/// # Summary
/// Runs a specified quantum operation with different parameters `ns`,
/// saving the resource estimates as a csv file to a specified location.
/// This also runs the operation with a second parameter, which varies
/// between specified minimum and maximum values. It only runs over the
/// second parameter until it minimizes depth and T count.
/// The main purpose is to estimate optimal window sizes for windowed operations.
///
/// # Inputs
/// ## runner
/// The quantum operation being tested (must also match the type `Qop`).
/// This operation must take a boolean `isControlled` and an integer parameter
/// ## ns
/// An array of integer parameters. This method will run the quantum operation
/// with each parameter
/// ## isControlled
/// A boolean argument to pass to the quantum operation. The intention is that
/// it tells the operator whether to test a controlled or uncontrolled version.
/// ## isAmortized
/// Decides how to select the optimal second parameter. If it's amortized, it divides
/// the resulting cost by the value of the second parameter. This is intended
/// for windowed addition: as the window size increases, we need to do fewer additions.
/// ## filename
/// The filename, including directory, of where to save the results
/// ## full_depth
/// If true, counts all gates as depth 1; if false, only counts T-gates as depth 1,
/// all others as depth 0
/// ## minParameters
/// The minimum value for the second parameter, corresponding to values in ns
/// ## maxParameters
/// The maximum value for the second parameter.
private static void TwoArgResourceTest <TypeQop>(
RunTwoArgQop runner,
int[] ns,
int[][] ms,
bool isControlled,
string filename,
bool full_depth
)
{
if (full_depth)
{
filename += "-all-gates";
}
if (isControlled)
{
filename += "-controlled";
}
filename += ".csv";
// Create table headers
if (!System.IO.File.Exists(filename))
{
string estimation = DisplayCSV.GetHeader(full_depth) + ", first arg, second arg";
System.IO.File.WriteAllText(filename, estimation);
}
ReaderWriterLock locker = new ReaderWriterLock();
for (int i = 0; i < ns.Length; i++)
{
// Local variables to prevent threading issues
var thisThreadProblemSize = ns[i];
var thisTheadSecondParams = ms[i];
// Starts a thread for each value in ns.
// Each thread will independently search for an optimal size.
Thread oneParameterTest = new Thread(() => SingleTwoArgResourceTest <TypeQop>(
runner,
locker,
thisThreadProblemSize,
thisTheadSecondParams,
isControlled,
filename,
full_depth));
oneParameterTest.Start();
}
}
private static void SingleTwoArgResourceTest <TypeQop>(
RunTwoArgQop runner,
ReaderWriterLock locker,
int n,
int[] ms,
bool isControlled,
string filename,
bool full_depth)
{
// Iterate through values of the second parameter
foreach (int m in ms)
{
QCTraceSimulator estimator = GetTraceSimulator(full_depth); // construct simulator object
// we must generate a new simulator in each round, to clear previous estimates
var res = runner(estimator, n, m, isControlled).Result; // run test
// Get results
var roundDepth = estimator.GetMetric <TypeQop>(MetricsNames.DepthCounter.Depth);
var roundTGates = estimator.GetMetric <TypeQop>(PrimitiveOperationsGroupsNames.T);
// Create string of a row of parameters
string thisCircuitCosts = DisplayCSV.CSV(estimator.ToCSV(), typeof(TypeQop).FullName, false, string.Empty, false, string.Empty);
// add the row to the string of the csv
thisCircuitCosts += $"{n}, {m}";
try
{
locker.AcquireWriterLock(int.MaxValue); // absurd timeout value
System.IO.File.AppendAllText(filename, thisCircuitCosts);
}
finally
{
locker.ReleaseWriterLock();
}
}
}
