From 631d8d7f77445f482f944f1657798a717ebf35ef Mon Sep 17 00:00:00 2001 From: Peter Komar Date: Thu, 26 Sep 2024 23:17:51 -0400 Subject: [PATCH] implemented requested changes and more --- README.md | 4 +- .../Allocating_Qubits_on_QPU_Devices.ipynb | 4 +- ...vices_and_Checking_Device_Properties.ipynb | 180 +++++++++--------- ...ting_Started_with_OpenQASM_on_Braket.ipynb | 6 +- .../Noise_models_on_Rigetti.ipynb | 36 ++-- .../Noise_models/ankaa2_edge_specs.png | Bin 0 -> 120636 bytes .../Noise_models/ankaa2_qubit_specs.png | Bin 0 -> 131693 bytes .../Noise_models/aspenm_edge_specs.png | Bin 46592 -> 0 bytes .../Noise_models/aspenm_qubit_specs.png | Bin 57279 -> 0 bytes .../Verbatim_Compilation.ipynb | 13 +- .../0_Creating_your_first_Hybrid_Job.ipynb | 6 +- .../console_figures/queue_viz.png | Bin 138714 -> 137517 bytes .../ankaa-2/0_Getting_started_papermill.ipynb | 6 +- .../Creating_your_first_Hybrid_Job.ipynb | 36 ++-- .../0_Getting_started/0_Getting_started.ipynb | 4 +- .../qubit_spectroscopy_sweep.py | 5 - examples/qiskit/0_Getting_Started.ipynb | 127 +++++++++--- .../pulse_control/1_6_pulse_results.json | 2 +- .../qiskit/0_Getting_Started_mocks.py | 2 +- .../qiskit/rig_pulse_device_capabilities.json | 2 +- 20 files changed, 250 insertions(+), 183 deletions(-) create mode 100644 examples/braket_features/Noise_models/ankaa2_edge_specs.png create mode 100644 examples/braket_features/Noise_models/ankaa2_qubit_specs.png delete mode 100644 examples/braket_features/Noise_models/aspenm_edge_specs.png delete mode 100644 examples/braket_features/Noise_models/aspenm_qubit_specs.png diff --git a/README.md b/README.md index bf3a711e0..47947c963 100644 --- a/README.md +++ b/README.md @@ -250,11 +250,11 @@ This folder contains examples that illustrate the use of Amazon Braket Hybrid Jo ## Analog Hamiltonian Simulation -- [**Instruction to Analog Hamiltonian Simulation**](examples/analog_hamiltonian_simulation/00_Introduction_of_Analog_Hamiltonian_Simulation_with_Rydberg_Atoms.ipynb) +- [**Introduction to Analog Hamiltonian Simulation**](examples/analog_hamiltonian_simulation/00_Introduction_of_Analog_Hamiltonian_Simulation_with_Rydberg_Atoms.ipynb) This tutorial provides an introduction to Analog Hamiltonian Simulation (AHS), a quantum computing paradigm different from gate-based computing. AHS uses a well-controlled quantum system and tunes its parameters to mimic the dynamics of another quantum system, the one we aim to study. -- [**Instruction to Aquila**](examples/analog_hamiltonian_simulation/01_Introduction_to_Aquila.ipynb) +- [**Introduction to Aquila**](examples/analog_hamiltonian_simulation/01_Introduction_to_Aquila.ipynb) This tutorial illustrates how to run an AHS program on QuEra’s Aquila, a Rydberg based QPU, via Amazon Braket. diff --git a/examples/braket_features/Allocating_Qubits_on_QPU_Devices.ipynb b/examples/braket_features/Allocating_Qubits_on_QPU_Devices.ipynb index 93c1a9e1a..da493676b 100644 --- a/examples/braket_features/Allocating_Qubits_on_QPU_Devices.ipynb +++ b/examples/braket_features/Allocating_Qubits_on_QPU_Devices.ipynb @@ -26,7 +26,7 @@ "\n", "When you submit a circuit for execution on a QPU, Amazon Braket performs a series of compilation steps: it maps the _abstract qubits_ in your circuit to _physical qubits_ in the device; it synthesizes gates into the native gate set of the device; it optimizes the circuit to reduce the number of gates; and finally, it translates the gates into executable pulses.\n", "\n", - "This section shows how the first step, called qubit allocation, works for the Rigetti Ankaa 2 device." + "This section shows how the first step, called qubit allocation, works for the Rigetti Ankaa-2 device." ] }, { @@ -57,7 +57,7 @@ "\n", "The example that follows shows how to create a GHZ state on qubits that are not physically connected. After the quantum task is completed, you can obtain a list of the actual gates executed on the device, by viewing the result metadata.\n", "\n", - "First, instantiate the Rigetti Ankaa 2 device and retrieve its connectivity graph, which shows the qubits that are directly connected on the chip." + "First, instantiate the Rigetti Ankaa-2 device and retrieve its connectivity graph, which shows the qubits that are directly connected on the chip." ] }, { diff --git a/examples/braket_features/Getting_Devices_and_Checking_Device_Properties.ipynb b/examples/braket_features/Getting_Devices_and_Checking_Device_Properties.ipynb index a7ea932c0..45dd39fb5 100644 --- a/examples/braket_features/Getting_Devices_and_Checking_Device_Properties.ipynb +++ b/examples/braket_features/Getting_Devices_and_Checking_Device_Properties.ipynb @@ -62,6 +62,7 @@ "data": { "text/plain": [ "[Device('name': SV1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/sv1),\n", + " Device('name': TN1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/tn1),\n", " Device('name': dm1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/dm1)]" ] }, @@ -87,7 +88,6 @@ " Device('name': Aquila, 'arn': arn:aws:braket:us-east-1::device/qpu/quera/Aquila),\n", " Device('name': Aria 1, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Aria-1),\n", " Device('name': Aria 2, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Aria-2),\n", - " Device('name': Aspen-M-3, 'arn': arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-3),\n", " Device('name': Forte 1, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Forte-1),\n", " Device('name': Garnet, 'arn': arn:aws:braket:eu-north-1::device/qpu/iqm/Garnet)]" ] @@ -195,6 +195,7 @@ " Device('name': Forte 1, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Forte-1),\n", " Device('name': Garnet, 'arn': arn:aws:braket:eu-north-1::device/qpu/iqm/Garnet),\n", " Device('name': SV1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/sv1),\n", + " Device('name': TN1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/tn1),\n", " Device('name': dm1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/dm1)]" ] }, @@ -221,8 +222,7 @@ { "data": { "text/plain": [ - "[Device('name': Aria 2, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Aria-2),\n", - " Device('name': Aspen-M-3, 'arn': arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-3)]" + "[Device('name': Aria 2, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Aria-2)]" ] }, "execution_count": 7, @@ -290,14 +290,14 @@ { "data": { "text/plain": [ - "[Device('name': SV1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/sv1),\n", + "[Device('name': TN1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/tn1),\n", + " Device('name': SV1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/sv1),\n", " Device('name': dm1, 'arn': arn:aws:braket:::device/quantum-simulator/amazon/dm1),\n", " Device('name': Garnet, 'arn': arn:aws:braket:eu-north-1::device/qpu/iqm/Garnet),\n", " Device('name': Aria 1, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Aria-1),\n", " Device('name': Aria 2, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Aria-2),\n", " Device('name': Forte 