Physics Modes

Contents

Physics Modes#

class BtoDpiDtoKpipiValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'BtoDpiDtoKpipi'#
latex_str = '$B^0 \\rightarrow D^- \\pi^+, D^- \\rightarrow K^+\t \\pi^- \\pi^-$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Mbc

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • Mbc_matched

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • deltaE

    • Label: \(\Delta(E)\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • All

  • deltaE_matched

    • Label: \(\Delta(E)\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • beamE

    • Label: \(E(beam)\)

    • Range: (10.8, 11.2)

    • Unit: \(GeV\)

    • Components:

      • All

  • mKpi1

    • Label: \(m(K^+\pi^-_1)\)

    • Range: (0.5, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • mKpi1_matched

    • Label: \(m(K^+\pi^-_1)\)

    • Range: (0.5, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • mKpi2

    • Label: \(m(K^+\pi^-_2)\)

    • Range: (0.5, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • mKpi2_matched

    • Label: \(m(K^+\pi^-_2)\)

    • Range: (0.5, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • mpipi

    • Label: \(m(\pi^-\pi^-)\)

    • Range: (0.2, 1.5)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • mD

    • Label: \(m(D)\)

    • Range: (1.75, 1.95)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • mD_matched

    • Label: \(m(D)\)

    • Range: (1.75, 1.95)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • pD

    • Label: \(p(D^-)\)

    • Range: (1.4, 3.5)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • pK

    • Label: \(p(K^+)\)

    • Range: (0, 3.0)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • pDPi1

    • Label: \(p(\pi_1^+)\)

    • Range: (0, 3.0)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • pDPi2

    • Label: \(p(\pi_2^+)\)

    • Range: (0, 3.0)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • pDPi1_matched

    • Label: \(p(\pi_1^+)\)

    • Range: (0, 3.0)

    • Unit: \(GeV/c\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • pDPi2_matched

    • Label: \(p(\pi_2^+)\)

    • Range: (0, 3.0)

    • Unit: \(GeV/c\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • pion1PID

    • Label: \(binary PID(\pi_1^+)\)

    • Range: (0.2, 1.0)

    • Unit: :math:` `

    • Components:

      • All

  • pion1PID_matched

    • Label: \(binary PID(\pi_1^+)\)

    • Range: (0.2, 1.0)

    • Unit: :math:` `

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • pPi

    • Label: \(p(\pi^+)\)

    • Range: (1.5, 3.5)

    • Unit: \(GeV/c\)

    • Components:

      • All

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class BtoDpiDtoKspipiValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'BtoDpiDtoKspipi'#
latex_str = '$B^+ \\rightarrow D \\pi^+, D \\rightarrow K^0_S \\pi^+ \\pi^-$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Mbc

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • deltaE

    • Label: \(\Delta(E)\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • All

  • beamE

    • Label: \(E(beam)\)

    • Range: (10.8, 11.2)

    • Unit: \(GeV\)

    • Components:

      • All

  • mKs

    • Label: \(m(K_S^0)\)

    • Range: (0.48, 0.52)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • pKs

    • Label: \(p(K_S^0)\)

    • Range: (0, 3.5)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • mD

    • Label: \(m(D)\)

    • Range: (1.75, 1.95)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • pD

    • Label: \(p(D)\)

    • Range: (1.2, 3.5)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • pPi

    • Label: \(p(\pi^-)\)

    • Range: (1.5, 3.5)

    • Unit: \(GeV/c\)

    • Components:

      • All

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class BtoDstLNuValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'BtoDstLNu'#
latex_str = 'B^0 \\rightarrow D^{*-} \\ell \\nu, D^{*-} \\rightarrow \\bar{D^0} \\pi^+'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Mbc

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • Mbc_corr_noCuts

    • Label: \(M_{bc} corrected\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • Mbc_corr_nominalMask

    • Label: \(M_{bc} corrected, cleaned ROE\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • deltaE

    • Label: \(\Delta E\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • DeltaE_corr_noCuts

    • Label: \(\Delta E corrected\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • DeltaE_corr_nominalMask

    • Label: \(\Delta E corrected, cleaned ROE\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • lep_p

    • Label: \(p_{\ell}\)

    • Range: (0.5, 10)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • q2_noCuts

