frarzani.github.io
qat.inria.fr
Comments welcome! 🙂 (4/4)
Comments welcome! 🙂 (4/4)
If you
1. Start from vacuum
2. Use continuous-variable gates from a Lloyd-Braunstein universal set
3. Optimize gate parameters to prepare GKP qubits
→ you can achieve error rates below the threshold for GKP-surface-code quantum memory ✅ (2/4)
If you
1. Start from vacuum
2. Use continuous-variable gates from a Lloyd-Braunstein universal set
3. Optimize gate parameters to prepare GKP qubits
→ you can achieve error rates below the threshold for GKP-surface-code quantum memory ✅ (2/4)
🔗 arxiv.org/abs/2501.13857
Would love to hear your thoughts! #QuantumComputing #QuantumOptics #Physics
🔗 arxiv.org/abs/2501.13857
Would love to hear your thoughts! #QuantumComputing #QuantumOptics #Physics
✔️ Validates common modeling approaches in quantum optics & computing.
✔️ Provides a general way to engineer bosonic quantum states & gates.
✔️ Leads to an infinite-dimensional Solovay–Kitaev theorem.
✔️ Validates common modeling approaches in quantum optics & computing.
✔️ Provides a general way to engineer bosonic quantum states & gates.
✔️ Leads to an infinite-dimensional Solovay–Kitaev theorem.
1️⃣ Any physical bosonic unitary evolution can be approximated by a finite-dimensional one.
2️⃣ Any finite-dimensional unitary evolution can be exactly generated by a Hamiltonian that's a polynomial of canonical operators.
1️⃣ Any physical bosonic unitary evolution can be approximated by a finite-dimensional one.
2️⃣ Any finite-dimensional unitary evolution can be exactly generated by a Hamiltonian that's a polynomial of canonical operators.
They also involve some continuous quantities (position, momentum etc), which require infinite dimensional spaces, making some calculations more involved.
They also involve some continuous quantities (position, momentum etc), which require infinite dimensional spaces, making some calculations more involved.