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Record W4361213434 · doi:10.22331/q-2023-03-28-963

Beyond transcoherent states: Field states for effecting optimal coherent rotations on single or multiple qubits

2023· article· en· W4361213434 on OpenAlexafffund
Aaron Z. Goldberg, Aephraim M. Steinberg, Khabat Heshami

Bibliographic record

VenueQuantum · 2023
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of CalgaryUniversity of TorontoCanadian Institute for Advanced ResearchNational Research Council CanadaUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsField (mathematics)Excited stateAlgorithmAtom (system on chip)PhysicsQuantum mechanicsComputer scienceMathematics

Abstract

fetched live from OpenAlex

Semiclassically, laser pulses can be used to implement arbitrary transformations on atomic systems; quantum mechanically, residual atom-field entanglement spoils this promise. Transcoherent states are field states that fix this problem in the fully quantized regime by generating perfect coherence in an atom initially in its ground or excited state. We extend this fully quantized paradigm in four directions: First, we introduce field states that transform an atom from its ground or excited state to any point on the Bloch sphere without residual atom-field entanglement. The best strong pulses for carrying out rotations by angle <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>&amp;#x03B8;</mml:mi></mml:math> are are squeezed in photon-number variance by a factor of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow class="MJX-TeXAtom-ORD"><mml:mi mathvariant="normal">s</mml:mi><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:mrow><mml:mi>&amp;#x03B8;</mml:mi></mml:math>. Next, we investigate implementing rotation gates, showing that the optimal Gaussian field state for enacting a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>&amp;#x03B8;</mml:mi></mml:math> pulse on an atom in an arbitrary, unknown initial state is number squeezed by less: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow class="MJX-TeXAtom-ORD"><mml:mi mathvariant="normal">s</mml:mi><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:mrow><mml:mstyle displaystyle="false" scriptlevel="0"><mml:mfrac><mml:mi>&amp;#x03B8;</mml:mi><mml:mn>2</mml:mn></mml:mfrac></mml:mstyle></mml:math>. Third, we extend these investigations to fields interacting with multiple atoms simultaneously, discovering once again that number squeezing by <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mstyle displaystyle="false" scriptlevel="0"><mml:mfrac><mml:mi>&amp;#x03C0;</mml:mi><mml:mn>2</mml:mn></mml:mfrac></mml:mstyle></mml:math> is optimal for enacting <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mstyle displaystyle="false" scriptlevel="0"><mml:mfrac><mml:mi>&amp;#x03C0;</mml:mi><mml:mn>2</mml:mn></mml:mfrac></mml:mstyle></mml:math> pulses on all of the atoms simultaneously, with small corrections on the order of the ratio of the number of atoms to the average number of photons. Finally, we find field states that best perform arbitrary rotations by <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>&amp;#x03B8;</mml:mi></mml:math> through nonlinear interactions involving <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>m</mml:mi></mml:math>-photon absorption, where the same optimal squeezing factor is found to be <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow class="MJX-TeXAtom-ORD"><mml:mi mathvariant="normal">s</mml:mi><mml:mi mathvariant="normal">i</mml:mi><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:mrow><mml:mi>&amp;#x03B8;</mml:mi></mml:math>. Backaction in a wide variety of atom-field interactions can thus be mitigated by squeezing the control fields by optimal amounts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.287
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes2
Has abstractyes

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