A5023515127- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Quantum and electron transport phenomena
- Error Correcting Code Techniques
- Parallel Computing and Optimization Techniques
- Quantum many-body systems
- Advanced Wireless Communication Techniques
- Quantum Mechanics and Applications
- Neural Networks and Applications
- Markov Chains and Monte Carlo Methods
- COVID-19 epidemiological studies
- Mathematical Approximation and Integration
- Explainable Artificial Intelligence (XAI)
- graph theory and CDMA systems
- Graph Theory and Algorithms
- Anomaly Detection Techniques and Applications
- Low-power high-performance VLSI design
- Machine Learning and Algorithms
- Misinformation and Its Impacts
- Complexity and Algorithms in Graphs
- Molecular Communication and Nanonetworks
- Advancements in Semiconductor Devices and Circuit Design
University of Chicago
2024
NASA Research Park
2024
Ames Research Center
2022-2024
Research Institute for Advanced Computer Science
2022-2024
University of California, Berkeley
2021-2022
Los Alamos National Laboratory
2021
We develop a hardware-efficient ansatz for variational optimization, derived from existing ansatzes in the literature, that parametrizes subsets of all interactions cost Hamiltonian each layer. treat gate orderings as parameter and observe doing so can provide significant performance boosts experiments. carried out experimental demonstration runs compilation-optimized implementation fully connected Sherrington-Kirkpatrick Hamiltonians on 50-qubit linear-chain subsystem Rigetti's Aspen-M-3...
Quantum computers provide new avenues to access ground and excited state properties of systems otherwise difficult simulate on classical hardware. New approaches using subspaces generated by real-time evolution have shown efficiency in extracting eigenstate information, but the full capabilities such are still not understood. In recent work, we developed variational quantum phase estimation (VQPE) method, a compact efficient algorithm extract eigenvalues Here build that work theoretically...
The quantum alternating operator ansatz (QAOA) is a generalized approach for solving challenging optimization problems that builds on the structure of approximate algorithm. Finding high-quality parameters efficiently QAOA remains major challenge in practice. In this work, we introduce classical strategy parameter setting, suitable cases which number distinct cost values grows only polynomially with problem size, such as common constraint-satisfaction problems. crux our replace function...
In order to assess whether quantum resources can provide an advantage over classical computation, it is necessary characterize and benchmark the nonclassical properties of algorithms in a practical manner. this paper, we show that using measurements no more than three out possible ${3}^{N}$ bases, one not only reconstruct single-qubit reduced density matrices measure ability create coherent superpositions, but also possibly verify entanglement across all $N$ qubits participating algorithm....
B. Nachman et al. [Phys. Rev. Lett. 126, 062001 (2021)] recently introduced an algorithm (QPS) for simulating parton showers with intermediate flavor states using polynomial resources on a digital quantum computer. We make use of new hardware capability called dynamical computing to improve the scaling this algorithm, which significantly improves method precision. In particular, we modify shower circuit incorporate midcircuit qubit measurements, resets, and operations conditioned classical...
The Variational Quantum Eigensolver (VQE) is a method of choice to solve the electronic structure problem for molecules on near-term gate-based quantum computers. However, circuit depth expected grow significantly with size. Increased can both degrade accuracy results and reduce trainability. In this work, we propose novel approach ansatz depth. Our approach, called PermVQE, adds an additional optimization loop VQE that permutes qubits in order qubit Hamiltonian minimizes long-range...
Forward Error Correction (FEC) provides reliable data flow in wireless networks despite the presence of noise and interference. However, its processing demands significant fraction a network's resources, due to computationally-expensive decoding process. This forces network designers compromise between performance implementation complexity. In this paper, we investigate novel architecture for FEC decoding, one based on quantum approximate optimization algorithm (QAOA), evaluate potential...
Unitary <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><a:mi>t</a:mi></a:math>-designs are distributions on the unitary group whose first <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" overflow="scroll"><d:mi>t</d:mi></d:math> moments appear maximally random. Previous work has established several upper bounds depths at which certain specific random quantum circuit ensembles approximate <g:math xmlns:g="http://www.w3.org/1998/Math/MathML"...
We design two variational algorithms to optimize specific 2-local Hamiltonians defined on graphs. Our are inspired by the Quantum Approximate Optimization Algorithm. develop formulae analyze energy achieved these with high probability over random regular graphs in infinite-size limit, using techniques from [arXiv:2110.14206]. The complexity of evaluating scales exponentially number layers algorithms, so our numerical evaluation is limited a small constant layers. compare simple classical...
We develop a hardware-efficient ansatz for variational optimization, derived from existing ansatze in the literature, that parametrizes subsets of all interactions Cost Hamiltonian each layer. treat gate orderings as parameter and observe doing so can provide significant performance boosts experiments. carried out experimental runs compilation-optimized implementation fully-connected Sherrington-Kirkpatrick Hamiltonians on 50-qubit linear-chain subsystem Rigetti Aspen-M-3 transmon processor....
Parameterized quantum circuits are widely studied approaches for tackling optimization problems. A prominent example is the Quantum Alternating Operator Ansatz (QAOA), an approach that builds off structure of Approximate Optimization Algorithm. Finding high-quality parameters efficiently QAOA remains a major challenge in practice. In this work, we introduce classical strategy parameter setting, suitable common cases which number distinct cost values grows only polynomially with problem size....
In order to understand the capabilities and limitations of quantum computers, it is necessary develop methods that efficiently characterize benchmark error channels present on these devices. this paper, we a method faithfully reconstructs marginal (local) approximation effective noise (MATEN) channel, acts as single layer at end circuit. We first introduce dual map framework allows us analytically derive expectation values observables with respect noisy circuits. These findings are supported...
Unitary t-designs are distributions on the unitary group whose first t moments appear maximally random. Previous work has established several upper bounds depths at which certain specific random quantum circuit ensembles approximate t-designs. Here we show that these can be extended to any fixed architecture of Haar-random two-site gates. This is accomplished by relating spectral gaps such architectures those 1D brickwork architectures. Our bound depends details only via typical number...
B. Nachman et al. [Phys. Rev. Lett. 126, 062001 (2021)] recently introduced an algorithm (QPS) for simulating parton showers with intermediate flavor states using polynomial resources on a digital quantum computer. We make use of new hardware capability called dynamical computing to improve the scaling this algorithm, which significantly improves method precision. In particular, we modify shower circuit incorporate midcircuit qubit measurements, resets, and operations conditioned classical...
Quantum computers provide new avenues to access ground and excited state properties of systems otherwise difficult simulate on classical hardware. New approaches using subspaces generated by real-time evolution have shown efficiency in extracting eigenstate information, but the full capabilities such are still not understood. In recent work, we developed variational quantum phase estimation (VQPE) method, a compact efficient algorithm extract eigenvalues Here build that work theoretically...
Disruptions of university campuses caused by COVID-19 have motivated strategies to prevent the spread infectious diseases while maintaining some level in person learning. In response, proposed approach recursively applied a quantum annealing algorithm for Max-Cut optimization on D-Wave Systems, which grouped students into cohorts such that number possible infection events via shared classrooms was minimized. To test this approach, available coursework data used generate highly clustered...