When you hear the word hardware, what is the first thing that comes to mind? Maybe a motherboard, a green PCB, a laptop, or a smartphone battery.

Now think about software.

What comes to mind? Perhaps lines of Python code, an app icon, or the logo of a tech company. Software feels different. Less tangible. More abstract. It is difficult to point at software in the same way you can point at a transistor or a battery.

But fundamentally, software is just a set of instructions. Now let us go one level deeper.

What exactly is data? What is information?

Again, these ideas feel abstract. A number in memory. A message. A photograph. A quantum state. A string of bits. Information seems to exist in some invisible mathematical world detached from physical reality.

But here is the subtle and profound realization that changed modern physics and computing:

Every form of information, whether carved into stone, written as ink on paper, stored as tiny magnetic patterns on a hard drive, or transmitted as light through optical fibers, requires matter or energy to exist physically. And this realization leads to one of the deepest ideas in modern science:

This statement, famously emphasized by physicist Rolf Landauer, sounds deceptively simple. But hidden inside it is a bridge connecting information theory, computation, thermodynamics, and quantum mechanics.

You might disagree with Rolf Landauer and argue that information itself is not physical, that only a physical medium is needed to represent it. After all, the number “5” remains the same whether it is written on paper, stored in your phone, or encoded in the atoms of a quantum computer.

But the fact that we all agree to is that:

And because these are physical systems, they must obey the laws of physics. This means the nature of computation, and even its fundamental limits, can ultimately be derived from physical laws themselves. And that immediately raises some fascinating questions:

These are not engineering questions alone. They are questions about nature itself.

In the 1960s, Rolf Landauer asked a revolutionary question:

At first glance, computation appears purely logical. A computer flips bits from 0 to 1 and performs mathematical operations. But Landauer realized something profound:

Thermodynamics tells us that physical systems have entropy, energy costs, and irreversibility. This means information processing cannot escape the laws governing heat and energy.

And this led to what is now known as Landauer’s Principle.

Landauer discovered that not all computational operations are equal. Some operations are reversible, meaning the original information can always be recovered from the final state. In principle, these operations can be performed with almost no energy cost. But irreversible operations, like erasing a bit, permanently destroy information, and that changes everything.

He showed that this loss of information is not just abstract, it has a physical cost. When you erase a bit, the information about what it used to be does not simply vanish. Instead, it is pushed into the environment, making the surrounding system slightly more disordered. That added disorder appears as heat released into the surroundings.

This connects directly to the idea of entropy, which describes how spread out or mixed up energy and information become. Landauer showed that whenever information is irreversibly erased, this disorder must increase somewhere else. The only way for that to happen is for energy to be dissipated into the environment as heat.

So computation itself is not necessarily expensive. What fundamentally costs energy is the irreversible loss of information.

This naturally leads to a fascinating idea:

A reversible process is one where no information is destroyed. In physics, perfectly reversible processes can, in principle, occur without dissipating energy as heat. For example, imagine a logic gate where the inputs can always be reconstructed uniquely from the outputs.

Traditional logic gates like AND and OR are irreversible because information about inputs is lost. But reversible gates preserve information. This inspired the field of reversible computing.

In theory, a perfectly reversible computer could perform computation with arbitrarily small energy dissipation. The challenge is that real physical systems are never perfectly isolated. Noise, friction, and decoherence inevitably introduce irreversibility.

Still, the idea remains profoundly important because it connects computation directly to the arrow of time and entropy.

This is where quantum computing enters the story. Quantum mechanics is fundamentally reversible. The evolution of an isolated quantum system follows unitary dynamics, meaning information is preserved over time. Quantum gates are therefore naturally reversible. For example, many quantum operations can simply be “undone” by applying the inverse transformation.

This is radically different from classical digital logic, where information is constantly discarded during computation. In that sense, quantum computing is much closer to thermodynamically reversible computation.

But there is an important subtlety. Quantum computers are not magically free from energy costs. Real quantum devices still require:

And measurement itself introduces irreversibility because quantum information collapses into classical outcomes. So while quantum mechanics provides a fundamentally reversible framework for computation, practical quantum computing still faces thermodynamic constraints.

Perhaps the most beautiful aspect of Landauer’s Principle is how it dissolves the boundary between the abstract and the physical.

We often think of information as intangible. But information always lives in a physical system. And because information is physical, computation is not separate from nature. It is part of nature.

The next time your computer heats up while compiling code or training an AI model, remember:

somewhere inside those billions of transistors, information is being erased, entropy is increasing, and thermodynamics is quietly enforcing the rules of the universe.