/Quantum Computing Memory And Storage (via Qpute.com)
Quantum Computing Memory And Storage

Quantum Computing Memory And Storage (via Qpute.com)

At the 2021 SNIA Storage Developers Conference (SDC) Doug Finke, Managing Editor of the Quantum Computing Report talked about how storage and memory will play roles in Quantum Computing (QC) and how quantum computing can play a role in discovery and optimization in the storage industry.  The figures below are from his presentation, with my commentary.

There has been much discussion about the future of quantum computing.  Briefly, quantum computing uses physical quantum mechanical processes such as superposition and entanglement to create a processing device.  The Qubits in quantum computing can hold an exponential number of states using superposition and entanglement which can be an equivalent number of bits.

N-qubits is comparable to 2n bits.  To get an idea what this means, Finke said that 100 qubits can hold more states than all the hard disk drives in the world.  300 qubits can hold more states than the number of atoms in the universe.  However, qubits will collapse (or decohere) to a single 0 or 1 state due to small environmental disturbances.

The problem with QC is that the Hoelvo’s bound means that the amount of data that can be retrieved form n qubits cannot be any larger than the amount of data that could be retrieved from n bits.  That means that most of the data in a collection of qubits cannot be retrieved.  This is referred to as the no cloning theorem, the data in qubits collapses upon measurement.  Also, quantum gates, the equivalent of traditional binary gates in conventional computing, are very slow, error prone and quickly lose data.

As a consequence of these limitations QC is not going to be useful for all computing problems.   In general quantum computing is useful in solving problems where a quantum algorithm scales in the time taken to solve a problem slower than the corresponding classical algorithm as illustrated in the figure below.  In particular, QC is good for problems with very complex relations between the data elements.

This makes it useful for traveling salesman and logistical problems as well as chemical and physical simulations and binary optimization.  QC can also be used in artificial intelligence (AI) and machine learning (ML) problems where large amounts of data are processed where the data is stored.  Finke said that this is the equivalent of a computational storage technique.

Quantum communication uses quantum mechanical entanglement of photons in an optical communication channel.  The figure below shows how a “quantum memory” can be used to create a repeater to extend the distance the data is transported using “entanglement swapping”.

Qunnect is shipping a quantum memory for such applications as shown in the next slide.

Besides this “quantum memory” the biggest impact on the memory and storage industry (as with other industries) may be in using the technology to solve specific types of problems such as materials discovery for developing new hard disk drive head or semiconductor materials, logistics optimization for manufacturing and the supply chain and to use for customer forecasting and detecting customer patterns for product targeting.

Quantum computing and communication may use special “quantum memory” for certain applications.  The biggest impact on the conventional storage and memory industry may be on new device development and manufacturing and supply chain optimization as well as AI and ML applications.


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