Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session M74: Spin Qubit Measurement IFocus
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Sponsoring Units: DQI Chair: Nathan Holman, HRL Laboratories, LLC Room: Room 403/404 |
Wednesday, March 8, 2023 8:00AM - 8:36AM |
M74.00001: The role of Coulomb interactions in few-electron quantum dots in silicon Invited Speaker: Ekmel Ercan Gate-defined quantum dots in silicon are attractive systems for quantum computing thanks to the favorable material properties of silicon and their potential for scalability. Although single spins can be viewed as canonical qubits, in many situations researchers turn to multielectron dots to achieve better control, measurement or coherence properties. In this talk, I will describe our theoretical work investigating how Coulomb interactions affect the properties of qubits in Si/SiGe quantum dots. In the first part of the talk, I will discuss the interplay between these interactions and the valley physics in a two-electron quantum dot, with a particular focus on the singlet-triplet (ST) splitting due to its importance in qubit measurement and control [1,2]. I will also show how these results allow us to explain recent experiments that demonstrate wide-range tunability of the ST splitting and coherent manipulation of Wigner molecular states [3,4]. In the second part of the talk, I will focus on multielectron electrically driven spin resonance (EDSR) control. Other recent experiments in Si MOS have demonstrated that increasing the electron number in EDSR can lead to faster Rabi oscillations [5]. By providing comparisons between single- and three-electron systems I will describe the confinement and interface conditions that benefit dots with larger numbers of electrons and discuss prospects for further improvements [6]. |
Wednesday, March 8, 2023 8:36AM - 8:48AM |
M74.00002: Energy levels of the one and two electrons in a Silicon Quantum Dot Bilal Tariq, Xuedong Hu Spin qubits based on electrons confined in silicon quantum dots are promising candidates for universal quantum computation due to their long coherence time and high-fidelity qubit manipulation. The energy levels in a quantum dot are strongly dependent on its size and the coulomb interactions between the electrons. In silicon, the presence of the nearly degenerate valley states provides an additional complexity to the electron spectrum and dynamics. Here we study the effects of the valley-orbit coupling and the change in its value due to interface roughness on the energy spectrum in the spin blockade regime. We have included the valley-orbit coupling in the excited orbital states and studied their impact on the energy levels of a single- and two-electron quantum dot. Our results shed new lights on the controllability and detectability of silicon-based spin qubit for its application in quantum information processing. |
Wednesday, March 8, 2023 8:48AM - 9:00AM |
M74.00003: Two-spin relaxation in a silicon quantum dot Courtney E Fitzgerald, Xuedong Hu We calculate two-spin relaxation in a silicon quantum dot. We first perform a partial configuration interaction calculation to obtain the low-energy singlet and triplet states taking into consideration valley-orbit coupling. We then consider spin-flip transitions due to spin-orbit coupling, both intrinsic (Rashba and Dresselhaus terms) and extrinsic (such as the magnetic field gradient due to a micromagnet), and calculate relaxation rates enabled by electrical fluctuations such as phonon noise, Johnson noise, and background charge fluctuations. We then explore the dependence of the relaxation rates on physical parameters such as the dot size, the spin-orbit coupling strength, and the external magnetic field. |
Wednesday, March 8, 2023 9:00AM - 9:12AM |
M74.00004: Valley splitting in the disordered and deterministic regimes Merritt P Losert, Rajib Rahman, Giordano Scappucci, Mark A Eriksson, Susan N Coppersmith, Mark Friesen We show that there are two distinct ways to influence valley splitting in Si/SiGe devices: deterministically, using sharp features in the heterostructure, and through disorder, where valley splitting arises due to the random distribution of Ge atoms in the crystal lattice structure. Most current devices operate in the disordered regime: to give rise to significant deterministic valley splitting, the sharp features of the interface must be thinner than 3 monolayers. While difficult to construct, devices in the deterministic regime, like the recently-proposed wiggle well, can achieve high valley splittings with 100% yield. In the disordered regime, the average valley splitting can be enhanced by increasing the average Ge concentration. While this strategy does not require sharp heterostructure features and is not significantly affected by interface steps, it is statistical in nature, so there is always a nonzero probability of low valley splitting. We show that the ability to reposition a dot makes it possible to achieve high valley splittings with high yield. |
