IIR Cryogenics 2025 conference: latest advances in cryogenics for quantum computing

A keynote paper on cryogenics for quantum computing reviewed current cooling methods such as dilution refrigeration or cryocoolers, challenges associated with cryogenics for quantum computing, as well as recent advances to address those challenges.

During the last IIR Cryogenics 2025 conference held in Prague, Czech Republic on April 7-11, 2025, Pr. Ziad Melhem presented an overview of the recent advances in cryogenics for quantum computing [1]

 

Quantum computers can solve problems that are too complex for classical computers thanks in part to a phenomenon called superposition. While the building blocks of a classical computer — bits — can take a value of either 0 or 1, the most common building blocks in quantum computers — qubits — can have a value of 0 and 1 simultaneously. This superposition enables quantum computers to perform parallel computations. Refrigeration is essential to this technology, for qubits must be cooled to cryogenic temperatures, just a fraction of a Kelvin above absolute zero, to perform without errors for long periods of time. 

 

In his keynote, Pr. Melhem presented cooling methods currently employed to achieve the low temperatures required for quantum computing. These include: 

  • Dilution refrigeration. One of the most effective cooling techniques used in quantum computing, it utilises a mixture of two isotopes of helium: helium-3 (³He) and helium-4 (⁴He). At temperatures below 1 K, a process known as "dilution" occurs, in which helium-3 atoms mix with helium-4, absorbing heat and cooling the system to even lower temperatures 
  • Cryocoolers. These devices cool a system by expanding and compressing gases like helium, hydrogen, or neon. Compared to dilution refrigerators, cryocoolers can be more compact and efficient, making them an attractive option for specific quantum computing applications. 
  • Adiabatic demagnetisation. This cooling method is based on the principle that a system's entropy decreases when its magnetic field changes at a constant temperature. This technique is less commonly employed than dilution refrigeration and cryocoolers because it requires precise magnetic field control and is not as efficient at achieving the extremely low temperatures needed for most quantum computing systems. 

 

The use of cryogenics for quantum computing poses several ongoing challenges such as thermal fluctuations, heat generation from classical electronics, and the high costs of infrastructure requirements. Continued research and innovation are needed to address these issues, and solutions are emerging.

  

For instance, cryogenic CMOS (complementary metal-oxide-semiconductor) technology could allow for more efficient and compact integration of classical electronics and quantum processors. This would help address the challenge of heat generation from classical systems and make it easier to scale up quantum computers. 

 

Another significant topic of research and development is quantum error correction, which is essential for maintaining the stability and reliability of quantum computers. Due to the fragile nature of qubits, errors can quickly occur in quantum computations, and error correction is vital to prevent these errors from propagating and ruining results. However, quantum error correction requires additional qubits and resources, which adds complexity and requires advanced cryogenic techniques to ensure these systems operate at the necessary low temperatures.

 

Recent advances in cryogenic systems have led to improvements in quantum error correction, contributing to enhancing the performance and scalability of quantum systems.  

 

 

Find out more in the keynote available on FRIDOC 

Recent advances in cryogenics for quantum computing   

 

 

Sources 

[1] Melhem Z. Recent advances in cryogenics for quantum computing. Cryogenics 2025. Proceedings of the 18th IIR International Conference, Prague, Czech Republic, April 7-11 2025. https://iifiir.org/en/fridoc/recent-advances-in-cryogenics-for-quantum-computing-150585