THE CHALLENGES OF QUANTUM COMPUTING

ChinmayaIAS Academy - Current Affairs December 17, 2022 GS3, Science & technology Leave a comment 243 Views

The allure of quantum computers (QC) is their ability to take advantage of quantum physics to solve problems too complex for conventional computers.
Several institutes and companies worldwide have invested in developing QC systems, from software to solve specific problems to the science that goes into expanding their hardware capabilities.
In 2021, the Indian government launched a mission to study quantum technologies with an allocation of ₹8,000 crore; the army opened a quantum research facility in Madhya Pradesh; and the Department of Science and Technology co-launched another facility in Pune.
Given its wide-ranging applications and the scale of investments, understanding what QCs really are is crucial to sidestep the hype and develop expectations that are closer to reality.

What is quantum physics?

A macroscopic object — like a ball, a chair or a person — can be at only one location at a time, which can be predicted accurately; and the object’s effects on its surroundings can’t be transmitted faster than at the speed of light. This is the classical ‘experience’ of reality.
You can observe a ball flying through the air and plot its path. You can predict exactly where the ball will be at a given time. If the ball strikes the ground, you will see it doing so in the time it takes light to travel through the atmosphere to you.
Quantum physics describes reality at the subatomic scale, where the objects are particles like electrons.
Here, you can’t pinpoint the location of an electron. You can only know that it will be present in some volume of space, with a probability attached to each point in the volume: say, 10% at point A and 5% at point B.
When you probe the volume, you might find the electron at point B. If you repeatedly probe the volume, you will find the electron at point B 5% of the time.
Erwin Schrödinger described one interpretation of the laws of quantum physics in a famous thought-experiment in 1935.
There’s a cat in a closed box with a bowl of poison. You can’t know whether the cat is alive or dead without opening the box.
In this time, the cat is said to exist in a superposition of two states: alive and dead. When you open the box, you force the superposition to collapse to a single state.
The state to which it collapses depends on the probability of each state. The same thing happens with the electrons’ locations. (Note: This is a simplistic example.)
Another relevant phenomenon is entanglement. When two particles are entangled and then separated by an arbitrary distance (even more than 1,000 km), probing one particle, and thus causing its superposition to collapse, will instantaneously cause the superposition of the other particle to collapse as well. Note that ‘instantaneous’ is faster than the speed of light.

How would a computer use superposition?

The bit is the fundamental computational unit of a conventional computer. Its value is 1 if a corresponding transistor is on and 0 if the transistor is off.
The transistor can be in one of two states at a time — on or off — so a bit can have one of two values at a time, 0 or 1.
The qubit is the fundamental unit of a QC. It could be a particle like an electron. Some information is directly encoded on the qubit: if the electron’s spin is pointing up, it means 1; if the spin is pointing down, it means 0.
But instead of being either 1 or 0, the information is encoded in a superposition: say, 45% 0 plus 55% 1. This is entirely unlike the two separate states of 0 and 1 and is a third kind of state.
The qubits are entangled to ensure they work together. If one qubit is probed to reveal its state, the states of all entangled qubits will be revealed as well.
The computer’s final output is the state to which all the qubits have collapsed.
One qubit can encode two states, so a computer with N qubits can encode 2N states.
A computer with N transistors can only encode 2N states. So a qubit-based computer can access more states than a transistor-based computer, and thus access more computational pathways and, solutions to more complex problems.

How come we are not using them?

Researchers have figured out the basics and used QCs to model the binding energy of hydrogen bonds and simulate a wormhole model.
But to solve most practical problems, like finding the shape of an undiscovered drug, autonomously exploring space or factoring large numbers, they face fractious challenges.
A practical QC needs at least 1,000 qubits. The current biggest quantum processor has 433 qubits. There are no theoretical limits on larger processors; the barrier is engineering-related.
Qubits exist in superposition in specific conditions, including very low temperature (~0.01 K), with radiation-shielding and protection against physical shock.
Tap your finger on the table and the superposition of the qubit sitting on it could collapse. Material or electromagnetic defects in the circuitry between qubits could also ‘corrupt’ their states and bias the eventual result.
Researchers are yet to build QCs that completely eliminate these disturbances in systems with a few dozen qubits.
Error-correction is tricky. The no-cloning theorem states that it’s impossible to perfectly clone the states of a qubit.
So engineers can’t create a copy of a qubit’s states in a classical system to sidestep the problem. One way out is to entangle each qubit with a group of physical qubits that correct errors. A physical qubit is a system that mimics a qubit.
But reliable error-correction requires each qubit to be attached to thousands of physical qubits.
Researchers are also yet to build QCs that don’t amplify errors when more qubits are added. This challenge is related to a deeper problem: unless the rate of errors is kept under a threshold, more qubits will only increase the informational noise.
Practical QCs will require at least lakhs of qubits, operating with superconducting circuits that we are yet to build – apart from other components like the firmware, circuit optimisation, compilers and algorithms that make use of quantum-physics possibilities. Quantum supremacy itself — a QC doing something a classical computer can’t — is thus at least decades away.
The billions being invested in this technology today are based on speculative profits, while companies that promise developers access to quantum circuits on the cloud often offer physical qubits with noticeable error rates.