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Amplifying Power and Usability of Quantum Computing

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While today’s supercomputers do not lack processing power, they are not built to simulate the physical complexity of the scientific problem. Therefore simulating certain quantum-level phenomena is difficult with the current tools. The key that unlocks a slew of findings for physics and chemistry researchers may just be quantum computing.

U.S. researcher said that the boundaries of classical computing for investigating increasingly large, including solving complex chemistry problems. Exascale computing, quantum computing, and machine learning are tools to tackle the science problems in chemistry, such as carbon capture, water desalination, and renewable energy technologies.

The anticipated power of quantum machines could open the door to a wide range of research achievements in chemistry and beyond. U.S. lab directs the multi-institutional program Advancing Integrated Development Environments for Quantum Computing through Fundamental Research (AIDE-QC). Regarding quantum computing, working together with the hardware developers and science domains advances the software and algorithms to make it a useful tool for scientific discovery.

Scientists usually focus on the hardware when researching quantum computing. However, the software will make quantum computers more functional and accessible to a broader group of researchers. The goal of AIDE-QC is to deliver a top-down open-source integrated software environment for quantum computers developed by a collaboration of scientists from national labs and academia. The software could democratise the power of this budding technology among researchers.

AIDE-QC is an amalgamation of several research thrusts that come together to improve the usability and functionality of quantum computing. This includes programming languages that provide tools and a layer of abstraction that allow for easier use of quantum computers and compilers to communicate this code to the hardware. Other thrusts are more focused on smoothing out operations namely verification and debugging optimisation, and a software integration thrust that helps tie these various threads together.

AIDE-QC has already enabled quantum computers to do bigger, more efficient calculations with fewer qubits. AIDE-QC’s highest-level goal is to enable any researcher who wants to run a simulation that requires a quantum computer to be able to do that without needing to know the details of quantum computing.

The AIDE-QC team has also notched achievements in the computation of free energies, extending the timescale of dynamic simulations, and scaling quantum synthesis through the development of its  Berkeley Quantum Synthesis Toolkit (BQSKit). The group’s compilers are quite efficient and provide an important capability to the quantum computing environment.

Commercial entities have shown interest in using or collaborating on the development of the software. High-energy physicists, nuclear physicists, and materials scientists are already starting to make good use of the software stack to run calculations that tend to be too cumbersome for conventional hardware.

There are many other applications in chemical and materials sciences waiting for scientific discovery with the help of quantum computers, such as increasing solar energy capture efficiency, developing longer-lasting batteries, and capturing carbon to reduce greenhouse gases. The AIDE-QC project brings the scientific community closer to achieving one of the core promises of quantum computing which is to understand natural phenomena, particularly quantum phenomena, in a way that is both more holistic and granular.

When systems become too large, complex, and dynamic for classical computers to handle, the standard method is to segment or approximate systems to keep them simple enough for the current hardware. A quantum computer gives the potential to study bigger problems that are more realistic to nature.

As reported by OpenGov Asia, the same lab has also built unveiled the first phase of its next-generation supercomputer, called Perlmutter. The new system will greatly increase the high-performance computing (HPC) capability for a broad spectrum of unclassified scientific research within the U.S. Department of Energy (DOE) Office of Science.

Science has developed the ability to collect very large amounts of data and bring them all at one time. This allows the combination between science and the power of supercomputer facilities. The new supercomputer is exactly what scientists need to handle these datasets. As a result, they are expecting to find discoveries in cosmology, microbiology, genetics, climate change, material sciences and almost any other field.


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