Information is not energy itself, but every act of processing or erasing information requires a minimum amount of energy that can never be reduced to zero. This connection between information and physics, first proposed in 1961, has since been confirmed in laboratory experiments and now shapes how scientists think about everything from computer chip design to black holes. The relationship is precise and quantifiable: erasing a single bit of information at room temperature releases at least 0.0000000000000000000003 joules of heat into the surrounding environment.
The Landauer Limit: Information Has a Physical Cost
The key insight linking information to energy came from physicist Rolf Landauer, who argued that erasing information is fundamentally a physical process. When you delete a bit, the information doesn’t simply vanish. It produces a tiny but unavoidable amount of heat. The minimum energy released when one bit is erased at a given temperature is calculated by multiplying Boltzmann’s constant, the natural log of 2, and the temperature of the system. At room temperature (about 300 kelvin), that works out to roughly 3 × 10⁻²¹ joules per bit.
This isn’t a limitation of current technology. It’s a law of nature. No matter how cleverly you design a computer or any other information-processing device, you cannot erase a bit for less energy than Landauer’s bound predicts. The reason traces back to the second law of thermodynamics: erasing a bit reduces the number of possible states in a system by half, which lowers its entropy. That missing entropy has to go somewhere, and it leaves as heat.
Lab Confirmation in 2012
For decades, Landauer’s principle was a theoretical argument. The energy involved is so vanishingly small that no experiment could isolate it from background noise. That changed in 2012, when researchers built a one-bit memory using a single microscopic particle (a colloidal bead) trapped in a laser-created double-well potential, essentially two tiny energy valleys the particle could sit in. By slowly erasing the particle’s position information and measuring the heat released, they showed that the average energy dissipated during erasure approaches Landauer’s predicted minimum when the process is carried out slowly enough. This was the first direct confirmation that deleting information really does have a measurable, irreducible energy cost.
Maxwell’s Demon and Why Information Matters
The connection between information and energy also resolves one of the oldest puzzles in physics. In 1867, James Clerk Maxwell imagined a tiny intelligent being, later called a “demon,” that could sort fast and slow gas molecules into separate chambers. By doing so, the demon would create a temperature difference from nothing, seemingly violating the second law of thermodynamics and generating free energy.
The resolution lies in what happens inside the demon’s memory. To sort molecules, the demon must observe and record which ones are fast and which are slow. That memory fills up. Eventually the demon has to erase its stored information to keep working, and that erasure releases at least Landauer’s minimum heat per bit back into the environment. When you account for this cost, the total entropy of the system never decreases. Information processing saves the second law.
Could Information Have Mass?
Physicist Melvin Vopson has pushed the idea further, proposing that a stored bit of information doesn’t just require energy to erase but actually possesses a tiny amount of mass while it holds information. Using Einstein’s mass-energy equivalence (E = mc²) combined with Landauer’s energy per bit, Vopson calculated that at room temperature, one bit of information would weigh about 3.19 × 10⁻³⁸ kilograms. That’s roughly 30 million times lighter than an electron.
This mass-energy-information equivalence principle remains a hypothesis. No experiment has yet detected such a small mass contribution. But it illustrates how seriously physicists now take the physical nature of information. If the idea holds, it means every hard drive, DNA strand, and book is slightly heavier because of the information it contains, not just because of its physical material.
Biology Processes Information Far Better Than Computers
One of the most striking implications of information-energy physics is how it lets you compare the efficiency of different computing systems, including living cells. When a cell builds a protein, it reads genetic instructions and assembles amino acids in a specific sequence. This is an information-processing task, and it costs energy. The minimum energy required to specify a single amino acid during this process (the Landauer bound for that operation) is about 1.24 × 10⁻²⁰ joules. Cells actually spend about 3.17 × 10⁻¹⁹ joules per amino acid, roughly 26 times the theoretical minimum.
That might sound wasteful until you compare it to silicon. The best supercomputers spend about 5.27 × 10⁻¹³ joules per bit operation, which is approximately 100 million times worse than the Landauer bound. Biological protein assembly is about a million times more energy-efficient than a supercomputer when both are measured against their respective theoretical limits. Cells have had billions of years of evolution to optimize their information processing, and it shows.
How Far Modern Computers Are From the Limit
Today’s manufactured transistors operate at roughly 10 to 10,000 times above the theoretical minimum energy per logic operation. That gap has been shrinking for decades as chips have gotten smaller and more efficient, but fundamental barriers remain. Even the most optimized simple charging circuit hits what’s called the Landauer-Shannon limit, which sits about 50 times above Landauer’s absolute minimum. Getting closer to the bound would require radically different computing architectures, such as reversible computing, where operations are designed to avoid erasing information whenever possible.
This matters practically because energy consumption is now the primary constraint on computing performance. As transistors approach atomic scales, the heat generated per operation becomes a hard wall. Landauer’s bound tells engineers exactly where that wall sits.
Black Holes and the Ultimate Information Limit
The connection between information and energy scales all the way up to the largest objects in the universe. In the 1970s, Jacob Bekenstein and Stephen Hawking showed that a black hole’s entropy, a measure of its hidden information, is proportional to the surface area of its event horizon, not its volume. Specifically, a black hole’s entropy equals one quarter of its horizon area measured in units of Planck area (the smallest meaningful unit of area in physics, about 2.6 × 10⁻⁷⁰ square meters).
Because a black hole’s energy is simply its mass (through E = mc²), and its entropy is fixed by its surface area, black holes represent the densest possible packing of information in a given region of space. You physically cannot store more bits in a volume than a black hole of that size contains. This places an absolute upper limit on information density anywhere in the universe and reinforces the idea that information is not an abstract concept floating above physics. It is woven into the fabric of energy, mass, and spacetime itself.
So Is Information Energy?
Information is not a form of energy in the way that heat, light, or kinetic energy are. You cannot power a lightbulb with a string of ones and zeros. But information is physically real in a way that matters: it cannot exist without a physical substrate, it cannot be erased without releasing energy, it may carry a vanishingly small mass, and it obeys the same thermodynamic laws as everything else in the universe. The relationship between information and energy is not metaphorical. It is measurable, experimentally verified, and built into the deepest laws of physics we know.