1, 'arn': arn:aws:braket:us-east-1::device/qpu/ionq/Forte-1),\n", " Device('name': Aquila, 'arn': arn:aws:braket:us-east-1::device/qpu/quera/Aquila),\n", - " Device('name': Aspen-M-3, 'arn': arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-3),\n", " Device('name': Ankaa-2, 'arn': arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa-2)]" ] }, @@ -358,7 +358,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2023-08-29T21:52:17.486681Z", @@ -377,7 +377,7 @@ "# the on-demand simulator SV1\n", "device = AwsDevice(Devices.Amazon.SV1)\n", "# the on-demand simulator TN1\n", - "# device = AwsDevice(Devices.Amazon.TN1)\n", + "device = AwsDevice(Devices.Amazon.TN1)\n", "# the local simulator\n", "device = LocalSimulator()" ] @@ -393,7 +393,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2023-08-29T21:52:17.759631Z", @@ -441,7 +441,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2023-08-29T21:52:19.588547Z", @@ -469,7 +469,7 @@ " \"f1QRB_std_err\": 2.0679831486331732e-05,\n", " \"f1Q_simultaneous_RB\": 0.9977906923503519,\n", " \"f1Q_simultaneous_RB_std_err\": 5.022804153387717e-05,\n", - " \"fRO\": 0.916\n", + " \"fRO\": 0.9279999999999999\n", " },\n", " \"1\": {\n", " \"T1\": 1.1424822873905215e-05,\n", @@ -478,7 +478,7 @@ " \"f1QRB_std_err\": 2.5837382143438492e-05,\n", " \"f1Q_simultaneous_RB\": 0.9953277301386305,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00042743732391299096,\n", - " \"fRO\": 0.923\n", + " \"fRO\": 0.945\n", " },\n", " \"10\": {\n", " \"T1\": 1.4397388097206513e-05,\n", @@ -487,7 +487,7 @@ " \"f1QRB_std_err\": 0.0002540204792082052,\n", " \"f1Q_simultaneous_RB\": 0.9949091215921125,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0008697771710166471,\n", - " \"fRO\": 0.923\n", + " \"fRO\": 0.921\n", " },\n", " \"11\": {\n", " \"T1\": 1.3586183291642084e-05,\n", @@ -496,7 +496,7 @@ " \"f1QRB_std_err\": 3.472614079514786e-05,\n", " \"f1Q_simultaneous_RB\": 0.9729235723436281,\n", " \"f1Q_simultaneous_RB_std_err\": 0.002137921614257448,\n", - " \"fRO\": 0.874\n", + " \"fRO\": 0.8560000000000001\n", " },\n", " \"12\": {\n", " \"T1\": 1.4839379784194732e-05,\n", @@ -505,7 +505,7 @@ " \"f1QRB_std_err\": 4.4974028122863406e-05,\n", " \"f1Q_simultaneous_RB\": 0.9979066727008618,\n", " \"f1Q_simultaneous_RB_std_err\": 5.178760285397647e-05,\n", - " \"fRO\": 0.979\n", + " \"fRO\": 0.975\n", " },\n", " \"13\": {\n", " \"T1\": 1.5012868688046168e-05,\n", @@ -514,7 +514,7 @@ " \"f1QRB_std_err\": 9.068247000218935e-05,\n", " \"f1Q_simultaneous_RB\": 0.9960819770811921,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00020470342371224092,\n", - " \"fRO\": 0.9450000000000001\n", + " \"fRO\": 0.9319999999999999\n", " },\n", " \"14\": {\n", " \"T1\": 9.241177624502927e-06,\n", @@ -523,7 +523,7 @@ " \"f1QRB_std_err\": 7.483443152934302e-05,\n", " \"f1Q_simultaneous_RB\": 0.9899718004895154,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0004595459103652275,\n", - " \"fRO\": 0.913\n", + " \"fRO\": 0.9410000000000001\n", " },\n", " \"15\": {\n", " \"T1\": 1.3607903689853045e-05,\n", @@ -532,7 +532,7 @@ " \"f1QRB_std_err\": 4.027027495615709e-05,\n", " \"f1Q_simultaneous_RB\": 0.9929483241808174,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00023770765814441926,\n", - " \"fRO\": 0.942\n", + " \"fRO\": 0.945\n", " },\n", " \"16\": {\n", " \"T1\": 1.88513673725692e-05,\n", @@ -541,7 +541,7 @@ " \"f1QRB_std_err\": 3.375389696164912e-05,\n", " \"f1Q_simultaneous_RB\": 0.9833505453505913,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0009000282675945473,\n", - " \"fRO\": 0.8440000000000001\n", + " \"fRO\": 0.845\n", " },\n", " \"17\": {\n", " \"T1\": 6.727376139504448e-06,\n", @@ -550,7 +550,7 @@ " \"f1QRB_std_err\": 4.965553483148904e-05,\n", " \"f1Q_simultaneous_RB\": 0.9971513895552646,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00011975972016416049,\n", - " \"fRO\": 0.905\n", + " \"fRO\": 0.871\n", " },\n", " \"18\": {\n", " \"T1\": 1.3370961985133656e-05,\n", @@ -559,7 +559,7 @@ " \"f1QRB_std_err\": 3.334202920860159e-05,\n", " \"f1Q_simultaneous_RB\": 0.991212188518014,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0005735243624384439,\n", - " \"fRO\": 0.952\n", + " \"fRO\": 0.9450000000000001\n", " },\n", " \"19\": {\n", " \"T1\": 1.3694445091389104e-05,\n", @@ -568,7 +568,7 @@ " \"f1QRB_std_err\": 2.1809754472271395e-05,\n", " \"f1Q_simultaneous_RB\": 0.9377408142450181,\n", " \"f1Q_simultaneous_RB_std_err\": 0.022945728139192902,\n", - " \"fRO\": 0.881\n", + " \"fRO\": 0.86\n", " },\n", " \"2\": {\n", " \"T1\": 1.2858591189370053e-05,\n", @@ -577,7 +577,7 @@ " \"f1QRB_std_err\": 9.08541980198589e-05,\n", " \"f1Q_simultaneous_RB\": 0.9894961138887621,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0010389843019420724,\n", - " \"fRO\": 0.9279999999999999\n", + " \"fRO\": 0.9079999999999999\n", " },\n", " \"20\": {\n", " \"T1\": 1.4033755270253051e-05,\n", @@ -586,7 +586,7 @@ " \"f1QRB_std_err\": 0.0001003650197355637,\n", " \"f1Q_simultaneous_RB\": 0.9972607664140928,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0002625968643302963,\n", - " \"fRO\": 0.969\n", + " \"fRO\": 0.956\n", " },\n", " \"21\": {\n", " \"T1\": 1.2585205427234064e-05,\n", @@ -604,7 +604,7 @@ " \"f1QRB_std_err\": 2.9284210923276044e-05,\n", " \"f1Q_simultaneous_RB\": 0.9882440316368954,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00217791143691248,\n", - " \"fRO\": 0.955\n", + " \"fRO\": 0.926\n", " },\n", " \"23\": {\n", " \"T1\": 1.2842440379946409e-05,\n", @@ -613,7 +613,7 @@ " \"f1QRB_std_err\": 0.0001631397379850662,\n", " \"f1Q_simultaneous_RB\": 0.9865011235636009,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0010189758801580672,\n", - " \"fRO\": 0.962\n", + " \"fRO\": 0.956\n", " },\n", " \"24\": {\n", " \"T1\": 1.9346009082358398e-05,\n", @@ -622,7 +622,7 @@ " \"f1QRB_std_err\": 8.067632036104494e-05,\n", " \"f1Q_simultaneous_RB\": 0.9950712793653935,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0002141642699176358,\n", - " \"fRO\": 0.968\n", + " \"fRO\": 0.979\n", " },\n", " \"25\": {\n", " \"T1\": 1.1785048788788791e-05,\n", @@ -631,7 +631,7 @@ " \"f1QRB_std_err\": 6.060664140314965e-05,\n", " \"f1Q_simultaneous_RB\": 0.9940890082252032,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0007016219504682814,\n", - " \"fRO\": 0.96\n", + " \"fRO\": 0.966\n", " },\n", " \"26\": {\n", " \"T1\": 1.9757994068998704e-05,\n", @@ -640,7 +640,7 @@ " \"f1QRB_std_err\": 2.8473648925082652e-05,\n", " \"f1Q_simultaneous_RB\": 0.9892190315759715,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0018571214358147484,\n", - " \"fRO\": 0.966\n", + " \"fRO\": 0.97\n", " },\n", " \"27\": {\n", " \"T1\": 1.0772657302764382e-05,\n", @@ -649,7 +649,7 @@ " \"f1QRB_std_err\": 4.91454475921194e-05,\n", " \"f1Q_simultaneous_RB\": 0.9959353976666019,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00016001458516624184,\n", - " \"fRO\": 0.911\n", + " \"fRO\": 