A5074810782- Quantum Computing Algorithms and Architecture
- Parallel Computing and Optimization Techniques
- Graph Theory and Algorithms
- Advanced Graph Neural Networks
- Quantum Information and Cryptography
- Stochastic Gradient Optimization Techniques
- Advancements in Semiconductor Devices and Circuit Design
- Distributed and Parallel Computing Systems
- Industrial Vision Systems and Defect Detection
- Infrared Target Detection Methodologies
- Cloud Computing and Resource Management
- Quantum Mechanics and Applications
- Advanced Algorithms and Applications
IBM (United States)
2023-2025
Quantum (Australia)
2022
We describe Qiskit, a software development kit for quantum information science. discuss the key design decisions that have shaped its development, and examine architecture core components. demonstrate an end-to-end workflow solving problem in condensed matter physics on computer serves to highlight some of Qiskit's capabilities, example representation optimization circuits at various abstraction levels, scalability retargetability new gates, use quantum-classical computations via dynamic...
We present a quantum circuit optimization technique that takes into account the variability in error rates is inherent across present-day noisy computing platforms. This method can be run after qubit routing or postcompilation and consists of isomorphic subgraphs to input circuits scoring each using heuristic cost functions derived from system calibration data. Using an independent standard algorithmic test suite, we show it possible recover on average nearly 40% missing fidelity better...
We present Benchpress, a benchmarking suite for evaluating the performance and range of functionality multiple quantum computing software development kits. This consists collection over 1,000 tests measuring key metrics wide variety operations on circuits composed up to 930 qubits O(106) two-qubit gates, as well an execution framework running packages in unified manner. Here we give detailed overview benchmark its methodology generate representative results seven different packages. The...
In rustworkx, we provide a high-performance, flexible graph library for Python.rustworkx is inspired by NetworkX but addresses many performance concerns of the latter.rustworkx written in Rust and particularly suited performance-sensitive applications that use representations.
We introduce LightSABRE, a significant enhancement of the SABRE algorithm that advances both runtime efficiency and circuit quality. LightSABRE addresses increasing demands modern quantum hardware, which can now accommodate complex scenarios, circuits with millions gates. Through iterative development within Qiskit, primarily using Rust programming language, we have achieved version in Qiskit 1.2.0 is approximately 200 times faster than implementation 0.20.1, already introduced key...
We present Benchpress, a benchmarking suite for evaluating the performance and range of functionality multiple quantum computing software development kits. This consists collection over $1000$ tests measuring key metrics wide variety operations on circuits comprised up to $930$ qubits $\mathcal{O}(10^{6})$ two-qubit gates, as well an execution framework running packages in unified manner. give detailed overview benchmark suite, its methodology, generate representative results seven different...
We present a quantum circuit optimization technique that takes into account the variability in error rates is inherent across day noisy computing platforms. This method can be run post qubit routing or post-compilation, and consists of isomorphic subgraphs to input circuits scoring each using heuristic cost functions derived from system calibration data. Using an independent standard algorithmic test suite we show it possible recover on average nearly 40% missing fidelity better selection...
In rustworkx, we provide a high-performance, flexible graph library for Python. rustworkx is inspired by NetworkX but addresses many performance concerns of the latter. written in Rust and particularly suited performance-sensitive applications that use representations.