2, 6, 32], "_job": 2, "qpunamein": 2, "config": [2, 11, 33], "info": [2, 31, 45], "requir": [2, 3, 6, 7, 14, 18, 23, 25, 26, 28, 30, 34, 37, 40, 42, 43, 44, 47, 48, 49], "abl": [2, 11, 14, 19, 23, 47, 48], "date": 2, "even": [2, 11, 49], "after": [2, 3, 11, 14, 31, 34, 48], "async_result": [2, 34, 48], "face": 2, "which": [2, 3, 4, 5, 6, 7, 8, 11, 12, 14, 16, 18, 19, 22, 26, 28, 30, 31, 33, 34, 36, 38, 39, 47, 48, 49, 51], "itself": [2, 16, 25, 28, 37, 41], "collect": [2, 3, 7, 23], "pertin": [2, 14, 20, 25, 26], "remot": [2, 10, 14, 19, 45], "rest": [2, 11, 47, 48], "wait": [2, 3, 34, 41], "until": [2, 3, 34], "readi": [2, 11, 34, 48], "executionresult": 2, "bit": [2, 8, 14, 17, 19, 26, 28, 33, 34, 39, 48], "correspond": [2, 3, 4, 14, 34, 39, 48], "well": [2, 3, 11, 12, 14, 19, 30, 33, 36, 48, 49, 51], "integ": [2, 3, 24], "1st": [2, 8], "bitstr": [2, 3, 14, 48], "m": [2, 7, 11, 22, 31, 49], "tripl": [2, 31], "long": [2, 11, 14, 34, 48], "length": [2, 48], "deseri": 2, "discuss": [2, 32, 35, 36], "brief": [2, 33, 34, 48], "countsdictionari": [2, 14], "assum": [2, 11, 19, 26, 33, 34], "expval": [2, 14], "other": [2, 3, 10, 11, 16, 18, 22, 26, 28, 36, 40, 41, 49], "appendresult": 2, "globalregisternam": [2, 14], "classic": [2, 13, 15, 19, 21, 22, 26, 28, 30, 31, 33, 34, 35, 36, 38, 39, 40, 41, 48], "sequentialdata": 2, "sequenti": [2, 3, 14], "collat": [2, 3], "": [2, 3, 5, 6, 8, 11, 14, 19, 24, 26, 28, 30, 31, 32, 34, 37, 39, 43, 47, 48], "holist": 2, "nullari": 2, "precomputedexp": 2, "__global__": [2, 3, 14], "has_expect": 2, "string_view": [2, 14, 33], "anoth": [2, 3, 17, 18, 28, 34, 39, 48], "register_nam": [2, 3, 14], "tandem": [2, 7, 44], "to_map": [2, 14], "regnam": 2, "merg": [2, 31], "necessari": [2, 11, 31, 34, 47, 49], "document": [2, 3, 10, 11, 12, 21, 32, 33, 47, 51], "exp_val_z": 2, "deprec": [2, 3], "probabl": [2, 3, 8, 14, 34, 48], "most_prob": [2, 3, 48], "most": [2, 3, 11, 14, 28, 30, 31, 48], "ostream": 2, "output": [2, 6, 11, 31, 40, 47], "stream": [2, 19], "unord": 2, "get_margin": [2, 14], "marginalindic": [2, 14], "margin": 2, "those": [2, 18, 28, 31, 36, 39, 40, 41, 44, 49], "subset": [2, 3, 14, 18, 28], "rvalu": 2, "refer": [2, 10, 11, 14, 18, 19, 26, 28, 34, 36, 44, 47, 48], "reorder": 2, "newbitstr": 2, "oldbitstr": 2, "process": [2, 3, 7, 14, 19, 24, 31, 48, 49], "rang": [2, 4, 5, 6, 7, 11, 25, 26, 39, 41, 48], "const_iter": 2, "cbegin": 2, "cend": 2, "has_even_par": 2, "pariti": 2, "registeredtyp": 2, "declar": [2, 18, 19, 21, 31, 33], "themselv": [2, 47], "plugin": [2, 32], "myinterfac": 2, "describ": [2, 3, 8, 11, 24, 26, 33, 34], "column": [2, 3], "own": [2, 3, 8, 19, 24, 26, 31, 33, 36, 48, 49], "delet": [2, 11, 26], "upon": [2, 4, 5, 18, 19, 28, 48], "destruct": 2, "rawdata": 2, "exist": [2, 3, 11, 13, 14, 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"o": [2, 11, 31, 34, 38, 47, 49], "copi": [2, 11, 28, 36], "data_rep": 2, "serial": [2, 3], "encod": [2, 3, 14, 22, 33, 34, 48], "via": [2, 3, 5, 6, 8, 13, 14, 16, 19, 21, 25, 26, 28, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 47, 48, 49], "real": [2, 3], "imaginari": [2, 3], "part": [2, 3, 14, 26, 31, 32, 34, 44], "append": [2, 3, 4, 6, 7, 41, 47], "arrai": [2, 3, 7, 8, 26, 28, 31, 34, 36, 48], "larg": [2, 3, 21, 34, 49], "1d": [2, 3], "end": [2, 3, 8, 11, 14, 26, 34, 36, 47, 48], "total": [2, 3, 7, 11], "destructor": 2, "iter": [2, 3, 6, 14, 26, 44, 48], "begin": [2, 3, 8, 14, 26, 34, 37, 42, 48], "return": [2, 3, 4, 6, 7, 14, 16, 17, 18, 19, 26, 28, 31, 32, 33, 34, 36, 37, 39, 40, 44, 48], "start": [2, 3, 4, 10, 12, 21, 23, 26, 31, 32, 34, 37, 41, 47, 51], "equal": [2, 3, 5, 28, 41], "v": [2, 3, 7, 10, 14, 17, 23, 28, 31, 36, 38], "noexcept": [2, 21], "add": [2, 3, 8, 9, 11, 12, 23, 31, 32, 33, 34, 48, 49, 51], "subtract": [2, 3], "multipli": [2, 3, 37], "true": [2, 3, 6, 11, 14, 18, 47], "here": [2, 8, 10, 11, 12, 14, 16, 23, 31, 32, 34, 35, 36, 37, 40, 41, 44, 48, 51], "doe": [2, 3, 11, 12, 14, 26, 36, 38, 41, 51], "consid": [2, 3, 11, 19, 28, 41, 43], "valu": [2, 3, 4, 5, 6, 7, 14, 16, 18, 22, 28, 31, 36, 39, 40, 46, 48, 49], "num_qubit": 2, "num_term": 2, "get_coeffici": [2, 3, 22], "get": [2, 3, 8, 10, 12, 14, 16, 33, 34, 36, 37, 41, 47, 48, 51], "throw": [2, 36, 49], "except": [2, 3], "get_raw_data": [2, 3], "is_ident": [2, 3, 22], "void": [2, 3, 14, 16, 17, 18, 21, 22, 24, 25, 26, 31, 32, 33, 34, 36, 37, 40, 44], "dump": [2, 3, 5, 7, 8, 14, 17, 34, 39, 41, 48], "string": [2, 3, 11, 14, 16, 22, 24, 31, 34, 37, 39, 48], "standard": [2, 13, 14, 15, 16, 18, 21, 31, 32, 34, 41], "out": [2, 3, 8, 11, 14, 19, 26, 28, 30, 33, 34, 36, 38, 41, 44, 45, 48, 49], "to_str": [2, 3, 22], "printcoeffici": 2, "getdatarepresent": 2, "distribute_term": [2, 3], "numchunk": 2, "distribut": [2, 3, 7, 8, 11, 19, 48, 49], "chunk": [2, 3, 19], "for_each_term": [2, 3, 22], "give": [2, 11, 14, 34, 37, 41, 48, 50], "functor": 2, "method": [2, 3, 6, 14, 16, 41, 44, 48], "reduct": 2, "lambda": [2, 14, 18, 31, 34, 37, 40, 44, 48], "captur": [2, 18], "variabl": [2, 3, 7, 11, 18, 19, 34, 36, 41, 45, 47, 48, 49], "for_each_pauli": [2, 3, 