GpuState.h

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#pragma once
 
#ifndef _GPUSTATE_H_
#define _GPUSTATE_H_
 
#ifdef __linux__
 
#ifdef INCLUDED_BY_FACTORY
 
namespace Simulators {
// TODO: Maybe use the pimpl idiom
// https://en.cppreference.com/w/cpp/language/pimpl to hide the implementation
// for good but during development this should be good enough
namespace Private {
 
class GpuState : public ISimulator {
 public:
  void Initialize() override {
    if (nrQubits) {
      if (simulationType == SimulationType::kStatevector) {
        state = SimulatorsFactory::CreateGpuLibStateVectorSim();
        if (state) {
          const bool res = state->Create(nrQubits);
          if (!res)
            throw std::runtime_error(
                "GpuState::Initialize: Failed to create "
                "and initialize the statevector state.");
        } else
          throw std::runtime_error(
              "GpuState::Initialize: Failed to create the statevector state.");
      } else if (simulationType == SimulationType::kMatrixProductState) {
        mps = SimulatorsFactory::CreateGpuLibMPSSim();
        if (mps) {
          if (useDoublePrecision) mps->SetDataType(true);
          if (limitEntanglement && singularValueThreshold > 0.)
            mps->SetCutoff(singularValueThreshold);
          if (limitSize && chi > 0) mps->SetMaxExtent(chi);
          const bool res = mps->Create(nrQubits);
          if (!res)
            throw std::runtime_error(
                "GpuState::Initialize: Failed to create "
                "and initialize the MPS state.");
        } else
          throw std::runtime_error(
              "GpuState::Initialize: Failed to create the MPS state.");
      } else if (simulationType == SimulationType::kTensorNetwork) {
        tn = SimulatorsFactory::CreateGpuLibTensorNetSim();
        if (tn) {
          const bool res = tn->Create(nrQubits);
          if (!res)
            throw std::runtime_error(
                "GpuState::Initialize: Failed to create "
                "and initialize the tensor network state.");
        } else
          throw std::runtime_error(
              "GpuState::Initialize: Failed to create the tensor network "
              "state.");
      } else if (simulationType == SimulationType::kPauliPropagator) {
        pp = SimulatorsFactory::CreateGpuPauliPropagatorSimulatorUnique();
        if (pp) {
          const bool res = pp->CreateSimulator(nrQubits);
          if (!res)
            throw std::runtime_error(
                "GpuState::Initialize: Failed to create "
                "and initialize the Pauli propagator state.");
 
          pp->SetWillUseSampling(true);  // TODO: check setting
          if (!pp->AllocateMemory(0.9))
            throw std::runtime_error(
                "GpuState::Initialize: Failed to allocate memory for the "
                "Pauli propagator state.");
        } else
          throw std::runtime_error(
              "GpuState::Initialize: Failed to create the Pauli propagator "
              "state.");
      } else
        throw std::runtime_error(
            "GpuState::Initialize: Invalid simulation "
            "type for initializing the state.");
    }
  }
 
  void InitializeState(size_t num_qubits,
                       std::vector<std::complex<double>> &amplitudes) override {
    if (num_qubits == 0) return;
    Clear();
    nrQubits = num_qubits;
    Initialize();
 
    if (simulationType != SimulationType::kStatevector)
      throw std::runtime_error(
          "GpuState::InitializeState: Invalid simulation "
          "type for initializing the state.");
 
    if (nrQubits) {
      if (simulationType == SimulationType::kStatevector) {
        state = SimulatorsFactory::CreateGpuLibStateVectorSim();
        if (state)
          state->CreateWithState(
              nrQubits, reinterpret_cast<const double *>(amplitudes.data()));
      }
    }
  }
 
#ifndef NO_QISKIT_AER
  void InitializeState(size_t num_qubits,
                       AER::Vector<std::complex<double>> &amplitudes) override {
    if (num_qubits == 0) return;
    Clear();
    nrQubits = num_qubits;
    Initialize();
 
    if (simulationType != SimulationType::kStatevector)
      throw std::runtime_error(
          "GpuState::InitializeState: Invalid simulation "
          "type for initializing the state.");
 
    if (nrQubits) {
      if (simulationType == SimulationType::kStatevector) {
        state = SimulatorsFactory::CreateGpuLibStateVectorSim();
        if (state)
          state->CreateWithState(
              nrQubits, reinterpret_cast<const double *>(amplitudes.data()));
      }
    }
  }
#endif
 
