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Quantum-optimal information encoding using noisy passive linear optics (Quantum 8, 1218)

Determining the maximal amount of information that can be reliably transmitted through a noisy channel is a key question in information theory. This study delves into a class of optical quantum channels that stand out for their practicality: they do not require an external energy source for their operation. By focusing on these channels, the ... Read moreQuantum-optimal information encoding using noisy passive linear optics (Quantum 8, 1218)

Quantum Uncertainty Principles for Measurements with Interventions (Phys. Rev. Lett. 130, 240201)

Interactive measurements represent the most powerful way in which agents can learn about their environments. When toddlers want to understand cause and effect for example, they don't merely observe. Instead they try different actions, and observe the reactions. This interactivity is key to learning the causal relations between objects. As such, in Artificial intelligence and ... Read moreQuantum Uncertainty Principles for Measurements with Interventions (Phys. Rev. Lett. 130, 240201)

Implementing quantum dimensionality reduction for non-Markovian stochastic simulation (Nat Commun 14, 2624)

Complex systems such as traffic patterns weather forecasts, and financial markets are ‘stochastic’ processes typically modelled by storing vast amounts of information about events in the past – which quickly consumes lots of memory. The downside of of this is not only resource cost. The more things a model tracks, the harder it is to ... Read moreImplementing quantum dimensionality reduction for non-Markovian stochastic simulation (Nat Commun 14, 2624)

Thermodynamic machine learning through maximum work production (New J. Phys. 24 083040)

Adaptive systems, ranging from living organisms to autonomous robots, exhibit the ability to thrive by effectively utilizing the resources in their environments. Often this requires learning models of their environment, such that the agent can best understand what to anticipate in the future depending on past expereincces. However, such adaptive systems are physical, and so ... Read moreThermodynamic machine learning through maximum work production (New J. Phys. 24 083040)

Space-efficient optical computing with an integrated chip diffractive neural network (Nat Commun 13, 1044)

Optical neural networks (ONNs) are a rapidly developing field of technology that uses light to perform complex computing tasks. Until now, most ONNs have been large and power-hungry, limiting their practical use. Traditional approaches rely on units called Mach-Zehnder interferometers (MZIs) for their calculations. For large-scale computations, this approach can require an excessive amount of units ... Read moreSpace-efficient optical computing with an integrated chip diffractive neural network (Nat Commun 13, 1044)

Collaborative computing goes Quantum

In the Lego movie a master builder possesses the jedi like powers of being able to construct different getaway vehicles such as flying couches simply by cobbling together stray blocks and repurposed parts of existing structures. These constructions are only limited by the master builder’s imagination (ok and some engineering principles on the limits of ... Read moreCollaborative computing goes Quantum

Interfering trajectories in experimental quantum-enhanced stochastic simulation Nature Communications, 10, 1630)

In the 2018 movie Infinity War, a scene featured Dr. Strange looking into 14 million possible futures to search for a single timeline where the heroes would be victorious. Perhaps he would have had an easier time with help from a quantum computer. In with work, we worked with colleagues from Griffith university to constructed ... Read moreInterfering trajectories in experimental quantum-enhanced stochastic simulation Nature Communications, 10, 1630)

Quantifying memory capacity as a quantum thermodynamic resource (Phys. Rev. Lett. 122, 060601)

The Szilard Engine presented the iconic example that related information theory and thermodynamics. In this engine, it was shown that when a demon is supplied with a 'blank tape' to record information, he could use it as a resource to do work. Here, we looked at what happens to such a demon when he is ... Read moreQuantifying memory capacity as a quantum thermodynamic resource (Phys. Rev. Lett. 122, 060601)

Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators (New Journal of Physics 21, 013021)

We know from prior works that quantum models have an advantage when it comes to generating predictions, using less memory than all classical counterparts. This was first done in the context of processes that output symbols at discrete points in time. Subsequently similar advantages were discovered processes that can emit only a single symbol, but ... Read moreMemory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators (New Journal of Physics 21, 013021)

Matrix Product States for Quantum Stochastic Modelling (Phys. Rev. Lett. 121, 260602)

There are many notions of complexity and structure. In computational mechanics, for example, the complexity of a stochastic process can be characterized by how much information one must store about its past to general future statistical predictions faithfully. Meanwhile, in quantum any body systems, a prominent measure of complexity is in the amount of information ... Read moreMatrix Product States for Quantum Stochastic Modelling (Phys. Rev. Lett. 121, 260602)