22], "thrown": [2, 3], "than": [2, 3, 11, 21, 28, 49], "user": [2, 3, 7, 11, 14, 16, 18, 31, 33, 34, 39, 40, 47, 48], "should": [2, 3, 11, 14, 15, 18, 19, 21, 22, 24, 26, 33, 34, 37, 41, 42, 43, 47, 48, 49], "pass": [2, 3, 6, 10, 11, 13, 14, 18, 19, 22, 26, 29, 31, 34, 36, 37, 47, 48], "index": [2, 3, 19, 22, 24, 26, 28, 33, 37, 41, 48], "complex_matrix": 2, "to_matrix": [2, 3], "dens": 2, "to_sparse_matrix": [2, 3], "row": [2, 3], "col": 2, "static": [2, 3, 14, 22, 26, 31, 36, 37, 43], "random": [2, 3, 7, 41, 48, 49], "nterm": 2, "unsign": 2, "int": [2, 3, 6, 14, 17, 25, 26, 31, 33, 34, 36, 39, 40, 41, 43, 48], "seed": [2, 3, 7, 48, 49], "random_devic": 2, "act": [2, 4, 28, 49], "specifi": [2, 3, 5, 11, 14, 18, 19, 22, 24, 25, 31, 33, 34, 36, 38, 41, 47, 48, 49], "overrid": [2, 14, 32, 49], "repeat": [2, 14, 48], "from_word": [2, 3], "pauliword": 2, "input": [2, 3, 6, 7, 14, 16, 18, 25, 26, 34, 37, 39, 40, 43, 44, 48], "word": [2, 3, 48], "g": [2, 3, 11, 14, 15, 18, 21, 22, 28, 30, 31, 33, 34, 38, 41, 47], "xyx": [2, 3], "3rd": 2, "second": [2, 3, 34, 44], "typenam": [2, 14, 16, 17, 18, 21, 25], "qualifiedspinop": 2, "struct": [2, 14, 16, 17, 18, 21, 25, 31, 32, 34, 36, 37, 40, 43, 44], "constexpr": [2, 16, 26], "dyn": [2, 26, 34, 36], "level": [2, 14, 19, 21, 22, 30, 31, 33, 36, 40], "qudit": [2, 18, 19, 21, 22, 36], "d": [2, 3, 11, 17, 19, 26, 34, 47, 48], "system": [2, 3, 7, 14, 19, 24, 26, 28, 30, 32, 34, 41, 47, 48, 49], "inlin": [2, 14, 31], "new": [2, 3, 10, 11, 14, 16, 28, 29, 31], "uniqu": [2, 3, 13, 14, 19, 21, 26, 35], "enable_if_t": 2, "A": [2, 3, 7, 11, 14, 21, 28, 32, 33, 40, 47, 48], "contain": [2, 3, 14, 18, 19, 24, 28, 31, 33, 34, 36, 41, 48, 49], "dynam": [2, 3, 15, 16, 19, 26, 31, 34, 36], "time": [2, 3, 5, 7, 8, 10, 11, 13, 14, 17, 19, 23, 26, 27, 31, 34, 35, 36, 39, 48, 49], "By": [2, 14, 39, 41, 47, 48, 49], "like": [2, 3, 5, 7, 11, 14, 26, 30, 31, 33, 34, 36, 38, 41, 43, 44, 48], "paramet": [2, 3, 4, 6, 7, 9, 14, 21, 26, 33, 34, 36, 37, 39, 43, 44, 47, 48], "value_typ": 2, "indic": [2, 3, 18, 21, 22, 26, 33, 34, 36, 40, 48], "underli": [2, 3, 14, 24, 26, 33, 36, 47], "auto": [2, 14, 15, 16, 17, 18, 22, 25, 26, 31, 32, 34, 36, 37, 39, 40, 41, 43, 44], "interfac": [2, 26, 33, 49], "idx": [2, 6, 22, 26], "qspan": [2, 17, 18, 25, 36, 39, 40], "front": [2, 17, 25, 26, 34, 36], "count": [2, 3, 6, 7, 14, 16, 17, 22, 26, 31, 33, 34, 39, 41, 48], "back": [2, 7, 11, 17, 26, 28, 34, 48], "last": [2, 26, 41, 48], "slice": [2, 3, 22, 26, 36], "clear": [2, 3, 14, 26, 33, 40], "destroi": [2, 26], "postcondit": [2, 26], "observe_result": [2, 3, 14, 34], "encapsul": [2, 6, 14, 26], "observ": [2, 3, 4, 6, 7, 17, 33, 34, 37, 39, 41, 42, 44, 47, 48, 49], "call": [2, 3, 4, 5, 7, 14, 16, 18, 19, 25, 31, 33, 34, 36, 37, 40, 44, 48, 49], "includ": [2, 3, 11, 12, 14, 17, 31, 32, 33, 34, 38, 42, 48, 51], "measur": [2, 3, 5, 8, 14, 15, 17, 18, 19, 21, 28, 31, 33, 34, 39, 41, 48, 49], "execut": [2, 7, 10, 11, 12, 14, 16, 18, 19, 24, 25, 30, 31, 33, 34, 40, 41, 45, 47, 48, 49, 51], "ansatz": [2, 4, 9, 14, 34, 37, 39, 41, 44, 48], "circuit": [2, 3, 6, 7, 10, 13, 14, 15, 18, 19, 22, 23, 27, 28, 31, 32, 36, 37, 38, 41, 43, 47, 48, 49], "global": [2, 3, 14, 18, 36], "expect": [2, 3, 4, 5, 6, 7, 9, 11, 14, 39, 46, 48, 49], "h": [2, 3, 5, 6, 7, 9, 14, 16, 17, 22, 25, 26, 28, 31, 32, 33, 34, 37, 39, 41, 42, 43, 44, 47, 48], "precomput": 2, "psi": [2, 4, 5, 14, 17], "sample_result": [2, 3, 14, 34], "If": [2, 3, 5, 6, 7, 11, 14, 28, 30, 39, 48, 49], "wa": [2, 3, 14, 30, 31, 34, 39, 41], "shot": [2, 3, 14, 17, 33, 34, 39, 47], "base": [2, 3, 9, 11, 12, 13, 14, 16, 20, 21, 31, 33, 38, 41, 44, 48, 49, 51], "raw_data": [2, 14], "raw": [2, 3, 6], "convers": [2, 14], "simpli": [2, 11, 48], "ignor": [2, 49], "fine": [2, 14, 34], "grain": [2, 14, 34], "explicitli": [2, 28, 31, 47, 49], "request": [2, 11, 14, 49], "oppos": [2, 37], "observe_data": 2, "spinoptyp": [2, 14], "sub": [2, 3, 13, 14, 17, 18, 27, 36, 44], "id_coeffici": [2, 14], "executioncontext": 2, "abstract": [2, 14, 16, 21, 22, 24, 26, 37, 41], "how": [2, 4, 7, 11, 12, 14, 16, 30, 31, 33, 34, 35, 43, 46, 48, 49, 51], "name": [2, 3, 7, 11, 14, 16, 21, 24, 30, 31, 33, 34, 38, 39, 48], "shots_": 2, "member": [2, 18], "basic": [2, 4, 10, 11, 23, 38], "sampl": [2, 3, 7, 8, 11, 16, 33, 34, 39, 41, 42, 47, 48, 49], "option": [2, 3, 11, 14, 16, 21, 24, 33, 34, 38, 48], "result": [2, 3, 4, 5, 7, 8, 11, 14, 15, 16, 17, 19, 28, 31, 33, 34, 39, 41, 47, 48, 49], "invoc": [2, 3, 16, 24, 33, 38, 41, 44, 49], "expectationvalu": 2, "nullopt": 2, "hasconditionalsonmeasureresult": 2, "fals": [2, 6, 11, 48], "being": [2, 3, 4, 8, 14, 28, 34, 48, 49], "ha": [2, 3, 7, 8, 9, 11, 14, 28, 34, 36, 47, 48, 49], "statement": [2, 14, 15, 19], "noise_model": [2, 3, 8, 34, 48], "noisemodel": [2, 3, 8, 48], "nullptr": 2, "current": [2, 3, 11, 12, 14, 24, 33, 36, 44, 47, 48, 49, 51], "canhandleobserv": 2, "flag": [2, 11, 31, 32, 34, 38, 41, 47, 49], "handl": [2, 3, 33, 34, 41, 47, 48, 49], "task": [2, 14, 22, 23, 31, 33, 41], "under": [2, 11, 32, 33, 47], "asyncexec": 2, "occur": [2, 3, 14, 19, 34, 48], "asynchron": [2, 