  void InitializeState(size_t num_qubits,
                       Eigen::VectorXcd &amplitudes) override {
    if (num_qubits == 0) return;
    Clear();
    nrQubits = num_qubits;
    Initialize();
 
    if (simulationType != SimulationType::kStatevector)
      throw std::runtime_error(
          "GpuState::InitializeState: Invalid simulation "
          "type for initializing the state.");
 
    if (nrQubits) {
      if (simulationType == SimulationType::kStatevector) {
        state = SimulatorsFactory::CreateGpuLibStateVectorSim();
        if (state)
          state->CreateWithState(
              nrQubits, reinterpret_cast<const double *>(amplitudes.data()));
      }
    }
  }
 
  void Reset() override {
    if (state)
      state->Reset();
    else if (mps)
      mps->Reset();
    else if (tn)
      tn->Reset();
    else if (pp)
      pp->ClearOperators();
  }
 
  void SetInitialQubitsMap(
      const std::vector<long long int> &initialMap) override {
    if (mps) mps->SetInitialQubitsMap(initialMap);
  }
 
  void Configure(const char *key, const char *value) override {
    if (std::string("method") == key) {
      if (std::string("statevector") == value)
        simulationType = SimulationType::kStatevector;
      else if (std::string("matrix_product_state") == value)
        simulationType = SimulationType::kMatrixProductState;
      else if (std::string("tensor_network") == value)
        simulationType = SimulationType::kTensorNetwork;
      else if (std::string("pauli_propagator") == value)
        simulationType = SimulationType::kPauliPropagator;
    } else if (std::string("matrix_product_state_truncation_threshold") ==
               key) {
      singularValueThreshold = std::stod(value);
      if (singularValueThreshold > 0.) {
        limitEntanglement = true;
        if (mps) mps->SetCutoff(singularValueThreshold);
        if (tn) tn->SetCutoff(singularValueThreshold);
      } else
        limitEntanglement = false;
    } else if (std::string("matrix_product_state_max_bond_dimension") == key) {
      chi = std::stoi(value);
      if (chi > 0) {
        limitSize = true;
        if (mps) mps->SetMaxExtent(chi);
        if (tn) tn->SetMaxExtent(chi);
      } else
        limitSize = false;
    } else if (std::string("use_double_precision") == key) {
      useDoublePrecision =
          (std::string("1") == value || std::string("true") == value);
    }
    // TODO: add pauli propagator configuration options
  }
 
  std::string GetConfiguration(const char *key) const override {
    if (std::string("method") == key) {
      switch (simulationType) {
        case SimulationType::kStatevector:
          return "statevector";
        case SimulationType::kMatrixProductState:
          return "matrix_product_state";
        case SimulationType::kTensorNetwork:
          return "tensor_network";
        case SimulationType::kPauliPropagator:
          return "pauli_propagator";
        default:
          return "other";
      }
    } else if (std::string("matrix_product_state_truncation_threshold") ==
               key) {
      if (limitEntanglement && singularValueThreshold > 0.)
        return std::to_string(singularValueThreshold);
    } else if (std::string("matrix_product_state_max_bond_dimension") == key) {
      if (limitSize && limitSize > 0) return std::to_string(chi);
    }
    // TODO: add pauli propagator configuration options
 
    return "";
  }
 
  size_t AllocateQubits(size_t num_qubits) override {
    if ((simulationType == SimulationType::kStatevector && state) ||
        (simulationType == SimulationType::kMatrixProductState && mps) ||
        (simulationType == SimulationType::kPauliPropagator && pp))
      return 0;
 
    const size_t oldNrQubits = nrQubits;
    nrQubits += num_qubits;
 
    return oldNrQubits;
  }
 
  size_t GetNumberOfQubits() const override { return nrQubits; }
 
  void Clear() override {
    state = nullptr;
    mps = nullptr;
    tn = nullptr;
    pp = nullptr;
    nrQubits = 0;
  }
 
  size_t Measure(const Types::qubits_vector &qubits) override {
    // TODO: this is inefficient, maybe implement it better in gpu sim
    // for now it has the possibility of measuring a qubits interval, but not a
    // list of qubits
    if (qubits.size() > sizeof(size_t) * 8)
      std::cerr
          << "Warning: The number of qubits to measure is larger than the "
             "number of bits in the size_t type, the outcome will be undefined"
          << std::endl;
 
    size_t res = 0;
    size_t mask = 1ULL;
 
