Bulletin of the American Physical Society
Four Corners Section 2022 Meeting
Volume 67, Number 14
Friday–Saturday, October 14–15, 2022; Albuquerque, New Mexico
Session E02: Quantum Information I |
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Chair: Ivan Deutsch, University of New Mexico Room: UNM PAIS 1010 |
Friday, October 14, 2022 2:30PM - 2:54PM |
E02.00001: Demonstrating two-qubit entangling gates at the quantum speed limit using superconducting qubits Invited Speaker: Meenakshi Singh The speed at which quantum entanglement between qubits with short range interactions can be generated is limited by the Lieb-Robinson bound. Introducing longer range interactions relaxes this bound and entanglement can be generated at a faster rate. The speed limit for this has been explicitly found theoretically only for a two-qubit system and under the assumption of negligible single qubit gate time. We have theoretically determined this speed limit for a realistic experimental system. Furthermore, we go on to demonstrate this speed limit experimentally using two superconducting transmon qubits. This development has important implications for large scale quantum computing. |
Friday, October 14, 2022 2:54PM - 3:06PM |
E02.00002: Flag Gadgets based on Classical Codes Benjamin Anker, Milad Marvian Fault-tolerant quantum error correction is essential for full-scale quantum computing due to high noise levels; however, fault-tolerance in general requires many expensive resources, particularly qubits. Recently it has been shown that by using flag gadgets it is possible to perform fault-tolerant syndrome extraction, a key subroutine of quantum error correction, using fewer resources than conventional methods. Although flag gadgets have already been used in several experiments, a framework that applies to general quantum codes and does not require fast physical operations to achieve a resource reduction has been missing. |
Friday, October 14, 2022 3:06PM - 3:18PM |
E02.00003: Demonstration of Mølmer–Sørensen Gates Robust to 10 kHz Trap Frequency Error Matthew N Chow, Brandon P Ruzic, Ashlyn D Burch, Daniel S Lobser, Melissa C Revelle, Christopher G Yale, Joshua M Wilson, Susan M Clark Trapped ions are leading candidates for useful quantum computation in the near term. While reliable single-qubit operations are routine on trapped ion platforms, two-qubit operations are more difficult. Two-qubit entangling gates are strongly susceptible to technical noise, and achieving those that are robust to such noise is an outstanding challenge. Drift in trap frequencies is a prevalent error mechanism and leads to infidelity in entangling gates, such as the Mølmer–Sørensen gate, that are operated through motional modes. We propose and experimentally demonstrate that by using a Gaussian pulse shape to exponentially suppress displacement error and balancing the contribution of multiple motional modes to suppress gate angle error, we can implement a Mølmer–Sørensen gate that is robust to order 10 kHz drift in trap frequency. Further, our gate is technically simple to implement and requires no lengthy optimization, enabling straightforward integration on contemporary systems. |
Friday, October 14, 2022 3:18PM - 3:30PM |
E02.00004: Hamiltonian Quantum Generative Adversarial Networks Leeseok Kim, Seth Lloyd, Milad Marvian We introduce a framework to learn quantum states using two competing quantum optimal control protocols. Inspired by the success of classical Generative Adversarial Networks (GANs) to learn high-dimensional distributions, in our proposed Hamiltonian Quantum GAN (HQuGAN), the task of learning quantum states is achieved by playing an iterative game between two competing quantum agents, a generator and a discriminator. The optimal control approach not only makes the algorithm naturally adaptable to the experimental constraints of near-term hardwares but also has the potential to provide a better convergence due to overparameterization compared to the circuit model implementations. We numerically demonstrate the capabilities of the proposed framework to learn various highly entangled many-body quantum states, using two-body Hamiltonians and under experimentally relevant constraints such as low-bandwidth control. We analyze the computational cost of implementing HQuGAN on quantum computers, and show how the framework can be extended to learn quantum dynamics. |
Friday, October 14, 2022 3:30PM - 3:42PM |
E02.00005: An Entropic Lens on Stabilizer States William R Munizzi, Cynthia Keeler, Jason Pollack The holographic entropy cone provides a geometric description of multipartite entanglement by ascribing to each quantum state an entropy vector, the ordered set of von Neumann entropies of the 2n-1 reduced density matrices formed by tracing out each tensor product built from the factorized Hilbert space. Necessary satisfaction of associated entropy inequalities constrains the entropy vectors representing holographically-realizable states to the interior of a convex, polyhedral cone, a strict subspace of the ambient 2n-1 dimensional entropy vector space. In this way, entropy vectors offer a classification of states in a tensor product Hilbert space, however this alone does not select any one class as special. One way to distinguish unique states is by fixing a preferred multiplicative group of Hermitian operators to act on the Hilbert space. Stabilizer states can be defined as those quantum states reachable from vacuum through only combinations of Hadamard, Phase, and CNOT operations. This class of quantum states constitutes a strict superset of the holographic states and similarly admits a classical dual and entropic characterization through the stabilizer entropy cone. Analysis of the entropy cone model has given insight into the structure of nested entropy vector subspaces, however much is unknown about transitions from one class of states to another. We initiate a research program to combine these two classifications of states, within a graph-theoretic framework, by constructing a set of stabilizer graphs colored by entropy vector. We present new insight gained by considering restricted graphs generated by a subset of Clifford gates, specifically Hadamard and CNOT gates. At higher qubit number, we find entropy vectors which do not represent holographic states and describe their role in these stabilizer graphs. We demonstrate how higher-qubit structures can be understood as lifts of lower-qubit structures, and note the termination of new subgraphs at four qubits. |
Friday, October 14, 2022 3:42PM - 3:54PM |
E02.00006: Fault-tolerant quantum computation in spin systems using cat codes Sivaprasad T Omanakuttan, Milad Marvian, Jonathan Gross, Ivan H Deutsch In this work, we construct a class of quantum error-correcting codes for spin systems using the cat codes which is similar in spirit to the cat codes for the bosonic mode. We studied how concatenation of codes gives us the possibility of fault-tolerant quantum computation, for doing fault-tolerant quantum computation we developed a full set of universal gates which respects the error set, one key ingredient was the development of bias preserving CNOT gate which respects the error set. We categorized the errors as phase errors and amplitude errors, the phase errors are very similar to phase flip errors for qubits and can be corrected in a similar way. To correct amplitude errors, we could use the higher dimensional nature of our qubit and use a SWAP gate approach followed by destructive measurement of the data qubits. We also studied the threshold needed to correct for errors including the measurement errors and found that we could get a reasonable threshold including errors for the CNOT gate and errors in the measurement of X. |
Friday, October 14, 2022 3:54PM - 4:06PM |
E02.00007: Tensor Network Simulations of Variational Bayesian Quantum Metrology with Correlated Noise Tyler Thurtell, Akimasa Miyake Variational Bayesian metrology has emerged as a promising avenue toward quantum advantage in sensing in the presence of complex noise and prior information. For the sake of practical advantage, it would be important to understand how effective parametrized protocols are as well as how robust they are to the effects of complex noise, such as spatially correlated noise. First, we propose a new family of parametrized encoding and decoding protocols, called arbitrary-axis twist ansatzes, and demonstrate that this family of ansatzes can perform better than previous ansatzes despite having fewer entangling one-axis twist operators. Second, we utilize a polynomial-size tensor network algorithm to analyze realistic variational metrology beyond the symmetric subspace of the collective spin degree. |
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