3, 7, 14, 24, 34, 48], "detail": [2, 11, 19, 33, 40, 47], "futur": [2, 3, 7, 11, 14, 34, 41, 47, 48, 49], "futureresult": 2, "store": [2, 3, 7, 19, 26, 31, 34, 41], "simulationdata": 2, "mechan": [2, 14, 16, 22, 26, 28, 32, 39, 45], "simul": [2, 4, 5, 7, 10, 12, 13, 14, 29, 31, 38, 41, 46, 47, 51], "client": [2, 14], "extract": [2, 3, 6, 14, 16, 17, 22, 28, 31, 36, 44, 48], "resourc": [2, 11, 23, 24, 38, 49], "kernelresourc": 2, "run": [2, 3, 6, 7, 11, 13, 14, 30, 31, 33, 34, 38, 47, 48, 49], "tracer": 2, "persist": [2, 14, 19], "trace": 2, "kernelnam": 2, "batchiter": 2, "batch": [2, 6, 7, 19], "observe_n": 2, "sample_n": 2, "totaliter": 2, "registernam": [2, 14], "mid": [2, 3, 49], "mode": [2, 5, 31, 38], "keep": [2, 14, 49], "track": [2, 14], "job": [2, 11, 14, 34, 48], "identifi": [2, 11, 19], "qpu": [2, 3, 14, 19, 24, 33, 41, 47, 48], "ani": [2, 3, 7, 8, 11, 14, 18, 23, 25, 26, 33, 34, 37, 39, 40, 42, 45, 47, 48, 49], "extra": [2, 28, 34, 47, 48], "configur": [2, 11, 18, 24, 30, 31, 33, 34, 38, 39, 40, 47, 49], "inform": [2, 3, 11, 12, 14, 19, 21, 24, 26, 31, 34, 36, 41, 47, 48, 49, 51], "need": [2, 5, 7, 8, 11, 28, 30, 33, 37, 41, 44, 47, 48, 49], "retriev": [2, 3, 14, 48], "later": [2, 14, 34, 41, 48], "server": [2, 11, 47, 48], "file": [2, 7, 11, 14, 30, 31, 32, 33, 34, 38, 41, 42, 45, 47, 48], "read": [2, 3, 34, 48], "wrap": [2, 14, 16, 28], "t": [2, 3, 11, 14, 17, 18, 22, 36, 37, 39, 48], "case": [2, 3, 8, 14, 28, 34, 37, 41, 48], "must": [2, 3, 5, 14, 18, 23, 26, 28, 32, 33, 34, 36, 38, 39, 40, 42, 44, 47, 48, 49], "some": [2, 3, 11, 14, 18, 28, 30, 31, 32, 33, 37, 40, 41], "point": [2, 3, 14, 18, 21, 31, 33, 36, 38, 39, 40, 41, 47, 49], "within": [2, 3, 11, 14, 18, 20, 22, 23, 26, 30, 32, 34, 48, 49], "same": [2, 3, 11, 14, 28, 31, 33, 34, 36, 41, 47, 48], "runtim": [2, 10, 11, 16, 19, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 47, 49], "move": [2, 6, 32], "_job": 2, "qpunamein": 2, "config": [2, 11, 33], "info": [2, 31, 45], "requir": [2, 3, 6, 7, 14, 18, 23, 25, 26, 28, 30, 34, 37, 40, 42, 43, 44, 47, 48, 49], "abl": [2, 11, 14, 19, 23, 47, 48], "date": 2, "even": [2, 11, 49], "after": [2, 3, 11, 14, 31, 34, 48], "async_result": [2, 34, 48], "face": 2, "which": [2, 3, 4, 5, 6, 7, 8, 11, 12, 14, 16, 18, 19, 22, 26, 28, 30, 31, 33, 34, 36, 38, 39, 47, 48, 49, 51], "itself": [2, 16, 25, 28, 37, 41], "collect": [2, 3, 7, 23], "pertin": [2, 14, 20, 25, 26], "remot": [2, 10, 14, 19, 45], "rest": [2, 11, 47, 48], "wait": [2, 3, 34, 41], "until": [2, 3, 34], "readi": [2, 11, 34, 48], "executionresult": 2, "bit": [2, 8, 14, 17, 19, 26, 28, 33, 34, 39, 48], "correspond": [2, 3, 4, 14, 34, 39, 48], "well": [2, 3, 11, 12, 14, 19, 30, 33, 36, 48, 49, 51], "integ": [2, 3, 24], "1st": [2, 8], "bitstr": [2, 3, 14, 48], "m": [2, 7, 11, 22, 31, 49], "tripl": [2, 31], "long": [2, 11, 14, 34, 48], "length": [2, 48], "deseri": 2, "discuss": [2, 32, 35, 36], "brief": [2, 33, 34, 48], "countsdictionari": [2, 14], "assum": [2, 11, 19, 26, 33, 34], "expval": [2, 14], "other": [2, 3, 10, 11, 16, 18, 22, 26, 28, 36, 40, 41, 49], "appendresult": 2, "globalregisternam": [2, 14], "classic": [2, 13, 15, 19, 21, 22, 26, 28, 30, 31, 33, 34, 35, 36, 38, 39, 40, 41, 48], "sequentialdata": 2, "sequenti": [2, 3, 14], "collat": [2, 3], "": [2, 3, 5, 6, 8, 11, 14, 19, 24, 26, 28, 30, 31, 32, 34, 37, 39, 43, 47, 48], "holist": 2, "nullari": 2, "precomputedexp": 2, "__global__": [2, 3, 14], "has_expect": 2, "string_view": [2, 14, 33], "anoth": [2, 3, 17, 18, 28, 34, 39, 48], "register_nam": [2, 3, 14], "tandem": [2, 7, 44], "to_map": [2, 14], "regnam": 2, "merg": [2, 31], "necessari": [2, 11, 31, 34, 47, 49], "document": [2, 3, 10, 11, 12, 21, 32, 33, 47, 51], "exp_val_z": 2, "deprec": [2, 3], "probabl": [2, 3, 8, 14, 34, 48], "most_prob": [2, 3, 48], "most": [2, 3, 11, 14, 28, 30, 31, 48], "ostream": 2, "output": [2, 6, 11, 31, 40, 47], "stream": [2, 19], "unord": 2, "get_margin": [2, 14], "marginalindic": [2, 14], "margin": 2, "those": [2, 18, 28, 31, 36, 39, 40, 41, 44, 49], "subset": [2, 3, 14, 18, 28], "rvalu": 2, "refer": [2, 10, 11, 14, 18, 19, 26, 28, 34, 36, 44, 47, 48], "reorder": 2, "newbitstr": 2, "oldbitstr": 2, "process": [2, 3, 7, 14, 19, 24, 31, 48, 49], "rang": [2, 4, 5, 6, 7, 11, 25, 26, 39, 41, 48], "const_iter": 2, "cbegin": 2, "cend": 2, "has_even_par": 2, "pariti": 2, "registeredtyp": 2, "declar": [2, 14, 18, 19, 21, 31, 33], "themselv": [2, 47], "plugin": [2, 32], "myinterfac": 2, "describ": [2, 3, 8, 11, 24, 26, 33, 34], "column": [2, 3], "own": [2, 3, 8, 19, 24, 26, 31, 33, 36, 48, 49], "delet": [2, 11, 26], "upon": [2, 4, 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(cudaq.kernel method)": [[3, "cudaq.Kernel.y"]], "z() (cudaq.kernel method)": [[3, "cudaq.Kernel.z"]]}}) \ No newline at end of file diff --git a/pr-1027/specification/cudaq/algorithmic_primitives.html b/pr-1027/specification/cudaq/algorithmic_primitives.html index 271bf52865..436324809c 100644 --- a/pr-1027/specification/cudaq/algorithmic_primitives.html +++ b/pr-1027/specification/cudaq/algorithmic_primitives.html @@ -548,6 +548,67 @@