0.9139999999999999\n", " },\n", " \"28\": {\n", " \"T1\": 9.981191636291515e-06,\n", @@ -658,7 +658,7 @@ " \"f1QRB_std_err\": 3.876665371947724e-05,\n", " \"f1Q_simultaneous_RB\": 0.995992435403062,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00028985280637909165,\n", - " \"fRO\": 0.9359999999999999\n", + " \"fRO\": 0.9410000000000001\n", " },\n", " \"29\": {\n", " \"T1\": 1.1204638867006936e-05,\n", @@ -667,7 +667,7 @@ " \"f1QRB_std_err\": 8.275662897495279e-05,\n", " \"f1Q_simultaneous_RB\": 0.9952130715828645,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00034718794705519267,\n", - " \"fRO\": 0.93\n", + " \"fRO\": 0.925\n", " },\n", " \"3\": {\n", " \"T1\": 1.8719464515731677e-05,\n", @@ -676,7 +676,7 @@ " \"f1QRB_std_err\": 4.057304777251857e-05,\n", " \"f1Q_simultaneous_RB\": 0.9971535609092096,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0002838481061337756,\n", - " \"fRO\": 0.959\n", + " \"fRO\": 0.9239999999999999\n", " },\n", " \"30\": {\n", " \"T1\": 1.244220399426232e-05,\n", @@ -685,7 +685,7 @@ " \"f1QRB_std_err\": 2.951110700225705e-05,\n", " \"f1Q_simultaneous_RB\": 0.9919021348796022,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0006326939371417978,\n", - " \"fRO\": 0.961\n", + " \"fRO\": 0.971\n", " },\n", " \"31\": {\n", " \"T1\": 1.3062804950546854e-05,\n", @@ -694,7 +694,7 @@ " \"f1QRB_std_err\": 4.043660607731187e-05,\n", " \"f1Q_simultaneous_RB\": 0.9916620995172601,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0002275290208907156,\n", - " \"fRO\": 0.942\n", + " \"fRO\": 0.948\n", " },\n", " \"32\": {\n", " \"T1\": 1.4563700515623286e-05,\n", @@ -703,7 +703,7 @@ " \"f1QRB_std_err\": 4.946986179999276e-05,\n", " \"f1Q_simultaneous_RB\": 0.9964784937971644,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00014781010102640516,\n", - " \"fRO\": 0.941\n", + " \"fRO\": 0.959\n", " },\n", " \"33\": {\n", " \"T1\": 9.642732018105618e-06,\n", @@ -712,7 +712,7 @@ " \"f1QRB_std_err\": 2.9295348076164842e-05,\n", " \"f1Q_simultaneous_RB\": 0.983196638552863,\n", " \"f1Q_simultaneous_RB_std_err\": 0.002055539485119557,\n", - " \"fRO\": 0.929\n", + " \"fRO\": 0.918\n", " },\n", " \"34\": {\n", " \"T1\": 1.713988970837948e-05,\n", @@ -721,7 +721,7 @@ " \"f1QRB_std_err\": 3.0424905769125453e-05,\n", " \"f1Q_simultaneous_RB\": 0.9813599244580338,\n", " \"f1Q_simultaneous_RB_std_err\": 0.004669744757842596,\n", - " \"fRO\": 0.973\n", + " \"fRO\": 0.968\n", " },\n", " \"35\": {\n", " \"T1\": 1.4643912131398986e-05,\n", @@ -730,7 +730,7 @@ " \"f1QRB_std_err\": 6.418526794908951e-05,\n", " \"f1Q_simultaneous_RB\": 0.9900369543687392,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0005557840471862918,\n", - " \"fRO\": 0.942\n", + " \"fRO\": 0.94\n", " },\n", " \"36\": {\n", " \"T1\": 1.1051624768642374e-05,\n", @@ -739,7 +739,7 @@ " \"f1QRB_std_err\": 4.427599186346774e-05,\n", " \"f1Q_simultaneous_RB\": 0.9923702291289735,\n", " \"f1Q_simultaneous_RB_std_err\": 0.000734496046659809,\n", - " \"fRO\": 0.921\n", + " \"fRO\": 0.925\n", " },\n", " \"37\": {\n", " \"T1\": 9.952535549320594e-06,\n", @@ -748,7 +748,7 @@ " \"f1QRB_std_err\": 5.9621009368908024e-05,\n", " \"f1Q_simultaneous_RB\": 0.9928609905289468,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0002770065858464925,\n", - " \"fRO\": 0.971\n", + " \"fRO\": 0.97\n", " },\n", " \"38\": {\n", " \"T1\": 1.4542547472158691e-05,\n", @@ -757,7 +757,7 @@ " \"f1QRB_std_err\": 5.5489399743889144e-05,\n", " \"f1Q_simultaneous_RB\": 0.9927274464426054,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00034490346748517424,\n", - " \"fRO\": 0.913\n", + " \"fRO\": 0.94\n", " },\n", " \"39\": {\n", " \"T1\": 1.5813082724142702e-06,\n", @@ -765,7 +765,7 @@ " \"f1QRB_std_err\": 0.0015886479371489913,\n", " \"f1Q_simultaneous_RB\": 0.9800825196376993,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0019705352672016725,\n", - " \"fRO\": 0.912\n", + " \"fRO\": 0.948\n", " },\n", " \"4\": {\n", " \"T1\": 1.221600720686062e-05,\n", @@ -774,7 +774,7 @@ " \"f1QRB_std_err\": 5.148091906526168e-05,\n", " \"f1Q_simultaneous_RB\": 0.9955769056038452,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0002443674943745968,\n", - " \"fRO\": 0.859\n", + " \"fRO\": 0.85\n", " },\n", " \"40\": {\n", " \"T1\": 1.3836774470224874e-05,\n", @@ -783,7 +783,7 @@ " \"f1QRB_std_err\": 0.00010011566667630272,\n", " \"f1Q_simultaneous_RB\": 0.991993880228863,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0011854776333122688,\n", - " \"fRO\": 0.842\n", + " \"fRO\": 0.868\n", " },\n", " \"41\": {\n", " \"T1\": 1.2013952104481512e-05,\n", @@ -792,7 +792,7 @@ " \"f1QRB_std_err\": 3.519955021416773e-05,\n", " \"f1Q_simultaneous_RB\": 0.9976416856190857,\n", " \"f1Q_simultaneous_RB_std_err\": 7.139971507238868e-05,\n", - " \"fRO\": 0.977\n", + " \"fRO\": 0.98\n", " },\n", " \"42\": {\n", " \"T1\": 1.1897315657421982e-05,\n", @@ -801,7 +801,7 @@ " \"f1QRB_std_err\": 2.4842910954783737e-05,\n", " \"f1Q_simultaneous_RB\": 0.9886404187567864,\n", " \"f1Q_simultaneous_RB_std_err\": 0.000865545671861028,\n", - " \"fRO\": 0.9239999999999999\n", + " \"fRO\": 0.9199999999999999\n", " },\n", " \"43\": {\n", " \"T1\": 1.175387778291488e-05,\n", @@ -810,7 +810,7 @@ " \"f1QRB_std_err\": 3.047618557903109e-05,\n", " \"f1Q_simultaneous_RB\": 0.9966245346548614,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00012825235793464645,\n", - " \"fRO\": 0.88\n", + " \"fRO\": 0.897\n", " },\n", " \"44\": {\n", " \"T1\": 1.1317533527705256e-05,\n", @@ -819,7 +819,7 @@ " \"f1QRB_std_err\": 1.9566171677975698e-05,\n", " \"f1Q_simultaneous_RB\": 0.9895156725495968,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0013520876714959414,\n", - " \"fRO\": 0.942\n", + " \"fRO\": 0.9430000000000001\n", " },\n", " \"45\": {\n", " \"T1\": 1.3916136806546354e-05,\n", @@ -828,7 +828,7 @@ " \"f1QRB_std_err\": 7.720752371573168e-05,\n", " \"f1Q_simultaneous_RB\": 0.9951756210242256,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0001656578200493323,\n", - " \"fRO\": 0.893\n", + " \"fRO\": 0.883\n", " },\n", " \"46\": {\n", " \"T1\": 1.6800993490267442e-05,\n", @@ -837,7 +837,7 @@ " \"f1QRB_std_err\": 0.00020792543430694119,\n", " \"f1Q_simultaneous_RB\": 0.9740486054627526,\n", " \"f1Q_simultaneous_RB_std_err\": 0.003949225214890666,\n", - " \"fRO\": 0.907\n", + " \"fRO\": 0.935\n", " },\n", " \"47\": {\n", " \"T1\": 2.308141076017859e-05,\n", @@ -855,7 +855,7 @@ " \"f1QRB_std_err\": 1.8909296638901778e-05,\n", " \"f1Q_simultaneous_RB\": 0.997621217085471,\n", " \"f1Q_simultaneous_RB_std_err\": 7.677949592921175e-05,\n", - " \"fRO\": 0.978\n", + " \"fRO\": 0.968\n", " },\n", " \"49\": {\n", " \"T1\": 1.0015289971656016e-05,\n", @@ -864,7 +864,7 @@ " \"f1QRB_std_err\": 5.47736816118378e-05,\n", " \"f1Q_simultaneous_RB\": 0.995728017290028,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00015382936372201333,\n", - " \"fRO\": 0.918\n", + " \"fRO\": 0.908\n", " },\n", " \"5\": {\n", " \"T1\": 1.3004498440941119e-05,\n", @@ -873,7 +873,7 @@ " \"f1QRB_std_err\": 3.652268864366153e-05,\n", " \"f1Q_simultaneous_RB\": 0.9929592980797504,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00040364203755640396,\n", - " \"fRO\": 0.967\n", + " \"fRO\": 0.973\n", " },\n", " \"50\": {\n", " \"T1\": 1.3464075894863434e-05,\n", @@ -882,7 +882,7 @@ " \"f1QRB_std_err\": 6.748661568443685e-05,\n", " \"f1Q_simultaneous_RB\": 0.9959289209104987,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00014670291611745554,\n", - " \"fRO\": 0.9319999999999999\n", + " \"fRO\": 0.9410000000000001\n", " },\n", " \"51\": {\n", " \"T1\": 6.707631008093091e-06,\n", @@ -891,7 +891,7 @@ " \"f1QRB_std_err\": 2.2201834762021872e-05,\n", " \"f1Q_simultaneous_RB\": 0.996977835871332,\n", " \"f1Q_simultaneous_RB_std_err\": 5.7777036449914484e-05,\n", - " \"fRO\": 0.969\n", + " \"fRO\": 0.974\n", " },\n", " \"52\": {\n", " \"T1\": 1.0876444082164132e-05,\n", @@ -900,7 +900,7 @@ " \"f1QRB_std_err\": 3.717861285133706e-05,\n", " \"f1Q_simultaneous_RB\": 0.9933032810947588,\n", " \"f1Q_simultaneous_RB_std_err\": 0.000529988652814212,\n", - " \"fRO\": 0.9470000000000001\n", + " \"fRO\": 0.959\n", " },\n", " \"53\": {\n", " \"T1\": 1.3108836298338454e-05,\n", @@ -909,7 +909,7 @@ " \"f1QRB_std_err\": 5.2899593808349486e-05,\n", " \"f1Q_simultaneous_RB\": 0.9954968598641998,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0003350853484652073,\n", - " \"fRO\": 0.908\n", + " \"fRO\": 0.9179999999999999\n", " },\n", " \"54\": {\n", " \"T1\": 1.2661827615430663e-05,\n", @@ -918,7 +918,7 @@ " \"f1QRB_std_err\": 4.138291986479403e-05,\n", " \"f1Q_simultaneous_RB\": 0.9897788402240421,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0015090359441196236,\n", - " \"fRO\": 0.9450000000000001\n", + " \"fRO\": 0.944\n", " },\n", " \"55\": {\n", " \"T1\": 6.350408716879262e-06,\n", @@ -927,7 +927,7 @@ " \"f1QRB_std_err\": 4.848970175188756e-05,\n", " \"f1Q_simultaneous_RB\": 0.9953757916042162,\n", " \"f1Q_simultaneous_RB_std_err\": 4.183999712958921e-05,\n", - " \"fRO\": 0.968\n", + " \"fRO\": 0.98\n", " },\n", " \"56\": {\n", " \"T1\": 2.067563472320421e-05,\n", @@ -936,7 +936,7 @@ " \"f1QRB_std_err\": 0.00015874611974747805,\n", " \"f1Q_simultaneous_RB\": 0.9936475546766723,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00019979052355938962,\n", - " \"fRO\": 0.935\n", + " \"fRO\": 0.9339999999999999\n", " },\n", " \"57\": {\n", " \"T1\": 1.3158675098459701e-05,\n", @@ -945,7 +945,7 @@ " \"f1QRB_std_err\": 4.2934019506785746e-05,\n", " \"f1Q_simultaneous_RB\": 0.9816962799151328,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0014092574130662233,\n", - " \"fRO\": 0.9470000000000001\n", + " \"fRO\": 0.9099999999999999\n", " },\n", " \"58\": {\n", " \"T1\": 2.877245453838103e-05,\n", @@ -954,7 +954,7 @@ " \"f1QRB_std_err\": 3.1730303092790445e-05,\n", " \"f1Q_simultaneous_RB\": 0.9975652149478694,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00032303779596305114,\n", - " \"fRO\": 0.94\n", + " \"fRO\": 0.946\n", " },\n", " \"59\": {\n", " \"T1\": 1.160848612530693e-05,\n", @@ -963,7 +963,7 @@ " \"f1QRB_std_err\": 4.5643609775957636e-05,\n", " \"f1Q_simultaneous_RB\": 0.9676348487178844,\n", " \"f1Q_simultaneous_RB_std_err\": 0.004328527980352748,\n", - " \"fRO\": 0.867\n", + " \"fRO\": 0.873\n", " },\n", " \"6\": {\n", " \"T1\": 1.8239370061508387e-05,\n", @@ -981,7 +981,7 @@ " \"f1QRB_std_err\": 7.168583097486353e-05,\n", " \"f1Q_simultaneous_RB\": 0.9851982972890478,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0008258052575669145,\n", - " \"fRO\": 0.976\n", + " \"fRO\": 0.969\n", " },\n", " \"61\": {\n", " \"T1\": 1.2053050762532225e-05,\n", @@ -990,7 +990,7 @@ " \"f1QRB_std_err\": 4.9647881711067385e-05,\n", " \"f1Q_simultaneous_RB\": 0.9755784741860619,\n", " \"f1Q_simultaneous_RB_std_err\": 0.005164330252092108,\n", - " \"fRO\": 0.9139999999999999\n", + " \"fRO\": 0.881\n", " },\n", " \"62\": {\n", " \"T1\": 1.7808351268249727e-05,\n", @@ -999,7 +999,7 @@ " \"f1QRB_std_err\": 3.1724238532503364e-05,\n", " \"f1Q_simultaneous_RB\": 0.9952212272657633,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0001335378001105945,\n", - " \"fRO\": 0.952\n", + " \"fRO\": 0.944\n", " },\n", " \"63\": {\n", " \"T1\": 1.9533544910252338e-05,\n", @@ -1008,7 +1008,7 @@ " \"f1QRB_std_err\": 2.591163591836797e-05,\n", " \"f1Q_simultaneous_RB\": 0.9976971801778179,\n", " \"f1Q_simultaneous_RB_std_err\": 6.06654368005454e-05,\n", - " \"fRO\": 0.969\n", + " \"fRO\": 0.965\n", " },\n", " \"64\": {\n", " \"T1\": 5.3259203473510294e-06,\n", @@ -1026,7 +1026,7 @@ " \"f1QRB_std_err\": 3.225989961221664e-05,\n", " \"f1Q_simultaneous_RB\": 0.9915636857510693,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0009472909244109095,\n", - " \"fRO\": 0.958\n", + " \"fRO\": 0.957\n", " },\n", " \"66\": {\n", " \"T1\": 9.392627467562096e-06,\n", @@ -1035,7 +1035,7 @@ " \"f1QRB_std_err\": 0.0002669885055081551,\n", " \"f1Q_simultaneous_RB\": 0.9632084176103134,\n", " \"f1Q_simultaneous_RB_std_err\": 0.004999298462372134,\n", - " \"fRO\": 0.7729999999999999\n", + " \"fRO\": 0.786\n", " },\n", " \"67\": {\n", " \"T1\": 1.0798303446079845e-05,\n", @@ -1044,7 +1044,7 @@ " \"f1QRB_std_err\": 0.00015345056365693833,\n", " \"f1Q_simultaneous_RB\": 0.9807334968408162,\n", " \"f1Q_simultaneous_RB_std_err\": 0.002467546876349839,\n", - " \"fRO\": 0.848\n", + " \"fRO\": 0.871\n", " },\n", " \"68\": {\n", " \"T1\": 1.528570986098691e-05,\n", @@ -1053,7 +1053,7 @@ " \"f1QRB_std_err\": 5.381485644969931e-05,\n", " \"f1Q_simultaneous_RB\": 0.9757941434467859,\n", " \"f1Q_simultaneous_RB_std_err\": 0.006272810344326621,\n", - " \"fRO\": 0.968\n", + " \"fRO\": 0.9470000000000001\n", " },\n", " \"69\": {\n", " \"T1\": 1.1718733631190332e-05,\n", @@ -1062,7 +1062,7 @@ " \"f1QRB_std_err\": 4.875324178348875e-05,\n", " \"f1Q_simultaneous_RB\": 0.9959091496878513,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00016641915211360384,\n", - " \"fRO\": 0.95\n", + " \"fRO\": 0.9570000000000001\n", " },\n", " \"7\": {\n", " \"T1\": 1.2203293820996904e-05,\n", @@ -1071,7 +1071,7 @@ " \"f1QRB_std_err\": 4.437384879873306e-05,\n", " \"f1Q_simultaneous_RB\": 0.9920859423780137,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0001805274048861091,\n", - " \"fRO\": 0.9219999999999999\n", + " \"fRO\": 0.8979999999999999\n", " },\n", " \"70\": {\n", " \"T1\": 1.23265203941526e-05,\n", @@ -1080,7 +1080,7 @@ " \"f1QRB_std_err\": 0.00011750342197300224,\n", " \"f1Q_simultaneous_RB\": 0.9970195422483246,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00016257128630305394,\n", - " \"fRO\": 0.963\n", + " \"fRO\": 0.976\n", " },\n", " \"71\": {\n", " \"T1\": 1.583166332685028e-05,\n", @@ -1089,7 +1089,7 @@ " \"f1QRB_std_err\": 6.0616375932213985e-05,\n", " \"f1Q_simultaneous_RB\": 0.9944350325795311,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00022116553019116896,\n", - " \"fRO\": 0.9510000000000001\n", + " \"fRO\": 0.935\n", " },\n", " \"72\": {\n", " \"T1\": 