Achieving low-error, exchange-interaction operations in quantum dots for quantum computing imposes simultaneous requirements on the exchange energy's dependence on applied voltages. A double quantum dot qubit, approximated with a quadratic potential, is solved using a full configuration interaction method. This method is more accurate than Heitler-London and Hund-Mulliken approaches and captures new and significant qualitative behavior. We show that multiple regimes can be found in which the exchange energy's dependence on the bias voltage between the dots is compatible with current quantum error correction codes and state-of-the-art electronics. Identifying such regimes may prove valuable for the construction and operation of quantum gates that are robust to charge fluctuations, particularly in the case of dynamically corrected gates.
Achieving low-error, exchange-interaction operations in quantum dots for quantum computing imposes simultaneous requirements on the exchange energy's dependence on applied voltages. A double quantum dot qubit, approximated with a quadratic potential, is solved using a full configuration interaction method. This method is more accurate than Heitler-London and Hund-Mulliken approaches and captures new and significant qualitative behavior. We show that multiple regimes can be found in which the exchange energy's dependence on the bias voltage between the dots is compatible with current quantum error correction codes and state-of-the-art electronics. Identifying such regimes may prove valuable for the construction and operation of quantum gates that are robust to charge fluctuations, particularly in the case of dynamically corrected gates.
We describe in detail a full configuration interaction (CI) method designed to analyze systems of quantum dots. This method is capable of exploring large regions of parameter space, like more approximate approaches such as Heitler London and Hund Mulliken, though it is not limited to weakly coupled dots. In particular, this method is well-suited to the analysis of solid state quantum-dot-based qubits, and we consider the case of a double quantum dot (DQD) singlet-triplet qubit. Past analyses have used techniques which are either substantially restricted in the regimes they can be used, or device specific and unsuited to exploration of a large regions of parameter space. We analyze how the DQD exchange energy, which is central to the operation of qubit rotation gates, depends on a generic set of system parameters including magnetic field, DQD detuning, dot size, and dot separation. We discuss the implications of these results to the construction of real devices. We provide a benchmark of the CI by directly comparing results from the CI method with exact results for two electrons in a single parabolic potential (dot).
We consider qubit coupling resulting from the capacitive coupling between two double quantum dot (DQD) singlet-triplet qubits. Calculations of the coupling when the two DQDs are detuned symmetrically or asymmetrically are performed using a full configuration interaction (CI). The full CI reveals behavior that is not observed by more commonly used approximations such as Heitler London or Hund Mulliken, particularly related to the operation of both DQDs in the (0,2) charge sector. We find that there are multiple points in detuning space where a two-qubit entangling gate can be realized, and that tradeoffs between coupling magnitude and sensitivity to fluctuations in detuning make a case for operating the gate in the (0,2) regime not commonly considered.
Quantum computers offer a route to outperform classical methods in tasks such as molecular simulation, motivating hybrid algorithms like the Variational Quantum Eigensolver (VQE) for near-term devices. Silicon spin qubits are a promising platform for scalable quantum computation, but their performance is limited by hardware imperfections -- most notably charge-noise-induced potential fluctuations and static miscalibration of gate-electrode voltages -- which degrade quantum gate fidelities and, ultimately, algorithmic accuracy. Here we develop a hardware-algorithm co-simulation framework for silicon quantum-dot processors that links 3D electrostatics to effective g-factors and exchange couplings, and propagates voltage-level noise through realistic control pulses. Using VQE for H2 ground-state energy estimation as a circuit-level testbed, we study both static scaling/offset errors on the gate-electrode voltages and stochastic fluctuations modeled as random-telegraph noise with tunable amplitudes and switching times. At the gate level, we show that exchange-based two-qubit gates are roughly an order of magnitude more sensitive to these types of noise than ESR-driven single-qubit rotations. Quantum process tomography and Kraus-operator analysis further distinguish coherent and incoherent contributions and quantify the fraction of error that is, in principle, correctable by a compensating unitary. Embedding these noise models into the VQE circuit, we identify regimes of miscalibration strength and noise switching time compatible with chemically accurate energy estimates, and discuss how statistical post-processing based on the full distribution of noisy energy estimates could further improve accuracy.