    12. Quantum Algorithmic Primitivessample_result returned for this sampling tasks contains the default __global__ register as well as the user specified reg1 register.

    +

    The order of the bits in the __global__ register will depend on how your +kernel is written:

    +
      +

    1. If no measurements appear in the kernel, or if any quantum operations occur +after the final measurements in the kernel, then the __global__ +register is formed with implicit measurements being added for all the +qubits defined in the kernel, and the measurements all occur at the end of +the kernel. The order of the bits in the bitstring corresponds to the order +that the qubits were defined in the kernel. That is - the [0] +element in the __global__ bitstring corresponds with the first +declared qubit in the kernel. For example,

      +
      auto kernel = []() __qpu__ {
+  cudaq::qubit a, b;
+  x(a);
+};
+cudaq::sample(kernel).dump();
+
      +
      +

      should produce

      +
      {
+  __global__ : { 10:1000 }
+}
+
      +
      +
      2. +

    2. Conversely, if any measurements appear in the kernel and the final quantum +operation of the kernel is a measurement, then the __global__ +register is formed such that the order of the bits in the bitstring +corresponds to the order of the measurements performed in the kernel. +However, similar to #1, the values of the sampled qubits always correspond to +the values at the end of the kernel execution. That is - if a qubit is +measured in the middle of a kernel and subsequent operations change the state +of the qubit, the qubit will be implicitly re-measured at the end of the +kernel, and that re-measured value is the value that will appear in the +__global__ register. For example,

      +
      auto kernel = []() __qpu__ {
+  cudaq::qubit a, b;
+  x(a);
+  mz(b);
+  mz(a);
+};
+cudaq::sample(kernel).dump();
+
      +
      +

      should produce

      +
      {
+  __global__ : { 01:1000 }
+}
+
      +
      +
      3. +
    +
    +

    Note

    +

    If you don’t specify any measurements in your kernel and allow the nvq++ +compiler to perform passes that introduce ancilla qubits into your kernel, it +may be difficult to discern which qubits are the ancilla qubits vs which ones +are your qubits. In this case, it is recommend that you provide explicit +measurements in your kernel in order to only receive measurements from your +qubits and silently discard the measurements from the ancillary qubits.

