Abstract Interacting spin systems in solids underpin a wide range of quantum technologies, from quantum sensors and single-photon sources to spin-defect-based quantum registers and processors. We develop a quantum-computer-aided framework for simulating such devices using a general many-body electron-spin-resonance Hamiltonian that incorporates zero-field splitting, the Zeeman effect, hyperfine interactions, dipole–dipole spin–spin interactions, and electron-phonon decoherence. Within this framework, we combine gray-encoded qudit-to-qubit mappings, qubit-wise commuting aggregation, and a multi-reference selected quantum Krylov fast-forwarding (sQKFF) hybrid algorithm, aiming to access extended-time dynamics within the constraints of Noisy Intermediate-Scale Quantum and early fault-tolerant hardware. Numerical simulations demonstrate the computation of operationally useful quantities including autocorrelation functions up to ∼ 100 ns, together with microwave absorption spectra and the ℓ 1 -norm of coherence, achieving 18 % –30 % reductions in gate counts and circuit depth for Trotterized time-evolution circuits compared to unoptimized implementations. Using the nitrogen vacancy center in diamond as a testbed, we benchmark the framework against classical simulations and identify the reference-state selection in sQKFF as the primary factor governing accuracy at fixed hardware cost. This methodology provides a flexible blueprint for using quantum computers to design, compare, and optimize solid-state spin-qubit technologies under experimentally realistic conditions.
Abstract Interacting spin systems in solids underpin a wide range of quantum technologies, from quantum sensors and single-photon sources to spin-defect-based quantum registers and processors. We develop a quantum-computer-aided framework for simulating such devices using a general many-body electron-spin-resonance Hamiltonian that incorporates zero-field splitting, the Zeeman effect, hyperfine interactions, dipole–dipole spin–spin interactions, and electron-phonon decoherence. Within this framework, we combine gray-encoded qudit-to-qubit mappings, qubit-wise commuting aggregation, and a multi-reference selected quantum Krylov fast-forwarding (sQKFF) hybrid algorithm, aiming to access extended-time dynamics within the constraints of Noisy Intermediate-Scale Quantum and early fault-tolerant hardware. Numerical simulations demonstrate the computation of operationally useful quantities including autocorrelation functions up to ∼ 100 ns, together with microwave absorption spectra and the ℓ 1 -norm of coherence, achieving 18 % –30 % reductions in gate counts and circuit depth for Trotterized time-evolution circuits compared to unoptimized implementations. Using the nitrogen vacancy center in diamond as a testbed, we benchmark the framework against classical simulations and identify the reference-state selection in sQKFF as the primary factor governing accuracy at fixed hardware cost. This methodology provides a flexible blueprint for using quantum computers to design, compare, and optimize solid-state spin-qubit technologies under experimentally realistic conditions.
Interacting spin systems in solids underpin a wide range of quantum technologies, from quantum sensors and single-photon sources to spin-defect-based quantum registers and processors. We develop a quantum-computer-aided framework for simulating such devices using a general many-body electron-spin-resonance Hamiltonian that incorporates zero-field splitting, the Zeeman effect, hyperfine interactions, dipole-dipole spin-spin interactions, and electron-phonon decoherence. Within this framework, we combine Gray-encoded qudit-to-qubit mappings, qubit-wise commuting aggregation, and a multi-reference selected quantum Krylov fast-forwarding hybrid algorithm, aiming to access extended-time dynamics within the constraints of NISQ and early fault-tolerant hardware. Numerical simulations demonstrate the computation of operationally useful quantities including autocorrelation functions up to ∼100 ns, together with microwave absorption spectra and the ℓ1-norm of coherence, achieving 18-30% reductions in gate counts and circuit depth for Trotterized time-evolution circuits compared to unoptimized implementations. Using the nitrogen vacancy center in diamond as a testbed, we benchmark the framework against classical simulations and identify the reference-state selection in sQKFF as the primary factor governing accuracy at fixed hardware cost. This methodology provides a flexible blueprint for using quantum computers to design, compare, and optimize solid-state spin-qubit technologies under experimentally realistic conditions.
Molecular spins represent a versatile platform for quantum information science, with the potential to offer chemically tunable, addressable qubits. However, achieving this requires understanding and mitigating quantum decoherence. This Chapter provides a theoretical overview of current state-of-the-art chemical theory connecting ab initio electronic structure with open quantum system dynamics to guide the rational design of long-lived molecular qubits. Beginning at the electronic level, multi-reference and relativistic electronic structure methods to parameterize effective spin Hamiltonians are discussed, with a primary focus on accurately capturing g-tensors, zero-field splitting, and hyperfine interactions. These parameters feed into models of spin-phonon and spin-spin coupling to quantify T1 and T2 relaxation across various environmental regimes. This Chapter evaluates a hierarchy of dynamical methods, ranging from factorization to matrix product state approaches, balancing computational cost against accuracy and generalizability. Ultimately, mapping these theoretical models to molecular architecture can establish design principles, such as isotopic substitution and spatial spin delocalization, to understand and extend coherence lifetimes.
