Abstract Quantum simulation represents the most promising quantum application to demonstrate quantum advantage on near-term noisy intermediate-scale quantum (NISQ) computers, yet available quantum simulation algorithms are prone to errors and thus difficult to realize with limited circuit depth on nowadays quantum devices. Herein, we propose a novel scheme to utilize intrinsic gate errors of NISQ devices to enable controllable simulation of open quantum system dynamics without ancillary qubits or explicit bath engineering, thus turning unwanted quantum noises into useful quantum resources. Specifically, we simulate the energy transfer process in a photosynthetic dimer system on IBM-Q cloud. By employing tailored decoherence-inducing gates, we show that quantum dissipative dynamics can be simulated efficiently across coherent-to-incoherent regimes with results comparable to those of the numerically exact classical method. Moreover, we demonstrate a calibration routine that enables consistent and predictive simulations of open-quantum system dynamics in the intermediate coupling regime. This work provides a new direction for quantum advantage in the NISQ era.
Abstract Quantum simulation represents the most promising quantum application to demonstrate quantum advantage on near-term noisy intermediate-scale quantum (NISQ) computers, yet available quantum simulation algorithms are prone to errors and thus difficult to realize with limited circuit depth on nowadays quantum devices. Herein, we propose a novel scheme to utilize intrinsic gate errors of NISQ devices to enable controllable simulation of open quantum system dynamics without ancillary qubits or explicit bath engineering, thus turning unwanted quantum noises into useful quantum resources. Specifically, we simulate the energy transfer process in a photosynthetic dimer system on IBM-Q cloud. By employing tailored decoherence-inducing gates, we show that quantum dissipative dynamics can be simulated efficiently across coherent-to-incoherent regimes with results comparable to those of the numerically exact classical method. Moreover, we demonstrate a calibration routine that enables consistent and predictive simulations of open-quantum system dynamics in the intermediate coupling regime. This work provides a new direction for quantum advantage in the NISQ era.
We study whether dissipative energy-transfer dynamics can be simulated on noisy near-term quantum hardware by treating device noise as a calibrated resource rather than purely as an error source. Focusing on a biased exciton dimer, we encode the single-excitation manifold into a two-qubit subspace and implement the coherent dynamics through a shallow Trotterized propagator, while repeated noisy identity operations provide an effective dissipative channel. We benchmark the resulting short-time population dynamics against the hierarchical equations of motion (HEOM), which serves as a numerically accurate reference for the corresponding open-system model. On IBM quantum hardware, the calibrated noisy circuit reproduces a broad range of dissipative trajectories in the tested regime, and the fitted HEOM parameters exhibit an approximately linear dependence on the noisy-gate frequency. This empirical relation enables a practically useful interpolation strategy: once calibrated by a finite set of HEOM calculations, the noisy circuit can replace repeated HEOM fitting for intermediate parameter points within the same biased-dimer family. To extend the dynamics beyond the circuit-depth limit, we combine the short-time quantum data with the transfer tensor method (TTM). In simulator studies, TTM accurately extends the dynamics well beyond the directly simulated window, whereas on real hardware its performance is limited by the instability of coherence-sensitive initial states. Our results show that noisy few-qubit devices can act as calibrated phenomenological simulators of open-system dynamics and, within a restricted but experimentally relevant regime, can provide a practical surrogate for repeated HEOM-based modeling.
Abstract Simulating open quantum systems (OQS) is essential for understanding quantum thermodynamics and materials science. However, noisy intermediate-scale quantum (NISQ) devices are severely bottlenecked by limited coherence times and gate infidelities. Conventional quantum simulations of Amplitude-Damping Lindblad dynamics requires active dissipative gates and ancilla environments, leading to spurious qubit flips, state saturation, and a significant two-qubit overhead. While recent methods exploit intrinsic hardware noise for quantum simulation, they mainly rely on tailored decoherence-inducing gates or complex error mitigation. Here, we introduce a hardware-intrinsic time-scaling methodology that completely eliminates active dissipative gates. By mapping the processor's continuous energy relaxation (T1) explicitly via native delay instructions, our protocol captures targeted dissipative dynamics with a strict O(1) algorithmic overhead, bypassing conventional mitigation sampling costs. We experimentally demonstrate this efficient approach on two IBM quantum architectures, successfully emulating tight-binding parameter regimes. These include nanosecond magnon propagation in yttrium iron garnet (YIG) spin chains, as well as ultrafast picosecond phonon dynamics across 1D transport channels within 2D molybdenum disulfide (MoS2) and multi-site graphene lattices. Furthermore, to mitigate error accumulation in multi-site arrays, we implement a depth-dependent scaling protocol. Finally, the proposed method is extended to the fermionic domain, emulating the femtosecond relaxation of an isolated charge carrier across 4-qubit topologies. This methodology provides a scalable pathway for robust, hardware-tailored materials simulations.