    • Label: \(q^2 no cuts\)

    • Range: (0, 25)

    • Unit: \(Gev^2\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • q2_nominalMask

    • Label: \(q^2 cleaned ROE\)

    • Range: (0, 25)

    • Unit: \(Gev^2\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • MM2_noCuts

    • Label: \(MM^2 no cuts\)

    • Range: (-5, 15)

    • Unit: \(Gev^2\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • MM2_nominalMask

    • Label: \(MM^2 cleaned ROE\)

    • Range: (-5, 15)

    • Unit: \(Gev^2\)

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • ROE_Q_noCuts

    • Label: \(Q_{\mathrm{ROE}} no cuts\)

    • Range: (-2.5, 2.5)

    • Unit: ``

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

  • ROE_Q_nominalMask

    • Label: \(Q_{\mathrm{ROE}} cleaned ROE\)

    • Range: (-2.5, 2.5)

    • Unit: ``

    • Components:

      • Signal

        cut: isSignalAcceptMissingNeutrino == 1

      • Background

        cut: isSignalAcceptMissingNeutrino != 1

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class BtoJpsiKJpsitoeeValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'BtoJpsiKJpsitoee'#
latex_str = '$B^{+} \\rightarrow J/\\psi K^{+}, J/\\psi \\rightarrow e^{+} e^{-}$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Mbc

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • Mbc_matched

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • deltaE

    • Label: \(\Delta(E)\)

    • Range: (-0.1, 0.1)

    • Unit: \(GeV\)

    • Components:

      • All

  • deltaE_matched

    • Label: \(\Delta(E)\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • mJpsi

    • Label: \(M(e^{+}e^{-})\)

    • Range: (2.96, 3.2)

    • Unit: \(GeV\)

    • Components:

      • All

  • mJpsi_matched

    • Label: \(M(e^{+}e^{-})\)

    • Range: (2.96, 3.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class BtoJpsiKJpsitomumuValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'BtoJpsiKJpsitomumu'#
latex_str = '$B^{+} \\rightarrow J/\\psi K^{+}, J/\\psi \\rightarrow \\mu^{+} \\mu^{-}$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Mbc

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

  • Mbc_matched

    • Label: \(M_{bc}\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • deltaE

    • Label: \(\Delta(E)\)

    • Range: (-0.1, 0.1)

    • Unit: \(GeV\)

    • Components:

      • All

  • deltaE_matched

    • Label: \(\Delta(E)\)

    • Range: (-0.2, 0.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • mJpsi

    • Label: \(M(\mu^{+}\mu^{-})\)

    • Range: (3.0, 3.2)

    • Unit: \(GeV\)

    • Components:

      • All

  • mJpsi_matched

    • Label: \(M(\mu^{+}\mu^{-})\)

    • Range: (3.0, 3.2)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class BtoJpsiKstarValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'BtoJpsiKstar'#
latex_str = '$B \\rightarrow J/\\psi K^{*0}$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • qrGNN

    • Label: \(qrGNN (cleaned ROE)\)

    • Range: (-1, 1)

    • Unit: \(unitless\)

    • Components:

      • All

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

class BtoPiLNuValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'BtoPiLNu'#
latex_str = '$B \\rightarrow \\pi \\ell \\nu$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Mbc

    • Label: \(M_{bc} (cleaned ROE)\)

    • Range: (5.24, 5.29)

    • Unit: \(GeV/c^2\)

    • Components:

      • All

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class DtoKPiValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'DtoKPi'#
latex_str = '$D \\rightarrow K\\pi$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • deltaM

    • Label: \(\Delta M\)

    • Range: (0.14, 0.16)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • D0_K_kaonID

    • Label: \(kaonID(K)\)

    • Range: (0.0, 1.0)

    • Unit: ``

    • Components:

      • All

  • D0_K_nVXDHits

    • Label: \(nVXDHits(K)\)

    • Range: (0.0, 20.0)

    • Unit: ``

    • Components:

      • All

  • D0_K_nCDCHits

    • Label: \(nCDCHits(K)\)

    • Range: (0.0, 100.0)

    • Unit: ``

    • Components:

      • All

  • D0_pi_pionID

    • Label: \(pionID(\pi)\)