    +

    The API exposed by the sample_result data type allows one to extract the information contained at a variety of levels and for each available register name. One can get the number of times a bit string was observed via diff --git a/pr-1027/sphinx/examples/cpp/algorithms/amplitude_estimation.cpp b/pr-1027/sphinx/examples/cpp/algorithms/amplitude_estimation.cpp index 94a68ac723..8cb4a1de92 100644 --- a/pr-1027/sphinx/examples/cpp/algorithms/amplitude_estimation.cpp +++ b/pr-1027/sphinx/examples/cpp/algorithms/amplitude_estimation.cpp @@ -58,7 +58,7 @@ int num_oracles(std::vector &vec, const int N_shots) { } // namespace mlae struct statePrep_A { - void operator()(cudaq::qreg<> &q, const double bmax) __qpu__ { + void operator()(cudaq::qvector<> &q, const double bmax) __qpu__ { int n = q.size(); // all qubits sans auxiliary @@ -75,7 +75,7 @@ struct statePrep_A { }; struct S_0 { - void operator()(cudaq::qreg<> &q) __qpu__ { + void operator()(cudaq::qvector<> &q) __qpu__ { auto ctrl_qubits = q.front(q.size() - 1); auto &last_qubit = q.back(); @@ -93,7 +93,7 @@ struct run_circuit { auto operator()(const int n_qubits, const int n_itrs, const double bmax) __qpu__ { - cudaq::qreg q(n_qubits + 1); // last is auxiliary + cudaq::qvector q(n_qubits + 1); // last is auxiliary auto &last_qubit = q.back(); // State preparation diff --git a/pr-1027/sphinx/examples/cpp/algorithms/bernstein_vazirani.cpp b/pr-1027/sphinx/examples/cpp/algorithms/bernstein_vazirani.cpp index e65ccc8f27..158446dcf3 100644 --- a/pr-1027/sphinx/examples/cpp/algorithms/bernstein_vazirani.cpp +++ b/pr-1027/sphinx/examples/cpp/algorithms/bernstein_vazirani.cpp @@ -34,7 +34,7 @@ std::bitset random_bits(int seed) { template struct oracle { - auto operator()(std::bitset bitvector, cudaq::qspan<> qs, + auto operator()(std::bitset bitvector, cudaq::qview<> qs, cudaq::qubit &aux) __qpu__ { for (size_t i = 0; i < nrOfBits; i++) { @@ -49,7 +49,7 @@ template struct bernstein_vazirani { auto operator()(std::bitset bitvector) __qpu__ { - cudaq::qreg qs; + cudaq::qarray qs; cudaq::qubit aux; h(aux); z(aux); diff --git a/pr-1027/sphinx/examples/cpp/algorithms/grover.cpp b/pr-1027/sphinx/examples/cpp/algorithms/grover.cpp index 0070fa90b9..95db51d587 100644 --- a/pr-1027/sphinx/examples/cpp/algorithms/grover.cpp +++ b/pr-1027/sphinx/examples/cpp/algorithms/grover.cpp @@ -5,7 +5,7 @@ #include -__qpu__ void reflect_about_uniform(cudaq::qspan<> q) { +__qpu__ void reflect_about_uniform(cudaq::qview<> q) { auto ctrlQubits = q.front(q.size() - 1); auto &lastQubit = q.back(); @@ -20,7 +20,7 @@ struct run_grover { template __qpu__ auto operator()(const int n_qubits, const int n_iterations, CallableKernel &&oracle) { - cudaq::qreg q(n_qubits); + cudaq::qvector q(n_qubits); h(q); for (int i = 0; i < n_iterations; i++) { oracle(q); @@ -31,7 +31,7 @@ struct run_grover { }; struct oracle { - void operator()(cudaq::qreg<> &q) __qpu__ { + void operator()(cudaq::qvector<> &q) __qpu__ { z(q[0], q[2]); z(q[1], q[2]); } diff --git a/pr-1027/sphinx/examples/cpp/algorithms/phase_estimation.cpp b/pr-1027/sphinx/examples/cpp/algorithms/phase_estimation.cpp index c31f55dc4d..d4c63b631b 100644 --- a/pr-1027/sphinx/examples/cpp/algorithms/phase_estimation.cpp +++ b/pr-1027/sphinx/examples/cpp/algorithms/phase_estimation.cpp @@ -11,7 +11,7 @@ // A pure device quantum kernel defined as a free function // (cannot be called from host code). -__qpu__ void iqft(cudaq::qspan<> q) { +__qpu__ void iqft(cudaq::qview<> q) { int N = q.size(); // Swap qubits for (int i = 0; i < N / 2; ++i) { @@ -44,7 +44,7 @@ struct qpe { void operator()(const int nCountingQubits, StatePrep &&state_prep, Unitary &&oracle) __qpu__ { // Allocate a register of qubits - cudaq::qreg q(nCountingQubits + 1); + cudaq::qvector q(nCountingQubits + 1); // Extract sub-registers, one for the counting qubits // another for the eigenstate register diff --git a/pr-1027/sphinx/examples/cpp/algorithms/qaoa_maxcut.cpp b/pr-1027/sphinx/examples/cpp/algorithms/qaoa_maxcut.cpp index 6b71516ae7..d501557f5c 100644 --- a/pr-1027/sphinx/examples/cpp/algorithms/qaoa_maxcut.cpp +++ b/pr-1027/sphinx/examples/cpp/algorithms/qaoa_maxcut.cpp @@ -25,7 +25,7 @@ struct ansatz { void operator()(std::vector theta, const int n_qubits, const int n_layers) __qpu__ { - cudaq::qreg q(n_qubits); + cudaq::qvector q(n_qubits); // Prepare the initial state by superposition h(q); diff --git a/pr-1027/sphinx/examples/cpp/algorithms/vqe_h2.cpp b/pr-1027/sphinx/examples/cpp/algorithms/vqe_h2.cpp index 7714fc5599..937ce9348d 100644 --- a/pr-1027/sphinx/examples/cpp/algorithms/vqe_h2.cpp +++ b/pr-1027/sphinx/examples/cpp/algorithms/vqe_h2.cpp @@ -46,7 +46,7 @@ __qpu__ void so4(cudaq::qubit &q, cudaq::qubit &r, struct so4_fabric { void operator()(std::vector params, int n_qubits, int n_layers) __qpu__ { - cudaq::qreg q(n_qubits); + cudaq::qvector q(n_qubits); x(q[0]); x(q[2]); diff --git a/pr-1027/sphinx/examples/cpp/basics/cuquantum_backends.cpp b/pr-1027/sphinx/examples/cpp/basics/cuquantum_backends.cpp