SQuInT 2022 Program
Full Program | Thursday | Friday | Saturday | All Sessions | Posters | Talks
SESSION 13: New devices and characterization (Islands Ballroom)Chair: (Mohan Sarovar (Sandia National Lab)) | |
| 3:45 pm - 4:15 pm | Vasileios Niaouris, University of Washington Shallow donor spin-qubits in ZnO - Using ion implantation and focused-ion beam milling for donor formation and photonics integration | Abstract. Neutral shallow donors (D0) in ZnO such as In, Ga, and Al substituting for Zn are promising solid-state spin qubits for quantum technologies. The D0 are optically coupled to donor bound excitons. Studying donor ensembles, we have demonstrated narrow inhomogeneous linewidths (~10GHz), long spin relaxation time (T1, up to 0.48 sec at 1.75 T) [1], spin initialization via optical pumping [2], and all-optical coherent control [3]. In this contribution, we will be discussing the ability to control the number of donors accessed optically via implantation and the potential to use focused ion beam milling (fibbing) to fabricate on ZnO. Through implantation and annealing, we can form In donors within a thin layer of ZnO, with favorable optical and coherent properties. Via fibbing, a slice of different thicknesses, ranging between 0.1 and 3 um, was cut out of the ZnO crystal. Due to the reduced thickness, we can probe smaller ensembles that retain good optical properties (after annealing) and identify candidates for stable single emitters. Combining donor implantation and fibbing, we aim to fabricate photonic structures around implanted donors, a significant step towards scaling this emerging technology. [1] V. Niaouris, et al., Phys. Rev B 105, 195202 (2022) [2] X. Linpeng et al., Phys. Rev. Appl. 10, 064061 (2018) [3] M. L. K. Viitaniemi, et al., Nano Lett. 22, 5 (2022) *Supported by the U.S. DOE (DE-SC0020378), the NSF (1820614), and the Army Research Office MURI Grant (18057522). |
| 4:15 pm - 4:45 pm | Jordan Hines, University of California Berkeley Scaling randomized benchmarking into the quantum advantage regime | Abstract. Randomized benchmarks are widely used for quantifying the performance of quantum processors. However, most existing protocols are limited in scalability, often due to requiring classical computations that scale exponentially in the number of qubits. Here, we introduce two highly scalable randomized benchmarking methods with low classical computation cost. Our methods modify standard randomized benchmarking and cross entropy benchmarking, connecting those methods and preserving their core strengths. Our first method uses randomized mirror circuits to enable benchmarking a large class of universal gate sets. Our second method benchmarks Clifford gates by applying a streamlined fidelity estimation method to random circuits. We use theory, simulations, and experiments to show that our methods reliably estimate the average error rate of random circuit layers. We demonstrate randomized benchmarking of universal gate sets on four qubits of the Advanced Quantum Testbed, including a gate set containing a controlled S gate and its inverse, and we investigate the impact of non-Clifford gates on the observed error rate. Finally, we demonstrate that our methods scale to many qubits with experiments on a 27-qubit IBM Q processor, and quantify the contribution of crosstalk to the error rate. This work was supported in part by the LDRD program at SNL and by the US DOE SC/ASCR’s Quantum Testbeds for Science Program. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. |
| 4:45 pm - 5:15 pm | Stefan Seritan, Sandia National Laboratories How to benchmark quantum computers using any quantum algorithm | Abstract. Quantum computers promise better solutions to real-world problems, such as those arising in quantum chemistry, but only if they can successfully run large, complex programs implementing specific quantum algorithms. There is thus an urgent need for benchmarks that measure how well quantum computers can execute such programs. However, this appears impossible because quantum programs solving difficult problems are (1) too big to fit on current-generation quantum testbeds, and (2) seemingly impossible to verify on classical computers. We overcome both problems by applying circuit mirroring and subcircuit snipping to generate the first scalable, efficiently verifiable application-inspired volumetric benchmarks. We demonstrate our technique on a key subroutine for quantum chemistry algorithms: the application of a block-encoded second quantized Hamiltonian. While this is more resource intensive than near-term approaches to the same task, it is more representative of what will be executed on future fault-tolerant systems. Experiments were performed for small instances, i.e., minimal basis H2, HeH+, and LiH, using two different fermion-to-qubit mappings. We compare the performance of several IBM Q devices on our application-inspired benchmarks to their performance on prior mirror circuit benchmarks. We also validate our results against simulations using error models containing coherent and stochastic noise. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. |
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SQuInT Chief Organizer
Akimasa Miyake, Associate Professor
amiyake@unm.edu
SQuInT Co-Organizer
Hartmut Haeffner, Associate Professor, UC Berkeley
hhaeffner@berkeley.edu
SQuInT Administrator
Dwight Zier
d29zier@unm.edu
505 277-1850
SQuInT Program Committee
Alberto Alonso, Postdoc, UC Berkeley
Philip Blocher, Postdoc, UNM
Neha Yadav, Postdoc, UC Berkeley
Cunlu Zhou, Postdoc, UNM
SQuInT Founder
Ivan Deutsch, Regents' Professor, CQuIC Director
ideutsch@unm.edu
