Blog

Research notes & logs

Notes on quantum information, quantum sensing, noise modeling, and experimental physics.

August 3, 2026

The Microscopic Origins of Charge Noise in Solid-State Qubits

An exploration of surface charge noise, drift-diffusion dynamics, and how fluctuating surface states decohere solid-state quantum devices. Understanding these microscopic origins is key to engineering longer-lived qubits.

In solid-state quantum computing, charge noise is a primary source of decoherence. Whether you are working with superconducting qubits, semiconductor quantum dots, or color centers, the electric field from fluctuating charges in the environment couples directly to the qubit's energy levels, causing phase drift.

The dominant contributor is surface noise. Trapped charges on oxides and interfaces exhibit drift-diffusion dynamics, hopping between localized defect sites. Phenomenologically, this manifests as a 1/f noise spectrum, which is exceptionally difficult to filter out because it grows stronger at low frequencies.

In our calculations, we model these charge fluctuations using a master equation coupled to a Poisson solver to map out the spatial dependence of the noise. By understanding how the electric field power spectral density scales with the distance from the surface, we can design device geometries that minimize noise exposure.

Ultimately, material science and surface passivation are as critical as quantum control. Cleaning the surface oxide interfaces and using specialized capping layers are the most promising avenues for extending coherence times in heterogeneous photonic and semiconductor devices.

July 20, 2026

Coherent Control of Rare-Earth Ions in Photonic Cavities

How embedding rare-earth ions (like Erbium) into heterogeneous photonic crystal cavities enables long coherence times and strong light-matter interaction for quantum memories.

Rare-earth ions, particularly Erbium (Er³⁺), are highly attractive for quantum communication because their optical transitions lie in the telecommunications C-band (around 1.54 μm). This allows quantum states to be transmitted over optical fibers with minimal attenuation.

However, rare-earth ions in bulk crystals typically suffer from weak light-matter interaction due to their shielded, forbidden 4f-4f transitions. To overcome this, we embed them into nanophotonic cavities. These cavities confine light to small volumes, enhancing the electric field and significantly increasing the transition rate via the Purcell effect.

The challenge lies in preserving coherence inside these nanostructures. The proximity to etched surfaces and interfaces introduces strain, surface charge noise, and defects, which accelerate decoherence. We use coherent control techniques, such as dynamical decoupling pulse sequences, to refocus the spin and optical coherence.

Our recent simulations demonstrate that by optimizing both cavity design and PASS (phase-modulated spin echoes) sequences, we can achieve strong coupling while maintaining optical coherence times long enough for scalable quantum memory applications.

July 14, 2026

What quantum sensing taught me about measurement

Most of my PhD is about making measurements harder — squeezing information out of solid-state systems where the signal is tiny and the noise is everywhere. Rare-earth ions, decoherence in hybrid structures, charge noise at surfaces: the whole field is an exercise in understanding what limits sensitivity, and what you can do about it. These are the notes I'd give a friend about what that training does to the way you think.

First, sensitivity is always a story about a noise floor. A quantum sensor isn't good because it is sensitive; it's good because something specific is quiet enough that a small signal becomes resolvable. The question I learned to ask is always: what is the noise, where does it come from, and how do we push it down?

In my research that noise is often decoherence — the system forgetting its quantum state because it couples to the world. Charge noise at surfaces is a classic culprit: mobile charges near the device create fluctuating fields, and the fluctuations eat coherence. We spend enormous effort understanding the microscopic origins of that noise, because you can't fight what you can't name.

Second, averaging is not free. Averaging hides drift, and drift is the silent killer of long measurements. Every experiment has a time budget: average longer and the statistics improve, but the system drifts and the improvement saturates. The optimal experiment is a compromise between integration time and drift, and it is always a compromise.

Third, the instrument is part of the measurement. The sensor, the sample holder, the wiring, the room — all of it contributes to what you record. Changing any of it changes the data, whether or not you intended it. I now read 'instrument effects' into almost everything, including standard digital interfaces, which are built by people with their own choices baked in.

None of this is a trading strategy, but all of it is relevant. The discipline of naming the noise floor, budgeting averaging against drift, and suspecting the instrument — those habits are the most portable things my PhD is giving me.