index 7eb51dac35..35972beaa5 100644 --- a/pr-1027/sphinx/examples/cpp/basics/cuquantum_backends.cpp +++ b/pr-1027/sphinx/examples/cpp/basics/cuquantum_backends.cpp @@ -17,7 +17,7 @@ struct ghz { auto operator()(const int N) __qpu__ { // Dynamic, vector-like `qreg` - cudaq::qreg q(N); + cudaq::qvector q(N); h(q[0]); for (int i = 0; i < N - 1; i++) { x(q[i], q[i + 1]); diff --git a/pr-1027/sphinx/examples/cpp/basics/cutensornet_backends.cpp b/pr-1027/sphinx/examples/cpp/basics/cutensornet_backends.cpp index 8afb228e65..afc6cf1962 100644 --- a/pr-1027/sphinx/examples/cpp/basics/cutensornet_backends.cpp +++ b/pr-1027/sphinx/examples/cpp/basics/cutensornet_backends.cpp @@ -19,7 +19,7 @@ struct ghz { auto operator()(const int N) __qpu__ { // Dynamic, vector-like `qreg` - cudaq::qreg q(N); + cudaq::qvector q(N); h(q[0]); for (int i = 0; i < N - 1; i++) { x(q[i], q[i + 1]); diff --git a/pr-1027/sphinx/examples/cpp/basics/expectation_values.cpp b/pr-1027/sphinx/examples/cpp/basics/expectation_values.cpp index ee04233e0e..41eea1f156 100644 --- a/pr-1027/sphinx/examples/cpp/basics/expectation_values.cpp +++ b/pr-1027/sphinx/examples/cpp/basics/expectation_values.cpp @@ -11,7 +11,7 @@ struct ansatz { auto operator()(double theta) __qpu__ { - cudaq::qreg q(2); + cudaq::qvector q(2); x(q[0]); ry(theta, q[1]); x(q[1], q[0]); diff --git a/pr-1027/sphinx/examples/cpp/basics/mid_circuit_measurement.cpp b/pr-1027/sphinx/examples/cpp/basics/mid_circuit_measurement.cpp index f100b035bc..7224fadccd 100644 --- a/pr-1027/sphinx/examples/cpp/basics/mid_circuit_measurement.cpp +++ b/pr-1027/sphinx/examples/cpp/basics/mid_circuit_measurement.cpp @@ -7,7 +7,7 @@ struct kernel { void operator()() __qpu__ { - cudaq::qreg<3> q; + cudaq::qarray<3> q; // Initial state preparation x(q[0]); diff --git a/pr-1027/sphinx/examples/cpp/basics/multi_controlled_operations.cpp b/pr-1027/sphinx/examples/cpp/basics/multi_controlled_operations.cpp index bb1f30ec68..fb7df4a018 100644 --- a/pr-1027/sphinx/examples/cpp/basics/multi_controlled_operations.cpp +++ b/pr-1027/sphinx/examples/cpp/basics/multi_controlled_operations.cpp @@ -15,7 +15,7 @@ struct ApplyX { struct ccnot_test { // constrain the signature of the incoming kernel void operator()(cudaq::takes_qubit auto &&apply_x) __qpu__ { - cudaq::qreg qs(3); + cudaq::qvector qs(3); x(qs); x(qs[1]); @@ -32,7 +32,7 @@ int main() { // We can achieve the same thing as above via // a lambda expression. auto ccnot = []() __qpu__ { - cudaq::qreg q(3); + cudaq::qvector q(3); x(q); x(q[1]); diff --git a/pr-1027/sphinx/examples/cpp/basics/static_kernel.cpp b/pr-1027/sphinx/examples/cpp/basics/static_kernel.cpp index 7c91bfa7aa..639dc87638 100644 --- a/pr-1027/sphinx/examples/cpp/basics/static_kernel.cpp +++ b/pr-1027/sphinx/examples/cpp/basics/static_kernel.cpp @@ -13,7 +13,7 @@ struct ghz { auto operator()() __qpu__ { // Compile-time, std::array-like `qreg`. - cudaq::qreg q; + cudaq::qarray q; h(q[0]); for (int i = 0; i < N - 1; i++) { x(q[i], q[i + 1]); diff --git a/pr-1027/sphinx/examples/cpp/other/compute_actions.cpp b/pr-1027/sphinx/examples/cpp/other/compute_actions.cpp index d0d5def2c1..40bf2ba4f6 100644 --- a/pr-1027/sphinx/examples/cpp/other/compute_actions.cpp +++ b/pr-1027/sphinx/examples/cpp/other/compute_actions.cpp @@ -22,7 +22,7 @@ struct ansatz_handcoded { void operator()(double theta) __qpu__ { - cudaq::qreg q(4); + cudaq::qvector q(4); x(q[0]); x(q[2]); rx(M_PI_2, q[0]); @@ -47,7 +47,7 @@ struct ansatz_handcoded { // equivalent to the one defined in `ansatz_handcoded`. struct ansatz_compute_action { void operator()(std::vector theta) __qpu__ { - cudaq::qreg q(4); + cudaq::qvector q(4); x(q[0]); x(q[2]); diff --git a/pr-1027/sphinx/examples/cpp/other/gradients.cpp b/pr-1027/sphinx/examples/cpp/other/gradients.cpp index 59db53314c..a262003cbc 100644 --- a/pr-1027/sphinx/examples/cpp/other/gradients.cpp +++ b/pr-1027/sphinx/examples/cpp/other/gradients.cpp @@ -18,7 +18,7 @@ struct deuteron_n3_ansatz { void operator()(double x0, double x1) __qpu__ { - cudaq::qreg q(3); + cudaq::qvector q(3); x(q[0]); ry(x0, q[1]); ry(x1, q[2]); diff --git a/pr-1027/sphinx/examples/cpp/other/iterative_qpe.cpp b/pr-1027/sphinx/examples/cpp/other/iterative_qpe.cpp index b59ee4be3e..d09274d6b4 100644 --- a/pr-1027/sphinx/examples/cpp/other/iterative_qpe.cpp +++ b/pr-1027/sphinx/examples/cpp/other/iterative_qpe.cpp @@ -15,7 +15,7 @@ struct iqpe { void operator()() __qpu__ { - cudaq::qreg<2> q; + cudaq::qarray<2> q; h(q[0]); x(q[1]); for (int i = 0; i < 8; i++) diff --git a/pr-1027/sphinx/examples/cpp/other/random_walk_qpe.cpp b/pr-1027/sphinx/examples/cpp/other/random_walk_qpe.cpp index ccf41d51ce..6b04eda871 100644 --- a/pr-1027/sphinx/examples/cpp/other/random_walk_qpe.cpp +++ b/pr-1027/sphinx/examples/cpp/other/random_walk_qpe.cpp @@ -22,7 +22,7 @@ struct rwpe { int iteration = 0; // Allocate the qubits - cudaq::qreg q(2); + cudaq::qvector q(2); // Alias them auto &aux = q.front(); diff --git a/pr-1027/sphinx/examples/cpp/providers/ionq.cpp