    • Range: (0.0, 1.0)

    • Unit: ``

    • Components:

      • All

  • D0_pi_nVXDHits

    • Label: \(nVXDHits(\pi)\)

    • Range: (0.0, 20.0)

    • Unit: ``

    • Components:

      • All

  • D0_pi_nCDCHits

    • Label: \(nCDCHits(\pi)\)

    • Range: (0.0, 100.0)

    • Unit: ``

    • Components:

      • All

  • pi_pionID

    • Label: \(pionID(\pi_s)\)

    • Range: (0.0, 1.0)

    • Unit: ``

    • Components:

      • All

  • pi_nVXDHits

    • Label: \(nVXDHits(\pi_s)\)

    • Range: (0.0, 20.0)

    • Unit: ``

    • Components:

      • All

  • pi_nCDCHits

    • Label: \(nCDCHits(\pi_s)\)

    • Range: (0.0, 100.0)

    • Unit: ``

    • Components:

      • All

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class DtoKPiPi0ValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'DtoKPiPi0'#
latex_str = '$D \\rightarrow K\\pi\\pi^0$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • deltaM

    • Label: \(\Delta M\)

    • Range: (0.14, 0.16)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • D0_pi0_p

    • Label: \(p(\pi^0)\)

    • Range: (0.0, 5.0)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • D0_pi0_gamma_0_clusterTiming

    • Label: \(clusterTiming(\gamma_0)\)

    • Range: (0.0, 100.0)

    • Unit: \(ns\)

    • Components:

      • All

  • D0_pi0_gamma_1_clusterTiming

    • Label: \(clusterTiming(\gamma_1)\)

    • Range: (0.0, 100.0)

    • Unit: \(ns\)

    • Components:

      • All

  • D0_pi0_gamma_0_clusterE1E9

    • Label: \(clusterE1E9(\gamma_0)\)

    • Range: (0.0, 5.0)

    • Unit: \(GeV\)

    • Components:

      • All

  • D0_pi0_gamma_1_clusterE1E9

    • Label: \(clusterE1E9(\gamma_1)\)

    • Range: (0.0, 5.0)

    • Unit: \(GeV\)

    • Components:

      • All

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class DtoKsPiPiValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'DtoKsPiPi'#
latex_str = '$D \\rightarrow K_S^0\\pi\\pi$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • deltaM

    • Label: \(\Delta M\)

    • Range: (0.14, 0.16)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • D0_K_S0_p

    • Label: \(p(K_S^0)\)

    • Range: (0.0, 5.0)

    • Unit: \(GeV/c\)

    • Components:

      • All

  • D0_K_S0_significanceOfDistance

    • Label: \(significance of distance(K_S^0)\)

    • Range: (0.0, 50.0)

    • Unit: :math:``

    • Components:

      • All

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class eetomumugamma(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'eetomumugamma'#
latex_str = '$e^+ e^- \\rightarrow \\mu^+ \\mu^- \\gamma$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property output_trigger_lines#
property input_trigger_lines#
class LambdactoPKPiValidationMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'LambdactoPKPi'#
latex_str = '$\\Lambda_c^+ \\rightarrow p K \\pi$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • M

    • Label: \(M(pK\pi)\)

    • Range: (2.2, 2.4)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: isSignal == 1

      • Background

        cut: isSignal != 1

  • significanceOfDistance

    • Label: \(significance of distance (\Lambda_c^+)\)

    • Range: (0.0, 5.0)

    • Unit: ``

    • Components:

      • All

  • p_protonID

    • Label: \(protonID(p)\)

    • Range: (0.0, 1.0)

    • Unit: ``

    • Components:

      • All

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class MCCompareMode(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'mc_compare'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • cosThetaBY

    • Label: \(cos\theta_{BY}\)

    • Range: (-5, 5)

    • Unit: ``

    • Components:

      • rank1 B’s

        cut: sigProbRank==1

  • cosThetaBY_allVSrank1

    • Label: \(cos\theta_{BY}\)

    • Range: (-5, 5)

    • Unit: ``

    • Components:

