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Sharing A number of Quantum Info in One Operation

SHENZHEN, China, July 10, 2025 /PRNewswire/ — MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Firm”), a expertise service supplier, introduced the proposed multi-qubit quantum state sharing scheme, which, by way of an modern “one-time distribution + one-time recycle” mechanism, achieves the collaborative restoration of a number of multi-qubit states amongst contributors, offering a brand new paradigm for the environment friendly utilization of quantum sources. The scheme takes quantum entanglement encoding because the core, combining single-particle measurement and information collaborative processing to assemble a whole technical chain from state preparation to reconstruction.

The core strategy of the scheme might be likened to “quantum data specific supply”: first, the seller “packages” the goal quantum state right into a particular entangled state, distributes it to contributors by way of quantum channels, after which collaboratively reconstructs the unique state based mostly on native measurement information. Particularly, the seller encodes (m) variety of (ok)-qubit states right into a hyper-entangled state of (n=m×ok) particles, for instance, using multidimensional properties comparable to polarization and path of photons to assemble a “quantum specific field,” with every sub-entangled state carrying particular qubit data. After finishing the encoding by way of quantum gate operations, the particles are distributed to contributors, who acquire native information by way of generalized measurements and projective measurements. Lastly, the seller reconstructs the unique state utilizing a most chance estimation algorithm, with a constancy exceeding 90% deemed profitable.

HOLO’s technological innovation is mirrored in three dimensions: first, the hyper-entangled state multiplexing expertise breaks by way of the normal single-state single-resource limitation, using the multidimensional levels of freedom of particles to allow a single photon to hold 3 qubits of knowledge, enhancing useful resource effectivity by 3 instances; second, the adaptive measurement technique dynamically selects measurement bases, decreasing the variety of measurements by 30% and errors to 1/5 of random measurements, considerably enhancing information assortment effectivity; third, the distributed reconstruction algorithm allocates the multi-state revivification process to a number of computing nodes, making processing time improve linearly with the variety of states, avoiding the exponential complexity bottleneck of conventional centralized algorithms.

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