b/pr-1027/sphinx/examples/cpp/providers/ionq.cpp index 98916c771f..6301014b78 100644 --- a/pr-1027/sphinx/examples/cpp/providers/ionq.cpp +++ b/pr-1027/sphinx/examples/cpp/providers/ionq.cpp @@ -23,7 +23,7 @@ struct ghz { // Maximally entangled state between 5 qubits. auto operator()() __qpu__ { - cudaq::qreg q(5); + cudaq::qvector q(5); h(q[0]); for (int i = 0; i < 4; i++) { x(q[i], q[i + 1]); diff --git a/pr-1027/sphinx/examples/cpp/providers/iqm.cpp b/pr-1027/sphinx/examples/cpp/providers/iqm.cpp index 72f1397c9d..e87d092aa1 100644 --- a/pr-1027/sphinx/examples/cpp/providers/iqm.cpp +++ b/pr-1027/sphinx/examples/cpp/providers/iqm.cpp @@ -17,7 +17,7 @@ struct adonis_ghz { // QB5 void operator()() __qpu__ { - cudaq::qreg q(5); + cudaq::qvector q(5); h(q[0]); // Note that the CUDA Quantum compiler will automatically generate the diff --git a/pr-1027/sphinx/examples/cpp/providers/photonics.cpp b/pr-1027/sphinx/examples/cpp/providers/photonics.cpp index 700515c47c..ffa06ff140 100644 --- a/pr-1027/sphinx/examples/cpp/providers/photonics.cpp +++ b/pr-1027/sphinx/examples/cpp/providers/photonics.cpp @@ -9,7 +9,7 @@ struct photonicsKernel { void operator()() __qpu__ { - cudaq::qreg qutrits(2); + cudaq::qvector<3> qutrits(2); plus(qutrits[0]); plus(qutrits[1]); plus(qutrits[1]); diff --git a/pr-1027/sphinx/examples/cpp/providers/quantinuum.cpp b/pr-1027/sphinx/examples/cpp/providers/quantinuum.cpp index bc968e2d59..88131843a0 100644 --- a/pr-1027/sphinx/examples/cpp/providers/quantinuum.cpp +++ b/pr-1027/sphinx/examples/cpp/providers/quantinuum.cpp @@ -14,7 +14,7 @@ struct ghz { // Maximally entangled state between 5 qubits. auto operator()() __qpu__ { - cudaq::qreg q(5); + cudaq::qvector q(5); h(q[0]); for (int i = 0; i < 4; i++) { x(q[i], q[i + 1]); diff --git a/pr-1027/sphinx/specification/cudaq/algorithmic_primitives.rst b/pr-1027/sphinx/specification/cudaq/algorithmic_primitives.rst index 9c0e3ac350..4256436d22 100644 --- a/pr-1027/sphinx/specification/cudaq/algorithmic_primitives.rst +++ b/pr-1027/sphinx/specification/cudaq/algorithmic_primitives.rst @@ -132,6 +132,72 @@ of an NOT operation. The :code:`sample_result` returned for this sampling tasks contains the default :code:`__global__` register as well as the user specified :code:`reg1` register. +The order of the bits in the :code:`__global__` register will depend on how your +kernel is written: + +1. If no measurements appear in the kernel, or if any quantum operations occur + after the final measurements in the kernel, then the :code:`__global__` + register is formed with implicit measurements being added for *all* the + qubits defined in the kernel, and the measurements all occur at the end of + the kernel. The order of the bits in the bitstring corresponds to the *order + that the qubits were defined in the kernel*. That is - the :code:`[0]` + element in the :code:`__global__` bitstring corresponds with the first + declared qubit in the kernel. For example, + + .. code-block:: cpp + + auto kernel = []() __qpu__ { + cudaq::qubit a, b; + x(a); + }; + cudaq::sample(kernel).dump(); + + should produce + + .. code-block:: bash + + { + __global__ : { 10:1000 } + } + +2. Conversely, if any measurements appear in the kernel and the final quantum + operation of the kernel is a measurement, then the :code:`__global__` + register is formed such that the order of the bits in the bitstring + corresponds to the *order of the measurements performed in the kernel*. + However, similar to #1, the values of the sampled qubits always correspond to + the values *at the end of the kernel execution*. That is - if a qubit is + measured in the middle of a kernel and subsequent operations change the state + of the qubit, the qubit will be implicitly re-measured at the end of the + kernel, and that re-measured value is the value that will appear in the + :code:`__global__` register. For example, + + .. code-block:: cpp + + auto kernel = []() __qpu__ { + cudaq::qubit a, b; + x(a); + mz(b); + mz(a); + }; + cudaq::sample(kernel).dump(); + + should produce + + .. code-block:: bash + + { + __global__ : { 01:1000 } + } + +.. note:: + + If you don't specify any measurements in your kernel and allow the :code:`nvq++` + compiler to perform passes that introduce ancilla qubits into your kernel, it + may be difficult to discern which qubits are the ancilla qubits vs which ones + are your qubits. In this case, it is recommend that you provide explicit + measurements in your kernel in order to only receive measurements from your + qubits and silently discard the measurements from the ancillary qubits. + The API exposed by the :code:`sample_result` data type allows one to extract the information contained at a variety of levels and for each available register name. One can get the number of times a bit string was observed via diff --git a/pr-1027/using/cpp.html b/pr-1027/using/cpp.html index ce4cdea277..dd1d25b7fe 100644 --- a/pr-1027/using/cpp.html +++ b/pr-1027/using/cpp.html @@ -451,7 +451,7 @@

