State sample improvement

LICENSE

@@ -1,4 +1,4 @@
-Quantum Fast Circuit Optimizer (QFactor) JAX implementation Copyright (c) 2023,
+Quantum Fast Circuit Optimizer (QFactor) JAX implementation Copyright (c) 2024,
 U.S. Federal Government and the Government of Israel. All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

README.md

@@ -1,5 +1,5 @@
-# QFactor implementation on GPUs using JAX
-`bqskit-qfactor-jax` is a Python package that implements circuit instantiation with [QFactor](https://arxiv.org/abs/2306.08152) on GPUs to accelerate [BQSKit](https://github.com/bqskit/bqskit). It uses [JAX](https://jax.readthedocs.io/en/latest/index.html) as an abstraction layer of the GPUs, seamlessly utilizing JIT compilation and GPU parallelism.
+# QFactor and QFactor-Sample implementations on GPUs using JAX
+`bqskit-qfactor-jax` is a Python package that implements circuit instantiation using the [QFactor](https://ieeexplore.ieee.org/abstract/document/10313638) and [QFactor-Sample](https://arxiv.org/abs/2405.12866) algorithms on GPUs to accelerate [BQSKit](https://github.com/bqskit/bqskit). It uses [JAX](https://jax.readthedocs.io/en/latest/index.html) as an abstraction layer of the GPUs, seamlessly utilizing JIT compilation and GPU parallelism.
 