    DontNotify();
    if (simulationType == SimulationType::kStatevector) {
      // TODO: measure all qubits in one shot?
      for (size_t qubit : qubits) {
        if (state->MeasureQubitCollapse(static_cast<int>(qubit))) res |= mask;
        mask <<= 1;
      }
    } else if (simulationType == SimulationType::kMatrixProductState) {
      // TODO: measure all qubits in one shot?
      for (size_t qubit : qubits) {
        if (mps->Measure(static_cast<unsigned int>(qubit))) res |= mask;
        mask <<= 1;
      }
    } else if (simulationType == SimulationType::kTensorNetwork) {
      // TODO: measure all qubits in one shot?
      for (size_t qubit : qubits) {
        if (tn->Measure(static_cast<unsigned int>(qubit))) res |= mask;
        mask <<= 1;
      }
    } else if (simulationType == SimulationType::kPauliPropagator) {
      // TODO: measure all qubits in one shot?
      for (size_t qubit : qubits) {
        if (pp->MeasureQubit(static_cast<int>(qubit))) res |= mask;
        mask <<= 1;
      }
    }
 
    Notify();
    NotifyObservers(qubits);
 
    return res;
  }
 
  std::vector<bool> MeasureMany(const Types::qubits_vector &qubits) override {
    std::vector<bool> res(qubits.size(), false);
 
    DontNotify();
    if (simulationType == SimulationType::kStatevector) {
      for (size_t i = 0; i < qubits.size(); ++i)
        res[i] = state->MeasureQubitCollapse(static_cast<int>(qubits[i]));
    } else if (simulationType == SimulationType::kMatrixProductState) {
      for (size_t i = 0; i < qubits.size(); ++i)
        res[i] = mps->Measure(static_cast<unsigned int>(qubits[i]));
    } else if (simulationType == SimulationType::kTensorNetwork) {
      for (size_t i = 0; i < qubits.size(); ++i)
        res[i] = tn->Measure(static_cast<unsigned int>(qubits[i]));
    } else if (simulationType == SimulationType::kPauliPropagator) {
      for (size_t i = 0; i < qubits.size(); ++i)
        res[i] = pp->MeasureQubit(static_cast<int>(qubits[i]));
    }
    Notify();
    NotifyObservers(qubits);
 
    return res;
  }
 
  void ApplyReset(const Types::qubits_vector &qubits) override {
    DontNotify();
    if (simulationType == SimulationType::kStatevector) {
      for (size_t qubit : qubits)
        if (state->MeasureQubitCollapse(static_cast<int>(qubit)))
          state->ApplyX(static_cast<int>(qubit));
    } else if (simulationType == SimulationType::kMatrixProductState) {
      for (size_t qubit : qubits)
        if (mps->Measure(static_cast<unsigned int>(qubit)))
          mps->ApplyX(static_cast<unsigned int>(qubit));
    } else if (simulationType == SimulationType::kTensorNetwork) {
      for (size_t qubit : qubits)
        if (tn->Measure(static_cast<unsigned int>(qubit)))
          tn->ApplyX(static_cast<unsigned int>(qubit));
    } else if (simulationType == SimulationType::kPauliPropagator) {
      for (size_t qubit : qubits)
        if (pp->MeasureQubit(static_cast<int>(qubit)))
          pp->ApplyX(static_cast<int>(qubit));
    }
 
    Notify();
    NotifyObservers(qubits);
  }
 
  double Probability(Types::qubit_t outcome) override {
    if (simulationType == SimulationType::kStatevector)
      return state->BasisStateProbability(outcome);
    else if (simulationType == SimulationType::kMatrixProductState ||
             simulationType == SimulationType::kTensorNetwork) {
      const auto ampl = Amplitude(outcome);
      return std::norm(ampl);
    } else if (simulationType == SimulationType::kPauliPropagator) {
      return pp->Probability(outcome);
    }
 
    return 0.0;
  }
 
  std::complex<double> Amplitude(Types::qubit_t outcome) override {
    double real = 0.0;
    double imag = 0.0;
 
    if (simulationType == SimulationType::kStatevector)
      state->Amplitude(outcome, &real, &imag);
    else if (simulationType == SimulationType::kMatrixProductState ||
             simulationType == SimulationType::kTensorNetwork) {
      std::vector<long int> fixedValues(nrQubits);
      for (size_t i = 0; i < nrQubits; ++i)
        fixedValues[i] = (outcome & (1ULL << i)) ? 1 : 0;
      if (simulationType == SimulationType::kMatrixProductState)
        mps->Amplitude(nrQubits, fixedValues.data(), &real, &imag);
      else if (simulationType == SimulationType::kTensorNetwork)
        tn->Amplitude(nrQubits, fixedValues.data(), &real, &imag);
    } else if (simulationType == SimulationType::kPauliPropagator) {
      // Pauli propagator does not support amplitude calculation
      throw std::runtime_error(
          "GpuState::Amplitude: Invalid simulation type for amplitude "
          "calculation.");
    }
 