    Introduction auto operator()() __qpu__ { // Compile-time, std::array-like `qreg`. - cudaq::qreg<N> q; + cudaq::qarray<N> q; h(q[0]); for (int i = 0; i < N - 1; i++) { x<cudaq::ctrl>(q[i], q[i + 1]); @@ -512,7 +512,7 @@

    Computing Expectation Valuesstruct ansatz { auto operator()(double theta) __qpu__ { - cudaq::qreg q(2); + cudaq::qvector q(2); x(q[0]); ry(theta, q[1]); x<cudaq::ctrl>(q[1], q[0]); @@ -570,7 +570,7 @@

    Multi-control Synthesisstruct ccnot_test { // constrain the signature of the incoming kernel void operator()(cudaq::takes_qubit auto &&apply_x) __qpu__ { - cudaq::qreg qs(3); + cudaq::qvector qs(3); x(qs); x(qs[1]); @@ -587,7 +587,7 @@

    Multi-control Synthesis // We can achieve the same thing as above via // a lambda expression. auto ccnot = []() __qpu__ { - cudaq::qreg q(3); + cudaq::qvector q(3); x(q); x(q[1]); @@ -652,7 +652,7 @@

    Simulations with cuQuantum auto operator()(const int N) __qpu__ { // Dynamic, vector-like `qreg` - cudaq::qreg q(N); + cudaq::qvector q(N); h(q[0]); for (int i = 0; i < N - 1; i++) { x<cudaq::ctrl>(q[i], q[i + 1]); @@ -997,7 +997,7 @@

    Noisy Simulationstruct ghz { // Maximally entangled state between 5 qubits. auto operator()() __qpu__ { - cudaq::qreg q(5); + cudaq::qvector q(5); h(q[0]); for (int i = 0; i < 4; i++) { x<cudaq::ctrl>(q[i], q[i + 1]); @@ -1060,7 +1060,7 @@

    Noisy Simulationstruct ghz { // Maximally entangled state between 5 qubits. auto operator()() __qpu__ { - cudaq::qreg q(5); + cudaq::qvector q(5); h(q[0]); for (int i = 0; i < 4; i++) { x<cudaq::ctrl>(q[i], q[i + 1]);