qiskit-debugger 0.1.2

Quantum Circuit debugger for the Qiskit SDK.

Breakpoint Debugging on a Physical Qunatum Circuit

Problem Description

In classical computing, debugging with breakpoint means halting the program execution at any given point and freezing the program state. This allows programmers to examine the program internals mid-execution (as in, what variables contain which values, analyze control flow etc.) Unfortunately, in quantum computing, doing this is not possible. Qubits in a quantum circuit have probabilistic values (in superposition), and the act of measuring collapses the qubits to a deterministic state.

Breakpoint debugging is still needed for quantum computing, so our problem boils down to measuring at the breakpoint and preserving enough information to “recreate” that state and continue execution from that point.

Group Members

• Palvit Garg (pgarg5)
• Harshwardhan Joshi (hjoshi2)
• Shawn Salekin (ssaleki)

Presentation

URL

Quickstart

1. Install with pip

pip install qiskit_debugger

2. Import the following the classes to experiment with the debugger like this:

from qiskit_debugger import QuantumDebugCircuit, QCDebugger, run_circuit

3. A motivating example of how to use the debugger classes:

qc = QuantumDebugCircuit(2)
qc.x(0)
qc.h(range(2))
qc.cx(0, 1)
qc.h(range(2))
qc.bp()      # <-- Add a breakpoint here
qc.h(range(2))
qc.x(range(2))
qc.bp()      # <-- Add a breakpoint here
qc.cx(1, 0)
qc.h(range(2))
qc.bp()

qc.draw()

# run each breakpoints
qdb = QCDebugger(qc)
qdb.c()
qdb.c()
qdb.c()
qdb.c()

Run the circuit as a whole w/o debugger

qc.measure_all()
result = run_circuit(qc)
print(result.get_counts())

If you want to use hardware you have to initiate the QCDebugger like so:

from qiskit import IBMQ

# loading IBMQ account
IBMQ.load_account()
provider = IBMQ.get_provider(hub='ibm-q-ncsu', group='nc-state', project='grad-qc-class')
# This is important, fill up the hw_backend variable like this.
hw_backend = provider.get_backend('ibm_oslo')

qdb = QCDebugger(qc, use_hardware=True)

Solution Approaches

Let’s assume we have a circuit with multiple qubits, and it has a breakpoint brk. The circuit before the breakpoint is called A, and after is called B. The target is to measure the state of qubits at point brk.

To “recreate”, i.e., synthesize an equivalent circuit right after it is measured, we thought of two possible methods.

1. Approach 1: We make two circuits of varying length: one ends at the breakpoint, and the other stops at the original end without stopping at the breakpoint. Then we run both of these circuits.

(update 11/05/22): since this is a trivial and inefficient implementation, we will focus our attention to approach 2.

2. Approach 2: Create a custom gate using the unitary matrix that results from running circuit part A, save it somewhere. Then create a custom gate using the saved unitary matrix to circuit part B.This custom gate is equivalent to the circuit part A. Now run this custom gate and then part B.

Final Result

We have successfully implemented the first approach which uses a combination of simulation and hardware. Using unitary matrices from unitary simulator runs and actual output from hardware runs, we were able to correctly re-create the qubit states pre-measurement, and were able to successfully resume the circuit after the breakpoint. Our implementation is readily usable as well. Our expectation with limited erorr propagation with this approach is also
verified. This approach can aid the quantum computing programmers in interacting with and debugging their code in a more effective way, as long as the circuit width isn't too big.

On the other hand, we found that the pure hardware approach is cumbersome and expensive to implement. The key driver behind this approach is Quantum Phase Estimation, and while there are a number of algorithms uses this sub-routine, in practice it is a) not very precise, b) hard to implement, and c) limits the number of breakpoints to a handful due to error propagation.

Open Problems

• Implement a comprehensive test suite for the debugger implmentation
• Work out a way to extend the QPE and the hardware approach to extend to 2-,3-, and more qubit circuits

Contributions During the Final Round

• Research and experiments with pure hawrdware approach - Palvit
• Experiments and implementation with simulator approach - Shawn
• Benchmakring, experiments, and final reports - Harsh

Progress Made (Round 2)

• Synthesized a new circuit based on a unitary matrix and run it on a real hardware.
• Assessed the importance of phase date in synthesizing a circuit from breakpoint
• Investigated different methods of generating unitary matrices

Timeline (Detailed & Revised)

• Confirm whether and under what condition we can generate a unitary from a hardware run (11/12/2022)
• Decide whether to use simulation or hardware based on the outcome of generating unitary from the hardware runs (11/12/2022)
• Validate whether the phase data obtained from simulation(s) can be used in synthesizing an equivalent circuit after a breakpoint
• Figure out a method to extract phase data from parallel simulation runs (11/19/2022)
• Implement a qiskit module/extension that would allow qiskit users to add breakpoint(s) to their circuit.(11/26/2022)
• Add tests and run a number of experiments to validate the correctness of our implementation.(11/26/2022)

Project Timeline (Original)

• 11/01/2022: Implement approach 1
• 11/10/2022: Analyze the feasibility of implementing approach 2.
• 11/26/2022: Implement approach 2 (or a better one)

Future Readings

• https://dl.acm.org/doi/abs/10.1145/3373376.3378488
• https://arxiv.org/pdf/2103.09172.pdf

References

• https://qiskit.org/documentation/tutorials/circuits_advanced/02_operators_overview.html
• https://qiskit.org/documentation/stubs/qiskit.converters.circuit_to_instruction.html
• https://github.ncsu.edu/fmuelle/qc19/tree/master/hw/hw6/m3/csc591-quantum-debugging
• https://quantumcomputing.stackexchange.com/questions/27064/how-to-get-statevector-of-qubits-after-running-quantum-circuits-on-ibmq-real-har