Wednesday, March 8, 2023 9:12AM - 9:24AM |
M74.00005: Automated Characterization of a Double Quantum Dot using the Hubbard Model Will Wang, John Rooney, HongWen Jiang Semiconductor quantum dots are favorable candidates for quantum information processing due to their long coherence time and potential scalability. However, calibration and characterization of an interconnected quantum dot array have proven to be a difficult task. One method to characterize the configuration of such an array is to use the Hubbard model [1]. In this talk, we discuss an automated characterization algorithm that efficiently extracts the Hubbard model parameters including the tunnel coupling and capacitive coupling energy from experimental stability diagrams. Leveraging the dual annealing optimizer, we determine the set of Hubbard parameters that best characterize the experimental data. Our method is advantageous in its robustness in the large tunneling regime when compared to the commonly used DiCarlo method for extracting the tunnel coupling [2]. We extract tunnel couplings ranging from 60 to 470 μeV and discuss the limiting factors of our method, including the stability diagram resolution and parameter degeneracies. |
Wednesday, March 8, 2023 9:24AM - 9:36AM |
M74.00006: Fast compensation of rf-QD charge sensors Joseph Hickie, Barnaby van Straaten, Federico Fedele, Florian Vigneau, Daniel Jirovec, Andrea Ballabio, Daniel Chrastina, Giovanni Isella, Georgios Katsaros, Natalia Ares Quantum dot charge sensors allow for efficient spin qubit readout. The tuning of this quantum dot sensor is key for optimised readout. Crosstalk between the gates that define the quantum dot device and the quantum dot sensor often shifts the sensor away from its optimal operation condition. We present an approach for optimally tuning a radio-frequency sensor dot and for keeping it in tune. We use fast algorithms to optimise the readout contrast and to compensate for gate crosstalk. With this aim, we extract the coupling strength between both device and charge sensor gates and the sensing dot. We show that this approach can compensate over large voltage sweeps of greater than 1V , with a fast recalibration procedure to accurately compensate for gate crosstalk anywhere in gate parameter space. |
Wednesday, March 8, 2023 9:36AM - 9:48AM |
M74.00007: Universal qubit control through FPGA-accelerated qubit classification, Hamiltonian estimation and real-time feedback [Part 1] Joost van der Heijden, Fabrizio Berritta, Torbjørn R Rasmussen, Fabio Ansaloni, Federico Fedele, Saeed Fallahi, Geoffrey C Gardner, Michael J Manfra, Yonatan Cohen, Jonatan Kutchinsky, Anasua Chatterjee, Ferdinand Kuemmeth Gate-controlled spin qubits are a promising platform for implementing quantum processors [1,2] and now operate near the error-correctable threshold [3]. To correct errors, however, fast real-time feedback based on qubit measurements must be executed within the coherence time of the qubits. Moreover, continuous real-time feedback is also useful to tune and calibrate the qubit environment in order to maintain high fidelity gates and long coherence times. |
Wednesday, March 8, 2023 9:48AM - 10:00AM |
M74.00008: Universal qubit control through FPGA-accelerated qubit classification, Hamiltonian estimation and real-time feedback [Part 2] Fabrizio Berritta, Torbjørn R Rasmussen, Joost van der Heijden, Federico Fedele, Jan A Krzywda, Saeed Fallahi, Geoff C Gardner, Michael J Manfra, Evert Van Nieuwenburg, Jeroen Danon, Anasua Chatterjee, Ferdinand Kuemmeth Gate-controlled spin qubits are a promising platform for implementing quantum processors [1,2] and now operate near the error-correctable threshold [3]. To correct errors, however, fast real-time feedback based on qubit measurements must be executed within the qubit coherence time. Moreover, continuous real-time feedback is also useful to tune and calibrate the qubit environment in order to maintain high fidelity gates and long coherence times. |
Wednesday, March 8, 2023 10:00AM - 10:12AM |
