#### Why we need quantum computing

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### Why we need quantum computing

We experience the benefits of classical computing every day. Today’s computers help and entertain us, connect us with people all over the world, and allow us to process huge amounts of data to solve problems and manage complex systems.

However, there are problems that today’s systems will never be able to solve. For challenges above a certain size and complexity, we don’t have enough computational power on Earth to tackle them. To stand a chance at solving some of these complex problems, we need a new kind of computing: one whose computational power also scales exponentially as the system size grows.

Here, watch Dr. Jerry Chow, manager of experimental quantum computing for IBM Research, explain how quantum computing can be applied to molecular simulation, which could lead to the discovery of new materials and medicines.

#### What makes it ‘quantum’?

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### What makes it ‘quantum’?

All computing systems rely on a fundamental ability to store and manipulate information. Current computers manipulate individual bits, which store information as binary 0 and 1 states. Millions of bits work together to process and display information. Quantum computers leverage different physical phenomena — superposition, entanglement, and interference — to manipulate information. To do this, we rely on different physical devices: quantum bits, or **qubits**.

**Superposition** refers to a combination of states we would ordinarily describe independently. To make a classical analogy, if you play two musical notes at once, what you will hear is a superposition of the two notes.

**Entanglement** is a famously counter-intuitive quantum phenomenon describing behavior we never see in the classical world. Entangled particles behave together as a system in ways that cannot be explained using classical logic.

Finally, quantum states have a phase, and so can undergo interference. Quantum interference can be understood similarly to wave interference; when two waves are in phase, their amplitudes add, and when they are out of phase, their amplitudes cancel.

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#### Quantum computation

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### Quantum computation

How do quantum systems use quantum properties to compute? This question can be split into two parts:

- How are algorithms developed for the quantum computers available today?
- How do people create algorithms for future “fault tolerant” quantum systems that are still theoretical?

Many algorithms for near-term quantum hardware require you to find the “best” solution from among many possible solutions, such as finding the lowest energy state of a molecule among various possible molecular bond lengths. For each possible bond length, you represent parts of the energy on a quantum processor, and then measure the energy directly. Trying various solutions eventually leads to the bond length with to the lowest energy state, which represents the equilibrium molecular configuration. More information can be found here.

Algorithms for the kinds of quantum systems we hope to have in the future, called fault tolerant universal quantum computers, were among the first to be developed in the field. This includes some of the most well known examples: Shor’s factorization algorithm and Grover’s algorithm for unstructured search. While near-term algorithms involve relatively few qubits and operations, and errors can be compensated by running the algorithm many times to get an average value, fault-tolerant algorithms require extremely long gate sequences and high gate fidelities to perform well. The quantum hardware needed for fault-tolerant algorithms is still being developed; however, they demonstrate that certain quantum algorithms can outperform their classical counterparts, given the right quantum system.

How to measure a molecule’s energy using a quantum computer

The Variational Quantum Eigensolver: An unsung hero of approximate quantum computing

Future Focus: Quantum Computing in Next Generation AI Research 25:05

#### Scaling quantum systems

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### Scaling quantum systems

In order to increase the computational power of quantum computing systems, improvements are needed along two dimensions. One is **qubit count**; the more qubits you have, the more states can in principle be manipulated and stored. The second is to achieve lower **error rates**. We need to be able to manipulate the qubit states accurately and perform sequential operations that provide answers, not noise.

Combining these two concepts, we can create a single measure of a quantum computer’s power called quantum volume. **Quantum volume** measures the relationship between number and quality of qubits, circuit connectivity, and error rates of operations. Building larger systems with lower error rates will lead to discovering the first instances of **quantum advantage**, or applications where quantum computers can offer a computational advantage for solving real problems.