    return std::complex<double>(real, imag);
  }
 
  std::complex<double> ProjectOnZero() override {
    if (simulationType == SimulationType::kMatrixProductState)
      return mps->ProjectOnZero();
 
    return Amplitude(0);
  }
 
  std::vector<double> AllProbabilities() override {
    if (nrQubits == 0) return {};
    const size_t numStates = 1ULL << nrQubits;
    std::vector<double> result(numStates);
 
    if (simulationType == SimulationType::kStatevector)
      state->AllProbabilities(result.data());
    else if (simulationType == SimulationType::kMatrixProductState ||
             simulationType == SimulationType::kTensorNetwork) {
      // this is very slow, it should be used only for tests!
      for (Types::qubit_t i = 0; i < (Types::qubit_t)numStates; ++i) {
        const auto val = Amplitude(i);
        result[i] = std::norm(std::complex<double>(val.real(), val.imag()));
      }
    } else if (simulationType == SimulationType::kPauliPropagator) {
      // this is very slow, it should be used only for tests!
      for (Types::qubit_t i = 0; i < (Types::qubit_t)numStates; ++i) {
        result[i] = pp->Probability(i);
      }
    }
 
    return result;
  }
 
  std::vector<double> Probabilities(
      const Types::qubits_vector &qubits) override {
    std::vector<double> result(qubits.size());
 
    if (simulationType == SimulationType::kStatevector) {
      for (size_t i = 0; i < qubits.size(); ++i)
        result[i] = state->BasisStateProbability(qubits[i]);
    } else if (simulationType == SimulationType::kMatrixProductState ||
               simulationType == SimulationType::kTensorNetwork) {
      for (size_t i = 0; i < qubits.size(); ++i) {
        const auto ampl = Amplitude(qubits[i]);
        result[i] = std::norm(ampl);
      }
    } else if (simulationType == SimulationType::kPauliPropagator) {
      for (size_t i = 0; i < qubits.size(); ++i)
        result[i] = pp->Probability(qubits[i]);
    }
 
    return result;
  }
 
  std::unordered_map<Types::qubit_t, Types::qubit_t> SampleCounts(
      const Types::qubits_vector &qubits, size_t shots = 1000) override {
    if (qubits.empty() || shots == 0) return {};
 
    if (qubits.size() > sizeof(Types::qubit_t) * 8)
      std::cerr
          << "Warning: The number of qubits to measure is larger than the "
             "number of bits in the Types::qubit_t type, the outcome will be "
             "undefined"
          << std::endl;
 
    std::unordered_map<Types::qubit_t, Types::qubit_t> result;
 
    DontNotify();
 
    if (simulationType == SimulationType::kStatevector) {
      std::vector<long int> samples(shots);
      state->SampleAll(shots, samples.data());
 
      for (auto outcome : samples) {
        // qubits might not be in order, translate the outcome to the correct
        // order
        Types::qubit_t translatedOutcome = 0;
        Types::qubit_t mask = 1ULL;
        for (size_t i = 0; i < qubits.size(); ++i) {
          if (outcome & (1ULL << qubits[i])) translatedOutcome |= mask;
          mask <<= 1;
        }
        ++result[translatedOutcome];
      }
    } else if (simulationType == SimulationType::kMatrixProductState) {
      std::unordered_map<std::vector<bool>, int64_t> *map =
          mps->GetMapForSample();
 
      std::vector<unsigned int> qubitsIndices(qubits.begin(), qubits.end());
 
      mps->Sample(shots, qubitsIndices.size(), qubitsIndices.data(), map);
 
