Quantum computing often sounds like science fiction: particles in two places at once, strange correlations across space, and computers that could one day crack problems beyond any classical supercomputer. But between the headlines and the heavy mathematics, it can be hard to grasp what is happening during a quantum computing operation. The Quantum Zoo project at Fraunhofer IKS provides insight: hands-on quantum computing — not just for students.
April 13, 2026
© iStock/yekorzh
The Quantum Zoo is a software application developed at the Fraunhofer Institute for Cognitive Systems IKS that helps to understand key concepts of quantum computing by turning a quantum operation into an imaginary animal. It is both a scientific tool and a pedagogical playground: The Quantum Zoo lets you experiment with quantum principles, without requiring you to read a single equation.
Figure 1: Creating a hybrid animal with the Quantum Zoo.
Below, we’ll look at the ideas behind the Quantum Zoo, how it works, and why it’s a powerful way to learn what makes quantum computing fundamentally different.
Classical computers process information in bits—zeros and ones. Each bit is either 0 or 1 at any given time. Quantum computers, in contrast, work with quantum bits, or qubits. A single qubit can be in the state 0, the state 1, or in a superposition of both at once. When we measure the qubit, we obtain either 0 or 1, but before measurement the qubit is in a more general quantum state that encodes probabilities for both outcomes.
Two or more qubits can do even more surprising things. For example, quantum states can reinforce or cancel each other, much like overlapping waves in water (interference). Carefully designed sequences of operations can suppress unwanted outcomes and enhance the probability of the desired ones. Qubits can further become correlated in a way that has no classical equivalent, in a process called entanglement. Measuring one qubit can instantly give you information about another, even if they are far apart. The Quantum Zoo is the first steppingstone to making these abstract principles tangible for students and anyone curious about quantum technologies.
The promise of quantum computing lies in exploiting these effects to perform certain calculations more efficiently than classical machines. However, designing algorithms that truly benefit from quantum parallelism is hard. Only a few such algorithms are known today, such as Shor’s algorithm for factoring large numbers and Grover’s algorithm for speeding up search problems. Fraunhofer IKS researches how these concepts can be applied to real-world problems with current, imperfect quantum hardware - including optimization, simulation, and machine learning.
Under the hood, the Quantum Zoo uses the standard “gate-based” model of quantum computing. Instead of programming with lines of code, you design a quantum circuit: a sequence of operations (gates) acting on qubits over time.
In the Quantum Zoo interface, this becomes a visual workspace:
By composing gates on different qubits, you build up a quantum circuit. At the far right, you can imagine a final measurement: this collapses the combined quantum state into one of the possible classical outcomes, such as the binary numbers 000 or 101 with probabilities determined by your circuit. For N qubits, there are 2N possible outcomes. A key insight—which the Quantum Zoo makes visible—is that your circuit doesn’t pick just one path through these possibilities. Instead, it manipulates a full distribution over all of them at once.
Probabilities over abstract bit strings like 000 or 111 are not exactly intuitive. The Quantum Zoo solves this with a metaphor: each possible outcome is mapped to an animal species. For example, in a three-qubit system, there are eight possible quantum states. Each state, in quantum-mechanical notation | 000 >, | 001 >, …, | 111 > is assigned to a specific animal. Beneath the circuit panel, you see:
If your circuit yields only the state | 000 >, your probability distribution is concentrated on one animal. If you apply, say, two Hadamard gates, you might produce an equal superposition of four different states; the resulting animal is an even blend of four species, see Figure 1. Its features - ears, legs, colors - combine in a way that directly reflects the quantum probabilities.
© Fraunhofer IKS
Figure 2: A further example of a hybrid animal created with the quantum zoo
This translation from complex amplitudes to mixed animal features is the core pedagogical idea of the Quantum Zoo. When you add a Hadamard gate and see an animal class split into two, you are observing superposition. On the other hand, interference can be visualized by adding a gate that makes certain features fade or sharpen. When you introduce a two-qubit gate and see how a change on one qubit affects the overall mixture, this is entanglement. In this way, the Quantum Zoo turns an invisible quantum state into something funny and intuitive.
To guide exploration, the Quantum Zoo includes a set of challenges. You will find tasks of varying difficulty: for each one, your goal is to design a quantum circuit that produces a target animal. Those tasks provide a gentle path toward more complex circuit implementations as they would be used in real quantum algorithms.
Quantum computing is an emerging technology. Current hardware is noisy and limited, and large-scale, fault-tolerant quantum computers remain a long-term goal. But learning how quantum algorithms work - and where they might offer an advantage - already matters today. Quantum Zoo helps lower the barrier to that way of thinking. Step into the Quantum Zoo, design your own exotic creatures, and along the way, discover how the strange rules of quantum mechanics can be turned into powerful computation.
© Fraunhofer IKS
Figure 3: Hybrid animals created with the quantum zoo illustrate the principles og quantum computing.
To learn more or to get access, you can reach out to the Quantum Computing team at Fraunhofer IKS via email or check out the Fraunhofer IKS playground
