static void Main(string[] args)
{
// This is the name of the file we want to load
if (args.Length < 6)
{
Console.WriteLine("Too few parameters provided!");
Console.WriteLine("Must provide the path to the YAML, input state label, precision, step size, trotter order, and sample size");
}
else
{
string YAMLPath = args[0];
string inputState = $"|{args[1]}>";
int nBitsPrecision = Int16.Parse(args[2]);
float trotterStepSize = float.Parse(args[3]);
int trotterOrder = Int16.Parse(args[4]);
var numberOfSamples = Int16.Parse(args[5]);
Console.WriteLine($"Extracting the YAML from {YAMLPath}");
Console.WriteLine($"Input state: {inputState}");
Console.WriteLine($"Precision: {nBitsPrecision}");
Console.WriteLine($"Trotter step size: {trotterStepSize}");
Console.WriteLine($"Trotter order: {trotterOrder}");
Console.WriteLine($"Number of samples: {numberOfSamples}");
// This deserializes a Broombridge file, given its filename.
var broombridge = Deserializers.DeserializeBroombridge(YAMLPath);
// Note that the deserializer returns a list of `ProblemDescription` instances
// as the file might describe multiple Hamiltonians. In this example, there is
// only one Hamiltonian. So we use `.Single()`, which selects the only element of the list.
var problem = broombridge.ProblemDescriptions.Single();
// This is a data structure representing the Jordan-Wigner encoding
// of the Hamiltonian that we may pass to a Q# algorithm.
// If no state is specified, the Hartree-Fock state is used by default.
Console.WriteLine("Preparing Q# data format");
var qSharpData = problem.ToQSharpFormat(inputState);
Console.WriteLine("----- Begin simulation -----");
using (var qsim = new QuantumSimulator(randomNumberGeneratorSeed: 42))
{
// HelloQ.Run(qsim).Wait();
var runningSum = 0.0;
for (int i = 0; i < numberOfSamples; i++)
{
var(phaseEst, energyEst) = GetEnergyByTrotterization.Run(qsim, qSharpData, nBitsPrecision, trotterStepSize, trotterOrder).Result;
Console.WriteLine(energyEst);
runningSum += energyEst;
}
Console.WriteLine("----- End simulation -----");
Console.WriteLine($"Average energy estimate: {runningSum / (float)numberOfSamples}");
}
var config = new QCTraceSimulatorConfiguration();
config.usePrimitiveOperationsCounter = true;
QCTraceSimulator estimator = new QCTraceSimulator(config);
ApplyTrotterOracleOnce.Run(estimator, qSharpData, trotterStepSize, trotterOrder).Wait();
System.IO.Directory.CreateDirectory("_temp");
// var csvData = estimator.ToCSV();
// var csvStringData = String.Join(Environment.NewLine, csvData.Select(d => $"{d.Key};{d.Value};"));
// System.IO.File.WriteAllText("./_temp/_costEstimateReference.csv", csvStringData);
foreach (var collectedData in estimator.ToCSV())
{
File.WriteAllText(
Path.Combine("./_temp/", $"CCNOTCircuitsMetrics.{collectedData.Key}.csv"),
collectedData.Value);
}
}
}
static void Main(string[] args)
{
if (args.Length < 3)
{
Console.WriteLine("You did not provide the gatefile path, number of samples, and precision.");
}
else
{
// Extract important command line arguments
string JSONPath = args[0];
int numberOfSamples = Int16.Parse(args[1]);
var nBitsPrecision = Int64.Parse(args[2]);
if (File.Exists(JSONPath))
{
#region Extract Fermion Terms
string raw_JSON = System.IO.File.ReadAllText(JSONPath);
var output = JObject.Parse(raw_JSON);
// get the constants specifically
var constants = output["constants"];
// get important constants
float trotterStepSize = (float)constants["trotterStep"];
double rescaleFactor = 1.0 / trotterStepSize;
float energyOffset = (float)constants["energyOffset"];
int nSpinOrbitals = (int)constants["nSpinOrbitals"];
int trotterOrder = (int)constants["trotterOrder"];
#endregion
#region Convert to Q# Format
// var test = Auxiliary.ProduceLowLevelTerms(output);
// Console.WriteLine(test);
// var data = Auxiliary.ProduceCompleteHamiltonian(output);
// var qSharpData = Auxiliary.CreateQSharpFormat(output);
var data = Auxiliary.ProduceCompleteHamiltonian(output);
#endregion
#region Simulate Optimized Fermion Terms
using (var qsim = new QuantumSimulator(randomNumberGeneratorSeed: 42))
{
// keep track of the running total of the energy to produce the average energy amount
var runningSum = 0.0;
// iterate over the sample size
for (int i = 0; i < numberOfSamples; i++)
{
var(phaseEst, energyEst) = EstimateEnergyLevel.Run(qsim, data, nBitsPrecision).Result;
runningSum += energyEst;
Console.WriteLine($"Predicted energy: {energyEst}");
}
// Output to stdout
Console.WriteLine($"Average predicted energy: {runningSum / (float)numberOfSamples}");
}
#endregion
#region Produce Cost Estimates
var config = new QCTraceSimulatorConfiguration();
config.usePrimitiveOperationsCounter = true;
QCTraceSimulator estimator = new QCTraceSimulator(config);
ApplyTrotterOracleOnce.Run(estimator, data).Wait();
System.IO.Directory.CreateDirectory("_temp");
// System.IO.File.WriteAllLines("./_temp/_costEstimateOptimized.csv",estimator.ToCSV().Select(x => x.Key + " " + x.Value).ToArray());
foreach (var collectedData in estimator.ToCSV())
{
File.WriteAllText(
Path.Combine("./_temp/", $"CCNOTCircuitsMetrics.{collectedData.Key}.csv"),
collectedData.Value);
}
#endregion
}
}
}