      // put the results in the result map
      for (const auto &[meas, cnt] : *map) {
        Types::qubit_t outcome = 0;
        Types::qubit_t mask = 1ULL;
        for (Types::qubit_t q = 0; q < qubits.size(); ++q) {
          if (meas[q]) outcome |= mask;
          mask <<= 1;
        }
 
        result[outcome] += cnt;
      }
 
      mps->FreeMapForSample(map);
    } else if (simulationType == SimulationType::kTensorNetwork) {
      std::unordered_map<std::vector<bool>, int64_t> *map =
          tn->GetMapForSample();
      std::vector<unsigned int> qubitsIndices(qubits.begin(), qubits.end());
      tn->Sample(shots, qubitsIndices.size(), qubitsIndices.data(), map);
      // put the results in the result map
      for (const auto &[meas, cnt] : *map) {
        Types::qubit_t outcome = 0;
        Types::qubit_t mask = 1ULL;
        for (Types::qubit_t q = 0; q < qubits.size(); ++q) {
          if (meas[q]) outcome |= mask;
          mask <<= 1;
        }
        result[outcome] += cnt;
      }
      tn->FreeMapForSample(map);
    } else if (simulationType == SimulationType::kPauliPropagator) {
      std::vector<int> qb(qubits.begin(), qubits.end());
      for (size_t shot = 0; shot < shots; ++shot) {
        size_t meas = 0;
        auto res = pp->SampleQubits(qb);
        for (size_t i = 0; i < qubits.size(); ++i) {
          if (res[i]) meas |= (1ULL << i);
        }
        ++result[meas];
      }
    }
 
    Notify();
    NotifyObservers(qubits);
 
    return result;
  }
 
  std::unordered_map<std::vector<bool>, Types::qubit_t> SampleCountsMany(
      const Types::qubits_vector &qubits, size_t shots = 1000) override {
    if (qubits.empty() || shots == 0) return {};
 
    std::unordered_map<std::vector<bool>, Types::qubit_t> result;
 
    DontNotify();
 
    if (simulationType == SimulationType::kStatevector) {
      std::vector<long int> samples(shots);
      state->SampleAll(shots, samples.data());
 
      std::vector<bool> outcomeVec(qubits.size());
      for (auto outcome : samples) {
        for (size_t i = 0; i < qubits.size(); ++i)
          outcomeVec[i] = ((outcome >> qubits[i]) & 1) == 1;
        ++result[outcomeVec];
      }
    } else if (simulationType == SimulationType::kMatrixProductState) {
      std::unordered_map<std::vector<bool>, int64_t> *map =
          mps->GetMapForSample();
 
      std::vector<unsigned int> qubitsIndices(qubits.begin(), qubits.end());
      mps->Sample(shots, qubitsIndices.size(), qubitsIndices.data(), map);
 
      // put the results in the result map
      for (const auto &[meas, cnt] : *map) result[meas] += cnt;
 
      mps->FreeMapForSample(map);
    } else if (simulationType == SimulationType::kTensorNetwork) {
      std::unordered_map<std::vector<bool>, int64_t> *map =
          tn->GetMapForSample();
      std::vector<unsigned int> qubitsIndices(qubits.begin(), qubits.end());
      tn->Sample(shots, qubitsIndices.size(), qubitsIndices.data(), map);
      // put the results in the result map
      for (const auto &[meas, cnt] : *map) result[meas] += cnt;
      tn->FreeMapForSample(map);
    } else if (simulationType == SimulationType::kPauliPropagator) {
      std::vector<int> qb(qubits.begin(), qubits.end());
      for (size_t shot = 0; shot < shots; ++shot) {
        const auto res = pp->SampleQubits(qb);
        ++result[res];
      }
    }
 
    Notify();
    NotifyObservers(qubits);
 
    return result;
  }
 
  double ExpectationValue(const std::string &pauliString) override {
    double result = 0.0;
 
    if (simulationType == SimulationType::kStatevector)
      result = state->ExpectationValue(pauliString);
    else if (simulationType == SimulationType::kMatrixProductState)
      result = mps->ExpectationValue(pauliString);
    else if (simulationType == SimulationType::kTensorNetwork)
      result = tn->ExpectationValue(pauliString);
    else if (simulationType == SimulationType::kPauliPropagator)
      result = pp->ExpectationValue(pauliString);
    else
      throw std::runtime_error(
          "GpuState::ExpectationValue: Invalid simulation type for expectation "
          "value calculation.");
 
    return result;
  }
 
  SimulatorType GetType() const override { return SimulatorType::kGpuSim; }
 
  SimulationType GetSimulationType() const override { return simulationType; }
 
  void Flush() override {}
 
  void SaveStateToInternalDestructive() override {
    if (simulationType == SimulationType::kStatevector)
      state->SaveStateDestructive();
    else
      throw std::runtime_error(
          "GpuState::SaveStateToInternalDestructive: Invalid simulation type "
          "for saving the state destructively.");
  }
 