1.397358025395872e-05,\n", @@ -1098,7 +1098,7 @@ " \"f1QRB_std_err\": 6.054024131315892e-05,\n", " \"f1Q_simultaneous_RB\": 0.9849382823361392,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0013193296910071872,\n", - " \"fRO\": 0.9570000000000001\n", + " \"fRO\": 0.974\n", " },\n", " \"73\": {\n", " \"T1\": 1.1814906860408034e-05,\n", @@ -1107,11 +1107,11 @@ " \"f1QRB_std_err\": 4.031007930552348e-05,\n", " \"f1Q_simultaneous_RB\": 0.9873569114178359,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0009465125255858361,\n", - " \"fRO\": 0.9510000000000001\n", + " \"fRO\": 0.957\n", " },\n", " \"74\": {\n", " \"T1\": 1.8084856207509896e-05,\n", - " \"fRO\": 0.702\n", + " \"fRO\": 0.755\n", " },\n", " \"75\": {\n", " \"T1\": 1.4599833718085063e-05,\n", @@ -1120,7 +1120,7 @@ " \"f1QRB_std_err\": 5.203226380860018e-05,\n", " \"f1Q_simultaneous_RB\": 0.9966864148141727,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0001278973109537322,\n", - " \"fRO\": 0.9410000000000001\n", + " \"fRO\": 0.925\n", " },\n", " \"76\": {\n", " \"T1\": 1.2786019802371923e-05,\n", @@ -1129,7 +1129,7 @@ " \"f1QRB_std_err\": 5.331170411991985e-05,\n", " \"f1Q_simultaneous_RB\": 0.9942480052610472,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0005965011211577004,\n", - " \"fRO\": 0.966\n", + " \"fRO\": 0.964\n", " },\n", " \"77\": {\n", " \"T1\": 3.079908884466668e-06,\n", @@ -1138,7 +1138,7 @@ " \"f1QRB_std_err\": 0.0001248838776475144,\n", " \"f1Q_simultaneous_RB\": 0.9804732182715379,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0012486362086174888,\n", - " \"fRO\": 0.9019999999999999\n", + " \"fRO\": 0.87\n", " },\n", " \"78\": {\n", " \"T1\": 1.1244811327974159e-05,\n", @@ -1147,7 +1147,7 @@ " \"f1QRB_std_err\": 7.633315759862269e-05,\n", " \"f1Q_simultaneous_RB\": 0.9967692098406119,\n", " \"f1Q_simultaneous_RB_std_err\": 7.424979279055196e-05,\n", - " \"fRO\": 0.938\n", + " \"fRO\": 0.903\n", " },\n", " \"79\": {\n", " \"T1\": 5.6610288866255496e-06,\n", @@ -1156,7 +1156,7 @@ " \"f1QRB_std_err\": 2.781955255112645e-05,\n", " \"f1Q_simultaneous_RB\": 0.9958201350429458,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00013111493060712456,\n", - " \"fRO\": 0.959\n", + " \"fRO\": 0.948\n", " },\n", " \"8\": {\n", " \"T1\": 1.1407003611118413e-05,\n", @@ -1165,7 +1165,7 @@ " \"f1QRB_std_err\": 4.789620643962214e-05,\n", " \"f1Q_simultaneous_RB\": 0.9884117906966723,\n", " \"f1Q_simultaneous_RB_std_err\": 0.000709450806904051,\n", - " \"fRO\": 0.948\n", + " \"fRO\": 0.9490000000000001\n", " },\n", " \"80\": {\n", " \"T1\": 5.978238576247811e-06,\n", @@ -1174,7 +1174,7 @@ " \"f1QRB_std_err\": 9.601258779724653e-05,\n", " \"f1Q_simultaneous_RB\": 0.9957053001975825,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00011365614144994835,\n", - " \"fRO\": 0.95\n", + " \"fRO\": 0.966\n", " },\n", " \"81\": {\n", " \"T1\": 3.4310599698402173e-06,\n", @@ -1183,7 +1183,7 @@ " \"f1QRB_std_err\": 0.003063576918154014,\n", " \"f1Q_simultaneous_RB\": 0.9645298408956499,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0035177577054300957,\n", - " \"fRO\": 0.86\n", + " \"fRO\": 0.881\n", " },\n", " \"82\": {\n", " \"T1\": 1.1019548872967793e-05,\n", @@ -1192,7 +1192,7 @@ " \"f1QRB_std_err\": 3.675749841499251e-05,\n", " \"f1Q_simultaneous_RB\": 0.9968747556504615,\n", " \"f1Q_simultaneous_RB_std_err\": 0.00012065576365671228,\n", - " \"fRO\": 0.984\n", + " \"fRO\": 0.963\n", " },\n", " \"83\": {\n", " \"T1\": 1.090475453998459e-05,\n", @@ -1201,7 +1201,7 @@ " \"f1QRB_std_err\": 4.7535691835826344e-05,\n", " \"f1Q_simultaneous_RB\": 0.9941849216547207,\n", " \"f1Q_simultaneous_RB_std_err\": 0.0006464784829884674,\n", - " \"fRO\": 0.97\n", + " \"fRO\": 0.972\n", " },\n", " \"9\": {\n", " \"T1\": 9.785771028586126e-06,\n", @@ -1210,7 +1210,7 @@ " \"f1QRB_std_err\": 4.30889189756182e-05,\n", " \"f1Q_simultaneous_RB\": 0.9847208740742583,\n", " \"f1Q_simultaneous_RB_std_err\": 0.001365107107806661,\n", - " \"fRO\": 0.9450000000000001\n", + " \"fRO\": 0.945\n", " }\n", " },\n", " \"2Q\": {\n", @@ -1896,7 +1896,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.11" + "version": "3.10.10" } }, "nbformat": 4, diff --git a/examples/braket_features/Getting_Started_with_OpenQASM_on_Braket.ipynb b/examples/braket_features/Getting_Started_with_OpenQASM_on_Braket.ipynb index fef58eea0..a315cba69 100644 --- a/examples/braket_features/Getting_Started_with_OpenQASM_on_Braket.ipynb +++ b/examples/braket_features/Getting_Started_with_OpenQASM_on_Braket.ipynb @@ -226,7 +226,7 @@ " \n", " aws braket create-quantum-task \\\n", " --region \"us-west-1\" \\\n", - " --device-arn \"arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa 2\" \\\n", + " --device-arn \"arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa-2\" \\\n", " --shots 100 \\\n", " --action '{\n", " \"braketSchemaHeader\": {\n", @@ -1126,7 +1126,7 @@ "id": "3f01e6dc44e0e226", "metadata": {}, "source": [ - "We can run the above program on the Rigetti Ankaa 2 device," + "We can run the above program on the Rigetti Ankaa-2 device," ] }, { @@ -1171,7 +1171,7 @@ "metadata": {}, "source": [ "
\n", - " Note: This section and the next verbatim box section uses the Rigetti Ankaa 2 device. When you run this notebook, make sure the device is currently available. You can find QPU availability windows on the Devices page in the Amazon Braket Console\n", + " Note: This section and the next verbatim box section uses the Rigetti Ankaa-2 device. When you run this notebook, make sure the device is currently available. You can find QPU availability windows on the Devices page in the Amazon Braket Console\n", "
" ] }, diff --git a/examples/braket_features/Noise_models/Noise_models_on_Rigetti.ipynb b/examples/braket_features/Noise_models/Noise_models_on_Rigetti.ipynb index cb0ca136a..f8893ee9e 100644 --- a/examples/braket_features/Noise_models/Noise_models_on_Rigetti.ipynb +++ b/examples/braket_features/Noise_models/Noise_models_on_Rigetti.ipynb @@ -7,7 +7,7 @@ "source": [ "# Noise models on Rigetti\n", "\n", - "This notebook shows how to construct a noise model from device calibration data for Rigetti Ankaa 2. We compare the measurement outcomes of circuits run on a noisy simulator with the same circuits run on quantum processing units (QPUs), to show that simulating circuits with noise models more closely mimics QPUs.\n", + "This notebook shows how to construct a noise model from device calibration data for Rigetti Ankaa-2. We compare the measurement outcomes of circuits run on a noisy simulator with the same circuits run on quantum processing units (QPUs), to show that simulating circuits with noise models more closely mimics QPUs.