 ## Installation
 `bqskit-qfactor-jax` is available for Python 3.8+ on Linux.
@@ -34,7 +34,11 @@ echo quit | nvidia-cuda-mps-control
 ```
 
 # References
-Kukliansky, Alon, et al. "QFactor:A Domain-Specific Optimizer for Quantum Circuit Instantiation." arXiv preprint [arXiv:2306.08152](https://arxiv.org/abs/2306.08152) (2023).
+If you are using QFactor-JAX please cite:
+Kukliansky, Alon, et al. "QFactor: A Domain-Specific Optimizer for Quantum Circuit Instantiation." 2023 IEEE International Conference on Quantum Computing and Engineering (QCE). Vol. 1. IEEE, 2023. [Link](https://ieeexplore.ieee.org/abstract/document/10313638).
+
+If you are using QFactor-Sample please cite:
+Kukliansky, Alon, et al. "Leveraging Quantum Machine Learning Generalization to Significantly Speed-up Quantum Compilation" arXiv preprint [arXiv:2405.12866](https://arxiv.org/abs/2405.12866) (2024).
 
 ## License
 The software in this repository is licensed under a **BSD free software
@@ -45,5 +49,5 @@ for more information.
 
 ## Copyright
 
-Quantum Fast Circuit Optimizer (QFactor) JAX implementation Copyright (c) 2023,
+Quantum Fast Circuit Optimizer (QFactor) JAX implementation Copyright (c) 2024,
 U.S. Federal Government and the Government of Israel. All rights reserved.

examples/adder63_10q_block_28.qasm

@@ -0,0 +1,87 @@
+OPENQASM 2.0;
+include "qelib1.inc";
+qreg q[10];
+cx q[7], q[9];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[9];
+cx q[7], q[9];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[9];
+cx q[7], q[9];
+cx q[5], q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[5];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+cx q[5], q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[5];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+cx q[5], q[7];
+cx q[4], q[5];
+cx q[7], q[9];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[5];
+u3(0.0, 0.0, 0.7853981633974483) q[7];
+cx q[4], q[5];
+cx q[6], q[7];
+u3(0.0, 0.0, 5.497787143782138) q[9];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[5];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[6];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+cx q[4], q[5];
+cx q[6], q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[6];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+cx q[2], q[4];
+cx q[6], q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[2];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+u3(1.5707963267948966, 0.0, 6.283185307179586) q[6];
+cx q[7], q[8];
+u3(0.0, 0.0, 0.7853981633974483) q[2];
+cx q[3], q[4];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[8];
+cx q[0], q[2];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[3];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+cx q[7], q[8];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[0];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[2];
+cx q[3], q[4];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[8];
+cx q[0], q[2];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[3];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+cx q[7], q[8];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[0];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[2];
+cx q[3], q[4];
+cx q[7], q[9];
+cx q[0], q[2];
+cx q[1], q[3];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+u3(1.5707963267948966, 0.0, -3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[1];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[3];
+cx q[6], q[7];
+u3(0.0, 0.0, 7.0685834705770345) q[9];
+cx q[1], q[3];
+u3(1.5707963267948966, 2.356194490192345, -3.141592653589793) q[6];
+u3(1.5707963267948966, -2.356194490192345, 3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[1];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[3];
+cx q[7], q[9];
+cx q[1], q[3];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[9];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[1];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[3];
+cx q[7], q[9];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[9];
+cx q[7], q[9];
+cx q[6], q[7];
+u3(0.0, 0.0, 5.497787143782138) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[7];

examples/compare_qfactor_sample_to_qfactor.py

@@ -0,0 +1,141 @@
+from __future__ import annotations
+
+import argparse
+import time
+
+from bqskit import enable_logging
+from bqskit.compiler import CompilationTask
+from bqskit.compiler import Compiler
+from bqskit.ir.circuit import Circuit
+from bqskit.passes import ToVariablePass
+
+from qfactorjax.qfactor import QFactorJax
+from qfactorjax.qfactor_sample_jax import QFactorSampleJax
+
+enable_logging(verbose=True)
+
+
+parser = argparse.ArgumentParser(
+    description='Comparing the re-instantiation run time of QFactor-JAX and '
+    'QFactor-Sample-JAX. Running on adder63_10q_block_28.qasm the '
+    'difference is X4, and for heisenberg64_10q_block_104.qasm '
+    'the difference is X10 and QFactor-JAX doesn\'t find a solution. '
+    'For vqe12_10q_block145.qasm the difference is X34.',
+)
+
+parser.add_argument('--input_qasm', type=str, required=True)
+parser.add_argument('--multistarts', type=int, default=32)
+parser.add_argument('--max_iters', type=int, default=6000)
+parser.add_argument('--dist_tol', type=float, default=1e-8)
+parser.add_argument('--num_params_coef', type=int, default=1)
+parser.add_argument('--exact_amount_of_sample_states', type=int)
+parser.add_argument('--overtrain_relative_threshold', type=float, default=0.1)
+
+
+params = parser.parse_args()
+
+
+print(params)
+
+file_name = params.input_qasm
+dist_tol_requested = params.dist_tol
+num_mutlistarts = params.multistarts
+max_iters = params.max_iters
+
+num_params_coef = params.num_params_coef
+
+exact_amount_of_sample_states = params.exact_amount_of_sample_states
+overtrain_relative_threshold = params.overtrain_relative_threshold