M74.00009: Real-time quantum dot stability diagram measurement using on-the-fly generated waveforms Marc-Antoine Roux, Larissa Njejimana, Francesco Tafuri, Brendan Bono, Philip Krantz, Marc-André Tétrault, Michel Pioro-Ladrière Stability diagrams are essential to understand the energy landscape of quantum dots and tune them into the spin-qubit regime, but the voltage space to cover increases significantly with the number of quantum dots. Many advanced techniques have been proposed in the last few years to minimize the number of measurements needed to extract valuable information, where the speed bottleneck often comes from the means available to implement the algorithm itself, the measurement platform. To break this threshold, we explored Keysight’s Quantum Engineering Toolkit (QET) to program typical experimental routines and take advantage of the on-board field-programmable gate arrays (FPGAs). A novel dedicated module allows the user to define waveforms generated dynamically directly at the FPGA level, removing previously lengthy data transactions between sequences within an experiment. With this approach, we can perform multiple stability diagram measurements in under a second and virtual gate calculations in under 100 ns. The flexibility of the FPGA programming also allows the routines to be adapted to more complex measurements that may include accelerated machine learning, statistical models and local feedback loops. These tools are a step towards the scalable control of spin qubits using cryogenic electronics. |
Wednesday, March 8, 2023 10:12AM - 10:24AM Author not Attending |
M74.00010: Adaptive filtering and classification for automated tuning of quantum dots into the single electron regime Mathieu Moras, Marc-Antoine Roux, Larissa Njejimana, Stefanie Czischek, Victor Yon, Marc-André Tétrault, Michel Pioro-Ladrière One of the key challenges towards the scalability of spin qubits lies in the control and calibration of quantum dots. The gate voltages required to reach a desired charge state are different for each qubit thus requiring a lengthy and complex characterization process. This work presents an algorithm for automated tuning of single quantum dots into the single electron regime that is independent of the measurement system used. Although it is reliant on a small transition line width, the fast computation time and low amount of data required to reach the desired regime makes it an efficient tuning tool for quantum dots. The algorithm navigates the gate voltage space by performing sparse measurements of stability diagrams. Each measurement is filtered using an adaptive thresholding technique based on an exponentially weighted moving average. The filtered data is then classified using an established neural network approach that we upgraded with a line orientation detection module to help with the decision making. Combining this method with Keysight's fast measurement platform, reaching the single electron regime can be done in a matter of seconds while measuring only a small fraction of the data usually necessary when using full stability diagram measurements. |
Wednesday, March 8, 2023 10:24AM - 10:36AM |
M74.00011: Bayesian methods for optimising qubit quality factors Sebastian Orbell The development of error resistant and scalable quantum computers relies on having robust control over qubits with optimal metrics. In many qubit implementations, including semiconductor systems, these qubit metrics can be tuned by altering system control parameters. Here, we present an algorithm which enables the automatic optimisation of qubit quality factors. The algorithm performs appropriate measurements, and automatically analyses the results. It then intelligently selects the next set of device parameters to query in order to efficiently converge upon the optimum. We experimentally demonstrate the versatility of our method by optimising the properties of two different qubit parameterisations in two distinct semiconductor devices. We use Bayesian optimisation, Bayesian inference and optimal experimental design, motivated by information theory, to efficiently characterise and optimise qubit performance. This contribution represents a step towards the complete automation of the realisation and control of large scale quantum information devices. |
Wednesday, March 8, 2023 10:36AM - 10:48AM |
M74.00012: Rapid characterisation of over 1000 silicon quantum dots Mark A Johnson, Domenic Prete, Edward J Thomas, Mathieu de Kruijf, David Ibberson, Jonathan Warren, James Kirkman, Grayson M Noah, Alberto Gomez Saiz, John Morton, Fernando Gonzalez-Zalba
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