  void RestoreInternalDestructiveSavedState() override {
    if (simulationType == SimulationType::kStatevector)
      state->RestoreStateFreeSaved();
    else
      throw std::runtime_error(
          "GpuState::RestoreInternalDestructiveSavedState: Invalid simulation "
          "type for restoring the state destructively.");
  }
 
  void SaveState() override {
    if (simulationType == SimulationType::kStatevector)
      state->SaveState();
    else if (simulationType == SimulationType::kMatrixProductState)
      mps->SaveState();
    else if (simulationType == SimulationType::kTensorNetwork)
      tn->SaveState();
    else if (simulationType == SimulationType::kPauliPropagator)
      pp->SaveState();
  }
 
  void RestoreState() override {
    if (simulationType == SimulationType::kStatevector)
      state->RestoreStateNoFreeSaved();
    else if (simulationType == SimulationType::kMatrixProductState)
      mps->RestoreState();
    else if (simulationType == SimulationType::kTensorNetwork)
      tn->RestoreState();
    else if (simulationType == SimulationType::kPauliPropagator)
      pp->RestoreState();
  }
 
  std::complex<double> AmplitudeRaw(Types::qubit_t outcome) override {
    return Amplitude(outcome);
  }
 
  void SetMultithreading(bool multithreading = true) override {
    // don't do anything here, the multithreading is always enabled
  }
 
  bool GetMultithreading() const override { return true; }
 
  bool IsQcsim() const override { return false; }
 
  Types::qubit_t MeasureNoCollapse() override {
    if (simulationType == SimulationType::kStatevector)
      return state->MeasureAllQubitsNoCollapse();
    else if (simulationType == SimulationType::kMatrixProductState ||
             simulationType == SimulationType::kTensorNetwork ||
             simulationType == SimulationType::kPauliPropagator) {
      if (nrQubits > sizeof(Types::qubit_t) * 8)
        std::cerr
            << "Warning: The number of qubits to measure is larger than the "
               "number of bits in the Types::qubit_t type, the outcome will be "
               "undefined"
            << std::endl;
 
      Types::qubits_vector fixedValues(nrQubits);
      std::iota(fixedValues.begin(), fixedValues.end(), 0);
      const auto res = SampleCounts(fixedValues, 1);
      if (res.empty()) return 0;
      return res.begin()
          ->first;  // return the first outcome, as it is the only one
    }
 
    throw std::runtime_error(
        "QCSimState::MeasureNoCollapse: Invalid simulation type for measuring "
        "all the qubits without collapsing the state.");
 
    return 0;
  }
 
  std::vector<bool> MeasureNoCollapseMany() override {
    if (simulationType == SimulationType::kStatevector) {
      const auto meas = state->MeasureAllQubitsNoCollapse();
      std::vector<bool> result(nrQubits, false);
      for (size_t i = 0; i < nrQubits; ++i) result[i] = ((meas >> i) & 1) == 1;
      return result;
    } else if (simulationType == SimulationType::kMatrixProductState ||
               simulationType == SimulationType::kTensorNetwork ||
               simulationType == SimulationType::kPauliPropagator) {
      Types::qubits_vector fixedValues(nrQubits);
      std::iota(fixedValues.begin(), fixedValues.end(), 0);
      const auto res = SampleCountsMany(fixedValues, 1);
      if (res.empty()) return std::vector<bool>(nrQubits, false);
      return res.begin()
          ->first;  // return the first outcome, as it is the only one
    }
 
    throw std::runtime_error(
        "QCSimState::MeasureNoCollapseMany: Invalid simulation type for "
        "measuring "
        "all the qubits without collapsing the state.");
 
    return std::vector<bool>(nrQubits, false);
  }
 
 protected:
  SimulationType simulationType =
      SimulationType::kStatevector; 
  std::unique_ptr<GpuLibStateVectorSim>
      state;                         
  std::unique_ptr<GpuLibMPSSim> mps; 
  std::unique_ptr<GpuLibTNSim> tn;   
  std::unique_ptr<GpuPauliPropagator>
      pp; 
  size_t nrQubits = 0; 
  bool limitSize = false;
  bool limitEntanglement = false;
  Eigen::Index chi = 10;               // if limitSize is true
  double singularValueThreshold = 0.;  // if limitEntanglement is true
  bool useDoublePrecision = false;     // if true, GPU MPS uses float64
};
 
}  // namespace Private
}  // namespace Simulators
 
#endif
#endif
#endif