The Israel Innovation Authority and the Israel Ministry of Defense (IMOD) recently announced a $62 million USD collaborative effort to establish a domestic quantum computing (QC) infrastructure. The two-pronged approach calls for the Israel Innovation Authority, part of Israel’s Ministry of Economy charged with fostering domestic industrial R&D, to focus on developing QC algorithms, applications, and a related software stack to support both on-premises or cloud QC access models. For its part, the IMOD will stand up a national center to develop a complete quantum computer including a quantum processor expected to consist of 30-40 qubits, quantum control capabilities, and I/O interfacing hardware.
U.S. Senate Passes Innovation Act to Support U.S. Semiconductor Manufacturing Sector
Alex Norton and Bob Sorensen
The U.S. Senate passed the United States Innovation and Competition Act (USICA) on June 8th, a major step forward in providing support and financial investment in furthering the United States' competitive capabilities in technology, including semiconductor capabilities. The USICA is bipartisan legislation intended to give federal funding to key science and technology areas, including STEM research, technology transfer, semiconductor research and manufacturing, as well as NASA research activities. The bill also seeks to establish a framework for agencies including the NSF and DOE to collaborate in these areas, to help ensure U.S. leadership in science and technology.
6 2021 | HYP_Link
New Error Correction Scheme Seeks to Advance Quantum Computing Capabilities
Bob Sorensen, Tom Sorensen
Researchers at the US-based Lawrence Berkeley National Lab (LBNL) recently reported a new approach to error mitigation in a quantum computer (QC) that targets error-producing noise, a ubiquitous problem that can severely limit the performance and utility of existing and near-future quantum computers. The method developed at LBNL consists of taking an initial noisy target circuit and constructing an analogous estimation circuit that is configured specifically for accurate noise characterization. The information gathered from running the estimation circuit is then applied to correct the noise in the original target circuit.