Modern society increasingly depends on ever more capable computing devices. Yet some important problems remain beyond the reach of classical computers due to their inherent computational complexity. At the same time, the energy required to power this growing computational demand is an important concern. Over the past decade, quantum computers have received increased attention, not as a replacement for classical systems, but as a complementary technology with the potential to tackle complex problems more efficiently and significantly boost computational performance. This is made possible by leveraging the principles of quantum mechanics. To achieve this, quantum computers rely on a fundamental basic block called a qubit. There are several different technologies for realizing qubits, and no single approach has yet established itself as the definitive choice. In this work, we focus on silicon spin qubits in quantum dots, which use the intrinsic spin states of an electron as the computational basis states. This platform offers notable advantages including long coherence times, compatibility with the existing semiconductor industry and scalability. However, this technology is still very immature and substantial progress is still required. Just like for the design of classical electronics, simulations can play a crucial role by reducing development cycles, lowering costs, and improving overall efficiency. Throughout this thesis, we will propose a comprehensive simulation framework that allows to study and design spin qubit systems focusing on key aspects of the system architecture. First, a spin qubit compact model is presented that enables the co-simulation of spin qubits together with the classical CMOS control and readout circuitry that will significantly impact the performance of the qubits. We show that the model is capable of including all elements to build an elementary quantum gate set and illustrate its use by co-simulating a spin qubit coupled to a readout resonator with a complete cryo-CMOS readout chip design in a commercial electronic design automation tool. Next, we discuss a hybrid-Hamiltonian simulation approach that is aimed at simulating spin qubit microarchitectures that are suited for running quantum error correction protocols, which protect the encoded information against the errors that unavoidably happen due to the inherently noisy physical qubit devices. This simulation approach incorporates several novel strategies to tackle the challenge of the required computing power that grows exponentially with the size of the simulated system. Furthermore, additional functionality is incorporated to evaluate and track the performance of the implemented error correction protocols. Finally, we propose a characterization protocol for constructing a correlated noise model of the charge noise that is an important factor affecting spin qubit performance. The sources of charge noise are modelled as two-level fluctuators and the entire qubit array is characterized by dividing it into patches and running batches of benchmarking quantum gate sequences. The resulting noise model enables to scale the simulations to larger system sizes and to study the system performance and hardware demands of error correction protocols. Together, these models form a multi-layer simulation framework that enables detailed analysis and optimization of future spin qubit microarchitectures, with particular emphasis on error correction protocols. As such, the framework contributes to the realization of practical large-scale quantum computing.
Abstract Nitrogen-vacancy (NV) centers in diamond have been developed into essential hardware units for a wide range of solid-state-based quantum technology applications. While such applications require the long spin coherence times of the NV centers, they are often limited due to decoherence. In this study, we theoretically investigate the decoherence of NV-spin ensembles induced by nitrogen impurities (P1 centers), which are one of the most dominant and inevitable magnetic field noise sources in diamond. We combined cluster correlation expansion and density functional theory to compute the Hahn-echo spin-coherence time of the NV centers for a broad range of P1 concentrations. Results indicate a clear linear dependence of T2 on P1 concentrations on a log scale with a slope of −1.06, which is in excellent agreement with previous experimental results. The interplay between the Jahn–Teller effect and the hyperfine interaction in the P1 center plays a critical role in determining the bath dynamics and the resulting NV decoherence. Our results provide a theoretical upper bound for the NV-spin T2 over a wide range of P1 densities, serving as a key reference for materials optimization and spin bath characterization to develop highly coherent NV-based devices for quantum information technology.
Quantum computers hold promise to greatly improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties more complex than tractable on classical architectures. Here, we discuss computational frameworks to carry out electronic structure calculations of solids on noisy intermediate scale quantum computers using embedding theories and effective many-body Hamiltonians. We focus on a specific class of materials, i.e., spin defects in solids, which are promising systems to build future quantum technologies, e.g., computers, sensors and devices for quantum communications. Although quantum simulations on quantum architectures are in their infancy, promising results for realistic systems appear within reach.
The ability to manipulate individual quantum systems in a precise way has led to a new era of quantum technologies, including quantum computation and quantum simulation. In this thesis we present several new implementations of these quantum technologies. We first aim at addressing current experimental challenges for quantum dot based quantum computing. We propose a systematic way to study the dynamics of nuclear spin, which is responsible for the short electron spin coherence time. Our calculation is based on diffusion model and is consistent with experiments. We also invent a novel protocol to realize high-fidelity ultrafast universal quantum gate in recently-developed quantum dot molecule system. Experimental realization of our protocol requires only a simple time engineering of optical pulses. We then propose a new quantum state transfer scheme for Nitrogen-Vacancy center based quantum computer, which is applicable at room temperature. Our method accomplishes high fidelity robust quantum state transfer through uncontrolled thermal nitrogen spin chain between two remote NV registers. Our next study helps building a hybrid quantum computer by entangling disparate systems using photonic links. The photons emitted from two types of system need to be matched in both frequency and pulse shape. We propose a simple method to match the emitted pulse shape from two qubit systems with different transition linewidths. We then focus on quantum simulation with trapped ions. We show the possibility of observing a novel type of temperature driven structural phase transition in trapped ion chain, which originates from anharmonic interaction between different vibrational modes. Afterward, an experimental protocol to simulate a conceptually new state of matter, called time crystal, is proposed based on ions trapped in a ring trap. Finally, we propose two new applications based on the recently developed trapped ion quantum simulator of spin models: (1) simulation of Haldane-Shastry model, which opens the way of experimental study to a remarkable theoretical model involving spin liquid ground state and fractional excitations (2) observation of prethermalization and dynamical phase transition, which are poorly understood non-equilibrium phenomena in closed quantum many-body system.