Quantum systems are inherently open and susceptible to environmental noise, which can have both detrimental and beneficial effects on their dynamics.This phenomenon has been observed in biomolecular systems, where noise enables novel functionalities, making the simulation of their dynamics a crucial target for digital and analog quantum simulation.Nevertheless, the computational capabilities of current quantum devices are often limited due to their inherent noise.In this work, we present a novel approach that capitalizes on the intrinsic noise of quantum devices to reduce the computational resources required for simulating open quantum systems.Our approach combines quantum noise characterization methods with quantum error mitigation techniques, enabling us to manipulate and control the intrinsic noise in a quantum circuit.Specifically, we selectively enhance or reduce decoherence rates in the quantum circuit to achieve the desired simulation of open-system dynamics.We provide a detailed description of our methods and report on the results of noise characterization and quantum error mitigation experiments conducted on both real and emulated IBM Quantum computers.Additionally, we estimate the experimental resource requirements for our techniques.Our approach holds the potential to unlock new simulation techniques in noisy intermediate-scale quantum devices, harnessing their intrinsic noise to enhance quantum computations.
Quantum mechanical problems are among the hardest to simulate and, in some cases, remain intractable even for the most powerful computers. Quantum computing has emerged as a new technological platform to address such challenges, with rapid advances in recent years. Yet, current quantum devices remain noisy and limited in scale. Hence, it is essential to identify classically hard problems of practical interest and tractable with existing quantum devices. Among potential applications, the real-time simulation of quantum systems is one of the most promising to deliver an early, practical quantum advantage. This doctoral thesis is therefore centered around simulating quantum dynamics on quantum devices. We first present an overview of the most relevant quantum algorithms for quantum dynamics, highlighting respective advantages and limitations. Further, we identify relevant problems within quantum dynamics that could benefit from quantum simulation in the near future. Second, we propose a method for benchmarking hardware and error mitigation algorithms that is based on well-understood theoretical results and suffers from no scaling issues. The resulting quality metric is intuitive and transferable to other applications. We successfully implement the scheme on up to 133 qubits, demonstrating coherent evolution up to a two-qubit gate depth of 28, featuring 1396 two-qubit gates, before noise becomes prevalent. Third, we propose a novel variant of probabilistic error amplification to implement open quantum dynamics, relying on characterizing and altering hardware noise to mimic the system-environment interaction under study. Lastly, we present two studies on state preparation and phase classification: first, a hybrid algorithm to prepare ground states of electron-phonon systems; second, a quantum machine learning-based approach to distinguish phases in previously prepared quantum states.
Quantum computers are expected to help us to achieve accurate simulation of the dynamics of many-body quantum systems. However, the limitations of current NISQ devices prevents us from realising this goal today. Recently an algorithm for performing quantum simulations called quantum assisted simulator has been proposed that promises realization on current experimental devices. In this work, we extend the quantum assisted simulator to simulate the dynamics of a class of time-dependent Hamiltonians. We show that the quantum assisted simulator is easier to implement as well as can realize multi-qubit interactions and challenging driving protocols that are difficult with other existing methods. We demonstrate this for a time-dependent Hamiltonian on the IBM Quantum Experience cloud quantum computer by showing superior performance of the quantum assisted simulator compared to Trotterization and variational quantum simulation. Further, we demonstrate the capability to simulate the dynamics of Hamiltonians consisting of 10000 qubits. Our results indicate that quantum assisted simulator is a promising algorithm for current term quantum hardware.
Quantum simulation of open quantum systems in the noisy intermediate-scale quantum (NISQ) era is hindered by the non-unitary nature of dissipative dynamics and the limited quantum resources available on near-term quantum processors. In this work, we propose a resource-efficient algorithm for simulating Lindbladian dynamics on NISQ devices. For open quantum systems with Pauli dissipations, we first derive a compact and stable mixed-unitary adjoint channel that approximates the target dissipative dynamics and enables ancilla-free implementation through trajectory sampling. To further reduce the circuit depth required for implementing the sampled trajectories, we introduce an adaptive variational quantum trajectory compression framework. In this framework, a depth-adaptive parameterized quantum circuit is trained to approximate repeated Trotterized Hamiltonian simulation operators, which are then used to replace repeated unitary segments appearing in the sampled trajectories. Importantly, the training procedure can also be performed without auxiliary qubits. Numerical simulations of the dissipative quantum XY model demonstrate the accuracy and resource efficiency of the proposed algorithm. Our results provide a practical route toward ancilla-free and depth-reduced simulation of open quantum systems on near-term quantum hardware.