Photonics.institute

Although Nvidia are not releasing their optical quantum chip until 2026/7, other companies such as Xanadu’s Photonic have one already in production

Photonic quantum computing is a promising approach to building scalable quantum computers using photons (particles of light) as qubits. Unlike other quantum computing platforms that rely on trapped ions, superconducting circuits, or spin qubits, photonic systems leverage the unique properties of light to perform quantum computations. Photonic chips are set to disrupt multiple industries by enabling light speed computing, ultra efficient data centers, quantum breakthroughs, and advanced sensing. While challenges remain, the next decade will likely see photonics becoming mainstream, complementing nd eventually surpassing traditional electronics in many applications.

Photonic Qubit Advantage

Low decoherence: Photons do not easily interact with their environment, preserving quantum states longer.

Room temperature operation: Unlike superconducting qubits, photonic systems don’t require extreme cooling.

High speed operations: Photons travel at the speed of light, enabling fast quantum gates.

Natural compatibility with quantum communication: Photons are ideal for quantum networking (e.g. quantum internet).

Present Challenges

Difficulty in photon photon interactions: Photons don’t naturally interact, making two qubit gates hard to implement.

Loss and detection inefficiencies: Photons can be lost in optical systems, and detectors aren’t perfect.

Qubit Encoding in Photons

Photonic qubits can be encoded in different degrees of freedom:

Polarization qubits: Using horizontal (|H⟩) and vertical (|V⟩) polarization states.

Time bin qubits: Using early and late time slots (e.g. |0⟩ = early, |1⟩ = late).

Spatial mode qubits: Using different paths in an interferometer.

Frequency qubits: Using different optical frequencies.
B. Single Qubit Gates

Single qubit operations are performed using linear optical elements:

Waveplates (for polarization qubits).

Beam splitters (for path encoded qubits).

Phase shifters (for introducing relative phases).

Since photons don’t interact directly, two qubit gates require

Nonlinear optical effects (weak and hard to control). Measurement induced nonlinearity (e.g. using fusion gates or KLM protocol). D. Photon Sources. Post selection: Discarding unsuccessful operations (reduces efficiency).

Reliable quantum computing requires

Single photon sources (e.g. quantum dots, NV centers, SPDC crystals).Indistinguishable photons (critical for interference based gates).

E. Photon Detection

Superconducting nanowire single photon detectors (SNSPDs): High efficiency (~90%). Transition edge sensors (TES): Near perfect detection but slower.Silicon photomultipliers (SiPMs): Lower cost but higher noise.

Approaches to Photonic Quantum Computing

Linear Optical Quantum Computing (LOQC):

Probabilistic gates with post selection. Requires large overhead but is theoretically scalable. Measurement Based Quantum Computing (MBQC)

Uses cluster states (entangled states of many photons). Computation proceeds via single qubit measurements. Combines photons with matter qubits (e.g. atoms, quantum dots). Enables deterministic gates via photon atom interactions.

Quantum Networking

Photons are ideal for quantum repeaters and long distance QKD (quantum key distribution). D. Near Term Applications.

Quantum simulations (chemistry, optimization).

Machine learning (quantum enhanced algorithms).

Cryptanalysis (breaking RSA with Shor’s algorithm in the future).

Dark Photons

Dark photons remain a compelling bridge between the Standard Model and dark matter. While undiscovered, ongoing and future experiments keep narrowing the possibilities. If detected, they could unlock a hidden sector of the universe.

Experiments ongoing

LDMX (Light Dark Matter Experiment) – Planned at SLAC/Fermilab to probe A′ → invisible.

SHiP (CERN) – Will search for very weakly interacting particles, including dark photons.

Future High Intensity Colliders (e.g., ILC, FCC-ee) – Could discover A′ if it couples very weakly.

Dark photons, waves and particles:

Dark photons do not disrupt wave theory but could introduce:

Tiny power losses in lasers/cavities.

New polarization effects in strong EM fields.

Astrophysical anomalies in pulsars/CMB.

Ternary Computing (Base-3). This is the most direct "3 digit" replacement for binary

The Core Idea: Instead of using just two digits, 0 and 1 (the bits of binary), a ternary system uses three digits.
There are two main types:
Unbalanced Ternary: Uses 0, 1, 2. Balanced Ternary: Uses -1, 0, +1 (often written as -, 0, +). This is the most elegant and theoretically powerful form. Why is it a "Better" Idea? Higher Data Density: A single "trit" (ternary digit) can convey more information than a single "bit." One bit can be in 2 states (0 or 1). One trit can be in 3 states (-, 0, +). This means you can represent more numbers with fewer digits. For example, 8 trits can represent 6,561 distinct values (3^8), while 8 bits can only represent 256 (2^8).

More Efficient Logic: Some logical operations that require multiple gates in binary can be done with a single gate in ternary. The 'three way' nature can be more naturally suited to real world concepts like (negative, zero, positive), (false, unknown, true), or (low, medium, high).

Simpler arithmetic (in balanced ternary): Addition and subtraction become incredibly straightforward because the negative numbers are built into the representation. There is no need for complex systems like "two's complement" used in binary.

The Catch: Why Is is it not everywhere?

Binary won the early computing race for a simple, physical reason: hardware stability. It is much easier and cheaper to build reliable electronic components that only need to distinguish between two clear states (e.g. voltage ON vs. voltage OFF). Creating a stable, third intermediate state that can be measured quickly and reliably without error has been historically very difficult and power intensive.

Current Status: Ternary computing is seeing a revival in research. With advancements in materials science like memristors and nanotechnology, building efficient ternary processors is becoming more feasible. Some research institutes and companies have already built simple ternary chips, proving the concept works.