March Meeting is a signature event from the American Physical Society (APS) that draws a large international crowd of scholars each year. As the largest physics meeting in the world, this event contains the greatest assembly of cutting-edge innovations in physics research. At the virtual event March 14-18, Intel researchers and collaborators will present contributions across 14 papers.
At March Meeting, Intel will showcase research in many different areas. Otto Zietz, a quantum hardware engineer at Intel, will be giving an invited presentation on the development of a first-of-a-kind cryogenic wafer prober. It is capable of device characterization at 1K to enable rapid and statistically significant data collection of both traditional transistor and quantum dot metrics. Other papers cover their progress on optimizing control pulses to improve the quality of their two-qubit gates, their research on the potential for scalability of spin qubits, and more.
The Intel® Quantum SDK; a recently launched full-stack Software Development Kit optimized for executing hybrid algorithms will be presented as well. It includes an intuitive user interface based on C++, a compiler toolchain based on the industry standard LLVM, and a runtime environment adapted for quantum with a high-performance Intel® Quantum Simulator qubit target backend.
Intel and Research Collaborators’ Papers at APS March Meeting 2022
B39: Semiconductor Qubits I
D40: Noisy Intermediate Scale Quantum Computers III
- Observation of dynamical phase transitions in a superconducting quantum processor implementing five stabilizer terms
F39: Semiconductor Qubits III
G38: Quantum Annealing and Optimization II
M28: Quantum in Industry Invited Session: Quantum Information Hardware
N36: Quantum Software and Compilers: Optimization and Program Synthesis
S36: Spin Qubit Measurement I
T37: Quantum Machine Learning II
- Realization of a quantum neural network by repeat-until-success circuits in a superconducting quantum processor
T40: Quantum Error Correction Theory
- Measurement-free Quantum Error Correction with a Digital Entropy Pump: Part 1
- Measurement-free Quantum Error Correction with a Digital Entropy Pump: Part 2
T47: Machine Learning for Quantum Matter III
W40: Noise Reduction and Error Mitigation in Quantum Computing II
Y36: Novel Spin Qubit Materials and Technologies II
Y39: Quantum Dots and Vacancy Centers