\n", "\n", "**Before you begin**: We recommend being familiar with [Noise models on Amazon Braket.](https://github.com/amazon-braket/amazon-braket-examples/blob/main/examples/braket_features/Noise_models/Noise_models_on_Amazon_Braket.ipynb)\n", "Additionally, users should be familiar with [Running quantum circuits on QPU devices](https://github.com/amazon-braket/amazon-braket-examples/blob/main/examples/getting_started/2_Running_quantum_circuits_on_QPU_devices/2_Running_quantum_circuits_on_QPU_devices.ipynb). \n", @@ -45,7 +45,7 @@ "This can be used to construct noise models to approximate the behavior of the QPU when running circuits on a noisy simulator.\n", "In this tutorial, we focus on local noise models with no crosstalk interactions. Real devices can have crosstalk and unexpected effects that can further degrade the results.\n", "\n", - "The Ankaa 2 calibration data is available on the Braket devices page. Under qubit specs, the calibration data include the qubit index, with corresponding values for the $T_1$, $T_2$, fidelity from randomized benchmarking (fRB), fidelity from simultaneous randomized benchmarking (fsRB), readout fidelity (fRO), and active reset fidelity.\n", + "The Ankaa-2 calibration data is available on the Braket devices page. Under qubit specs, the calibration data include the qubit index, with corresponding values for the $T_1$, $T_2$, fidelity from randomized benchmarking (fRB), fidelity from simultaneous randomized benchmarking (fsRB), and readout fidelity (fRO).\n", "Under \"edge specs\", the data includes the RB fidelity for two qubit gates for each connected edge in the device topology." ] }, @@ -55,11 +55,11 @@ "metadata": {}, "source": [ "**One-qubit calibration data (Qubit specs)**\n", - "
\n", + "
\n", "\n", "\n", "**Two-qubit calibration data (Edge specs)**\n", - "
" + "
" ] }, { @@ -67,7 +67,7 @@ "id": "276d680f-887d-4929-bcaa-e276a6303496", "metadata": {}, "source": [ - "We can programmatically access all the calibration data with the Braket SDK. First we load the AwsDevice using the ARN for Rigetti Ankaa 2." + "We can programmatically access all the calibration data with the Braket SDK. First we load the AwsDevice using the ARN for Rigetti Ankaa-2." ] }, { @@ -104,7 +104,7 @@ "id": "661cca17-01fa-40be-bd3e-741bacc74ce4", "metadata": {}, "source": [ - "For Ankaa 2,We can get all qubit indices with `one_qubit_data.keys()` or with `rigetti.topology_graph.nodes`.\n", + "For Ankaa-2,We can get all qubit indices with `one_qubit_data.keys()` or with `rigetti.topology_graph.nodes`.\n", "\n", "The keys of the two qubit dictionary are the connected qubit pairs separated by a hyphen. \n", "For example, if qubit 0 and 1 are connected the key is \"0-1\".\n", @@ -151,8 +151,6 @@ "\n", "- **Fidelity (sRB)**: Single-qubit simultaneous randomized benchmarking fidelities. These are extracted by running single-qubit RB on all qubits simultaneously. Note that we expect the sRB fidelity to be lower than standard RB fidelity due to non-local crosstalk type noise on the device. \n", "\n", - "- **Active reset fidelity**: Single-qubit active reset fidelities represents the accuracy to which qubits are reinitalized into the ground state |0⟩.\n", - "\n", "- **Readout fidelity**: Single-qubit readout fidelities describes the probability of a bit flip error before readout in the computational basis. The readout fidelity is related to the probability of correctly measuring the ground state and excited states respectively, e.g. $f_{RO} =\\frac{p(0|0)+p(1|1)}{2}$" ] }, @@ -228,7 +226,7 @@ "#### Two-qubit noise \n", "Next we consider adding two-qubit noise to the model. \n", "\n", - "Let's first look at the data provided in the Ankaa 2 device calibration data. On the first connect, \"0-1\", the properties are:" + "Let's first look at the data provided in the Ankaa-2 device calibration data. On the first connect, \"0-1\", the properties are:" ] }, { @@ -259,7 +257,7 @@ "source": [ "Here, we see the fidelity per gate (ISWAP or CZ) and the associated standard error. \n", "\n", - "Next we loop over the entries in the `two_qubit_data` dictionary and add two-qubit depolarizing noise to the model. Notice that Ankaa 2 has symmetric connections (\"0-1\" and \"1-0\") so we need to add noise in both directions." + "Next we loop over the entries in the `two_qubit_data` dictionary and add two-qubit depolarizing noise to the model. Notice that Ankaa-2 has symmetric connections (\"0-1\" and \"1-0\") so we need to add noise in both directions." ] }, { @@ -409,7 +407,7 @@ "metadata": {}, "source": [ "
\n", - "Note: The below section runs tasks on the Rigetti Ankaa 2 device. When you run this notebook, make sure the device is currently available. You can find QPU availability windows on the Devices page in the Amazon Braket Console.\n", + "Note: The below section runs tasks on the Rigetti Ankaa-2 device. When you run this notebook, make sure the device is currently available. You can find QPU availability windows on the Devices page in the Amazon Braket Console.\n", "
\n", "\n", "
\n", @@ -538,10 +536,10 @@ "noisy_sim = pd.DataFrame.from_dict(noisy_probs, orient=\"index\").rename(\n", " columns={0: \"noisy_sim\"}\n", ")\n", - "Ankaam = pd.DataFrame.from_dict(rigetti_probs, orient=\"index\").rename(\n", + "Ankaa = pd.DataFrame.from_dict(rigetti_probs, orient=\"index\").rename(\n", " columns={0: \"Ankaa-2\"}\n", ")\n", - "df = Ankaam.join(noisy_sim).join(free_sim)\n", + "df = Ankaa.join(noisy_sim).join(free_sim)\n", "df" ] }, @@ -627,7 +625,7 @@ "id": "aa8ffab8-e062-4c33-9c9d-4a312cd76b63", "metadata": {}, "source": [ - "We confirm that the simulator with a noise model is closer to the distribution produced by Ankaa 2." + "We confirm that the simulator with a noise model is closer to the distribution produced by Ankaa-2." ] }, { @@ -637,7 +635,7 @@ "source": [ "### Smaller, reduced noise models\n", "\n", - "The full Rigetti Ankaa 2 noise model contains due to non-uniform qubit noise. We can obtain simpler, smaller noise models by coarse graining the model above.\n", + "The full Rigetti Ankaa-2 noise model contains due to non-uniform qubit noise. We can obtain simpler, smaller noise models by coarse graining the model above.\n", "\n", "Here, we consider taking the average over all qubits for the $T_1$, $T_2$, depolarizing, and readout depolarizing rates. This is a substantially smaller noise model, but may be less accurate. \n", "\n", @@ -952,9 +950,15 @@ "source": [ "## Summary\n", "\n", - "In this notebook, we showed how to construct a noise model for Rigetti Ankaa 2 based only on the available calibration data.\n", + "In this notebook, we showed how to construct a noise model for Rigetti Ankaa-2 based only on the available calibration data.\n", "We used a coarse assumption of gate-independent single-qubit depolarizing noise and gate-dependant two-qubit noise. Our qubit-dependent model could be improved in many ways. We could add gate-dependence noise, or change the depolarizing channel to Pauli channels. 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When you run this notebook, make sure the device is currently available. You can find QPU availability windows on the Devices page in the Amazon Braket Console\n", - "