+
+
+instantiate_options = {
+    'multistarts': num_mutlistarts,
+}
+
+
+qfactor_gpu_instantiator = QFactorJax(
+
+    dist_tol=dist_tol_requested,       # Stopping criteria for distance
+
+    max_iters=100000,      # Maximum number of iterations
+    min_iters=1,          # Minimum number of iterations
+
+    # One step plateau detection -
+    # diff_tol_a + diff_tol_r ∗ |c(i)| <= |c(i)|-|c(i-1)|
+    diff_tol_a=0.0,       # Stopping criteria for distance change
+    diff_tol_r=1e-10,     # Relative criteria for distance change
+
+    # Long plateau detection -
+    # diff_tol_step_r*|c(i-diff_tol_step)| <= |c(i)|-|c(i-diff_tol_step)|
+    diff_tol_step_r=0.1,  # The relative improvement expected
+    diff_tol_step=200,  # The interval in which to check the improvement
+
+    # Regularization parameter - [0.0 - 1.0]
+    # Increase to overcome local minima at the price of longer compute
+    beta=0.0,
+)
+
+
+qfactor_sample_gpu_instantiator = QFactorSampleJax(
+
+    dist_tol=dist_tol_requested,       # Stopping criteria for distance
+
+    max_iters=max_iters,      # Maximum number of iterations
+    min_iters=6,          # Minimum number of iterations
+
+    # Regularization parameter - [0.0 - 1.0]
+    # Increase to overcome local minima at the price of longer compute
+    beta=0.0,
+
+    amount_of_validation_states=2,
+    # indicates the ratio between the sum of parameters in the circuits to the
+    # sample size.
+    diff_tol_r=1e-4,
+    num_params_coef=num_params_coef,
+    overtrain_relative_threshold=overtrain_relative_threshold,
+    exact_amount_of_states_to_train_on=exact_amount_of_sample_states,
+)
+
+
+print(
+    f'Will use {file_name} {dist_tol_requested = } {num_mutlistarts = }'
+    f' {num_params_coef = }',
+)
+
+orig_10q_block_cir = Circuit.from_file(f'{file_name}')
+
+with Compiler(num_workers=1) as compiler:
+    task = CompilationTask(orig_10q_block_cir, [ToVariablePass()])
+    task_id = compiler.submit(task)
+    orig_10q_block_cir_vu = compiler.result(task_id)
+
+
+tic = time.perf_counter()
+target = orig_10q_block_cir_vu.get_unitary()
+time_to_simulate_circ = time.perf_counter() - tic
+print(f'Time to simulate was {time_to_simulate_circ}')
+
+tic = time.perf_counter()
+orig_10q_block_cir_vu.instantiate(
+    target, multistarts=num_mutlistarts, method=qfactor_sample_gpu_instantiator,
+)
+sample_inst_time = time.perf_counter() - tic
+inst_sample_dist_from_target = orig_10q_block_cir_vu.get_unitary(
+).get_distance_from(target, 1)
+
+print(
+    f'QFactor-Sample-JAX  {sample_inst_time = } '
+    f'{inst_sample_dist_from_target = }'
+    f' {num_params_coef = }',
+)
+
+tic = time.perf_counter()
+orig_10q_block_cir_vu.instantiate(
+    target, multistarts=num_mutlistarts, method=qfactor_gpu_instantiator,
+)
+full_inst_time = time.perf_counter() - tic
+inst_dist_from_target = orig_10q_block_cir_vu.get_unitary().get_distance_from(
+    target, 1,
+)
+
+print(f'QFactor-JAX {full_inst_time = } {inst_dist_from_target = }')

examples/gate_deletion_syth.py

@@ -7,6 +7,7 @@
 from timeit import default_timer as timer
 
 from bqskit import Circuit
+from bqskit import enable_logging
 from bqskit.compiler import Compiler
 from bqskit.passes import ForEachBlockPass
 from bqskit.passes import QuickPartitioner
@@ -18,6 +19,9 @@
 from qfactorjax.qfactor import QFactorJax
 
 
+enable_logging()
+
+
 def run_gate_del_flow_example(
         amount_of_workers: int = 10,
 ) -> tuple[Circuit, Circuit, float]:
@@ -102,7 +106,9 @@ def run_gate_del_flow_example(
 
 if __name__ == '__main__':
 
-    in_circuit, out_circuit, run_time = run_gate_del_flow_example()
+    in_circuit, out_circuit, run_time = run_gate_del_flow_example(
+        amount_of_workers=1,
+    )
 
     print(
         f'Partitioning + Synthesis took {run_time}'

examples/heisenberg64_10q_block_104.qasm

@@ -0,0 +1,57 @@
+OPENQASM 2.0;
+include "qelib1.inc";
+qreg q[10];
+u3(1.5707963267948966, -3.141592653589793, -3.141592653589793) q[1];
+cx q[0], q[1];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[2];
+u3(1.5707963267948966, -3.141592653589793, -3.141592653589793) q[3];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[4];
+u3(1.5707963267948966, -3.141592653589793, -3.141592653589793) q[5];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[6];
+u3(1.5707963267948966, -3.141592653589793, -3.141592653589793) q[7];
+u3(1.5707963267948966, 0.0, 3.141592653589793) q[8];
+u3(1.5707963267948966, -3.141592653589793, -3.141592653589793) q[9];
+u3(0.0, 0.0, 0.02) q[1];
+cx q[0], q[1];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[0];
+u3(0.0, 1.406583, -1.406583) q[1];
+cx q[1], q[2];
+u3(0.0, 0.0, 0.02) q[2];
+cx q[1], q[2];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[1];
+u3(0.0, 1.406583, -1.406583) q[2];
+cx q[2], q[3];
+u3(0.0, 0.0, 0.02) q[3];
+cx q[2], q[3];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[2];
+u3(0.0, 1.406583, -1.406583) q[3];
+cx q[3], q[4];
+u3(0.0, 0.0, 0.02) q[4];
+cx q[3], q[4];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[3];
+u3(0.0, 1.406583, -1.406583) q[4];
+cx q[4], q[5];
+u3(0.0, 0.0, 0.02) q[5];
+cx q[4], q[5];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[4];
+u3(0.0, 1.406583, -1.406583) q[5];
+cx q[5], q[6];
+u3(0.0, 0.0, 0.02) q[6];
+cx q[5], q[6];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[5];
+u3(0.0, 1.406583, -1.406583) q[6];
+cx q[6], q[7];
+u3(0.0, 0.0, 0.02) q[7];
+cx q[6], q[7];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[6];
+u3(0.0, 1.406583, -1.406583) q[7];
+cx q[7], q[8];
+u3(0.0, 0.0, 0.02) q[8];
+cx q[7], q[8];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[7];
+u3(0.0, 1.406583, -1.406583) q[8];
+cx q[8], q[9];
+u3(0.0, 0.0, 0.02) q[9];
+cx q[8], q[9];
+u3(1.5707963267948966, 0.0, 1.5707963267948966) q[8];
+u3(0.0, 1.406583, -1.406583) q[9];