Cookie Consent by Free Privacy Policy Generator
Search
Close this search box.
Search
Close this search box.

The Importance of Uncomputation: Is Quantum Mechanics Reversible?

Photo by Faye Cornish on Unsplash
Photo by Faye Cornish on Unsplash
Photo by Faye Cornish on Unsplash

Constrained by Nature

Quantum Mechanics is reversible and this is what we observe when we study the evolution of quantum states and see that information is not lost and that there are no 2 input states that will evolve to the same output state given a particular Hamiltonian.

This makes Quantum Computing really special both positively and negatively. It basically makes it difficult and expensive to even built simple concepts like basic arithmetic. Adding two numbers is not a reversible operation unless we keep track of at least one of the original inputs.

Pitfalls of Reversibility

Ignoring this fact can create big problems to your circuits. As we use “work” qubits (auxiliary qubits) to ensure reversibility we increase the chances of breaking things as these qubits become entangled with our computations the risks associated with entangled qubits collapsing and destroying everything increases.

Fortunately we can always uncompute. We can always reverse the operations that entangled the work qubits so that we can reuse them later on. But this is also an expensive thing to do specially with NISQ devices.

Reversibility & Reverse Engineering

On the other hand, this reversibility is also good news! You can always reverse-engineer a pure quantum algorithm! Sort of. With enough time and patience we can always try to uncompute a circuit. We can’t really access the state information when using a real device but with enough measurements we can approximate any circuit without really knowing any of its internals. Quantum Process Tomography is one of the techniques that can be employed to gain such inisghts.

Inspired by this constrain and taking advantage of simulators, I’ve employed a similar trick in order to solve the last exercise of IBM’s Quantum Challenge 2020.

The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Jake Vikoren

Jake Vikoren

Company Speaker

Deep Prasad

Deep Prasad

Company Speaker

Araceli Venegas

Araceli Venegas

Company Speaker

Daniel Colomer

Learning and Research in public.

Share this article:

Keep track of everything going on in the Quantum Technology Market.

In one place.

Related Articles

Index
Explore our intelligence solutions

Join Our Newsletter