" - ] - }, { "cell_type": "code", "execution_count": 4, @@ -363,7 +354,7 @@ "metadata": {}, "source": [ "As we have mentioned above, to build circuits with multi-qubit gates, you need to take into consideration the connectivity graph of the device. When a circuit contains a verbatim box, automatic qubit rewiring has to be disables, and you have manually allocate the qubits on the device that you want to use for your circuit.\n", - "You can access the connectivity graph on the [device detail page](https://console.aws.amazon.com/braket/home?region=us-west-1#/devices/arn:aws:braket:us-west-2::device/qpu/rigetti/Ankaa 2) in the Amazon Braket Console, or by using the code below." + "You can access the connectivity graph on the [device detail page](https://console.aws.amazon.com/braket/home?region=us-west-1#/devices/arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa-2) in the Amazon Braket Console, or by using the code below." ] }, { @@ -944,7 +935,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.11" + "version": "3.10.10" }, "vscode": { "interpreter": { diff --git a/examples/hybrid_jobs/0_Creating_your_first_Hybrid_Job/0_Creating_your_first_Hybrid_Job.ipynb b/examples/hybrid_jobs/0_Creating_your_first_Hybrid_Job/0_Creating_your_first_Hybrid_Job.ipynb index 842668156..4aa2d985e 100644 --- a/examples/hybrid_jobs/0_Creating_your_first_Hybrid_Job/0_Creating_your_first_Hybrid_Job.ipynb +++ b/examples/hybrid_jobs/0_Creating_your_first_Hybrid_Job/0_Creating_your_first_Hybrid_Job.ipynb @@ -477,9 +477,9 @@ "queue depth with `AwsDevice(device_arn).queue_depth().jobs`. We can also check if the device is\n", "currently available with `AwsDevice(device_arn).is_available()`.\n", "\n", - "You can check the queue depth on the devices page of the [Amazon Braket Console](https://console.aws.amazon.com/braket/home). Below, we show the devices page for Rigetti Ankaa 2.\n", + "You can check the queue depth on the devices page of the [Amazon Braket Console](https://console.aws.amazon.com/braket/home). Below, we show the devices page for Rigetti Ankaa-2.\n", "\n", - "![Rigetti Ankaa 2 showing the queue depths.](console_figures/queue_viz.png)\n" + "![Rigetti Ankaa-2 showing the queue depths.](console_figures/queue_viz.png)\n" ] }, { @@ -641,4 +641,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/examples/hybrid_jobs/0_Creating_your_first_Hybrid_Job/console_figures/queue_viz.png b/examples/hybrid_jobs/0_Creating_your_first_Hybrid_Job/console_figures/queue_viz.png index 05459570595144926e95856262f88c71f7f0095c..511519ad03334fd7201a331d3ff47b50372cf54b 100644 GIT binary patch literal 137517 zcmeFZbyQo;*FTDsLMc+gofg*?cW809;MNu^L4pSh(n2Zj?(R_BrMOc_aBGWuaS0(e zeZIQxd)M#j@87%Lv(`Cha?Z$^*)p>~drv|%)a3DTDR9xy(C`%%WVF!G9u%XYVT|J3 zM?HCXI{-jK!!5Oumex>|mZsBi23gtIS)!pSgd`+k1GIOZ_#?fcl$`WLtT}?OM9}jC zzhST_U{lgRc%<|>!2g}JjB!AH_OlPfCZ!*2(JdYmYubhRw{s0X%PtSYqGUV52>#M~ z)OIFnUc<+}#?%-fl??yq0 z!K+v3Xffn)@UIvN%|)rk690i6%UWRh4l12r0qzPBnV 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z{6|Ikk8=K>Y{74?`^WbFR!0AkrAR96{|DP!1H{`ym9AO4g`PpVd+vU@2IVF~_MnhlaJ+7f{X6$sFcM;h(O{7>Qwo%SfM~FqUiI|!BvX?(-EW=PEXyEahqw2RbNfm zJ4MZLQ!eNV)AQ5RuaB?-(_0tucrB&M3!qEtz>XP7wXdVaY|Ni}?8lPtZF3#)aQ6X3@xK?Or~gp(KM?01&iN0-`G<4<19AT0oc}" ] @@ -519,4 +519,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/hybrid_jobs/8_Creating_Hybrid_Job_Scripts/Creating_your_first_Hybrid_Job.ipynb b/examples/hybrid_jobs/8_Creating_Hybrid_Job_Scripts/Creating_your_first_Hybrid_Job.ipynb index c9e0ec7af..908f97dae 100644 --- a/examples/hybrid_jobs/8_Creating_Hybrid_Job_Scripts/Creating_your_first_Hybrid_Job.ipynb +++ b/examples/hybrid_jobs/8_Creating_Hybrid_Job_Scripts/Creating_your_first_Hybrid_Job.ipynb @@ -123,9 +123,9 @@ "text": [ "Initializing Braket Job: arn:aws:braket:::job/\n", "...............................................\n", - "\u001B[34m2021-11-10 20:55:24,467 sagemaker-training-toolkit INFO Invoking user script\u001B[0m\n", - "\u001B[34mTraining Env:\u001B[0m\n", - "\u001B[34m{\n", + "\u001b[34m2021-11-10 20:55:24,467 sagemaker-training-toolkit INFO Invoking user script\u001b[0m\n", + "\u001b[34mTraining Env:\u001b[0m\n", + "\u001b[34m{\n", " \"additional_framework_parameters\": {},\n", " \"channel_input_dirs\": {},\n", " \"current_host\": \"algo-1\",\n", @@ -157,19 +157,19 @@ " ],\n", " \"network_interface_name\": \"eth0\"\n", " },\n", - " \"user_entry_point\": \"braket_container.py\"\u001B[0m\n", + " \"user_entry_point\": \"braket_container.py\"\u001b[0m\n", "...............................................\n", "...............................................\n", - "\u001B[34mRunning Code As Subprocess\u001B[0m\n", - "\u001B[34mTest job started!!!!!\u001B[0m\n", - "\u001B[34mCounter({'0': 88, '1': 12})\u001B[0m\n", - "\u001B[34mCounter({'1': 58, '0': 42})\u001B[0m\n", - "\u001B[34mCounter({'1': 54, '0': 46})\u001B[0m\n", - "\u001B[34mCounter({'0': 100})\u001B[0m\n", - "\u001B[34mCounter({'0': 100})\u001B[0m\n", - "\u001B[34mTest job completed!!!!!\u001B[0m\n", - "\u001B[34mCode Run Finished\u001B[0m\n", - "\u001B[34m2021-11-10 20:55:58,953 sagemaker-training-toolkit INFO Reporting training SUCCESS\u001B[0m\n" + "\u001b[34mRunning Code As Subprocess\u001b[0m\n", + "\u001b[34mTest job started!!!!!\u001b[0m\n", + "\u001b[34mCounter({'0': 88, '1': 12})\u001b[0m\n", + "\u001b[34mCounter({'1': 58, '0': 42})\u001b[0m\n", + "\u001b[34mCounter({'1': 54, '0': 46})\u001b[0m\n", + "\u001b[34mCounter({'0': 100})\u001b[0m\n", + "\u001b[34mCounter({'0': 100})\u001b[0m\n", + "\u001b[34mTest job completed!!!!!\u001b[0m\n", + "\u001b[34mCode Run Finished\u001b[0m\n", + "\u001b[34m2021-11-10 20:55:58,953 sagemaker-training-toolkit INFO Reporting training SUCCESS\u001b[0m\n" ] } ], @@ -355,11 +355,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can seamlessly swap the SV1 simulator for a QPU by changing the device argument in `AwsQuantumJob.create()`. For instance, the code below will create a hybrid job with priority access on the Rigetti Ankaa 2 device:\n", - "\n", - "

\n", - " Note: The following cell uses the Rigetti Ankaa 2 device; before you uncomment and run it, make sure the device is currently available. You can find QPU availability windows on the Devices page in the Amazon Braket Console\n", - "