The spin of an electron confined in semiconductor quantum dots is currently a promising candidate for quantum bit (qubit) implementations. Taking advantage of the existing CMOS integration technologies, such devices can offer a platform for large scale quantum computation. However, a quantum mechanical framework bridging a device's physical design and operational parameters to the qubit's energy space is lacking. Furthermore, the spin to charge coupling introduced by intrinsic or induced spin-orbit interaction (SOI) exposes the qubits to charge noise compromising their coherence properties and inducing quantum gate errors. We present here a comodeling framework for double quantum dot (DQD) devices and their charge noise environments. We use a combination of an electrostatic potential solver, full configuration interaction quantum mechanical methods, and two-level-fluctuator models to study the quantum gate performance in realistic device designs and operation conditions. We utilize the developed models together alongside the single electron solutions of the quantum dots to simulate one- and two-qubit gates in the presence of charge noise. We find an inverse correlation between quantum gate errors and quantum dot confinement frequencies. We calculate X-gate fidelities >97 in the simulated Si-MOS devices at a typical TLF density of ${10}^{11}\phantom{\rule{4pt}{0ex}}{\mathrm{cm}}^{\ensuremath{-}2}$. We also find that exchange driven two-qubit SWAP gates show higher sensitivity to charge noise with fidelities down to 91 in the presence of the same density of TLFs. We further investigate the one- and two-qubit gate fidelities at different TLF densities. We find that given the small size of the quantum dots, sensitivity of a quantum gate to the distance between the noise sources and the quantum dot creates a strong variability in the quantum gate fidelities, which can compromise the device yields in scaled qubit technologies.
Abstract Quantum computers offer a route to outperform classical methods in tasks such as molecular simulation, motivating hybrid algorithms like the variational quantum eigensolver (VQE) for near-term devices. Silicon spin qubits are a promising platform for scalable quantum computation, but their performance is limited by hardware imperfections—most notably charge-noise–induced potential fluctuations and static miscalibration of gate-electrode voltages—which degrade quantum gate fidelities and, ultimately, algorithmic accuracy. Here we develop a hardware–algorithm co-simulation framework for silicon quantum-dot processors that links 3D electrostatics to effective g -factors and exchange couplings, and propagates voltage-level noise through realistic control pulses. Using VQE for H 2 ground-state energy estimation as a circuit-level testbed, we study both static scaling/offset errors on the gate-electrode voltages and stochastic fluctuations modeled as random-telegraph noise with tunable amplitudes and switching times. At the gate level, we show that exchange-based two-qubit gates are roughly an order of magnitude more sensitive to these types of noise than ESR-driven single-qubit rotations. Quantum process tomography and Kraus-operator analysis further distinguish coherent and incoherent contributions and quantify the fraction of error that is, in principle, correctable by a compensating unitary. Embedding these noise models into the VQE circuit, we identify regimes of miscalibration strength and noise switching time compatible with chemically accurate energy estimates, and discuss how statistical post-processing based on the full distribution of noisy energy estimates could further improve accuracy.
Electron spins in semiconductor devices are highly promising building blocks for quantum processors (QPs). Commercial semiconductor foundries can create QPs using the same processes used for conventional chips, once the QP design is suitably specified. There is a vast accessible design space; to identify the most promising options for fabrication, one requires predictive modeling of interacting electrons in real geometries and complex nonideal environments. In this work we explore a modeling method based on real-space grids, an approach without assumptions relating to device topology and therefore with wide applicability. Given an electrode geometry, we determine the exchange coupling between quantum dot qubits, and model the full evolution of a SWAP gate to predict qubit loss and infidelity rates for various voltage profiles. We determine full, three-dimensional solutions and introduce a method that can obtain near-identical predictions using far more efficient two-dimensional computations. Moreover we explore the impact of unwanted charge defects (static and dynamic) in the environment, and test robust pulse sequences. As an example we exhibit a sequence correcting both systematic errors and (unknown) charge defects, observing an order of magnitude boost in fidelity. The technique can thus identify the most promising device designs for fabrication, as well as bespoke control sequences for each such device.