      • all ranks

      • rank1 B’s

        cut: sigProbRank==1

offline_df_manipulation(df: DataFrame) → DataFrame[source]#

Offline Output Formats: parquet

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class Tautoe3pi(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'Tautoe3pi'#
latex_str = '$\\tau^+, \\tau^- \\rightarrow \\pi^+ \\pi^- \\pi^+ \\nu, e^-$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Thrust

    • Label: \(Thrust\)

    • Range: (0.7, 1.0)

    • Unit: ``

    • Components:

      • Signal

        cut: dmIDTag == 1 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • Visible_Energy

    • Label: \(E_{visible} in CMS\)

    • Range: (0.0, 12.0)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: tau_0_isSignal==1

  • M_a1

    • Label: \(M_{a1}\)

    • Range: (0.0, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 1 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_12

    • Label: \(M_{\pi^{\pm} \pi^{\mp}}\)

    • Range: (0.0, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 1 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_31

    • Label: \(M_{\pi^{\pm}\pi^{\pm}}\)

    • Range: (0.0, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 1 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_123

    • Label: \(M_{2\pi^{\mp}\pi^{\pm}}\)

    • Range: (0.0, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 1 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • Momentum_tag-track

    • Label: \(Momentum_{tag-track}\)

    • Range: (0.0, 8.0)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: dmIDTag == 1 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class Tautomu3pi(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'Tautomu3pi'#
latex_str = '$\\tau^+, \\tau^- \\rightarrow \\pi^+ \\pi^- \\pi^+ \\nu, mu^-$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Thrust

    • Label: \(Thrust\)

    • Range: (0.7, 1.0)

    • Unit: ``

    • Components:

      • Signal

        cut: dmIDTag == 2 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • Visible_Energy

    • Label: \(E_{visible} in CMS\)

    • Range: (1.0, 11.0)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: dmIDTag == 2 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_a1

    • Label: \(M_{a1}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 2 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_12

    • Label: \(M_{\pi^{\pm} \pi^{\mp}}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 2 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_31

    • Label: \(M_{\pi^{\pm}\pi^{\pm}}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 2 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_123

    • Label: \(M_{2\pi^{\mp}\pi^{\pm}}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 2 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • Momentum_tag-track

    • Label: \(Momentum_{tag-track}\)

    • Range: (0.0, 8.0)

    • Unit: \(GeV\)

    • Components:

      • signal

        cut: dmIDTag == 2 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
class Tautopi3pi(base_path: str, exp: int | None = None, run_type: str | None = None, processing_id: str | None = None, run_range: Tuple[int, int] | None = None, release: str | None = None, offline_run: bool | None = False)[source]#

Bases: ValidationModeBaseClass

name: str | None = 'Tautopi3pi'#
latex_str = '$\\tau^+, \\tau^- \\rightarrow \\pi^+ \\pi^- \\pi^+ \\nu, pi^-$'#
create_basf2_path()[source]#

Create the basf2 path for the validation of this mode. Consult the source for specifics on the validation steering.

property analysis_validation_histograms: List[Histogram]#

The histograms defined for this mode are listed below.:

  • Thrust

    • Label: \(Thrust\)

    • Range: (0.7, 1.0)

    • Unit: ``

    • Components:

      • Signal

        cut: dmIDTag == 3 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • Visible_Energy

    • Label: \(E_{visible} in CMS\)

    • Range: (1.0, 11.0)

    • Unit: \(GeV\)

    • Components:

      • signal

        cut: dmIDTag == 3 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_a1

    • Label: \(M_{a1}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • signal

        cut: dmIDTag == 3 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_12

    • Label: \(M_{\pi^{\pm} \pi^{\mp}}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 3 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_31

    • Label: \(M_{\pi^{\pm}\pi^{\pm}}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 3 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • M_123

    • Label: \(M_{2\pi^{\mp}\pi^{\pm}}\)

    • Range: (0.2, 1.8)

    • Unit: \(GeV/c^2\)

    • Components:

      • Signal

        cut: dmIDTag == 3 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

  • Momentum_tag-track

    • Label: \(Momentum_{tag-track}\)

    • Range: (0.0, 8.0)

    • Unit: \(GeV\)

    • Components:

      • Signal

        cut: dmIDTag == 3 and nPhotons_signal==0 and nPhotons_tag==0 and tau_0_isSignal==1

get_number_of_signal_for_efficiency(df: DataFrame) → float[source]#
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