" + "You can seamlessly swap the SV1 simulator for a QPU by changing the device argument in `AwsQuantumJob.create()`. For instance, the code below will create a hybrid job with priority access on the Rigetti Ankaa-2 device:" ] }, { @@ -603,4 +599,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/examples/pennylane/0_Getting_started/0_Getting_started.ipynb b/examples/pennylane/0_Getting_started/0_Getting_started.ipynb index 871e04f6e..0f6617888 100644 --- a/examples/pennylane/0_Getting_started/0_Getting_started.ipynb +++ b/examples/pennylane/0_Getting_started/0_Getting_started.ipynb @@ -545,7 +545,7 @@ "You can run your local Python code as an Amazon Braket hybrid job by annotating your code with the `@hybrid_job`` decorator, as shown in the following code example. Only Python 3.10 is supported by default. For custom Python versions, you can choose to use a custom container from [Amazon Elastic Container Registry (ECR)](https://aws.amazon.com/ecr/) (see [BYOC](https://docs.aws.amazon.com/braket/latest/developerguide/braket-jobs-byoc.html)).\n", "\n", "\n", - "In the following code, we create a hybrid job for 10 iterations targeting Rigetti Ankaa 2. Since we specified Ankaa 2 as the device, this job will run once Ankaa 2 is available and has no jobs running ahead of it." + "In the following code, we create a hybrid job for 10 iterations targeting Rigetti Ankaa-2. Since we specified Ankaa-2 as the device, this job will run once Ankaa-2 is available and has no jobs running ahead of it." ] }, { @@ -827,4 +827,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/examples/pulse_control/qubit_spectroscopy/qubit_spectroscopy_sweep.py b/examples/pulse_control/qubit_spectroscopy/qubit_spectroscopy_sweep.py index bd073dd15..c2f300dfe 100644 --- a/examples/pulse_control/qubit_spectroscopy/qubit_spectroscopy_sweep.py +++ b/examples/pulse_control/qubit_spectroscopy/qubit_spectroscopy_sweep.py @@ -27,11 +27,6 @@ qubit = hyperparams.get("qubit", None) assert qubit is not None experiment_configuration = { - "arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa 2": { - "drive_frame": f"q{qubit}_rf_frame", - "readout_frame": f"q{qubit}_ro_rx_frame", - "spectroscopy_wf": GaussianWaveform(100e-9, 25e-9, 0.1, True), - }, "arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa-2": { "drive_frame": f"Transmon_{qubit}_charge_tx", "readout_frame": f"Transmon_{qubit}_readout_tx", diff --git a/examples/qiskit/0_Getting_Started.ipynb b/examples/qiskit/0_Getting_Started.ipynb index 958c3b551..22b3e7b41 100644 --- a/examples/qiskit/0_Getting_Started.ipynb +++ b/examples/qiskit/0_Getting_Started.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "3a9504c9", "metadata": {}, "outputs": [], @@ -65,7 +65,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "f162ba69", "metadata": {}, "outputs": [], @@ -88,7 +88,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "2bfe0170", "metadata": {}, "outputs": [], @@ -107,10 +107,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "70a24c64", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[BraketBackend[SV1], BraketBackend[TN1], BraketBackend[dm1]]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from qiskit_braket_provider import BraketProvider\n", "\n", @@ -132,7 +143,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "19024712", "metadata": {}, "outputs": [], @@ -153,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "54e855a5", "metadata": {}, "outputs": [], @@ -220,10 +231,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "f5329bca", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[BraketBackend[Ankaa-2],\n", + " BraketBackend[Aria 1],\n", + " BraketBackend[Forte 1],\n", + " BraketBackend[Garnet]]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "provider.backends(statuses=[\"ONLINE\"], types=[\"QPU\"])" ] @@ -263,12 +288,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "a5beeb7b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "BraketBackend[Ankaa-2]\n" + ] + } + ], "source": [ - "qpu_backend = provider.get_backend(\"Ankaa 2\")\n", + "qpu_backend = provider.get_backend(\"Ankaa-2\")\n", "# qpu_backend = provider.get_backend(\"Aria\")\n", "\n", "print(qpu_backend)" @@ -276,10 +309,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "e9d90ed2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
     ┌───┐          \n",
+                            "q_0: ┤ H ├──■────■──\n",
+                            "     └───┘┌─┴─┐  │  \n",
+                            "q_1: ─────┤ X ├──┼──\n",
+                            "          └───┘┌─┴─┐\n",
+                            "q_2: ──────────┤ X ├\n",
+                            "               └───┘
" + ], + "text/plain": [ + " ┌───┐ \n", + "q_0: ┤ H ├──■────■──\n", + " └───┘┌─┴─┐ │ \n", + "q_1: ─────┤ X ├──┼──\n", + " └───┘┌─┴─┐\n", + "q_2: ──────────┤ X ├\n", + " └───┘" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from qiskit import QuantumCircuit\n", "\n", @@ -292,7 +351,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "32fd1f51", "metadata": { "slideshow": { @@ -316,10 +375,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "d6f5d0da", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'arn:aws:braket:us-west-1:606892779558:quantum-task/59f83e11-3b1d-44cb-9d3e-bbb87ce37dd7'" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "task_id = qpu_task.task_id()\n", "task_id" @@ -336,7 +406,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "dec44bb5", "metadata": {}, "outputs": [], @@ -356,10 +426,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "bb84627d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "retrieved_task.status()" ] @@ -384,7 +465,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "c510eb22", "metadata": {}, "outputs": [], @@ -521,9 +602,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.10.10" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/test/integ_tests/pulse_control/1_6_pulse_results.json b/test/integ_tests/pulse_control/1_6_pulse_results.json index 121993bea..c7163e4ed 100644 --- a/test/integ_tests/pulse_control/1_6_pulse_results.json +++ b/test/integ_tests/pulse_control/1_6_pulse_results.json @@ -59,7 +59,7 @@ 5236931123.13734 ], "task summary": { - "arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa 2": { + "arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa-2": { "shots": 2500, "tasks": { "COMPLETED": 25 diff --git a/test/integ_tests/qiskit/0_Getting_Started_mocks.py b/test/integ_tests/qiskit/0_Getting_Started_mocks.py index e1c465a68..1a353f45b 100644 --- a/test/integ_tests/qiskit/0_Getting_Started_mocks.py +++ b/test/integ_tests/qiskit/0_Getting_Started_mocks.py @@ -38,7 +38,7 @@ def pre_run_inject(mock_utils): }, { "deviceArn": "arn:aws:braket:us-west-2::device/qpu/arn/TestARN", - "deviceName": "Ankaa 2", + "deviceName": "Ankaa-2", "deviceType": "QPU", "deviceStatus": "ONLINE", "providerName": "Test Provider" diff --git a/test/integ_tests/qiskit/rig_pulse_device_capabilities.json b/test/integ_tests/qiskit/rig_pulse_device_capabilities.json index 5ef9aa629..6be646db0 100644 --- a/test/integ_tests/qiskit/rig_pulse_device_capabilities.json +++ b/test/integ_tests/qiskit/rig_pulse_device_capabilities.json @@ -8114,7 +8114,7 @@ "name": "braket.device_schema.pulse.pulse_device_action_properties", "version": "1" }, - "nativeGateCalibrationsRef": "https://dsq6c4wdong7p.cloudfront.net/native_gate_calibrations/device:arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa 2?versionId=.sbF0vCCQLMmN2bPi_YILDyNv7VUJUut", + "nativeGateCalibrationsRef": "https://dsq6c4wdong7p.cloudfront.net/native_gate_calibrations/device:arn:aws:braket:us-west-1::device/qpu/rigetti/Ankaa-2?versionId=.sbF0vCCQLMmN2bPi_YILDyNv7VUJUut", "supportedQhpTemplateWaveforms": { "constant": { "functionName": "constant",